on evaluation and modelling of human exposure to …782793/fulltext01.pdfto maximize the performance...

KTH Engineering Sciences

On Evaluation and Modelling of HumanExposure to Vibration and Shock on

Planing High-Speed Craft

Katrin Olausson

Licentiate ThesisStockholm, Sweden

2015

Academic thesis with permission by KTH Royal Institute of Technology,Stockholm, to be submitted for public examination for the degree of Li-centiate in Vehicle and Maritime Engineering, Thursday the 12th of Feb-ruary, 2015 at 10.00, in D3, Lindstedtsvägen 5, KTH - Royal Institute ofTechnology, Stockholm, Sweden.

TRITA-AVE 2015:01ISSN 1651-7660

c© Katrin Olausson, 2015

Postal address: Visiting address: Contact:KTH, AVE Teknikringen 8 [email protected] for Naval Arcitechture StockholmSE-100 44 Stockholm

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Abstract

High speed in waves, necessary in for instance rescue or military op-erations, often result in severe loading on both the craft and the crew.To maximize the performance of the high-speed craft (HSC) system thatthe craft and crew constitute, balance between these loads is essential.There should be no overload or underuse of crew, craft or equipment.For small high-speed craft systems, man is often the weakest link. Thehuman exposure to vibration and shock results in injuries and other ad-verse health effects, which increase the risks for non-safe operations andperformance degradation of the crew and craft system. To achieve asystem in balance, the human acceleration exposure must be consideredearly in ship design. It must also be considered in duty planning and indesign and selection of vibration mitigation systems.

The thesis presents a simulation-based method for prediction and eval-uation of the acceleration exposure of the crew on small HSC. A numer-ical seat model, validated with experimental full-scale data, is used todetermine the crew’s acceleration exposure. The input to the model isthe boat acceleration expressed in the time domain (simulated or meas-ured), the total mass of the seated human, and seat specific parameterssuch as mass, spring stiffness and damping coefficients and the seat’slongitudinal position in the craft. The model generates seat responsetime series that are evaluated using available methods for evaluation ofwhole-body vibration (ISO 2631-1 & ISO 2631-5) and statistical methodsfor calculation of extreme values.

The presented simulation scheme enables evaluation of human expos-ure to vibration and shock at an early stage in the design process. It canalso be used as a tool in duty planning, requirements specification orfor design of appropriate vibration mitigation systems. Further studiesis proposed within three areas: investigation of the actual operationalprofiles of HSC, further development of seat models and investigationof the prevailing injuries and health problems among the crew of HSC.

Keywords: Whole-body vibration, high-speed craft, working condi-tions, seat modelling, apparent mass, ergonomics, human factors, ISO2631-1, ISO 2631-5

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Sammanfattning

Hög fart genom vågor är nödvändigt under exempelvis räddningsupp-drag eller militära operationer men innebär ofta svåra belastningar påsåväl båt som människa. För att maximera prestandan av det tekniskasystem som en högfartsbåt och dess besättning utgör, krävs att dessa be-lastningar balanseras. Båt, utrustning eller människa ska varken över-belastas eller underutnyttjas. På små högfartsbåtar utgör människanofta den svagaste länken. Stötar och vibrationer resulterar i skador ochandra negativa hälsoeffekter som också ökar risken för nedsatt säker-het såväl som försämrad prestanda av det tekniska systemet. För attuppnå ett system i balans är det nödvändigt att ta hänsyn till män-niskans vibrations- och stötexponering tidigt i utvecklingen av nya hög-fartsbåtar. Likaså vid planering och schemaläggning av tjänst samt vidval och design av dämpningssystem.

Avhandlingen presenterar en simuleringsbaserad metod för predikter-ing och utvärdering av accelerationsexponeringen för besättningen påsmå högfartsbåtar. En numerisk stolsmodell som validerats mot exper-imentell accelerationsdata används för att modellera besättningens ac-celerationsexponering. Modellens indata är båtens acceleration uttryckti tidsplanet (simulerad eller experimentell), förarens totala massa samtstolsspecifika parametrar såsom massa, fjäder- och dämpkonstant samtstolens longitudinella position i båten. Stolsmodellen genererar tidsser-ier av stolsresponsen som utvärderas med hjälp av tillgängliga metoderför utvärdering av helkroppsvibrationer (ISO 2631-1 och ISO 2631-5) ochmed statistiska metoder för beräkning av extremvärden.

Simuleringsschemat som presenteras möjliggör utvärdering av männis-kans stöt- och vibrationsexponering tidigt i designskedet men kan ocksåanvändas som ett verktyg vid planering av tjänst, kravställning ellerför utformning av lämpliga dämpningssystem. Vidare studier föreslåsinom tre områden: kartläggning av högfartsbåtars verkliga operation-sprofil, vidareutveckling av stolsmodell samt kartläggning av skadoroch hälsoproblem bland personal på högfartsbåtar.

Nyckelord: Helkroppsvibration, högfartbåt, arbetsmiljö, stolsmodel-lering, skenbar massa, ergonomi, mänskliga faktorn, ISO 2631-1, ISO2631-5

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Preface

The work presented in this thesis has been performed at the Centre forNaval Architecture at the Department of Aeronautical and Vehicle En-gineering at KTH Royal Institute of Technology, from November 2012 toJanuary 2015. The work was initiated and supported by Dr. Karl Garme,Prof. Jakob Kuttenkeuler, Dr. Anders Rosén and Dr. Ivan Stenius.The research has been financially supported by Sjöfartsverket (SwedishMaritime Administration), the Lundeqvist Foundation (promoting sci-entific research within the field of Naval Architecture at KTH) and FMV(Swedish Defence Materiel Administration).

I would like to sincerely thank my supervisors Karl Garme and JakobKuttenkeuler for their eminent support, guidance, and help during thiswork. To you and to all my colleagues at KTH Centre for Naval Archi-tecture - it has been a pleasure to work with you. I also would liketo thank Stefan Andersson (Swedish Coast Guard), Gustav Kjellberg(Swedish Armed Forces) and Carl-Magnus Ullman (Ullman Dynamics)for their valuable contributions and for putting my work into a widercontext. To my colleagues at the department, thank you for giving meenergy and motivation during lunch breaks and jam sessions.

Finally, a special thank to my family and friends for always being therein times of joy and doubt. To my husband Lars, words cannot expresshow grateful I am to you, and how much I appreciate your never endingsupport and your ability to always make me laugh.

Katrin Olausson

Stockholm, 12th January 2015

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Dissertation

This thesis consists of two parts: The first part gives an overview ofthe research area and work performed. The second part contains thefollowing research papers (A-C):

Paper AK. Olausson and K. Garme. Prediction and evaluation of working condi-tions on high-speed craft using suspension seat modelling. Proceedingsof the Institution of Mechanical Engineers, Part M: Journal of Engineering forthe Maritime Environment, published online before print, January 2014.

Paper BK. Olausson and K. Garme. Simulation-based assessment of HSC crewexposure to vibration and shock. In Proceedings of the 12th InternationalConference on Fast Sea Transportation (FAST2013), December 2013.

Paper CM. Razola, K. Olausson, K. Garme and A. Rosén. On High-Speed CraftAcceleration Statistics, preprint paper, January 2015.

Publications not included in this thesisConference paper: M. Razola, A. Rosén, K. Garme and K. Olausson. To-wards Simulation-Based Structural Design of High-Speed Craft. In Pro-ceedings of the Fourth Chesapeake Powerboat Symposium, Annapolis, Mary-land, June 2014.

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Division of work between authors

Paper AOlausson developed the presented methods and validated the seat modelusing experimental data provided by Garme. Olausson wrote the papersupervised by Garme.

Paper BOlausson determined the seat response to boat accelerations, which werenumerically simulated by Garme. The disposition of the paper is a res-ult of a collaboration between Olausson and Garme. Olausson wrote themajor part of the paper.

Paper COlausson developed the descriptive statistics methods and Razola de-veloped the inferential statistics methods. Olausson and Razola plannedthe study, performed the analysis and wrote the paper in collaboration.Garme performed boat simulations used in the analysis. The study wasinitiated and supervised by Garme and Rosén.

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Contents

I OVERVIEW 1

1 Introduction 31.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3 Thesis overview . . . . . . . . . . . . . . . . . . . . . . . . . 41.4 Vibration mitigation techniques . . . . . . . . . . . . . . . . 51.5 Human factors based ship design . . . . . . . . . . . . . . . 81.6 Operational actions to reduce acceleration exposure . . . . 10

2 Health effects of whole-body vibration and shock 132.1 Injuries and health problems among HSC operators . . . . 14

3 Modelling the acceleration exposure of HSC crews 173.1 Modelling the seat response . . . . . . . . . . . . . . . . . . 183.2 Modelling the human response . . . . . . . . . . . . . . . . 193.3 Seat and human interaction model for HSC . . . . . . . . . 213.4 Crew and craft exposure profile . . . . . . . . . . . . . . . . 24

4 Evaluation of whole-body vibration and shock exposure 274.1 Measures in international standards . . . . . . . . . . . . . 274.2 Statistical measures . . . . . . . . . . . . . . . . . . . . . . . 30

4.2.1 Extreme value predictions using the Weibull andGeneralized Pareto Distributions . . . . . . . . . . . 35

5 Risk analysis based on injury statistics 395.1 Preliminary Hazard Analysis . . . . . . . . . . . . . . . . . 39

xiii

CONTENTS

5.2 Risk of low back injuries . . . . . . . . . . . . . . . . . . . . 41

6 Summary & conclusions 476.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 476.2 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

7 Summary of appended papers 53

References 57

II APPENDED PAPERS A-C 65

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Part I

OVERVIEW

1 Introduction

1.1 Background

Over the years, advanced high-strength and lightweight materials havebeen developed, resulting in stronger and faster high-speed craft (HSC).However, the loads acting on the crew cause tiredness, muscle damage[1] and injuries [2] and limit the utilization of the craft’s performance.In order to achieve efficient HSC systems, balance between loads onthe hull, crew and equipment is necessary. It is therefore essential toimprove working conditions on HSC, both from human and technicalpoint of view.

The thesis adresses measures for improved working conditions with fo-cus on the crew’s exposure to vibration and shock. Three different ap-proaches to reduce the acceleration exposure are discussed: techniquesfor vibration mitigation, human factors based ship design and opera-tional acceleration reductive actions. The latter may for example be re-lated to duty planning or installation of decision support systems on-board. To maximize the possibilities of achieving safe and efficient high-speed craft operations, all these measures need to be addressed. Adop-tion of any of these ways of action, however, presupposes that workingconditions can be properly predicted and evaluated; a procedure thatis everything but straightforward. The conditions in terms of sea state,speed and heading are stochastic and constantly changing. In addition,the relation between working on HSC and effects on health and workperformance is unclear.

3

CHAPTER 1. INTRODUCTION

1.2 Objective

The long term goal is to achieve safe and efficient high-speed craft. Thethesis aims to contribute to the development of methods for predictionand evaluation of working conditions on HSC. In other words, methodsthat can be used when evaluating working conditions on both existingand future HSC.

One of the main objectives of the presented work is to enable humanfactors to be introduced as a parameter in ship design. However, pre-diction of working conditions also enables requirements specificationand planning of the crew’s duty to be performed with respect to humanhealth risk. Therefore, the presented work is supposed to be useful notonly for the naval architect, but also for the seat designer or employer,who wants to reduce the acceleration levels transmitted to the humanbody.

