adverse climatic c 00 sach

7/30/2019 Adverse Climatic c 00 Sach

1/252


2/252

. COHOOL


3/252


4/252


5/252

ADVERSE CLIMATIC CONDITIONS AND IMPACTON CONSTRUCTION SCHEDULING AND COST

BYROBERT J. SACHUK

A REPORT PRESENTED TO THE GRADUATE COMMITTEEOF THE DEPARTMENT OF CIVIL ENGINEERING INPARTIAL FULFILLMENT OF THE REQUIREMENTSFOR THE DEGREE OF MASTER OF ENGINEERING

UNIVERSITY OF FLORIDASummer 1988


6/252

5/5-/


7/252

TABLE OF CONTENTSPage

List of Tables illList of Figures ivList of AbbreviationsChapter I - INTRODUCTION 1Chapter II - CALCULATION OF PRODUCTIVITY EFFICIENCIES 5FOR THE EXAMPLE PROJECT SITEChapter III - ESTIMATING PROJECT SCHEDULE AND COST 15BASED ON CLIMATIC CONDITIONSChapter IV - CONCLUSION 33Appendix A - DESCRIPTION OF THE EXAMPLE PROJECT 37Appendix B - USE OF LOTUS 1-2-3 FOR CPM NETWORK 44CALCULATIONSAppendix C - DEVELOPMENT OF SCENARIOS C, D, AE 53Appendix D - METHOD FOR DERIVING PRODUCTIVITY AS A . . . 65FUNCTION OF TEMPERATURE AND RELATIVEHUMIDITYAppendix E - CALCULATION OF AVERAGE MONTHLY 67TEMPERATURES USING THE SIMPLE

AVERAGE METHODAppendix F - CALCULATION OF HEATING REQUIREMENTS AND.. 108COSTS FOR TEMPORARY ENCLOSURE FORSCENARIOS C, D, AND EReferences 112Bibliography 113


8/252


9/252

LIST OF TABLESTable Page2-1. Construction Productivity Efficiencies as a . . . . 9Function of Temperature and Relative Humidity2-2. Calculated Average Monthly Temperatures for .... 13MWTC Bridgeport Using the Simple AverageMethod2-3. Calculated Productivity Efficiencies for 14MWTC Bridgeport Using Koehn/BrownRelationships3-1 . Monthly Temperatures and Calculated 20Efficiencies for Scenarios C, D, & E3-2. Critical Dates for Temporary Shelters for 23Scenarios C, D, & E3-3. Expected Winter Protection Costs and Profit .... 29

as a Function of Mean Daily Temperature3-4. Expected Winter Protection Costs and Profit .... 31as a Function of Duration of Winter ProtectionA-1. List of Activities for Example Project 40A-2. Example Project CPM Network Based on 41Contractor's Actual ScheduleC-1 CPM Network for Scenario A 55C-2 CPM Network for Scenario B 57C-3 CPM Network for Scenario C 59C-4. CPM Network for Scenario D 61C-5 CPM Network for Scenario E 63E-1 January Temperature Statistics 71E-2. Minimum Daily Temperatures for January 72E-3. Maximum Daily Temperatures for January 73


10/252


11/252

Table PageE-4 February Temperature Statistics 74E-5. Minimum Daily Temperatures for February 75E-6. Maximum Daily Temperatures for February 76E-7 March Temperature Statistics 77E-8 Minimum Daily Temperatures for March 78E-9 Maximum Daily Temperatures for March 79E-10. April Temperature Statistics 80E-11 Minimum Daily Temperatures for April 81E-12. Maximum Daily Temperatures for April 82E-13 . May Temperature Statistics 83E-14. Minimum Daily Temperatures for May 84E-15 Maximum Daily Temperatures for May 85E-16 June Temperature Statistics 86E-17. Minimum Daily Temperatures for June 87E-18. Maximum Daily Temperatures for June 88E-19 July Temperature Statistics 89E-20. Minimum Daily Temperatures for July 90E-21 Maximum Daily Temperatures for July 91E-22 August Temperature Statistics 92E-23. Minimum Daily Temperatures for August 93E-24. Maximum Daily Temperatures for August 94E-25. September Temperature Statistics 95E-26. Minimum Daily Temperatures for September 96E-27. Maximum Daily Temperatures for September 97E-28 October Temperature Statistics 98E-29. Minimum Daily Temperatures for October 99


12/252


13/252

Table PageE-30. Maximum Daily Temperatures for October 100E-31 November Temperature Statistics 101E-32. Minimum Daily Temperatures for November 102E-33. Maximum Daily Temperatures for November 103E-34. December Temperature Statistics 104E-35. Minimum Daily Temperatures for December 105E-36. Maximum Daily Temperatures for December 106E-37. Computation of Index of Seasonal Variation 107


