structural robustness against accidents

STRUCTURAL ROBUSTNESSAGAINST ACCIDENTS

Franco Bontempi*, Marco Lucidi, Pier Luigi Olmati*PhD, PE, Professor of Structural Analysis and Design

School of Civil and Industrial EngineeringUniversity of Rome La Sapienza

Rome - ITALY

1

introduction

2

LINEAR interactions NONLINEAR

LOO

SE

co

up

lings

TIG

HT

3

4

5

6

7

8

Design Complexity(Optimization)

Loosely – Tightly Couplings (Interactions)

No

nlin

ear

–Lin

ear

Be

hav

ior

9

SYSTEM CONTINGENCY

NatureCharacteristics

Weakness…

NatureCharacteristics

Strengths…

COUPLINGS / INTERACTIONSNONLINEARITY

10

Joh

n B

oyd

du

rin

g th

e K

ore

an W

ar

11

12

Structural Robustness =

Structural Survivability

13

SYSTEMS

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Structural Sistems Performance

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RESILIENCE

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Levels of Structural Crisis

Us

ua

l U

LS

& S

LS

Veri

fica

tio

n F

orm

at

Structural Robustness

Assessment

1st level:

Material

Point

2nd level:

Element

Section

3rd level:

Structural

Element

4th level:

Structural

System

17

Structural Robustness (1)

ATTRIBUTES

RELIABILITY

AVAILABILITY

SAFETY

MAINTAINABILITY

INTEGRITY

SECURITY

FAILURE

ERROR

FAULT

permanent interruption of a system ability

to perform a required function

under specified operating conditions

the system is in an incorrect state:

it may or may not cause failure

it is a defect and represents a

potential cause of error, active or dormant

THREATS

NEGATIVE CAUSEST

RU

CT

UR

AL

QU

AL

ITY

more robust

less robust

18

•Capacity of a construction to show regular decrease of its structural quality due to negative causes.

• It implies: a) some smoothness of the decrease of

structural performance due to negative events (intensive feature);

b) some limited spatial spread of the rupture (extensive feature).

Structural Robustness (2)

19

202020

Connect

21

Robustness comparison

5

8 6 97

12 10 1311

4 2 31

l

VIERENDEEL STRUCTURE ROBUSTNESS

00

,51

0 1 2 3 4 5 6 7 8 9 10Damage Level

PU [ad] MAX MIN

6

6

1

2

3

7 8 9 4 5 1010

TRUSS STRUCTURE ROBUSTNESS

00

,25

0,5

0,7

51

0 1 2 3 4 5 6 7 8 9Damage Level

PU [ad] MAX MIN

High element connectionHigh element number

14

5 3 1 2 4 6 8

l

7 5 3 1 2 4 6 8

14

11 9 1210

18 20 1921

13 15 1617

l

STATICINDETERMINANCY

i = 4 i = 12

9

3

12

1 2

11 5 6 13 14

17

22

2323

Subdivide

24

25

•Capacity of a construction to show regular decrease of its structural quality due to negative causes.

• It implies: a) some smoothness of the decrease of

structural performance due to negative events (intensive feature);

b) some limited spatial spread of the rupture (extensive feature).

Structural Robustness (2)

26

Bad vs Good CollapseSTRUCTURE

& LOADSCollapse

Mechanism

NO SWAY

“IMPLOSION”OF THE

STRUCTURE

“EXPLOSION”OF THE

STRUCTURE

is a process in which

objects are destroyed by

collapsing on themselves

is a process

NOT CONFINED

SWAY

27

Cascade Effect / Domino Effect

• A cascade effect is an inevitable and sometimes unforeseen chain of events due to an act affecting a system.

• In biology, the term cascade refers to a process that, once started, proceeds stepwise to its full, seemingly inevitable, conclusion.

• A domino effect or chain reaction is the cumulative effect produced when one event sets off a chain of similar events.

• It typically refers to a linked sequence of events where the time between successive events is relatively small.