1.3 Thesis overview

A simulation-based method for prediction of HSC crew vibration andshock exposure is presented in Paper A & B [3, 4] and is further elabor-ated in Chapter 3 - Modelling the acceleration exposure of HSC crews. Anintroduction to the prevailing health problems among HSC operators isgiven in Chapter 2 - Health effects of whole-body vibration and shock. Aswill be seen, the most severe injuries are caused by severe impact eventsrather than vibration. In order to appropriately analyse extreme valuesof HSC acceleration exposures, two different statistical approaches ap-plicable to HSC acceleration is presented in Paper C [5]. These methodsare discussed and compared with other acceleration based evaluationmethods in Chapter 4 - Evaluation of whole-body vibration and shock expos-ure. As a complement to these detailed analysis methods, an additionalapproach for evaluation of HSC crew’s exposure to health risks is intro-duced in Chapter 5 - Risk analysis based on injury statistics. The suggestedapproach is not a complete evaluation method but may become use-ful in the future if more statistical data on injuries and health problemsamong HSC operators are available. Chapter 6 - Summary & conclusionssummarizes the work and suggests future studies.

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1.4. VIBRATION MITIGATION TECHNIQUES

1.4 Vibration mitigation techniques

Suspension seats are common on high-speed craft and can be effectivein order to reduce the vibration transmitted to the human body. Gen-erally, suspension seats have a spring unit that absorbs energy, and adamper unit, which dissipates energy. The spring can for example bea coil spring or a pneumatic spring, but other solutions also exist. Forexample, the suspension seat displayed in Figure 1.1 designed for useon HSC has a type of leaf spring system.

Figure 1.1: Example of suspension seat designed for use on HSC [6].

When operating small high-speed craft in waves, suspension seats canreduce the acceleration levels by 50 % [7, 8] in some situations and can bea necessity in order to avoid immediate injuries, as concluded by Garmeet al [7]. The seat’s mitigating performance depends on its transmissib-ility, in relation to the prevailing acceleration exposure. A seat’s trans-missibility is defined as the ratio of the vibration on the seat surface tothe vibration at the seat base as a function of frequency,

T( f ) =aseat( f )a f loor( f )

(1.1)

where T( f ) is the transmissibility, aseat( f ) is the amplitude of the acceler-

5


ation on the seat and a f loor( f ) is the amplitude of the acceleration at theseat base at frequency f [9]. Essentially, a suspension seat is a low passfilter, which has resonance frequency at around 2 Hz [9] and thus amp-lifies acceleration at this frequency, but mitigatets at larger frequencies.When designing a suspension seat, it is therefore essential to considerthe frequency spectrum of the acceleration exposure for which the seatis supposed to provide isolation. For marine high-speed craft, this isa non-trivial task since they are operated in stochastic waves and withspeed, heading and sea conditions being constant only for very shorttime periods. This naturally complicates the process of designing suit-able mitigation systems, as these generally are tuned for one type of ex-posure. This is the case for suspension seats and other passive mitigationsystems, although the occupant of a suspension seat sometimes has thepossibility to adjust the damper before or during ride. As an example,consider the acceleration signal in Figure 1.2.

Time [s]88 90 92 94 96

Acce

lera

tion

[m/s

2 ]

0

20

40

60Seat baseSeat cushion

Figure 1.2: Illustration of mitigating effect of a suspension seat. The boat and seat acceler-ations are simulated according to the methods proposed in Paper B [4].

The signal displayed in Figure 1.2 is a sequence of a simulated accelera-tion signal for a high-speed craft equipped with a suspension seat that isassumed to be occupied by a 85 kg human (see further Chapter 3 and Pa-per A & B [3, 4]). As seen, the seat provides mitigation for the two largestimpacts, but amplifies most of the impacts of lower magnitudes. Similarobservations have been made also for full-scale experiment data, for ex-ample by De Alwis [10]. One explanation to the effects seen in Figure 1.2

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1.4. VIBRATION MITIGATION TECHNIQUES

is the discussed seat transmissibility, which varies with frequency (seeEquation 1.1). Since severe impact events are related to very short timescales (see Paper C [5]), the seat mitigates these better than accelerationof lower frequencies. However, the seat transmissibility is not the onlyfactor influencing the performance of the seat in terms of mitigation.For instance, the human body is flexible and interacts with the seat. Theseat model used to generate the time series shown in Figure 1.2 includesa human representation in order to capture these effects. Furthermore,the seat cushion is also likely to influence the seat’s transmissibility (seeDe Alwis [10]), although the model in Paper A [3] has been successfullyvalidated with experimental data without describing the properties ofthe seat cushion.

It should be noted that the transmissibility of the seat-human system isnot the only important factor that needs to be considered when design-ing a suspension seat. Human sensitivity to vibration at different fre-quencies should also be considered, as well as the risk for the suspen-sion mechanisms to bottom out. In Paper B [4], the influence of seatdesign (in terms of spring stiffness and damping) on crew vibration ex-posure is investigated using methods for evaluation of whole-body vi-bration. These methods account for the human sensitivity to vibrationof different frequencies by a frequency weighting filter that is appliedbefore quantifying the acceleration. In the study, it is demonstrated thatthe acceleration exposure decrease if the spring stiffness is reduced, butalso that a lower spring stiffness requires a larger motion stroke (verticaldisplacement). If the available motion stroke of the seat is too short withrespect to the current spring stiffness, bottoming-out events may occurand subject the occupant to severe impacts. Thus, it is crucial to designthe seat with a sufficient motion stroke. In practice, however, there islimitation on stroke length with respect to practical aspects as well ascomfort. Concluding, designing a suspension seat is always a trade offbetween stroke and mitigating effect.

To meet the demands for reduced acceleration on HSC, developing andadopting complementary and/or more advanced methods for vibrationmitigation may be necessary. There are several advantages of mitiga-tion systems reducing acceleration not only for the crew, but for wholecompartments or the entire craft. Such systems can limit the need of isol-ation mountings for sensitive equipment on board, and allow the crewto be standing behind the seats, which is often impossible during HSC

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transits [7]. Townsend et al [11] investigated the effects of using variousflexible hull systems by simulating and comparing three different flex-ible hulls; a suspended hull design, an elastomer coated hull and a hullwith reduced stiffness, to a regular aluminium hull. Of the three hulldesigns, only the suspended hull showed potential in shock mitigation.It is thus likely that suspending not only seats, but also larger compart-ments of the craft (e.g. cockpit) may be a suitable way of reducing theacceleration exposures for both the crew and equipment on HSC.

Since passive mitigation systems tuned for one type of exposure cannotperform equally well in all situations, active and semi-active suspensionsystems can be advantageous. Such systems are controlled using sensorsthat read the environment conditions [12]. For semi-active systems, thedamper is typically adjusted to best dissipate energy, whereas active sys-tems exert a force that controls the motion, e.g. using hydraulic, mag-netic or electric actuators [12]. On HSC, active or semi-active suspen-sion systems are rare; probably due to the difficulty of predicting thecraft motion when speed, heading and waves change more or less ran-domly. In addition, these systems are associated with high costs, powerresource dependency and need for maintenance. This may further ex-plain why passive systems, which are more robust, are the most com-monly used mitigation systems on HSC.

1.5 Human factors based ship design

Numerous decisions in the design process influence the accelerationlevels that the crew and craft will be exposed to during high speed op-eration. Such design decisions are related e.g. to hull shape, displace-ment, design speed and running attitude [13]. With current design rules(e.g. [14, 15]), these parameters are chosen with respect to hull struc-tural loads, and with little or no consideration of human factors beforethe boat is built, launched and tested. This may result in boat designswhere the human acceleration exposure is limiting the performance ofthe technical system and/or the crew is exposed to health risks. That is,the performance of the craft cannot be fully utilized due to the severelevels of vibration and shock that the crew is subjected to while operat-ing at high speed in waves. To improve the balance between loads on thecrew and the craft and thereby achieve efficient high-performance sys-

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1.5. HUMAN FACTORS BASED SHIP DESIGN

tems, the key is to consider human factors continuously in the designprocess. As a part of the refined design methods currently being de-veloped with the goal to achieve more efficient HSC hull structures, seefor instance Razola et al [16, 17, 18], it is essential to develop methodsfor working condition assessment that can be introduced into the designprocess. Although several authors have proposed such methods [19, 20],there is none yet established. In Paper B [4], a simulation-based methodaiming for a rational approach for introducing measures for workingcondition evaluation as requirements in HSC design is presented. Themethod is summarized in the simulation scheme displayed in Figure 1.3.

1)#Define#hull#geometry,#load#case#and#a#set#of#opera8onal#condi8ons#(combina8ons#of#boat#speeds#and#sea#states#in#which#the#cra=#will#be#opera8ng).#

2)#Simulate#cra=#accelera8on#8me#series#for#each#opera8onal#condi8on#defined#in#1).#

3)#Define#the#seat’s#suspension#characteris8cs#and#longitudinal#posi8on#in#cra=.#

6)#Calculate#crew#accelera8on#exposure#with#respect#to#the#exposure#profile#in#5),#e.g.#using#methods#in#ISO2631I1#&#ISO2631I5.#

4)#Simulate#seat#accelera8on#response,#using#the#cra=#accelera8on#8me#series#generated#in#2)#and#input#from#3).#

7)#Assess#the#risk#for#adverse#health#effects.#If#not#sa8sfactory,#return#to#and#adjust#1)#and/or#3)#and/or#5).#

5)#Define#crew#accelera8on#exposure#profile#with#respect#to#the#considered#opera8onal#condi8ons.#

CRAFT#SIMULATION#MODULE#

SEAT#SIMULATION#MODULE#

HUMAN#EXPOSURE#EVALUATION#MODULE#

SIMULATION*SCHEME*

Figure 1.3: Simulation scheme as proposed in Paper B [4].

9


As can be seen, the simulation scheme consists of three modules. In thefirst module, the craft acceleration time series for operation at constantspeed in head seas are generated. Input data are sea state and craft spe-cific details such as hull geometry, load case and speed. The output ofthe first module is used in the second module to generate the seat ac-celeration time series. In this module, the seat’s spring and dampingcharacteristics are specified, as well as the seat’s longitudinal position inthe craft. Finally, the crew exposure to vibration and shock is assessedin two steps in the third and the last module. First, the crew expos-ure profile is formulated as the time spent per day in each of the condi-tions defined by the operational profile. Then, the seat acceleration timeseries are used together with the information in the exposure profile toassess the working conditions using the evaluation methods describedin Chapter 4.

The simulation scheme is applicable at many stages both in the designand operation of HSC, e.g. when investigating the effect of changing theseat configuration (stiffness and damping) or its longitudinal positionin the craft. In that case, the craft design, operational profile and crewexposure profile is held constant. However, if all parameters related tothe craft and the seat are held constant, the simulation scheme can beused to assess different working schedules for a given system. This maybe of interest for the employer, who is legally responsible to reduce themechanical vibration and attendant risks for the empolyees to a min-imum (EU Directive 2002/44/EG [21]). Concluding, the simulation toolcan be used for various purposes; by the seat designer, naval architectand the employer, in requirements specification, ship design and opera-tion of HSC.

1.6 Operational actions to reduce accelerationexposure

High-speed craft operations often result in physical and mental fatigue[22], which both increase the risk of injuries and reduce the crew’s work-ing capacity. For safe and efficient operations, it is thus essential to un-derstand the mechanisms that cause fatigue. As an example, workingnight shift is more fatiguing than working day shift. This is partly dueto the added concentration required when navigating at night. Other

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1.6. OPERATIONAL ACTIONS TO REDUCE ACCELERATIONEXPOSURE

factors that impact on fatigue are physical performance and the access toperiods of rest [22]. Thus, planning the duty appropriately, with phys-ical training and periods of rest considered, the negative effects of fa-tigue can be limited.

In addition to adequate duty planning, health risks may also be reducedby installing a decision support system. For example, a configurationwhere real-time acceleration measurements continuously give feedbackon the current loading situation (both on hull structure and human) tothe coxswain may prevent acceleration criteria to be exceeded. Such sys-tems are currently being developed and tried out by the Swedish CoastGuard in cooperation with KTH. A difficulty arising with the imple-mentation of such a system is the definition of limits that are both safeand trustworthy.