14/252


15/252

LIST OF FIGURESFigure Page2-1. Construction Productivity as a Function ofTemperature and Relative Humidity (Graph) .... 103-1. Comparative Cost Forecast For Example Project .. 26

VI


16/252


17/252

LIST OF ABBREVIATIONSABS MAX MAX TEMP Absolute maximum maximum temperatureABS MIN MIN TEMP Absolute minimum minimum temperatureAVG AverageBTU British thermal unitCD Calendar dayCPM Critical path methodCU FT Cubic feetD . DurationDCAA Defense Contract Audit AgencyEF Early finishEIFS Exterior Insulation Finish SystemES ^ Early start*F Degrees FarenheitLF Late finishLS Late startMEAN MAX TEMP Mean maximum temperatureMEAN MIN TEMP Mean minimum temperatureMWTC Mountain Warfare Training CenterNCDC National Climatic Data CenterRH Relative humiditySAM Simple average methodTEMP TemperatureWD Work day


18/252


19/252

CHAPTER IINTRODUCTION

The success of a construction project from the pointof view of the contractor can be defined in differentterms. However, of all possible definitions the most impor-tant may be the profit generated by a single project. Incases where the project management concept is used, theconstruction manager is tasked with the overall managementof design, procurement, construction operations. In thesetypes of projects, the construction manager also has thegreatest amount of influence in controlling costs and gener-ating profit. However, in the case of competitively adver-tised, fixed-price government construction contracts, theextent of contractor influence is normally limited to theprocurement/construction portion of the project's lifecycle. Therefore, the contractor's degree of success ishighly dependent on two different operations that occurduring procurement and construction phases of the project.The first operation, project planning, involves estimatingthe labor, materials, equipment, and preliminary scheduleneeded to execute a project as established by the owner'sdesign. The second operation, the implementation phase, isfor the most part dependent on the prior planning. In thecase of a fixed-price contract, the project cost as


20/252


21/252

presented in the base bid also becomes the control amountupon which the contractor's control budget is based. There-fore, what estimating and planning is done in the prepara-tion of the base bid can be considered essential to thesuccess of the construction project.

However, there is a certain amount of uncertainty inthe bidding process. Material quotes may be based on mate-rials that do not conform to the specifications. The mate-rial take-off may contain errors that result in quantitiesdifferent than what is required. Equipment costs are basedon what the estimator considers to be the most efficientpiece of equipment for the job while not knowing what willbe available at the time the equipment is needed.

Overall, the items noted above can be considered to becontrollable and therefore not subject to creating substan-tial additive costs. In comparison, however, estimatinglabor productivity is the most complicated part of theestimating process. Many of the factors influencing laborproductivity are highly qualitative in nature, and a greatdeal of experience and judgement is needed to develop thetype of qualitative information that is required. However,the productivity component also offers the contractor byfar the greatest opportunity to control his labor costs,assuming that the contractor also has some basic understand-ing of the factors that influence the variable in thisequation


22/252


23/252

Preliminary estimates of productivity are normallybased on either average or historical productivity rates.However, average productivity rates normally do not consid-er climatic effects. Historical productivity rates consid-er climatic effects only if prior construction projectshave been executed in similar conditions. Therefore, forthe estimator that is basing productivity solely on averageproductivity or dissimilar historical rates, there is ahigh probability that adverse climatic conditions willresult in unforeseen additive costs that only serve todeduct from the desired profit.

The ability to anticipate adverse climatic conditionsalso has legal implications. As noted above, a schedulethat does not address or take into account climatic condi-tions will more than likely be subject to delay. However,precedence has been set that daily variations in weatherpatterns should be expected. Precedence goes on to statethat climatic conditions are only to be considered adversewhen a condition arises and that condition is considered tobe occurring at an unusual time of the year. Therefore ifthe climatic condition is not unusual for the particulartime and place, or if a contractor should have reasonablyanticipated it, the contractor would not be entitled torelief [1].

Therefore, the question that arises is how does acontractor estimate productivity for a project subjected toadverse climatic conditions and how do these efficiencies


24/252


25/252

impact on schedule and cost estimates. Additionally, whatalternatives are available to the contractor in completinga project subject to adverse climatic conditions.

It is therefore the intent of this report to demon-strate one method of estimating productivity efficienciesand to demonstrate their impact on construction schedulingand cost. Additionally, it is intended to investigatealternatives available to the contractor.

In order to demonstrate the impact of adverse climaticconditions on project schedule and cost, an actual construc-tion contract was selected as the basis for comparison.The project selected is a two story building of approximate-ly 4800 square feet for fire station use including an appa-ratus room, a dormitory area, a living/dining area, alarmroom, reception room, and administrative spaces. Thisfacility is located at the Marine Corps Mountain WarfareTraining Center (MWTC), Bridgeport, California. Construc-tion was started in September 1984 and was completed inDecember 1985. Further information concerning the projectand details concerning the construction execution are foundin Appendix A (Page 37).