28

29

CONTINGENCIES

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High Probability Low Consequences

HPLCevents

31

Low

Pro

bab

ility

Hig

h C

on

seq

uen

ces LPHC

events

32

3333

NTC2005

34

HPLCHigh Probability

Low Consequences

LPHCLow Probability

High Consequences

release of energy SMALL LARGE

numbers of breakdown SMALL LARGE

people involved FEW MANY

nonlinearity WEAK STRONG

interactions WEAK STRONG

uncertainty WEAK STRONG

decomposability HIGH LOW

course predictability HIGH LOW

HPLC – LPHC EVENTS

35

RUNAWAY (1)

effect

time

decomposability

course predictability

36

EFFECT

RU

NA

WA

Y (

2)

decomposability

course predictability

37

Framework of Analysis

HPLCEventi Frequenti con

Conseguenze Limitate

LPHCEventi Rari con

Conseguenze Elevate

Complessità:Non linearita’,

Interazioni,Incertezze

Impostazionedel problema:

Deterministica

Probabilistica

ANALISIQUALITATIVA

DETERMINISTICA

ANALISIQUANTITATIVA

PROBABILISTICA

ANALISIPRAGMATICACON SCENARI

38

A Black Swan is an event with the following three attributes.

1. First, it is an outlier, as it lies outside the realm of regular expectations,

because nothing in the past can convincingly point to its possibility.

Rarity -The event is a surprise (to the observer).

2. Second, it carries an extreme 'impact'.

Extreme impact - the event has a major effect.

3. Third, in spite of its outlier status, human nature makes us concoct

explanations for its occurrence after the fact, making it explainable and

predictable.

Retrospective (though not prospective) predictability -

After the first recorded instance of the event, it is rationalized by hindsight,

as if it could have been expected; that is, the relevant data were available

but unaccounted for in risk mitigation programs.

References: Taleb, Nassim Nicholas (April 2007). The Black Swan: The Impact of the Highly Improbable (1st ed.).

London: Penguin. p. 400. ISBN 1-84614045-5.

Black Swan Events

39

Word Cloud

40

41

42

43

HAZARD

IN-D

EPTH

DEFE

NCE

HOLES DUE TO

ACTIVE ERRORS

HOLES DUE TO

HIDDEN ERRORS

FAILURE PATH

44

Structural Robustness =

Structural Survivability

45

STUDIES

46

47

48

• The cladding system is a crucial component of the

building for protecting the inside against external

explosions.

• In this experimental program three specimens aretested.

• The first specimen (A) is conventionally designed witha minimum amount of required reinforcement (0.15%),

• the second specimen (B) is designed to achieve aspecific maximum deflection if subjected to a specificblast demand,

• and the third specimen (C) is equal to the specimen(B), subjected to a larger explosive charge.

Introduction

49

• All the specimens are horizontally simply supported andthe explosive charge is orthogonally suspended at 1500mm from the center of the exposed blast side of theconcrete panel.

• The experimental texts were conducted at the facility ofthe R.W.M. ITALIA s.p.a. (www.rwm-italia.com) atDomusnovas (Sardinia - Italy).

• Finite Element Analyses (FEAs) are carried out with theexplicit Finite Element (FE) code LS-Dyna® for predictingthe deflection of the precast panels. Solid elements areutilized for modeling the concrete instead beamelements are adopted for modeling the reinforcement.Contact algorithm for modeling the boundary conditionsis utilized.

Introduction

Specimen A-B-C

50

campione A

51

campioni B e C

52

Test bed arrangement

53

54

55 Test matrix

The specimens are simply horizontally supported, and the supports are made by concrete blocks.The explosive charge is suspended at 1500 mm from the panel surface and it is orthogonal with thecenter of panel surface. The supports are 400 mm high and the lateral open space between thepanels and the ground is closed by sandbags (see Fig.1). In this way the shock wave would be notable to diffract on the back face of the panels.

Fig. 2 - Longitudinal section of the testing site

The explosive, provided by the R.W.M. ITALIA s.p.a., is the PBXN-109 (composed by the 64.12 % of RDX, the 19.84 % of Aluminum, and the 16.04 % of Binder)

Panelt a b c

[mm] [mm] [mm] [mm]

A 150 1550

B 200 1160 1550

C 200 880 1550 2030

Thickness of the panels and position of the meter devices

Two kinds of displacement meter are used andprovided by the R.W.M. ITALIA s.p.a.: the combdevice and the coaxial tube device, as well asshown in figure.

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57

58 Experimental results

Specimen A

The specimen A is designed with the minimum reinforcement for a concrete cladding wall panel.