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2Health effects ofwhole-body vibrationand shock

The effects of whole-body vibration (WBV) on human health have beenfrequently discussed since the 1950’s, as a consequence of the rapidlyincreased use of machines in industries and transportation. Althoughthere is a wide range of health effects often being associated with WBV,it is generally difficult to link these effects to WBV exposure specific-ally. However, there seems to be an existing relationship between WBVexposure and health effects such as blood pressure, heart rate and res-piration rate, due to increased muscular activity or psychological stress[23]. People exposed to whole-body vibration and shock have reportedtiredness and headache in connection to duty [2, 7], as well as motionsickness, which is known to be caused by vibration of low frequencies[23]. Such temporary effects of WBV may result in reduced safety in anytechnical system operated by human exposed to vibration.

Due to the difficulty of distinguishing health effects caused by WBVfrom those caused by other factors, e.g. prolonged sitting, poor sittingposture or heavy lifting, there is little evidence indicating that WBV it-self increases the risk of acute and/or chronic injuries or other permanenteffects [24]. Nevertheless is it of importance to identify the most com-mon and most problematic health effects, related to both vibration andshock, among the crew of HSC. Otherwise, appropriate actions to im-prove the working situation cannot be taken, nor is it possible to assessthe working conditions, or finding the adequate parameters for doingso.

13

CHAPTER 2. HEALTH EFFECTS OF WHOLE-BODY VIBRATIONAND SHOCK

2.1 Injuries and health problems among HSCoperators

Although the attention to the risks related to HSC crews’ acceleration ex-posure has increased significantly in recent years (see for example [25]),there is little documentation of the prevalence of injuries and healthproblems among the operators of small HSC. Stevens and Parsons [26]presented a survey on effects of motion at sea on crew performance. Sev-eral aspects are discussed, although effects related to sea sickness are infocus. Ensign et al [2] presented a survey of self-reported injuries amonghigh-speed boat operators within the US Navy. The result gives an ideaof the variety of injuries that can occur while operating HSC; see Table2.1 where the number of injuries reported at different anatomical loca-tions is summarized. The table also presents the number of injuries thatrequired medical attention.

Table 2.1: Distribution of reported injuries (149 in total) and medical attention frequencyaccording to Ensign et al. [2]. The medical attention frequency refers to the number ofpersons that answered yes to the question if they sought for medical attention in relationto the number of injured persons that responded to the question.

Anatomical Location No. injuries Sought medical attentionHead 3 3(3) (100 %)Neck and upper back 9 6(9) (67 %)Shoulder 21 15(20) (75 %)Elbow 2 1(2) (50 %)Wrist 1 1(1) (100 %)Hand 1 1(1) (100 %)Trunk 2 1(1) (100 %)Low back 50 40(48) (83 %)Hip/Buttocks 6 6(6) (100 %)Thigh 2 1(2) (50 %)Knee 32 24(32) (75 %)Leg 7 5(7) (71 %)Ankle 10 9(10) (90%)Foot 3 1(2) (50 %)

14

2.1. INJURIES AND HEALTH PROBLEMS AMONG HSCOPERATORS

According to Table 2.1 it is clear that injuries to the lower back are themost common, accounting for 34% of the total number of reported in-juries (149) [2]. This result is consistent with other studies on health ef-fects caused by whole-body vibration and shock exposure, for exampleWikström et al [27] and Burström et al [24]. However, the diversity of in-juries to different anatomical locations seen in Table 2.1 shows that HSCcrews are exposed to a great variety of health risks. Not only the loca-tion, but also the type of injury varies. According to Ensign et al. [2],the most common type of injuries were sprain/strain (46 %), trauma (7%), disc problems (7 %), dislocation/separation (6 %), stress fracture (5%) and chronic pain (5 %). The study gives no details regarding whatinjury type is the most common for each anatomical location.

In addition to the acute and chronic injuries found in Ensign et al [2],symptoms such as headache and tiredness have been reported to becommon in connection to duty among HSC operators, for instance withinthe Swedish Coastguard [7]. Several studies also show that high-speedcraft transits can result in reduced physical capacity, muscle damageand fatigue [8, 22]. In Myers et al [8], the physiological consequencesof a three hours high-speed boat transit were investigated. It was foundthat the occupants’ physical performance, assessed by a number of per-formance tests such as exhaustive shuttle-run, handgrip, vertical-jumpand push-up, were reduced after the transit. In addition, the creatinekinase activity was increased, which is an indication of muscle damage[8]. Stevens and Parsons [26] refer to tests performed on a ship mo-tion simulator from which it was found that the maximum capacity foroxygen for an individual was significantly reduced when performingphysical excercises on the moving platform, compared to when the taskswere performed in a stationary motion simulator.

Although muscle damage and fatigue are probably consequences of mus-cle contractions following when occupants try to compensate for and at-tenuate the mechanical shocks they are exposed to [8, 28], accelerationexposure is not necessarily the only reason to the health effects associ-ated with HSC operation. Fatigue for example, can be both physical andmental, although Stevens and Parsons [26] suggest that mental fatigueis a manifestation of physical fatigue. Still, it is reasonable to believethat some health effects (e.g. tiredness and headache) may be a resultof mental fatigue caused for example by demanding tasks such as high-speed navigation or navigation at night, as well as a result of physical

15

CHAPTER 2. HEALTH EFFECTS OF WHOLE-BODY VIBRATIONAND SHOCK

fatigue caused by whole-body vibration and shock exposure.

To conclude, there is limited statistical data of the prevalence of injur-ies among HSC operators available. More data are needed in order toenable appropriate risk mitigation. To understand the risks of injuriesamong HSC operators, it is essential to study also other health effects,such as muscle damage and fatigue. These are factors that most likelyincrease the probabilities of both acute and chronic injuries, if the expos-ure to vibration and shock continues.

16

3Modelling theacceleration exposureof HSC crews

Predicting the crew’s acceleration exposure is fundamental to enable im-provement of working conditions onboard HSC. However, stochasticwaves and constantly varying boat speed and heading make the predic-tion difficult. To predict the acceleration exposure, these random condi-tions need to be identified and described. In addition, acceleration timeseries need to be collected either through experimental measurements ornumerical modelling. Since experimental data acquisition is time con-suming and restricted to existing vessels, numerical methods are desir-able, especially in a design or planning process. Numerical modellingfacilitates evaluation of various operational situations, such as differentseat configurations, sea states and craft designs.

Previously, several authors have presented work on modelling of plan-ing craft in waves, for example [29, 30, 31, 32]. By combining one of thesemodels with a numerical seat model, the crew’s acceleration exposurecan be predicted and later evaluated. This approach can be utilized toevaluate an existing working situation on a HSC. It can also be used todetermine an adequate crew exposure profile, in order to minimize therisks for adverse health effects for the crew on a particular craft with agiven operational profile.

In Paper A [3] a seat model is introduced and validated using full-scaleexperiment data. The seat model is also included in Paper B [4], as partof a simulation-based approach for assessment of working conditions on

17

CHAPTER 3. MODELLING THE ACCELERATION EXPOSURE OFHSC CREWS

HSC. The following sections elaborate further on what is needed to pre-dict and evaluate working conditions on HSC using numerical methods.

3.1 Modelling the seat response

Although the configuration of various HSC suspension seats may differ(see Chapter 1, Section 1.4), they can usually be described mechanicallyusing a combination of springs, masses and dampers as illustrated inFigure 3.1. Numerically, the equation of motion for a single degree-of-freedom (DOF) system as in Figure 3.1 is given by

mz + cz + kz = F (3.1)

where m is the mass, c is the damping coefficient, k is the spring stiff-ness coefficient and F is the external forces. For a suspension seat, m isthe mass of those parts of the seat that move relative to the seat base,whereas k and c describe the seat’s spring stiffness and damping, re-spectively.

m

c k

z

Figure 3.1: Single degree-of-freedom mass-spring-damper system.

Depending on the application (and purpose of the analysis) different de-grees of complexities of the seat model may be required. A wide rangeof models is therefore found in previous research; from single DOF sys-tems to more refined models including end-stop units [33, 34, 35, 36].Although a number of studies on seat modelling have been performedfor the application of marine, high-speed craft [28, 37, 38], most of thepublished studies are applied to on-land vehicles [34, 35, 36], for whichthe acceleration exposures differ significantly from those of HSC.

18

3.2. MODELLING THE HUMAN RESPONSE

In Cripps et al [28], an improved seat design for a high-speed rescuecraft using a single DOF seat and human interaction model is proposed.A similar model, but for three directions, is used in Coe et al [37] to studyseat isolation system designs for use on HSC. Both these studies focus onseat modelling as a tool to investigate the influence of seat parameterson human acceleration exposure. In Paper A [3], however, the presen-ted seat model aims for prediction and evaluation of HSC crew workingconditions and experimental full-scale acceleration data are used to val-idate the model. A further description of the seat-human interactionmodel is given in Section 3.3.

3.2 Modelling the human response

Human response to acceleration plays a significant role in seat model-ling since the human body is flexible and therefore interacts with the seatwhen excited. The feedback from the human body varies with frequencyand can be described by the mechanical impedance of the human body,which is also called the apparent mass, defined as

M( f ) =F( f )a( f )

(3.2)

where F( f ) is the excitation force and a the seat acceleration. The ap-parent mass at zero frequency, M(0), corresponds to the static weighton the seat. Griffin [23] exposed 60 seated humans to vertical vibra-tion of frequencies between 0.5 and 20 Hz and found that the apparentmass, M( f ), varies greatly between individuals. However, he also foundthat the normalized apparent mass, M( f )/M(0), vary considerably lessbetween individuals and can be well predicted by a lumped parametermodel as the one illustrated in Figure 3.2. Figure 3.3 shows the normal-ized apparent mass obtained with a model as the one in Figure 3.2. Fora detailed description of how to calculate the apparent mass, see PaperA1 [3].

1Figure 3.3 is the correct graph for the normalized apparent mass as proposed byGriffin. In Paper A [3] the corresponding figure is unfortunately errenous with resonanceat 5 Hz.

19


Mass of upper body

Mass of legs & thighs

c2 k2

z1

z2

Figure 3.2: According to Griffin [23], the normalized apparent mass for a seated humanexposed to vertical vibration (0.5 < f < 20Hz) can be well predicted by a mass-springdamper system as displayed.

Frequency [Hz]0 5 10 15 20

Nor

mal

ized

app

aren

t mas

s [-]

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Figure 3.3: Normalized apparent mass for a single DOF system, determined according tothe procedure described in Paper A [3]. The resonance frequency is 4.3 Hz.

20

3.3. SEAT AND HUMAN INTERACTION MODEL FOR HSC

3.3 Seat and human interaction model for HSC

Several authors have utilized the findings of Griffin [23] to define a nu-merical seat and human interaction model [3, 28, 37], but validation withexperimental, shock-dominated HSC acceleration data is only providedin Paper A [3]. The seat model as of Paper A [3] is displayed in Figure3.4 and the input data that need to be defined by the user are shown inTable 3.1.

m1 = m1,s + m1,h

m2

c2

c1

k2

k1

z2

z1

zb

Figure 3.4: Seat model presented in Paper A [3].