26/252


27/252

CHAPTER IICALCULATION OF PRODUCTIVITY EFFICIENCIESFOR THE EXAMPLE PROJECT SITE

All types of productivity are influenced by air temper-ature, wind velocity, relative humidity, precipitation, andlight. Therefore, it is universally accepted that opera-tions in adverse climatic conditions suffer from a loss ofproductivity - the extent of which depends upon, in part,the type of activity and the degree of protection.

Adverse conditions, here limited to both warm and coldconditions, create varying degrees of problems. In gener-al, the effect of adverse climatic conditions on construc-tion projects plays a major part on the success of theproject. Adverse conditions have been shown to requireconsiderable planning due to the impact on [2]:

1) Arrival of personnel2) Transportation of equipment3) Delivery of materials4) Construction of temporary shelters5) Environmental protection

However, not only does severe conditions effect differ-ent facets of a construction project, but it also can havea severe impact on individuals. In extreme conditions,


28/252


29/252

studies have indicated that workers would more likely besubject to the following factors [3,4]:

1) Errors in judgement2) Carelessness3) Complaints4) General lethargy5) Irritability and poor mental attitudes6) Decrease in quality of workmanship7) General slowdown of work pace8) Unscheduled stoppage of work

In warm climates, injuries take the form of sunburn,cramps, heat exhaustion and heat stroke. These types ofinjuries can be prevented by utilizing preventive measuressuch as ensuring adequate salt and water intake, properwork/rest cycles and adequate acclimatization. These pre-ventive measures, however, generally result in an overallslowdown and, therefore, reduced productivity.

In comparison, cold weather brings about a wider rangeand a more severe degree of injury. Wind chill guidelinesindicate that in an equivalent temperature of -25 F (whichcan occur with an actual thermometer temperature of 10 Fcombined with a 20 mile per hour wind) exposed dry skin mayfreeze within one minute. It has also been shown thatfrostbite can occur in relatively warm temperatures (30*F)if the skin is wet and the wind speed is 15 miles per hour.

Prevention of cold weather injuries is complicated ina construction environment. Normally, proper clothing is


30/252


31/252

required for exposed workers with the materials being light-weight and designed with a great degree of mobility. Howev-er, protective clothing creates the problem of maintaininga worker's skin dry. This results in a decrease in thebody's pain threshold of approximately 5'F and the risk offrostbite is greatly increased.

In order to reduce the effect of cold weather, tempo-rary shelters are often built [5]. However, these tempo-rary shelters result in increased field overhead costsattributable to the cost of the shelter itself, the cost ofheating the shelter, and the cost of maintaining the shel-ter.

Therefore, it can be inferred that a cold weatherenvironment will have a greater impact on productivity,schedule, and costs. The problem, therefore is to estimateproductivity rates, establish a construction schedule, anddetermine costs based on anticipated climatic conditions.In order to do this, the contractor must do the following:

1) Estimate efficiencies that are based on climaticconditions

2) Establish a construction schedule based on aver-age production rates.

3) Apply calculated efficiencies to the averageconstruction schedule and calculate a new sched-ule based on climatic conditions.


32/252


33/252

4) Reevaluate field overhead requirements based ona new schedule (i.e., determine requirements fortemporary shelters and heating equipment in coldweather)

The first step involves the contractor utilizing thebasic methodology in creating a construction schedule. Asseen in the third step, the efficiencies are then appliedto the average productivity rates, thereby modifying theindividual activity durations and the overall schedule.The difficulty, however, is utilizing a valid and repeat-able method to calculate efficiencies in a cold weatherclimate

As illustrated in Appendix D (Page 65), E. Koehn andG. Brown provide one method to calculate productivity effi-ciencies whereby they derived two non-linear relationshipsfor both cold and warm weather climates [6]. For the pur-pose of this paper, these relationships will be utilized todetermine the impact of adverse climatic conditions onproject schedule and cost. The expected productivity effi-ciency values as determined by these authors follows asTable 2-1. These productivity values are also graphicallyillustrated in Figure 2-1. It should be noted that thesevalues represent efficiencies for a broad range of tempera-tures and humidities. For the example project, productivi-ty efficiency values were calculated for specific siteconditions. These values are shown in Table 2-3.