The deflection of the specimen A reached the fullscale value of the coaxial tubes device. The panelduring the deflection impacted the external tubeof the coaxial tubes device and the panel stoppedits deformation.

The maximum and residual deflection of the panel is so 108 mm.

59 Experimental results

Specimen B

This panel is designed to achieve a specific performance under a blast load, so the specimen B isdesigned for blast (the amount of explosive is the same of the specimen A, 3.5 Kg TNTeq).

The maximum and the residual deflection achieved by the specimen B is of 70 mm and 35 mm respectively.

The specimen B shows a ductile failure with a diffuse crack patterns on the central one third ofthe panel span (the major cracks are 3 mm width). However, some radial crack patterns are present,this is due to the short stand-off distance, and develops a flexural mechanism as designed.

60 Experimental results

Specimen C

The specimen C is equal to the specimen B but the blast demand is greater for leading significantdamages to the panel without reach a failure. The specimen C would test the blast resisting rangeof the panel over the limit of his specific design (the amount of explosive is increased at 5.5 Kg TNTeq).

The maximum and the residual deflection are of 123 mm and 82 mm respectively.

Heavy crack patterns are assessed. Along the mid-span of the panel diffuse cracks are presentwith significant width until 10 mm. Moreover some cracks at the mid-span pass through thepanel cross section thickness (maximum width of the crack passing is the 5 mm)

61 Numerical investigation

In order to reproduce the experimental tests numerically the explicit Finite Elements (FE) code LS-Dyna® is adopted.To simulate physic phenomena, in this study a “Lagrangian” method is adopted and the uncoupledapproach is preferred, thus the blast load is computed and applied independently from thestructural response of the concrete wall panels.The FE models have constant solid stress elements for the concrete, and beams elements for thereinforcement. To bond the beams and solid elements, the LS-Dyna® keyword ConstrainedLagrange in Solid is used.For reducing the computational effort the model of the specimens are only a square part of thepanel, so opportune boundary conditions are provided.

Support

Blast load BC

Panel

Detail view of the finite element model

The concrete supports of the panels are explicitlymodeled and the contact between the panel and thesupport is provided by the LS-Dyna® keywordContact Automatic Surface to Surface. Furthermore,in order to take into account correctly the clearingeffect the boundary conditions for the blast load areprovided; a rigid surface modeling the other threequarter of the panel is added.

Numerical investigation

The material constitutive law of the reinforcement is the kinematic hardening plasticity modeland the strain rate effects is accounted for by the Cowper and Symonds strain-rate model.

The parameters selected for this model are:• D=500 s-1;• q=6;• steel Young’s modulus=200 Gpa;• Poisson coefficient=0.3;• yielding stress=543 MPa 0

2

4

6

8

0.001 0.1 10 1000

DIF

[-]

Strain-rate [1/sec]

CompressiveTensile

AB

C

Reflecting surface

Reflecting surface

Dynamic Increase Factor relation

1

Density 2.248 lbf/in

4 s2

2.4*103 kg/m3

fcm 4060 psi

28 N/mm2

Cap

retraction active

Rate

effect active

Erosion none

Input data for the concrete model

Concrete model input data

Due to the walls delimiting the testing site, multiple reflections of the original shock waveoccurred. Consequently the blast load on the specimens is greater than the blast load on aspecimen tested in an open space.

Using the uncoupled approach theimage charge method (instead of the

ALE method) provides acceptableresults without increasing thecomputational effort.

Elementary scenario of reverberatingShock waves

Image charge

side

Stand-off α

[m] [degrees]

West 6009 27

North 4705 35

South 4705 35

East 13505 13

Table 1: Image charge positions 1

62

63 Numerical investigation

0

40

80

120

160

200

240

280

0 0.05 0.1 0.15 0.2 0.25

δ[m

m]

time [sec]

Experimental

Numerical

Specimen A

δmaxδres

0

10

20

30

40

50

60

70

80

0 0.05 0.1 0.15

δ[m

m]

time [sec]

NumericalExperimental

Specimen B

δmax

δres

(a) (b)

0

20

40

60

80

100

120

140

0 0.05 0.1 0.15

δ[m

m]

time [sec]

Numerical

Experimental

Specimen C

δmax

δres

0

40

80

120

160

200

240

280

0 0.05 0.1 0.15 0.2 0.25

δ[m

m]

time [sec]

Specimen A

Specimen B

Specimen C

(c) (d)

Figure 1: Experimental and numerical mid-span displacement

1

64 Numerical investigation

The following table shows the summary of the results for each specimen reporting both themaximum and the residual deflections of the experimental and numerical investigations. Moreoverthe support rotation θ is shown for both the experimental and numerical investigations.