Table 3.1: Seat model input defined by user.

mh Human body mass kgm1,s Seat mass (moving parts) kgc1 Seat damping coefficient Ns/mk1 Seat spring stiffness coefficient N/mzb(t) Seat base acceleration time series m/s2

As seen in Table 3.1, the only input required to obtain time series of theseat response, except from the exciting acceleration (which can be eithermeasured or simulated), are the mass of the moving parts of the seat,

21


the seat’s spring stiffness and damping coefficients and the total massof the seated person. Based on these data, the seat model calculates theupper body mass m2 as well as the spring stiffness k2 and damping coef-ficient c2 of the human response model based on the Griffin normalizedapparent mass curve. The following assumptions are made:

• The normalized apparent mass transfer function is constant for allhuman bodies and can be approximated by a single DOF systemas previously displayed in Figure 3.2 (see [23])

• The apparent mass for a seated human is linear with respect tovibration magnitude and has a resonance frequency at 5 Hz (see[39, 40])

• The mass of the upper body, thighs and legs (including the feet) is72%, 18% and 10% of the total body mass respectively (i.e. m2 =0.72mh and m1,h = 0.18mh) (see [3])

• The thighs move with the seat and thus the mass of the thighs canbe added to the mass of the seat, m1, in the lumped parametermodel (see [3])

• The feet are supported on a footrest and the total mass of the legsand the feet can therefore be neglected as they do not influence theseat or human response (see [3, 23])

The assumption that the normalized apparent mass of a seated humanis well represented by a single DOF system enables the spring stiffnessand damping coefficients c2 and k2 to be calculated for various humanbody masses (see Paper A [3] for further details). However, it shouldbe noted that the spring stiffness and damping coefficients, c2 and k2,as well as the z2 degree-of-freedom have no clear physical interpreta-tion. The model representing the human body is a "construction" withthe purpose of reproducing similar feedback to the seat model as theseated human gives to the seat in reality. Concluding, the purpose ofthe human representation is to achieve time series of the seat acceler-ation (z1) that accurately describe the working environment onboardHSC and that can be used for further evaluation.

Validation of the seat model in Paper A [3] is performed using accelera-tion time series collected during sea trials of a 10-meters HSC, which wasequipped with high-standard suspension seats for which data in terms

22

3.3. SEAT AND HUMAN INTERACTION MODEL FOR HSC

of mass, spring stiffness and damping coefficients were provided by themanufacturer. Also the coxswain’s mass, occupying the instrumentedseat, was known. The seat acceleration were measured using a 3-axialseat pad mounted accelerometer and the craft acceleration by accelero-meters mounted on two bulkheads (for further details, see [3, 7]). Datafrom the latter two measurement points were used to calculate the seatbase acceleration, using linear interpolation. A representative examplefrom the validation is displayed in Figure 3.5, where the measured seatacceleration is compared with the seat acceleration generated by the seatmodel, when fed by experimental (interpolated) seat base acceleration.As can be seen, the acceleration passed through the seat model correl-ates well with the measured seat acceleration, although the peak valuesare generally higher for the measured signal.

Time [s]780 785 790 795

Acce

lera

tion

[m/s

s ]

-10

0

10

20

30

40

50MeasurementSeat model

Figure 3.5: Measured and predicted (using seat model) seat acceleration.

The lumped parameter apparent mass model is of course a simplifica-tion and a generalisation of the seated human body. Parameters such asbody composition (physique), posture and eventual use of arm or backrests influence the apparent mass, but are not considered here. Despitethis, the single DOF model (which parameters are set based on the totalhuman weight) appears to have a sufficient level of detail for the pur-poses of the present work. The lumped parameter model describingthe seat seems to be sufficient as well. Nevertheless, there is potentialin developing the model to capture the effect of bottoming-out events.Currently, the risk for bottoming-out is determined by studying the timeseries for the seat displacement generated by the model, and by identify-

23


ing eventual time instants where the displacement exceeds the availablemotion stroke of the seat. This is a reasonable approach since the ambi-tion should be to completely eliminate the risk for such events in orderto ensure safety for the occupant.

Concluding, connecting two single DOF systems in series allows the seatacceleration to be repeated with good accuracy when the system is ex-cited by shock-dominating acceleration. The proposed model, with onemass-spring-damper system each to describe the seat and the human re-sponses, seems to have a sufficient level of detail to generate accelerationtime series that agree well with experimental data. The current model isdefined for the vertical direction since vertical accelerations are clearlydominating on HSC [3, 7, 10, 41, 42]. However, if future investigationsshow that acceleration in several directions have significant influence onhuman health, comfort and performance, the model can be expanded toseveral degrees-of-freedom (as in Coe et al [37]) in order to enable designand evaluation of more complex mitigation systems.

3.4 Crew and craft exposure profile

Defining a craft’s operational profile is crucial in order to properly de-scribe and evaluate the loads acting both on the human and on the craft.Nevertheless, the task is not straight-forward, as high-speed craft opera-tion is highly non-homogeneous and associated with random variationsof sea state, loading condition, heading and forward speed. In addition,the knowledge about the craft’s actual operation is very often limitedand would benefit from further research.

In Paper B [4], a simplified but nevertheless useful approach is proposedto tackle the difficulty of evaluating the acceleration exposure when theconditions are stochastic and constantly changing. A simulation-schemein three steps is presented (see also Chapter 1) and used to evaluate twodifferent seat configurations and two load cases with respect to crewworking conditions. A set of operational conditions is defined as a num-ber of combinations of speeds and sea states. These combinations formthe basis for the craft operational profile, defined as a percentage of thetotal operational time spent in each of these conditions, as illustrated inFigure 3.6. The crew exposure profile is defined as percentage of the day

24

3.4. CREW AND CRAFT EXPOSURE PROFILE

spent in each condition, resulting in a characteristic day of exposure.By generating acceleration time series for the craft and coxswain seat,based on the conditions in the operational profile, working conditionscan be evaluated with respect to a characteristic daily dose. The long-term evaluation is performed based on a number of characteristic daysa year and number of years in service.

12%$ 6%$ 2%$

30%$ 15%$ 5%$

18%$ 9%$ 3%$

Sea$state$Calm$$$$$$$Mod.$$$$$Severe$$$$$$$$$$$

Speed$

$$Low

$$$$$$Med

$$$$$$High$

60%$ 30%$ 10%$

20%$

50%$

30%$

Figure 3.6: Example of operational profile. The sea state is divided into three categories;calm, moderate and severe. Similarly, three speed regimes are defined; low, medium andhigh speed.

The generalized operational profile in Paper B [4] and Figure 3.6 de-scribes a craft’s operation in a lifetime perspective, using a limited num-ber of operational conditions, and for craft simulated in head seas only.Although this is a simplification of reality, the approach is useful frommany aspects. For example, operation in head seas is known to causethe most severe acceleration impacts [42], which is relevant when eval-uating loads on craft and human (even though loads in other directionsshould not be considered as unimportant). Furthermore, by defining thecraft operational profile (and the crew exposure profile) with respect toa limited number of conditions, a collection of time series can be gener-ated for each craft and/or seat design and used in many analyses. Thatmeans, as soon as a set of craft and seat acceleration time series onceis established, different seat designs, craft operational profiles or crewexposure profiles can be evaluated without generating or collecting newdata. In addition, the resolution of the exposure profile can easily be var-ied in order to suite the current analysis by refining the condition matrixin Figure 3.6. This is an important aspect, as the level of details required

25


depends on the purpose of the analysis. For the naval architect, who isinterested in determining the design loads, the most severe condition(s)that the craft will be operated in is of primary interest. For the employeror seat designer on the other hand, who aims for minimizing the healthrisks for the crew, a more detailed exposure profile may be relevant. Forexample, severe injuries may not only be the result of a single heavyimpact; a wide range of injury types and health risks also arise fromaccumulated vibration and shock exposure (see further Chapter 4). Inaddition, it may be of interest to include details such as posture (stand-ing or sitting) and pattern of work (day or night shift), when evaluatinga crew’s exposure to WBV and shock.

26

4Evaluation ofwhole-body vibrationand shock exposure

There are at least two important factors deciding whether the risk forinjuries can be determined appropriately or not. Firstly, the evaluationmethods must be defined in a stringent way so that the entire procedure,from data acquisition to post processing and interpretation of result, canbe repeated regardless of where or by who the analysis is performed.As will be seen later in this chapter and in Paper C [5], this is one of thedisadvantages with many of the statistical measures being used to date.Secondly, to express the risk for human injuries, the evaluation meas-ures must be related to human endurance. Furthermore, it is import-ant to note that acute and chronic injuries can be the result of a single,severe high-acceleration event or a large quantity of smaller accelerationevents, as well as a result of long-term exposure. Therefore, these differ-ent types of exposures must be evaluated separately, and probably witha set of different methods.

In the following sections, the evaluation methods that are available todate are presented, and their pros and cons discussed.

4.1 Measures in international standards

To date, the most common methods to assess the risk of adverse healtheffects are those defined in the International Standards ISO 2631-1 [43]and ISO 2631-5 [44], not least since EU legislation refers to these stand-

27

CHAPTER 4. EVALUATION OF WHOLE-BODY VIBRATION ANDSHOCK EXPOSURE

ards. Similar methods are used in the British Standard BS 6481-1987 [45].In the EU Directive 2002/44/EG [21], action and limit values are statedwith reference to the root mean square (RMS) value and the vibrationdose value (VDV) defined in ISO 2631-1 [43] as

RMS ={

1T

∫ T

0[aw(t)]2 dt

}1/2

[m/s2] (4.1)

VDV ={∫ T

0[aw(t)]4 dt

}1/4

[m/s1.75] (4.2)

but evaluated for an 8-hour time period

RMS(8h) = RMS(T) ·[

8T

]1/2(4.3)

VDV(8h) = VDV(T) ·[

8T

]1/4(4.4)

where aw(t) is the frequency weighted acceleration signal and T is themeasurement time period. Since the RMS value porly displays the effectof shock in an acceleration signal, the VDV has been defined for signalshaving a significant shock content and should be used if the crest factor,defined as the maximum instantaneous peak value of the signal dividedby its RMS value, exceeds a value of 9. The VDV is commonly usedwithin the HSC community.

The EU directive 2002/44/EG [21] states that the employer must takeimmediate action to reduce the acceleration levels if the daily exposure,VDV(8h), exceeds the limit value (21 m/s1.75) and take action to reducethe acceleration to as low as reasonably possible if the action value (9.1m/s1.75) is exceeded. However, there is an exception for the legislatedlimit value that applies for sea transport. The background to this ex-ception is that the methods of ISO 2631-1 [43] initially were developedfor evaluation of whole-body vibration under homogeneous conditions.Therefore, the applicability of these methods and limits when evaluat-ing impact dominating, non-homogeneous exposures may be dubious.Within the HSC forum, the ISO 2631-1 methods are therefore sometimescriticized to be inadequate. The scepticism can be understood, as the le-gislated limit value is often exceeded only after tens of minutes of highspeed operation [7, 46]. Of course, the crew of high-speed craft can, and

28

4.1. MEASURES IN INTERNATIONAL STANDARDS

do, operate the craft for much longer time periods.

Scepticism is also directed to the action and limit values because they arebased on subjectively determined comfort criteria for human exposed tovibration. Although pain and discomfort are generally considered as in-dicators of prevailing health risks, i.e. "if it feels bad, it probably is bad",the link between discomfort and risk for injuries is not obvious [23, 47].Mansfield [9] explains that the physiological receptors adressing painor discomfort when exposed to WBV, not necessarily are located whereinjury may occur. Nevertheless, there is no doubt that the accelerationlevels on HSC can be severe. Thus, it is not obvious that a higher limitvalue should apply for HSC, even though the legislated levels may notbe perfectly tuned for non-homogenous, peak dominating accelerationexposures.

Before criticising any measures it is relevant to reflect on what the pur-pose of the analysis is. Perhaps is the VDV measure itself not the prob-lem, but rather the interpretation of its magnitude. In Annex B of ISO2631-1 [43], Guide to the effects of vibration on health, it is stated that sincethere are not sufficient data to show a quantitative relationship betweenvibration exposure and risk of adverse health effects, it is not possible toassess whole-body vibration in terms of the probability of risk at variousexposure magnitudes and durations. Nevertheless, VDV captures theeffects of both vibration and shock [4, 7], which is relevant when eval-uating acceleration exposures on HSC, which contain both types. Aspointed out in the beginning of this chapter, different types of exposuresand health problems may require different evaluation methods. SinceVDV is formulated as a daily dose measure and the relation betweendose and health effects is not yet clear, it is considered as a useful com-parative measure for short-term analyses. However, for assessement ofthe risk for acute injuries, additional methods are needed.