34/252


35/252

TABLE 2-1. CONSTRUCTION PRODUCTIVITY EFFICIENCIES AS AFUNCTION OF TEMPERATURE AND RELATIVE HUMIDITY

Temperature ( *F)Relative Humidity {%)

25 45 65 85 9520-10

10203040

5060708090100110120

0.280.440.590.710.810.890.961.001.001.001.000.950.810.58

0.250.420.570.700.810.900.961.001.001.001.000.940.800.580.29

0.180.380.550.690.810.900.961.001.001.001.000.920.770.550.25

0.060.290.490.660.790.890.961.001.001.000.970.880.710.470.15

0.100.360.580.750.880.961.001.001.000.950.820.610.33

0.240.510.720.870.961.001.001.000.930.780.540.21

Source: Enno Koehn and Gerald Brown, "Climatic Effects onConstruction," Journal of Construction Engineering andManagement . ASCE, Vol. Ill, No. 2, June 1985, 129-137.


36/252


37/252

o

o

Oo

o

eo

o

OI

oI

Ck c c*- tc lf> -* n M Vo o o o o o o O

AXIAIXDnaOHd


38/252


39/252

As noted above, the first step is to estimate efficien-cies based on historical weather data. In doing so, onemust decide what data will be used and how to use it.Generally, average temperature and humidity data is easilyobtainable from various sources. However, as in the caseof weather data obtained from the National Oceanic andAtmospheric Administration, National Climatic Data Center(NCDC) for the example project, weather data may not berepresentative of the project location. For the purpose ofdata collection, the NCDC utilizes only specific populationcenters, usually supported by an airport. In the case ofthe example project and as indicated in Appendix A (Page37), major population areas were twenty-five miles to thesouth (Bridgeport, California) and seventy miles to thenorth (South Lake Tahoe, California) of the site. There-fore, it may be necessary to calculate the average monthlytemperature and relative humidity prior to calculatingefficiencies

For the purpose of this report, it is assumed thatavailable average temperature and humidity data is notavailable for the example project site. Therefore, proce-dures used to calculate the required data are presented.For the purpose of these calculations, available tempera-ture data was taken from Bridgeport, California as weathersystems affect both the example project site and the townsimultaneously. Humidity data was taken from South Lake


40/252


41/252

Tahoe records. Elevations of both data sources are within1000 feet of the example project site.

In order to firmly establish seasonal trends, tempera-ture and humidity data for a twenty year period was ob-tained. This provided five hundred sixty (560) to sixhundred twenty (620) daily mean temperature data points forany given month from which a statistical analysis could bemade

Prior to utilizing the productivity relationshipsestablished by Koehn and Brown, a determination had to bemade as to what was to be considered a proper average ortypical temperature. Ultimately, it was the goal of thisanalysis to establish an average monthly temperature foreach respective month from which productivity estimatescould be made. However, with daily minimum, mean, andmaximum temperatures available, a determination had to bemade as to whether forecasts were based on absolute, mean,or statistically derived temperatures.

Invariably, the data can first be considered a season-al variation in that there is a more or less regular move-ment within the year which occurs year after year. There-fore, in a time series with seasonal variation each monthhas a typical or average value position in relation to theyear as a whole. The problem of seasonal variation there-fore is to determine this typical or average position ofeach month


42/252


43/252

Of the various methods used for measuring the seasonalvariation occurring within a time series, the Simple Aver-age Method (SAM) was selected to analyze the availabletemperature data [7]. Typically, SAM analyzes monthlyvalues to establish a typical value for each of the twelvemonths. However, with approximately 22,000 minimum andmaximum daily temperatures, the method was modified tofirst establish a typical value for each day of the month.The typical daily values were then used to establish atypical value for each of the twelve months. The resultingmonthly values are shown in Table 2-2 below. A detaileddescription of the procedures used involving SAM and theanalysis of the available temperature data is provided asAppendix E (Page 67).

TABLE 2-2. CALCULATED AVERAGE MONTHLY TEMPERATURES FORMWTC BRIDGEPORT USING THE SIMPLE AVERAGE METHOD

AVERAGE MONTHLYMONTH TEMPERATURE ( " FJANUARY 24.95 + 2.59FEBRUARY 27.94 + 1.47MARCH 33.28 + 1.41APRIL 38.47 + 1.29MAY 47.40 0.91JUNE 55.18 0.71JULY 60.99 + 0.67AUGUST 59.57 + 0.66SEPTEMBER 52.90 + 0.98OCTOBER 43.43 + 1.18NOVEMBER 34.85 + 1.43DECEMBER 27.20 + 1.30


44/252


45/252

With average monthly temperature data calculated,average productivity efficiencies for each month could becalculated using the Koehn/Brown relationships. Results ofthese calculations are shown in Table 2-3 below.