Specime

n

Experimental Numerical Experimental Numerical

δmax

[mm]

δres

[mm]

δmax

[mm]

δres

[mm]

θmax

[deg]

θres

[deg]

θmax

[deg]

θres

[deg]

A 108* 108* 244 240 4.0* 4.0* 8.9 8.8

B 70 35 58 50 2.6 1.3 2.1 1.8

C 123 82 114 106 4.5 3.0 4.2 3.9

* Full scale value

Looking at the maximum support rotations experimentally assessed:• specimen B goes over the Moderate

Damage CDL but does not exceed the Heavy Damage CDL;

• specimen C does not exceed the Heavy Damage CDL

Component damage levels θ [degree] μ [-]

Blowout >10° none

Hazardous Failure ≤10° none

Heavy Damage ≤5° none

Moderate Damage ≤2° none

Superficial Damage none 1

1

<<<<<<<<<<<<<

Component damage levels (CDLS) forU.S. antiterrorism performance-based

blast design approach

65 Numerical investigation

The below figure shows the simulated crack patterns of the three specimens; in view is the brittledamage parameter in the range from 0.95 to 1

Specimen C Specimen BSpecimen A

(a)

Specimen C

Specimen B

Specimen A

(b)

Figure 1: Crack patterns of the specimens: (a) back view, (b) longitudinal view

1

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conclusion

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Structural Robustness =

Structural Survivability

71

Keywords

•Complexity

•Predictability

•Dependability

• Structural Robustness

•Accident Scenarios

•Back-analysis

• Learning

72

Next Dating

SPRING 2017

KICK-OFF MEETING ON

EXPLOSION GROUP IN ITALYUNIVERSITY OF ROME LA SAPIENZA

SCHOOL OF CIVIL AND INDUSTRIAL ENGINEERING

analisi-strutturale@uniroma1.it

Scientific Coordination by Franco Bontempi

Technical Coordination by Dario Porfidia73

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bonus track

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risk

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ATTRIBUTES

THREATS

MEANS

RELIABILITY

FAILURE

ERROR

FAULT

FAULT TOLERANT

DESIGN

FAULT DETECTION

FAULT DIAGNOSIS

FAULT MANAGING

DEPENDABILITY

of

STRUCTURAL

SYSTEMS

AVAILABILITY

SAFETY

MAINTAINABILITY

permanent interruption of a system ability

to perform a required function

under specified operating conditions

the system is in an incorrect state:

it may or may not cause failure

it is a defect and represents a

potential cause of error, active or dormant

INTEGRITY

ways to increase

the dependability of a system

An understanding of the things

that can affect the dependability

of a system

A way to assess

the dependability of a system

the trustworthiness

of a system which allows

reliance to be justifiably placed

on the service it delivers

SECURITY

High level / activeperformance

Low level / passiveperformance

88

Prevention

Pro

rect

ion

Risk = Probability · Magnitudo

89

Ris

k=

Pro

bab

ility

·Mag

nit

ud

od

od

iscr

etiz

atio

nin

log-

log

pla

ne

90

Ris

k tr

eat

me

nt

91

Option 1 – Risk avoidance, which usually means not proceeding to continue with the system; this is not always a feasible option, but may be the only course of action if the hazard or their probability of occurrence or both are particularly serious;

Ris

k tr

eat

me

nt

92

Option 2 – Risk reduction, either through (a) reducing the probability of occurrence of some events, or (b) through reduction in the severity of the consequences, such as downsizing the system, or (c) putting in place control measures;

Ris

k tr

eat

me

nt

93

Option 3 – Risk transfer, where insurance or other financial mechanisms can be put in place to share or completely transfer the financial risk to other parties; this is not a feasible option where the primary consequences are not financial;

Ris

k tr

eat

me

nt

94

Ris

k tr

eat

me

nt

Option 4 – Risk acceptance, even when it exceeds the criteria, but perhaps only for a limited time until other measures can be taken.

95

boyd

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100

101

102

103

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