As discussed in Chapter 2, one of the most common health problemsfor people exposed to high acceleration events is injuries to the lumbarspine [2]. In order to enable estimation of the risk for adverse healtheffects due to such injuries, the ISO 2631-5 [44] method has been de-veloped. In contrast to the ISO 2631-1 [43] method, which considersonly daily exposure, the ISO 2631-5 [44] method also has a long-termperspective. This is achieved by accounting for the number of days andyears an employee is exposed to vibration of a daily equivalent static

29


compression dose Sed. The Sed is calculated using a lumbar spine model,which considers the ultimate strength of the lumbar spine and thus alsoadds a link to human endurance to the analysis. From the dose Sed therisk factor R, which indicates if the risk for an injury to the lumbar spineis high or low, can be calculated as function of years of duty.

It should be noted that the lumbar spine model included in the stand-ard ISO2631-5 [44] is applicable only for peak acceleration up to 40 m/s2

[44, 48], a level that is routinely exceeded on small high-speed craft. Itis of course highly desirable to develop the method to be valid also forlarger acceleration levels. The American standard ASTMF1166-07 has,based on Peterson et al [19], defined a maximum limit for the Sed(8) (4.7MPa) below which the probability of risk for adverse health effects canbe considered as low for exposures where “impacts routinely exceed 4Gs”. However, as stated by Bass et al [48], the neural network dynam-ics model in ISO 2631-5 should clearly not be used outside its range ofapplicability. Therefore, the authors present a refined human responsemodel that is validated with experimental data from sea trials and canbe used for acceleration exposures up to 14 g.

Except from being valid only up to 4 g with the present lumbar spinemodel, the ISO 2631-5 evaluation method is considered as promising forevaluation of risks for long-term adverse health effects on HSC [7, 19].Concluding, there is relevance in the standardized ISO 2631 methods,but the purpose of the analysis must be carefully considered before anymeasure is applied. The ability of VDV to predict the risk for injuriesis dubious, but can be useful as a comparative measure, which also Sedcan. Perhaps, the ISO 2631-1 with corresponding evaluation limits canbe linked to exposure duration and magnitude variations in order to bebetter suited for sea transport, where the conditions vary over time. Inaddition, the procedures from data collection (or simulation) to inter-pretation of the result must be unified and clearly defined.

4.2 Statistical measures

When aiming to determine the most severe loads that the crew is subjec-ted to, which may be of interest in the ship design process for example, astatistical measure is preferable. The measure should typically describe

30

4.2. STATISTICAL MEASURES

the peaks in terms of quantity and magnitude, in order to be useful forinjury risk assessment. It is also advantageous to express the measurein units of m/s2 or ’g’, since these units are communicated more eas-ily than for instance VDV, which is expressed in the non-intuitive unitm/s1.75. Finally, as highlighted in the beginning of this chapter, it is cru-cial that evaluation measures are clearly defined, so that the outcome ofthe analysis does not rely on the analyst’s judgement.

Historically, a number of attempts to formulate a single-figure statist-ical measure for quantification of acceleration exposures with signific-ant shock content have been made. For example, peak fraction averagessuch as the average of the 1/10th or 1/100th largest acceleration peakvalues (a1/10 and a1/100) are common in structural design but have alsobeen used to evaluate ride comfort, for example by Riley et al [49]. Asimilar approach is the Impact Count Index, proposed by Dobbins et al[50]. However, these measures give no information regarding the topmagnitudes or statistical distribution of peak values. Neither are theydefined with respect to sample duration nor the number of peaks in-cluded in the analysis. This makes the results ambiguous and difficultto interpret and reduces the possibilities to successfully compare results.As an example, consider the acceleration signal in Figure 4.1. The accel-eration sample was measured on the HSC unit of the Swedish CoastGuard displayed in the same figure.

0 200 400 600−40

−20

0

20

40

Time [s]

Acce

lera

tion

[m/s

2 ]

Figure 4.1: Acceleration signal measured upon the coxswain seat onboard the 10meters HSC shown in the figure. Photo: Jonas Andersson, The Swedish Coast-guard.

In order to calculate fractional peak value averages, the peak valuesof the acceleration signal must first be identified. In this example, the

31


predefined Matlab command f indpeaks is used, with an accelerationthreshold equal to the standard deviation of the signal and a minimumpeak distance equal to 0.85 times the sampling frequency, which was 800Hz. The result is 630 identified peaks. By sorting these peaks in orderof magnitude, the cumulative distribution of the observed data can bedrawn; see Figure 4.2.

Time [s]0 100 200 300 400 500 600 700

Acce

lera

tion

[m/s

2 ]

-50

0

50

Acceleration [m/s2]0 10 20 30 40

F

0

0.2

0.4

0.6

0.8

1

Figure 4.2: Acceleration signal with 630 identified peaks and the correspondingempirical cumulative distribution.

The 1/Nth fractional peak value average is then calculated as the meanvalue of the 1/N largest peaks in the collection. Thus, in this particu-lar case, the a1/10 and a1/100 is the mean value of the largest 63 and thelargest 6 peaks respectively, which is 20.6 m/s2 and 30.8 m/s2. The ac-curacy of a measure such as a1/100, calculated based on only 6 points, isof course doubtful. To be accurate, a significantly larger amount of peaksis needed. In addition, the peak value averages do not capture any ef-

32


fects of variations in the signal. As an example, consider the accelerationsignal in Figure 4.1 again. As seen, the magnitude is on average higherin the first half of the signal. However, if the second half of the signalhad the same level as the first, as illustrated in Figure 4.3, the numberof identified peaks would have been 620 and the peak fraction averagesa1/10 and a1/100 would have been 23.5 m/s2 and 33.7 m/s2. Thus the dif-ference between the two signals in Figure 4.2 and Figure 4.3 is very smallif the a1/10 and a1/100 are considered. However, any crew exposed to thetwo signals would most likely experience the accelration of Figure 4.3more severe than the acceleration of Figure 4.2. Hence, it is clear that theacceleration peak fraction average gives information neither regardingthe largest peak value in the data collection, nor the quantity and mag-nitude (i.e. the statistical distribution) of large peaks; information thatis of particular interest when assessing loads that the craft or human aresubjected to.

Time [s]0 100 200 300 400 500 600 700

Acce

lera

tion

[m/s

2 ]

-50

0

50

Figure 4.3: Acceleration signal with 620 identified peaks.

A powerful method when searching for the largest loads that the crewwill be subjected to during a certain exposure time period, is to fit astatistical distribution to the empirical collection of peak values. Thisenables extreme values such as the most probable largest value duringX hours or the largest value to be exceeded within 1% of probabilityto be determined, even for a time period longer than for the availabledata set (extrapolated extreme values). The accuracy of the calculatedextreme value will naturally depend on the accuracy of the fitting. Theselection of distribution function is therefore critical. In addition, de-cisions related to the collection and processing of acceleration data, e.g.sampling rate and duration, filtering and peak identification, influencethe final result.

33


When analysing acceleration of planing high-speed craft, the procedureof determining extreme values is not obvious. HSC acceleration impactsare caused by different physical mechanisms and generally belong toseveral statistical distributions. To perform an analysis of good accur-acy, these mechanisms must be understood. In Paper C [5], an extens-ive amount of simulated craft acceleration time series for systematicallyvaried speeds and sea states are investigated in order to improve theunderstanding of the complex acceleration process that high-speed craftoperation is associated with. The investigations result in important con-clusions regarding sample size, sampling rate, filtering and peak iden-tification. For example, it is concluded that low-pass filtering below 20Hz will adversely affect the results; see Figure 4.4 where the effect oflow-pass filtering with cut-off frequency 20 Hz and 10 Hz is illustrated.

225 230 235 240 245 250Acce

lera

tion

[m/s

2 ]

-50

0

50

100

150

Time [s]233.2 233.3 233.4 233.5 233.6 233.7 233.8Ac

cele

ratio

n [m

/s2 ]

-500

50100150

Cut-off 10 HzCut-off 20 HzUnfiltered

Figure 4.4: Illustration of the effect of low-pass filtering with cut-off frequency 10Hz and 20 Hz, using a Butterworth filter of 8th order. The studied accelerationsignal corresponds to a 10.5 meter high-speed combat boat of 6500 kg, simulatedat constant speed (21.7 m/s) in rough sea (1.0 m significant wave height and 3.58s wave period). The peak fraction average a1/100 for the three signals are: 96.5m/s2 (unfiltered), 93.4 m/s2 (cut-off 20 Hz) and 75.3 m/s2 (cut-off 10 Hz).

The paper also presents two stringently defined methods for determina-tion of extreme values. A Weibull and a Generalized Pareto distribution

34


are fitted to the empirical data set using automated fitting threshold se-lections. Both two methods work well and enable analysis of large datasets with good reproducibility and almost completely removes subject-ive analyst judgement. An overview of these methods are given in thefollowing section. Further details are found in Paper C [5].

4.2.1 Extreme value predictions using the Weibull andGeneralized Pareto Distributions

According to Ochi [51] the short-term cumulative distribution functionfor a sample of independent and identically distributed data, F(x), isrelated to the cumulative distribution of the extreme values, Fe(x), as

Fe(x) = Fn(x) (4.5)

where n is the number of identified peaks and related to the exposuretime T. The probability α that an extreme load Xe exceeds a certain valueof x can then be formulated as

P(Xe > x) = α = 1− F(x)n (4.6)

Using Taylor expansion and assuming α << 1, Equation 4.6 can be ex-pressed as

1− F(x) =α

n(4.7)

Ochi [51] also shows that the most probable largest value (MPL) for asample of independent and identically distributed data can be estimatedby solving

1− F(x) =1n

(4.8)

given that n is large. Consequently, the extreme value with a certainprobability of being exceeded as well as the MPL value can be calculatedif the cumulative distribution function for the short-term responses canbe determined.

When aiming for extreme value predictions, modelling of the largestvalues, i.e. the tail of the distribution, is of particular interest. This is

35


typically done by fitting all values above a certain threshold, in this textreferred to as the fitting threshold, to a given family of distributions. Ac-cording to the extreme value theorem (Fisher & Tippett [52], Gnedenko[53]), the maximum of a sample of independent and identically distrib-uted variables can only converge to one of the three Generalized Ex-treme Value (GEV) distributions; the Gumbel, Fréchet or Weibull dis-tribution. For high-speed craft responses the preferred distribution hasbeen the Weibull distribution (see e.g. [42, 54, 55]), which cumulativedistribution function is given by

F(x) = 1− e(−x/a)b(4.9)

where a and b is the scale and shape parameter respectively.

The choice for the Generalized Pareto Distribution (GPD) in Paper C [5]derives from the peak over threshold method (POT). The POT-method isbased on Pickand’s theorem, stating that if the parent distribution F(x)is in the domain of attraction of one of the GEV distributions, the dis-tribution of peaks exceeding a threshold, i.e. the conditional excess dis-tribution function, is well approximated by the Generalized Pareto Dis-tribution if the threshold is high enough. The cumulative GPD is givenby

G(x; c, λ) =

{1− (1 + cx/λ)−1/c if c 6= 01− ex/λ if c = 0

(4.10)

where c and λ is the shape and scale parameter, respectively. The distri-bution of the tail of F(x) is given by G(x; c, λ) if

Fu(x) =F(x)− F(ugpd)

1− F(ugpd), x > ugpd and ugpd → ∞ (4.11)

where ugpd is the fitting threshold. By rewriting Equation 4.11 the un-known CDF can be expressed as

F(x) = Fu(x)(1− F(ugpd)) + F(ugpd) (4.12)

A large benefit of the POT method is that the mathematical properties ofthe GPD can be used to guide the threshold selection. These propertiesare used to formulate an automated threshold selection algorithm in Pa-per C [5] and listed below.