TABLE 2-3. CALCULATED PRODUCTIVITY EFFICIENCIES FORMWTC BRIDGEPORT USING KOEHN/BROWN RELATIONSHIPS

AVG MEAN RELATIVE CALCULATEDTEMPERATURE HUMIDITY PRODUCTIVITYMONTH CF) (%) EFFICIENCYJANUARY 25 74 0.84FEBRUARY 28 76 0.87MARCH 33 64 0.92APRIL 38 59 0.95MAY 47 57 0.99JUNE 55 51 1.00JULY 61 41 1.00AUGUST 59 37 1.00SEPTEMBER 52 43 1.00OCTOBER 43 55 0.98NOVEMBER 34 59 0.93DECEMBER 26 67 0.85


46/252


47/252

CHAPTER IIIESTIMATING PROJECT SCHEDULE AND COSTBASED ON CLIMATIC CONDITIONS

In order to evaluate the impact of climatic conditionson a construction project's schedule and cost, it was decid-ed to establish five scenarios in which both schedule andcost could be traced. Prior to developing these scenarios,it was necessary to duplicate the contractor's CPM schedulein a form that could be easily cost loaded and modified.In order to accomplish this, the CPM network was duplicatedon a Lotus 1-2-3 spreadsheet. Use of Lotus 1-2-3 in theconstruction of this CPM network and a listing of all cellformula is included as Appendix B (Page 44).

Two separate formats were used to provide for schedul-ing and cost loading. The first format, as seen in Appen-dix C (Page 53), Tables C-1 through C-5, utilizes a prece-dence network format to calculate early start, late start,early finish, late finish, float, and determine whether theactivity is on the critical path. The second format, notshown in this report, utilized early start-early finishinformation to construct a Gantt chart upon which dailycost information for each activity was loaded. This costloading information was then used to construct cost fore-casts .


48/252


49/252

Scenario A was based on the actual CPM schedule used bythe contractor. For this scenario, a total of 466 calendardays was used to accomplish the project. From the contrac-tor's schedule of prices, the cost of the project to thegovernment was $663,810. Of the total project cost, totaldirect labor and material costs equalled $520,406, includ-ing $2,125 for maintenance during winter shutdown. Fieldoverhead costs equalled $117,384 or $253.53 per calendarday. These field overhead costs included superintendentand quality control personnel wages, job trailer costs,utilities, laboratory services, etc. The remaining amount,$26,020 is attributed to a profit of approximately 5%. Theproductivity efficiencies in this actual case are assumedto be at 100% and therefore not affected by climatic condi-tions .

Scenario B (Table C-2, Page 57), is based on the idealcase of the actual CPM without any time taken for wintershutdown. Without this time period, total project time isreduced to 289 calendar days. In comparison, total directcosts were calculated at $518,281 and total field overheadat $73,017. Based on the actual cost to the government(the base bid), this would have left a total of $72,512 or12.26% attributable to profit. It should be noted howeverthat it is considered unreasonable to assume that construc-tion execution will reach ideal conditions. Therefore,Scenario B shall only be used as the basic schedule from


50/252


51/252

which Scenarios C,D, & E are constructed. Scenario B,therefore, shall not be considered in any further com-parative analyses.

As it is being hypothesized that temperatures affectthe productivity and therefore scheduling and cost, theideal case was then used as the basis for calculating thecontract duration after applying the calculated productivi-ty efficiencies. In order to allow for a comparison be-tween different climate scenarios, it was decided to firstuse the mean temperature data to modify the project sched-ule. It was then decided to create worst and best casescenarios by arbitrarily subtracting from and adding to themonthly mean temperatures.

Scenario C, the precedence network based on mean climat-ic conditions, was created by using the calculated produc-tivity efficiencies indicated in Table 2-3 (Page 14) tomodify the ideal case in Scenario B.

For Scenario D, the average monthly temperature minusten degrees was used. For Scenario E, the average monthlytemperature plus ten degrees was used. In both scenarios,the resulting efficiencies were then factored into theresulting CPM schedule.

Table 3-1 (Page 20) shows the monthly temperatures andefficiencies used for Scenarios C, D, and E.

Once productivity efficiencies were established for theMWTC construction site, they were then factored into thecost loaded Gantt chart. Simply, the procedure utilized


52/252


53/252

was to take the monthly efficiency corresponding with thestarting date of the activity and dividing the activityduration by the efficiency. This would result in a modi-fied, usually longer, activity duration. For those activi-ties that extended over multiple months, the efficiencyused corresponded with the longest partial duration. Goingthrough each activity of the network resulted in a listingof modified activity durations. This was then used tocalculate total direct cost per activity day. These directcosts were then inserted into the cost loaded Gantt chart.The cost loaded Gantt chart was then set up to calculatetotal direct costs per day and cumulative direct cost perday.

The modified activity durations were then inserted intothe precedence network spreadsheet to determine float andcritical activities. This also served the purpose of veri-fying the early starts and finishes of each activity andthe overall project duration.

As seen in Table C-3 (Page 59), Scenario C, based onmean climatic conditions, resulted in a total project dura-tion of 306 calendar days. Total direct costs again werecalculated at $518,281. Field overhead was calculated at$77,327. Based on the actual cost to the government($663,810), a total of $68,202 is left for potential prof-it.

As seen in Table C-4 (Page 61), Scenario D, based ontemperatures ten degrees below the calculated monthly mean


54/252


55/252

temperatures, resulted in a total project duration of 327calendar days. Total direct costs were verified at$518,281. Field overhead costs were calculated at $82,651.Based on the actual cost to the government, a total of$62,878 is left for potential profit.

As seen in Table C-5 (Page 63), Scenario E, based ontemperatures ten degrees above the calculated monthly meantemperatures, resulted in a total project duration of 296calendar days. Total direct costs were verified at$518,281. Field overhead costs were calculated at $74,284.Based on the actual cost to the government, a total of$71,245 is left for potential profit.

The costs noted above for Scenarios C through E, howev-er, are misleading. In the actual execution of the exampleproject, the contractor shut down the job from the begin-ning of October through to the beginning of April. A re-view of the activities surrounding this shutdown also indi-cates that the work done immediately before and after theshutdown did not require any extraordinary measures toprotect work or construction personnel. In the actualschedule, the first activity that occurred that would re-quire monitoring of weather conditions (concrete placement)didn't occur until June. In addition, the exterior finish-es that were also temperature dependent (the exterior insu-lation finish system (EIFS) and the roof membrane) werecompleted prior to the onset of winter. Therefore, all


56/252


57/252

TABLE 3-1. MONTHLY TEMPERATURES AND CALCULATEDEFFICIENCIES FOR SCENARIOS C, D, & E

Temperature(Efficiency)

Month Scenario C(Mean Temp)Scenario D(Mean Temp- 10 'F)

Scenario E(Mean Temp+ 10 'F)

January- 25(0.84) 15(0.71)35

(0.93)February 28

(0.87)18

(0.75)38

(0.95)March 33

(0.92)23

(0.83) 43(0.98)April 38(0.95) 28(0.88) 48(0.99)May 47

(0.99)37

(0.95)57

(1.00)June 55

(1.00)45

(0.98)65

(1.00)July 61

(1.00)51

(1.00)71

(1.00)August 59(1.00) 49(1.00) 69(1.00)September 52

(1.00)42

(0.97) 62(1.00)October 43

(0.98)33

(0.92)53

(1.00)November 34

(0.93)24(0.84)

44(0.98)

December 26(0.85) 16(0.74)

36(0.94)


58/252


59/252

work that was temperature dependent was done at a timewhere little or no protection was required.

Scenarios C, D, & E, however, force temperaturedependent activities into the winter thereby requiring somelevel of protection. The cost of this protection, then,will offset the potential profit.

For the purpose of this report, arbitrary decisions aremade concerning weather protection. A review of contractspecifications indicates the following areas as temperaturedependent

1) Section 03301, Cast-in-place Concrete2) Section 04230, Reinforced Masonry3) Section 07111, Elastomeric Waterproofing,

Sheet Applied4) Section 07240, Exterior Insulation Finish System5) Section 07920, Sealants and Caulking6) Section 09310, Ceramic Tile7) Section 09650, Resilient Tile8) Section 09910, Painting of Buildings

Scenarios C, D, and E were then evaluated to establishweather protection requirements.

It was first assumed that the target period for weatherprotection would be from the beginning of October throughto the beginning of April, matching the winter shutdownperiod in the actual contract. From within that period,each scenario was reviewed to identify where in the sched-ule the first temperature dependent activity occurred.


60/252


61/252

Then, each scenario was reviewed to establish the end ofthe last temperature dependent activity within the protec-tion period. This period was then noted as the duration inwhich some sort of weather protection and supplementalheating would be required.

After initial review of the three scenarios, it wasdecided that it would be assumed that one enclosure couldbe constructed to protect the construction area. It wastherefore assumed that the enclosure would allow for tenfeet of clear space around the building and for a fifteenfoot clearance above the structures highest elevation.This then required an enclosure of 77 feet wide by 87 feetlong by 52 feet high for a total of 348,348 cubic feet ofenclosed and heated space. For the purpose of this report,it was assumed that the enclosure would be constructed ofheavy duty steel tubular scaffolding along the perimetercovered with a reinforced, oil resistant, fire retardant,polyethylene tarpaulin. It was also assumed that both thescaffolding and the tarpaulin were rented. Due to thenature of the enclosure, it was also assumed that fourteencalendar days would be required to both set up and removethe enclosure. From current pricing data, it was estimatedthat both set up and removal would cost a total of $5,000each time and that rental would cost $6,020 per month.