36


Properties of GPDGiven that the sampled peak values follow a Generalized Pareto Distri-bution, for increasing threshold ugpd

• the shape parameter remains constant,

• the scale parameter develops linearly as a function of ugpd, and

• the mean of the peaks above the threshold ugpd develops linearlywith a slope of c/(1− c).

No similar properties exist for the Weibull distribution, which explainsthe difficulty of selecting an appropriate fitting threshold when usingthe Weibull approach. In Paper C [5], an automated algorithm is definedby formulating an optimization problem that minimizes the 1− R2 stat-istic. Both the Weibull and GPD approach result in good fits of the dis-tributions to the observed data and predict the extreme values well. TheGPD approach, however, requires larger samples in order to achieve thesame level of uncertainty as the Weibull approach. It is concluded thatsample durations of 1200 s is required for convergence of the most prob-able extreme values, based on the studied conditions.

Figure 4.5 shows the most probable largest values (MPL) based on thePOT method and the Weibull approach compared with the accelerationpeak value averages a1/10 and a1/100. Also the influence of the thresholdselection for the peak identification is illustrated, with the standard de-viation of the signal as starting point, as suggested by Riley et al [56].As can be seen, the average of the 1/10th and 1/100th largest accelera-tion peak values are significantly lower than the MPL values. Based onthe data set in Paper C [5], it is concluded that the relation between theextreme values and the peak fraction averages is consistent for all condi-tions. This is important since it makes this type of measure less ambigu-ous. The fact that the acceleration peak fraction averages converge fastand are straight-forward in their derivation makes the measures power-ful for instance in ship design, despite the discussed weaknesses relatedto the measure. However, as seen in Figure 4.5, the acceleration peakfraction averages is strongly related on the peak identification threshold.This implies that a common standard for the peak identification proced-ure, as suggested by Riley et al [56], is a prerequisite. Finally, to be suit-able for evaluation of risk for injuries, the measures have to be related tothe human endurance and to exposure duration.

37


0

10

20

30

40

50

60

70

80

a1/10 a1/100 MPL3h WBL MPL3h GPD

Acce

lera

tion

[m/s

2 ]

0.5m0.75m1m1.25m1.5m

0

10

20

30

40

50

60

70

80

a1/10 a1/100 MPL3h WBL MPL3h GPD

Acce

lera

tion

[m/s

2 ]

0.5Te0.75Te1Te1.25Te1.5Te

Figure 4.5: Peak fraction averages (aa/10 and aa/100) and extreme values (MPL3h)based on Weibull and GPD approach. The acceleration threshold used for peakidentification is varied between 0.5σ and 1.5σ, where σ is the standard deviationof the acceleration.

38

5Risk analysis basedon injury statistics

This chapter elaborates on a concept, i.e. not a complete method, for analternative approach to estimate risks for adverse health effects amongthe crew of high-speed boats. The approach is based on injury (healthproblem) statistics, and may become a useful complement to simulation-based assessment of working conditions. Evaluating working condi-tions using statistical data has the advantage of actually enabling risksto be determined. As discussed in Section 4.1, there is yet no quantitat-ive relationship between vibration exposure and risk of adverse healtheffects. The following approach may therefore be of particular interestin organizational planning, e.g. when aiming to identify, reduce and/oreliminate potential health risks.

5.1 Preliminary Hazard Analysis

Risk analysis is a concept used within a large variety of fields and ap-plications. It can be used to estimate the risk of a failure in a system,project or organization, or to estimate the risk of accidents in a tunnel orat a certain workplace. In such cases, risk is usually defined as a functionof the likelihood of an unwanted event to occur and the consequences ofthe same event. As a first step in the risk analysis process, a PreliminaryHazard Analysis (PHA) can be used (see for example [57]). In principle,the PHA is based on identification of all potential unwanted events in asystem, and ranking of the corresponding risks. Risks can be ranked bygrading the likelihood and the consequence of each event using a scalefrom 1-5, for example as in Table 5.1, and calculating the risk as a func-tion of probability and consequence. Note that risk can be mitigated

39

CHAPTER 5. RISK ANALYSIS BASED ON INJURY STATISTICS

both by reducing the likelihood and the consequences of the unwandedevent.

Table 5.1: Grading levels for estimation of probability and consequence of an event.

Probability Consequence1. Very unlikely 1. Minor2. Unlikely 2. Moderate3. Possible 3. Significant4. Likely 4. Severe5. Very likely 5. Very severe

The aim of the PHA is to identify the largest risks in a system, in order tofind out how to focus the proceeding steps of the analysis and to selectappropriate means of controlling or eliminating the risks. According to[57], a PHA should include:

• experience data

• a list of known hazardous events

• measures taken to eliminate/minimize hazardous events

• requirements as a result of identified hazardous events

• recommended countermeasures, in order to eliminate/minimizehazardous events

Here, a simplified PHA is performed in order to illustrate the method-ology. Table 5.2 shows an example where a number of injury risks forHSC operators have been ranked using the injury statistics presentedin Ensign et al [2] (see also Chapter 2). The risk r is here defined asthe product of the estimated probability p and consequence c. As canbe seen, the largest risks are found for low back disorders. Based onthis knowledge, it is reasonable to proceed the risk analysis with a re-fined analysis of this particular injury. However, the results also showclearly that the personnel of HSC are exposed to several significant in-jury risks. The probability of acute and chronic injuries to the head,knees, neck and upper back are for example estimated to be either verylikely (head, chronic) or possible with reference to Table 5.1. Although theconsequences of these injuries are perhaps not as severe as an injury to

40

5.2. RISK OF LOW BACK INJURIES

the lower back may be, they are of importance for the safety onboard asthey influence the crew’s working performance and/or working capa-city.

Table 5.2: Ranking of potential injuries for operators of HSC, based on data from [2].

Injury location Probability, p Consequence, c Risk, p · cKnee 3 3 9Low back 4 5 20Shoulder 2 3 6Leg 2 3 6Head (chronic) 5 2 10Head (acute) 1 5 5Neck and upper back 3 3 9

The following section aims to illustrate how the risk analysis can pro-ceed after a first coarse analysis. A refined analysis of the risk for lowback injuries is performed using the injury statistics of Ensign et al [2].The results are compared with those achieved using the methods of ISO2631-5 [44].

5.2 Risk of low back injuries

The solid line in Figure 5.1 shows the percentage of the participants inthe study of Ensign et al [2] that were injured at least once after x yearsin duty. Out of the 154 participants, only 30 were still working on HSCafter six years. This may be an explanation to the decrease in injury oc-currence after six years of duty seen in Figure 5.1. Another explanationto this decrease may be increased working experience and habituation,although it is more likely that the occurence of injuries increases in aver-age with the time of duty. The dashed line in Figure 5.1 shows an expo-nential function fitted to the empirical data of Ensign et al [2]. Based onthis curve fitting, the likelihood for a HSC crew member to be injuredcan be expressed analytically as

Pinjury = 1− 0.73x (5.1)

where x is the number of years in duty.

41


Years in duty, x0 2 4 6 8 10 12 14Sh

are

of H

SC o

pera

tors

that

wer

e in

jure

d

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 5.1: Share of HSC operators that were injured at least once as functionof years in duty. Statistical injury data (solid line) and analytical estimation(dashed line).

Out of the 149 reported injuries, 33% (50) were low back injuries. Thus,the probability of low back injury can be estimated as

Plowbackinjury = 0.33 · Pinjury (5.2)

Among the 149 reported injuries, 11 were of the type disc problems. As-suming that all these are connected to the low back (which is not certain),a rough but reasonable estimation is that 20% of the low back injuries areacute and 80% are chronic. Based on this assumption, the risk of acuteand chronic lowback injury is given by

Plowbackinjury,acute = 0.2 · PlowbackinjuryPlowbackinjury,chronic = 0.8 · Plowbackinjury

(5.3)

Figure 5.2 shows the probability of acute and chronic injuries to the lowback as function of years in duty, calculated using Equation 5.3. Afterfive years, the probability for an acute injury is 5 %, which must be con-sidered as high risk (since acute injuries to the back have severe con-sequences).

42

5.2. RISK OF LOW BACK INJURIES

Years in duty0 2 4 6 8 10 12 14

Prob

abilit

y

0

0.05

0.1

0.15

0.2

0.25

0.3Acute or chronicAcuteChronic

Figure 5.2: Probability of low back injury for personnel on HSC.

For comparison, Figure 5.3 shows the risk factor R defined in ISO 2631-5[44] for evaluation of risk for acute lumbar spine injury. The R factor iscalculated for a person initiating duty at the age of 20 and travelling at45 knots in relatively rough sea conditions (Hs = 0.65 m, Tz = 3.5 s) 12.5minutes a day, 45 days a year. 10 combinations of seat configurationsand running attitudes are compared (see Paper B [4] for further details).

Age of person [years]25 30 35 40 45 50

Rz-v

alue

[-]

0.5

1

1.5

2

2.5

3 k1 = 5000 N/m (Boat 1)k1 = 7500 N/m (Boat 1)k1 = 15000 N/m (Boat 1)k1 = 25000 N/m (Boat 1)k1 = 35000 N/m (Boat 1)k1 = 5000 N/m (Boat 2)k1 = 7500 N/m (Boat 2)k1 = 15000 N/m (Boat 2)k1 = 25000 N/m (Boat 2)k1 = 35000 N/m (Boat 2)Low riskHigh risk

Figure 5.3: Risk of lumbar spine injury according to ISO 2631-5 [44] for a personinitiating HSC duty at the age of 20 and travelling at 45 knots in relatively roughsea conditions (Hs = 0.65 m, Tz = 3.5 s) 12.5 minutes a day, 45 days a year. Redline indicates high risk, green line low risk. For further details, see Paper B [4].

43


As can be seen, the risk for acute injuries to the lumbar spine is highafter 1-15 years of duty, depending on load case and seat configuration.Assuming that HSC suspension seats have a spring stiffness coefficientaround 25000 N/m (which was the case for the instrumented seat in Pa-per A [3]), then high risk is reached after only 1-5 years. This result iscomparable with the results in Figure 5.2, which indicated a 5 % prob-ability of acute low back injury after 5 years in duty.

In addition to the refined analysis of the risks for lumbar spine injury,a refined consequence analysis may be desirable in order to enable im-plementation of suitable risk management. For an employer within thefield of HSC, it may for instance be of interest to evaluate the probab-ility for sick leave or reduced working performance for the employees,as function of years of duty. Given that the probabilities for these con-sequences can be estimated, either based on statistics or expert opinion,the likelihood for different consequences can be estimated as functionof years of duty using the probability of injury, Pinjury. However, forhealth effects or consequences from which recovery is possible, for in-stance through periods of rest, it is not relevant to evaluate for a longerhorizon than perhaps a day.

The present chapter illustrates the principles of an alternative approachfor evaluation of HSC crews’ risks for adverse health effects. The ex-amples given are based on a very limited amount of statistical data, andthe reader should rather pay attention to the presented methodologythan to the absolute values obtained. The concept of performing riskanalysis based on injury statistics can be advantageous and may be auseful complement to the presented simulation-based approach, whichrequires specification of for example craft operational profile, load caseand seat configuration to generate acceleration time series. In addition,the possibility to estimate risks for injuries and adverse health effectsbased on this acceleration data is currently limited.

To achieve accurate and useful results using the presented risk analysisapproach, extensive and adequate statistical data are required. The bestresults will be achieved if the statistical data are based on the same typeof operation as is in question for the HSC system being assessed. Thus,to introduce the risk analysis approach in practice, more statistical dataon injuries, health problems (e.g. fatigue, motion sickness) and otherconsequences (e.g. reduced working performance) are needed.