Taking set up, protection and removal periods intoconsideration. Table 3-2 (Page 23) indicates the time peri-ods for weather protection for the three scenarios. Calcu


62/252


63/252

TABLE 3-2. CRITICAL DATES FOR TEMPORARYSHELTERS FOR SCENARIOS C, D, & E

Activity-Scenario

Description C D EStart construction 14 NOV 84 20 NOV 84 . 30 NOV 84of shelterComplete construc- 28 NOV 84 4 DEC 84 14 DEC 84tion of shelter,start heatingComplete heating, 15 MAR 85 3 APR 85 2 APR 85start demolitionof shelterComplete demolition 29 MAR 85 17 APR 85 15 APR 85of shelter


64/252


65/252

lations for estimated fuel costs and heater rental also areto be included in the estimates for winter protection.These costs are summarized below. Assumptions and calcu-lations concerning these costs are found in Appendix F(Page 108).

Based on these heating scenarios, potential profit forScenario C is affected as follows:

Set up of shelter: $5,000Shelter rental: $21,177Shelter removal: $5,000Heater rental: $5,113Heater fuel: $12,060Total Cost for Protection: $48,350

Potential Profit: $68,202Anticipated Profit after $19,852subtracting protection costsBased on these heating scenarios, potential profit for

Scenario D is affected as follows:Set up of shelter: $5,000Shelter rental: $23,750Shelter removal: $5,000Heater rental: $5,728Heater fuel: $14,236Total Cost for Protection: $53,714

Potential Profit: $62,878Anticipated Profit after $9,164subtracting protection costsBased on these heating scenarios, potential profit for

Scenario E is affected as follows:Set up of shelter: $5,000Shelter rental: $21,573Shelter removal: $5,000Heater rental: $5,160Heater fuel: $11,449


66/252


67/252

Total Cost for Protection: $48,182Potential Profit: $71,245Anticipated Profit after $23,063subtracting protection costsThe impact of the winter protection costs on the over-

all cumulative costs is graphically shown on the cost fore-casts in Figure 3-1.

The following is a summary of all factors used tocompare Scenario A, the actual project, to Scenarios C, D,and E.

In terms of critical activities. Table C-1 (Page 55)identifies a total of twenty five activities deemed criti-cal. Review of Scenarios C, D, and E and the applicationof the productivity efficiencies to the 69 activities indi-cate that the activities originally deemed critical remaincritical after the application of the efficiencies. Thisthen serves to validate the method in which the efficien-cies were factored.

In addition, the application of productivity efficien-cies had little impact on the available float. Overall,the efficiencies applied had little effect on the durationof the individual activities. Scenario C, with a meanefficiency of 0.94, only resulted in a seventeen (17) calen-dar day increase in the overall schedule. This would leavelittle time available to add to the float of all thenon-critical activities. Even in the worst case. ScenarioD where temperatures ten degrees below the mean were consid


68/252


69/252

oCO

3

_ oO *"oIenwa

oI

I

CO

o Or-t M t-H+ 1 H H D < QP D H P4 H X< 0^ < O S a COM M HfU Eh &< JS z


70/252


71/252

ered, the mean efficiency stands at 0.88. This results inincreases in float above 30% in only three of the 44non-critical activities. All remaining non-criticalactivities gain one or two days in float.

In the case of overall project duration, there is adefinite advantage to working during periods of adverseclimatic conditions. Scenarios A, C, D, and E have overallproject durations of 466, 306, 327, and 296 calendar days,respectively. The first advantage is that the contractorcan reduce direct costs by eliminating a caretaker forceduring the winter shutdown period. Though, for the exampleproject, this equates to only less than one percent of thedirect costs, this could increase substantially for otherprojects depending on the severity of the weather and onthe amount of the work in place that must be maintained.

The primary advantage to a shorter project duration isthe reduction in field overhead costs. As indicated previ-ously, the example project was estimated to incur fieldoverhead costs of $117,384. Field overhead costs for Sce-narios C, D, and E, in comparison ranged from $74,284 to$82,651. This alone represents a 29-36 percent decrease incosts. For a fixed-price construction project, this sav-ings becomes potential profit.

However, as indicated previously, working throughadverse climatic conditions does come without additivecosts. In Scenario A, the actual construction project, thecontractor's period of winter shutdown resulted in minimal

27


72/252


73/252

costs ($2,125) due to caretaker maintenance. In ScenariosC, D, and E, the cost for a temporary shelter and supple-mental heating would have cost the contractor an average of$50,082. This cost would then have an impact on thepotential profit.