44

6Summary &conclusions

The thesis adresses the need for a simulation-based method for predic-tion and evaluation of HSC crew acceleration exposure. The main con-tributions of the work are:

• Development of a numerical seat model validated using full-scale,acceleration data (Paper A [3]).

• Development of a simulation-scheme that enables prediction andevaluation of working conditions on HSC (Paper B [4]).

• Development and evaluation of clearly defined methods for char-acterization and statistical analysis of the vertical acceleration pro-cess for planing HSC (Paper C [5]).

• Recommendations related to the acquisition of acceleration datafor HSC, such as sample size, sampling rate and cut-off frequency(Paper C [5]).

6.1 Conclusions

A single-degree of freedom, mechanical seat model, consisting of a seatrepresentation and a representation of the seated human body, can beused to predict the seat acceleration time series with high accuracy. Ageneralized apparent mass model considering the human body massbut neglecting other variations between individuals appear to be de-tailed enough to reflect the feedback of the human response to the seat.

45

CHAPTER 6. SUMMARY & CONCLUSIONS

Numerous evaluation measures appropriate for HSC acceleration ex-posures are available. What the most suitable measure is, depends onthe purpose of the analysis. For instance, the craft designer may be in-terested in extreme values, wheras the employer may be more interestedin long-term doses. The VDV has the advantage of capturing the effectof both vibration and shock, which is relevant for HSC where the con-ditions vary over time. The interpretation of the levels, however, is notclear since there is yet no dose-effect relationship linking the measure tothe risk for adverse health effects. Nevertheless, VDV is a useful com-parative measure and may in the future be better linked to the risk forinjuries. To increase the credibility and in order be more appropriate forapplications where the exposures vary significantly, the measure withcorresponding evaluation limits may possibly be defined with respectto exposure duration.

The Sed measure evaluates the risks of lumbar spine injuries, but is onlyvalid for acceleration levels up to 4 g. However, with reference to ongo-ing research, the method is expected to be developed for higher accel-eration levels in a quite near future. In addition to Sed, extreme valuespredicted using e.g. the Weibull or Generalized Pareto distribution islikely to be useful for evaluation of risk for acute injuries, given thathuman endurance can be linked to the measures. The two alternativeapproaches proposed in Paper C [5] are clearly defined and describe thedistribution of peak values well. In addition, the dependence on analystjudgement is reduced. Since the methods are applicable when evaluat-ing loads on both human and hull structure, they are particularly suit-able when aiming to introduce human factors in HSC design. Extremevalues can also be used in requirement specification or to describe theperformance of e.g. a HSC or a suspension seat.

The accuracy of the results of the evaluation of crew acceleration ex-posure is strongly dependent on the accuracy of the operational profile.A realistic, although generalized, operational profile enables determ-ination of efficient and suitable craft designs, mitigation systems andoperational actions. To properly specify the operational profile, goodknowledge of how HSC actually is operated is necessary; however, thisknowledge is today often lacking.

Introducing a simplified approach for evaluation of working conditionsbased on traditional risk analysis methodologies and injury statistics

46

6.2. FUTURE WORK

may be useful as a complement to the simulation-based approach. Riskanalysis based on injury statistics can be performed without definingdetails regarding e.g. craft design or operational profile, but naturallyrequires statistical data of health problems among HSC personnel. Todate, there is not sufficient data for such an approach to be useful, butas soon as more data are available, the approach may be useful to helpfocusing future actions to improve working conditions and to developappropriate assessment methods. As the crew of HSC may experiencehealth problems caused by vibration and shock as well as other factorseventually causing physical or mental fatigue (e.g. navigation at night),it is recommended that the prevalence not only of acute injuries, but ofall types of health problems, is investigated. This should also be kept inmind when choosing and developing evaluation methods.

Finally, it should be remembered that the work within this thesis aimsfor improved working conditions on HSC with the focus of reducingacceleration exposures. To reach the long-term goal of safe and effi-cient HSC, all means to improve the working conditions are needed.A holistic approach is desirable, meaning that measures to evaluate andactions to improve the crew’s situation in a broader perspective, withfocus not only on (reduced) acceleration levels, are needed. As an ex-ample, limiting the crew’s time of operation in darkness may result inreduced risks for mental fatigue. Similarly, the risks of physical andmental fatigue (which can cause injuries in the long term) may be re-duced by preparation, health examination, physical training and peri-ods of rest. Furthermore, other measures to evaluate the performance ofthe technical system than those covered by this thesis may be useful; forexample measures for estimating the risk for motion sickness or motioninduced interruptions.

6.2 Future work

With reference to the conclusions, the following three research areashave been identified to be of particular interest when aiming for safeand efficient HSC by improved working conditions.

HSC’s actual useThe better description of the craft actual operational profile, the better

47

CHAPTER 6. SUMMARY & CONCLUSIONS

decisions are possible to make regarding craft design, mitigation sys-tems and operational actions. By collecting long-term measurements ofcraft acceleration, e.g. using permanent measurement systems, know-ledge about the actual use of different HSC can be gained. With thispurpose as well as for real-time feedback to the crew, the Swedish CoastGuard in cooperation with KTH is since 2013 continuously collectingdata from several HSC units. This data will be used in coming researchand will improve the picture of the actual conditions at sea. Data fromthe first instrumented unit is presented in De Alwis [10].

Seat model developmentBottoming-out events can result in severe acceleration peaks that arehazardous for the occupant. Modelling the seat’s end-stop is thereforehighly recommended in order to improve the accuracy of the predictedacceleration exposure for the crew.

As several experimental studies have indicated that suspension seats insome situations amplifies the acceleration levels, investigating the effectof the seat cushion would be of great interest. Depending on the out-come, it may become relevant to include the seat cushion in the seatmodel.

Due to the practical aspects limiting the lowest possible spring stiffnessof the seat, it may be of interest to expand the seat model to a largersuspension system, isolating not only the crew, but also larger compart-ments, from accleration. It is likely that a larger motion stroke may be al-lowable for a larger suspension system, which increase the possibilitiesto mitigate acceleration of a wider range of frequencies or magnitudes.

Prevalence of health problems among HSC operatorsExamining the prevailing health problems on HSC, caused by vibration,shock or other factors, is a key factor in order to succeed in reachingimproved working conditions. Research cooperation initiatives for aprevalence/incidence survey on musculoskeletal pain and the relatedrisks to personnel at sea, is now taken by KTH and Karolinska insti-tutet. The research includes development and validation of a web-basedquestionnaire and is expected to enable identification of risk factors for;injuries or adverse health effects, performance impairment or for jeop-ardizing safety at sea. Based on this knowledge, risk reducing actionscan be focused appropriately. A questionnaire study may also improve

48

6.2. FUTURE WORK

the knowledge about a crew’s actual exposure, which enables the crewexposure profile to be defined with better precision.

Finally, there is a need to link current evaluation measures to humanendurance. For measurable health effects, simultanous measurementson craft and human may be a viable way to link the effects to variousexposure types and levels.

49

7Summary ofappended papers

Paper A - Prediction and evaluation of workingconditions on high-speed craft using suspension seatmodelling

K. Olausson and K. Garme, Proceedings of the Institution of Mechanical En-gineers, Part M: Journal of Engineering for the Maritime Environment, pub-lished online before print, January 2014

Severe working conditions on board high-speed craft adversely affectnot only the safety, health and performance of the crew but also the per-formance of the vessel as a technical system. Human factors–based shipdesign combined with appropriate vibration mitigation techniques andwork routines for the crew can improve the working conditions and re-duce the risks for performance degradation and adverse health effects.To enable development and use of such means, methods for predictionand evaluation of working conditions are needed for both existing high-speed craft and craft under design. This article presents a 2-degree-of-freedom seat model compatible with both measured and simulated in-put data. The interaction between seat and human is treated using theconcept of apparent mass. The model is validated against experimentdata collected on board a 10-m, 50-knot high-speed craft equipped withhigh-standard suspension seats. Evaluation measures defined in ISO2631-1 and ISO 2631-5 are used to compare experiment data to modelleddata. The seat model slightly overestimates the experiment Sed dose bya mean of 6.5% and underestimates the experiment vibration dose value(8 h) by 4.0%. It is concluded that model data correlate well with exper-iment data.

51

CHAPTER 7. SUMMARY OF APPENDED PAPERS

Paper B - Simulation-based assessment of HSC crewexposure to vibration and shock

K. Olausson and K. Garme, In Proceedings of the 12th International Conferenceon Fast Sea Transportation (FAST2013), Amsterdam, Netherlands, December2013.

A simulation-based method for assessment of HSC crew vibration andshock exposure is presented. The simulation scheme includes three mod-ules: Craft response module, Seat response module and Human expos-ure evaluation module. The first module computes the craft accelerationin the time-domain by a non-linear strip method and delivers input tothe second module, where a crew seat model determines the human ac-celeration exposure time history. The crew’s acceleration exposure isassessed in the third module, which includes a strategy to describe theoperational profile. The human vibration exposure is evaluated usinginternational standards (ISO 2631-1, ISO 2631-5). In addition, statist-ical extreme value analyses are used to evaluate the human exposure toshock. The potential to reduce the vibration and shock level is discussedand exemplified using the simulation-based evaluation method to ana-lyse how different seat designs and running attitudes influence the crewvibration exposure.

Paper C - On High-Speed Craft Acceleration Statistics

M. Razola, K. Olausson, A. Rosén and K. Garme, preprint paper, January 2015.

This paper presents an extensive set of acceleration data for a smallhigh-speed craft that is generated using a nonlinear strip method. Craftspeeds and sea states are systematically varied and simulations extendto three hours. The data set is used to establish and evaluate methodsfor calculation of acceleration statistics, for example used in design loadprediction and crew safety evaluation. The Standard-G approach foridentification of peak values is evaluated and two alternative methodsfor fitting of analytical distribution functions to the acceleration datais established and evaluated. The Weibull distribution and the Gener-alized Pareto distribution are used. The established methods are ap-plied on the simulation data and a number of aspects are clarified anddiscussed, such as the general characteristics of high-speed craft accel-erations, slamming time scales, statistical convergence, and the rela-

52

tion between the peak fraction averages and the actual extreme val-ues. It is for example concluded that calculation of the average of thelargest 1/10th and 1/100th peak acceleration values converge for 300and 600 acceleration peaks respectively. Further, it is shown that scal-ing of the average peak acceleration using the exponential distributionis erroneous. The most probable largest acceleration values require sig-nificantly larger samples to converge. For the conditions studied in thispaper 2400 s of nonlinear simulations are required. Important resultsrelated to sampling and filtering of the vertical acceleration process arealso presented. It is for example concluded that for craft of similar sizeas that studied in the paper sampling should be performed with a periodof less than 0.01 s and low-pass filtering with cut-off frequency of no lessthan 20 Hz.

53

References

[1] S. D. Myers, T. D. Dobbins, S. King, B. Hall, R. M. Ayling, S. R.Holmes, T. Gunston, and R. Dyson. Physiological consequencesof military high-speed boat transits. European Journal of AppliedPhysiology, 111(9):2041–2049, 2011.

[2] W. Ensign, J. A. Hodgdon, W. K. Prusaczyk, S. Ahlers, D. Shapiro,and M. Lipton. A survey of self-reported injuries among specialboat operators. Naval Health Research Center, Report No. 00-48,San Diego, California, USA, 2000.

[3] K. Olausson and K. Garme. Prediction and evaluation of workingconditions on high-speed craft using suspension seat modelling.Proceedings of the Institution of Mechanical Engineers, Part M: Journalof Engineering for the Maritime Environment, published online beforeprint, January 2014.

[4] K. Olausson and K. Garme. Simulation-based assessment of HSCcrew exposure to vibration and shock. In Proceedings of the 12th In-ternational Conference on Fast Sea Transportation (FAST2013), Decem-ber 2013.

[5] M. Razola, K. Olausson, K. Garme, and A. Rosén. On High-SpeedCraft Acceleration Statistics, preprint paper, January 2015.

[6] Picture from www.ullmandynamics.com.

[7] K. Garme, L. Burström, and J. Kuttenkeuler. Measures of vibrationexposure for a high-speed craft crew. Proceedings of the Institution ofMechanical Engineers, Part M: Journal of Engineering for the MaritimeEnvironment, 225(4):338–349, 2011.

55

REFERENCES

[8] S. D. Myers, T. D. Dobbins, S. King, B. Hall, S. R. Holmes, T. Gun-ston, and R. Dyson. Effectiveness of Suspension Seats in Main-taining Performancce Following Military High-Speed Boat Trans-its. Human Factors: The Journal of the Human Factors and ErgonomicsSociety, 54(2):264–276, 2012.

[9] N. J. Mansfield. Human response to vibration. CRC Press, 2005.

[10] P. De Alwis. Methods for shock and vibration evaluation appliedon offshore power boats (Master’s Thesis). KTH Royal Institute ofTechnology, 2014.

[11] N. C. Townsend, T. E. Coe, P. A. Wilson, and R. A. Shenoi. Highspeed marine craft motion mitigation using flexible hull design.Ocean Engineering, 42:126–134, 2012.

[12] C. Liam. Testing and Modeling of Shock Mitigating Seats for HighSpeed Craft (Master’s Thesis). Virginia Polytechnic Institute andState University, 2011.

[13] K. Garme, A. Rosén, I. Stenius, and J. Kuttenkeuler. Rough waterperformance of lightweight high-speed craft. Proceedings of the In-stitution of Mechanical Engineers, Part M: Journal of Engineering for theMaritime Environment, 228(3):293–301, 2014.

[14] DNV. Rules for Classification of High Speed, Light Craft and NavalSurface Craft. Det Norske Veritas, 2013.

[15] ABS. Rules for building and classing high-speed craft. AmericanBureau of Shipping, 2013.

[16] M. Razola, A. Rosén, K. Garme, and K. Olausson. TowardsSimulation-Based Structural Design of High-Speed Craft. In Pro-ceedings of the Fourth Chesapeake Power Boat Symposium, Annapolis,Maryland, June 2014.

[17] M. Razola, A. Rosén, and K. Garme. Experimental evaluation ofslamming pressure models used in structural design of high-speedcraft. International Shipbuilding Progress, 61:17–39, 2014.

[18] M. Razola, A. Rosén, and K. Garme. Allen and jones revisited.Ocean Engineering, 89:110–133, 2014.

56

REFERENCES

[19] R. Peterson, E. Pierce, B. Price, and C. Bass. Shock Mitigation forthe Human on High Speed Craft: Development of an Impact InjuryDesign Rule. In Proc RTO AVT Symposium on Habitability of Combatand Transport Vehicles: Noise, Vibration and Motion, Prague, CzechRepublic, 2004.

[20] D. M. Schleicher and D. L. Blount. Research Plan for the Investiga-tion of Injury and Fatigue Criteria for Personnel Aboard High Per-formance Craft. In Proceedings of the Second Chesapeake Power BoatSymposium, Annapolis, Maryland, March 2010.

[21] Directive 2002/44/EC of the European Parliament and of the Coun-cil of 25 June 2002 on the minimum health and safety requirementsregarding the exposure of workers to the risk arising from physicalagents (vibration) (sixteenth individual Directive within the mean-ing of Article 16(1) of Directive 89/391/EEC). Official Journal of theEuropean Communities, L 177:13–19, 2002.

[22] A. W. S. Leung, C. C. H. Chan, J. J. M. Ng, and P. C. C. Wong. Factorscontributing to officers’ fatigue in high-speed maritime craft oper-ations. Applied Ergonomics, 37:565–576, 2006.

[23] M. J. Griffin. Handbook of Human Vibration. Elsevier Academic Press,1990.

[24] L. Burström, T. Nilsson, and J. Wahlström. Arbete och helkropps-vibrationer - hälsorisker. Arbetsmiljöverket Rapport 2011:8. ISSN1650-3171, 2011.

[25] P. Lazarus. Analyzing Accelerations, Part 1. Professional BoatBuilder,140:34–47, 2013.

[26] S. C. Stevens and M. G. Parsons. Effects of Motion at Sea on CrewPerformance: A Survey. Marine Technology, 39(1):29–47, January2002.

[27] B.-O. Wikström, A. Kjellberg, and U. Landström. Health effects oflong-term occupational exposure to whole-body vibration: A re-view. International Journal of Industrial Ergonomics, 14:273–292, 1994.

[28] B. Cripps, S. Rees, H. Phillips, C. Cain, D. Richards, and J. Cross.Development of a crew seat system for high speed rescue craft. InProceedings of the 7th International Conference on Fast Sea Transporta-tion (FAST2003), 2003.

57

REFERENCES

[29] E. E. Zarnick. A Nonlinear Mathematical Model of Motions of aPlaning Boat in Regular Waves. David Taylor Naval Ship Researchand Development Center, DTNSRDC-78/032, 1978.

[30] R. H. Akers. Dynamic Analysis of Planing Hulls in the VerticalPlane. Presented at the April 29, 1999 meeting of the New EnglandSection of The Society of Naval Architects and Marine Engineers,29 April 1999.

[31] J. A. Keuning. The Nonlinear Behavior of Fast Monohulls in HeadWaves. Diss., Delft University of Technology, Faculty of Mechan-ical Engineering and Marine Technology. ISBN 90-370-0109-2, 1994.

[32] K. Garme. Modeling of Planing Craft in Waves. Diss., KTH RoyalInstitute of Technology. ISBN 91-7283-861-2, 2004.

[33] T. Gunston. The development of a suspension seat dynamic model.Presented to the 33rd meeting of the U.K. Group on Human Re-sponse to Vibration, Buxton, England, 16-18 September 1998.

[34] Xiao Qing Ma, Subhash Rakheja, and Chun-Yi Su. Damp-ing requirement of a suspension seat subject to low frequencyvehicle vibration and shock. International Journal of Vehicle Design,47(1/2/3/4):133–156, 2008.

[35] J. Rebelle. Development of a numerical model of seat suspension tooptimise the end-stop buffers. Paper presented at the 35th UnitedKingdom Group Meeting on Human Responses to Vibration, Uni-versity of Southampton, Southampton, England, 13-15 September2000.

[36] I. Maciejewski, L. Meyer, and T. Krzyzynski. Modelling and multi-criteria optimisation of passive suspension vibro-isolating proper-ties. Journal of Sound and Vibration, 324:520–538, 2009.

[37] T. E. Coe, J. T. Xing, R. A. Shenoi, and D. J. Taunton. A simplified3-D human body-seat interaction model and its applications to thevibration isolation design of high-speed marine craft. Ocean Engin-eering, 36:736–746, 2009.

[38] T. Coe, R. A. Shenoi, and J. T. Xing. Human body vibration responsemodels in the context of high speed planing craft and seat isolation

58

REFERENCES

systems. In Proceedings of the sixth international conference on high-performance marine vehicles (HIPER ’08), University of Naples, Naples,Italy, pages 63–69, 18-19 September 2008.

[39] T. E. Fairley and M. J. Griffin. The apparent mass of the seatedhuman body: vertical vibration. Journal of Biomechanics, 22(2):81–94, 1989.

[40] P.-E. Boileau, X. Wu, and S. Rakheja. Definition of a range of ideal-ized values to characterize seated body biodynamic response un-der vertical vibration. Journal of Sound and Vibration, 215(4):841–862,1998.

[41] N. C. Townsend, P. A. Wilson, and S. Austen. What influences rigidinflatable boat motions? Proceedings of the Institution of MechanicalEngineers, Part M: Journal of Engineering for the Maritime Environ-ment, 222:207–217, 2008.

[42] K. Garme and A. Rosén. Time-domain simulations and full-scaletrials on planing craft in waves. International Shipbuilding Progress,50(3):177–208, 2003.

[43] ISO 2631-1:1997. Mechanical vibration and shock – evaluation ofhuman exposure to whole-body vibration part 1: General require-ments. International Organization for Standardization, Geneva,1997.

[44] ISO 2631-5:2004. Mechanical vibration and shock – evaluation ofhuman exposure to whole-body vibration part 5: Method for eval-uation of vibration containing multiple shocks. International Or-ganization for Standardization, Geneva, 2004.

[45] BS 6841-1987. Guide to measurement and evaluation of human ex-posure to whole-body mechanical vibration and repeated shock.British Standards Institution, London, 1987.

[46] D. P. Allen, D. J. Taunton, and R. Allen. A study of shock impactsand vibration dose values onboard high-speed marine craft. Inter-national Journal of Maritime Engineering (RINA Trans. Part A), 150:1–10, 2008.

[47] R. M. Stayner. Whole-body vibration and shock: A literature re-view. RMS Vibration Test Laboratory for the Health and SafetyExecutive, 333/2001, ISBN 0 7176 2004 2, 2001.

59

REFERENCES

[48] C. R. Bass, R. S. Salzar, J. H. Ash, A. A. Ziemba, and S. R. Lucas.Development of Dynamics Models for Assessing Spinal Dynam-ics and Injury from Repeated Impact in High Speed Planing Boats.SAE technical paper series, 2008.

[49] M. R. Riley, T. Coats, K. Haupt, and D. Jacobson. A simplified ap-proach and interim criteria for comparing the ride quality of highspeed craft in rough water. In Proceedings of the Seventh Interna-tional Conference On High-Performance Marine Vehicles, Melbourne,Florida, USA, 13-15 October 2010.

[50] T. Dobbins, S. Myers, R. Dyson, T. Gunston, Stuart King, and Regin-ald Withey. High speed craft motion analysis - impact count index(ICI). In Proceedings of the 43rd United Kingdom Conference on HumanResponses to Vibration, Leicester, England, 15-17 September 2008.

[51] M. K. Ochi. Principles of Extreme Value Statistics and their Ap-plication. Extreme Loads Response Symposium, Arlington, VA,October 19-20 1981.

[52] R. A. Fisher and L. H. C. Tippett. Limiting forms of the frequencydistribution of the largest and smallest member of a sample. Math-ematical Proceedings of the Cambridge Philosophical Society, 24(2):180–190, 1928.

[53] B. V. Gndenko. On a Local Limit Theorem of the Theory of Probab-ility. Uspekhi mat. nauk, 3(25):187–194, 1948.

[54] L. Wang and T. Moan. Probabilistic Analysis of Nonlinear WaveLoads on Ships Using Weibull, Generalized Gamma, and ParetoProbabilistic Analysis of Nonlinear Wave Loads on Ships UsingWeibull, Generalized Gamma, and Pareto Distributions. Journal ofShip Research, 48(3):202–217, September 2004.

[55] L. McCue. Statistics and Design Implications of Extreme Peak Ver-tical Accelerations from Slamming of Small Craft. Journal of ShipProduction and Design, 28(3):112–127, August 2012.

[56] M. R. Riley, K. D. Haupt, and D. R. Jacobson. A Generalized Ap-proach and Interim Criteria for Computing A1/n Accelerations Us-ing Full-Scale High-Speed Craft Trials Data. Naval Surface WarfareCenter, NSWCCD- 23-TM-2010/13, West Bethesda, MD, 2010.

60

REFERENCES

[57] A. Emanuelson and A. Börtemark. The Armed Forces’ Handbookon System Safety 2011 Part 2 - Methods (H SystSäkE 2011). TheArmed Forces’ Security Inspectorate and Swedish Defence MaterielAdministration, M7739-352032 H SYSTSÄK E D2, 2011.

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