In terms of the potential profit, Scenario A estimatesa profit of $26,020, or 5.0% of the direct costs. In com-parison. Scenario C estimates an anticipated profit of$19,852 after deducting the cost of weather protection.This anticipated profit represents only 3.8% of the directcosts, a decrease from the actual 5%. Scenario D estimatesan anticipated profit of $9,164, only 1.7% of the estimateddirect costs. Lastly, Scenario E estimates an anticipatedprofit of $23,063, or 4.4% of the estimated direct costs.It should be noted, however, that for the purposes of esti-mating project costs, only those values generated by Scenar-io C would be considered. A review of the estimated temper-atures for the three scenarios indicates that the tempera-tures used in Scenarios D and E are well outside of therange of values generated for Scenario C. A cursory reviewof this data would indicate that there is little probabili-ty that the daily mean temperatures would continuously beoutside of the range of the calculated mean value. If meantemperature values were to continuously remain outside ofthe expected range, the contractor would then have reasonto claim unusual adverse conditions thereby setting thestage for damages.

28


74/252


75/252

In order to test the validity of the procedures, asensitivity analysis was conducted by, first, varying theexpected mean temperature during the winter protectionperiod and evaluating the resulting anticipated profit, andsecondly, by varying the length of the winter protectionperiod and evaluating the resulting profit. In both cases,Scenario C, the mean temperature case was used.

In the case of varying the expected mean temperatureduring the winter protection period, it was anticipated anincrease in the mean temperature would reduce the require-ment for heating and therefore reduce winter protectioncosts and increase profit. Temperatures for the monthsNovember through March were increased incrementally usingthe average standard error for the months in question. Theresulting winter protection costs, profit, and mean tempera-ture for the winter protection period were then calculat-ed. Results are shown below in Table 3-3.

TABLE 3-3. EXPECTED WINTER PROTECTION COSTS AND PROFITAS A FUNCTION OF MEAN DAILY TEMPERATURE.

AMOUNT OF EXPECTEDINCREASE PROTECTION EXPECTED(F) COSTS PROFIT0.00 $48,344 $19,8581.64 $48,227 $19,9743.28 $48,111 $20,0914.92 $47,994 $20,2076.56 $47,878 $20,3249.84 $47,644 $20,55710.50 $47,598 $20,604

RESULTANT MEANTEMPERATURE ( F29313334363940

29


76/252


77/252

The significance of Table 3-3 above is that as hypothe-sized, an increase in the average mean temperature duringthe winter protection period will decrease the winter pro-tection costs and therefore increase the profit. However,of particular note is that once the average mean tempera-ture is above 40 'F, there is no longer a requirement forwinter protection. Therefore, winter protection costswould equal zero. However, once the mean temperature forthe winter protection period goes below 40 *F, the contrac-tor can plan on spending a minimum of $47,598. This costwould include set up, rental of both shelter and heaters,dismantling the shelter and minimal fuel costs. At no timeis this analysis, does the expected profit match or exceedthat of the actual case. Of major significance is that amajor increase in average mean temperature will producelittle in the way of savings.

Of equal significance is the probability of the averagemean temperature increase to a degree in which winter pro-tection costs can be disregarded. It should be pointed outthat an increase in mean daily temperatures for the entirewinter protection period are unrealistic just by the natureof the available temperature data.

Sensitivity analysis was also conducted on the lengthof the winter protection period. In doing this analysis,it is anticipated that a decrease in the length of thewinter protection period will also decrease the overallwinter protection costs and increase expected profit. In

30


78/252


79/252

Scenario C, heating and a temporary shelter was providedfrom 28 November to 15 March, a total of 107 calendardays. Two additional data points were then calculated forwinter protection periods ending 28 February and 31 March.Results of this analysis are found below in Table 3-4.

TABLE 3-4. EXPECTED WINTER PROTECTION COSTS AND PROFIT ASA FUNCTION OF DURATION OF WINTER PROTECTION

LENGTH OFWINTER EXPECTEDPROTECTION PROTECTION EXPECTED(CD) COSTS PROFIT93 $43,381 $24,821107 $48,350 $19,852124 $54,383 $13,819

As hypothesized, the shorter the winter protectionperiod, the lower the winter protection costs. Of signifi-cance is that the decrease in the winter protection dura-tion brings about a greater degree in reduced costs thanincreased mean daily temperatures. However, as indicatedin the previous sensitivity analysis, one reason for de-creasing the winter protection period may be the arrival ofwarmer weather. This would mean that the mean daily temper-atures would require to be above 40 'F for a period of over30 days before anticipated increase in order to match theanticipated profit identified in Scenario A. Basing in-creased savings solely on anticipated temperatures decreas-ing the length of the winter protection period may be total-ly unreasonable and expose the contractor to undue risks.

31


80/252


81/252

Alternatively, the contractor may consider decreasingthe winter protection period by compressing the activitiesthat fall in that protection period. Two things must thenbe considered. The first is that if the contractor com-presses the activities planned to occur during the winterprotection period, will the activities filling the avail-able float also require protection. Overall, this mayresult in completion of the entire schedule in a shortertime period but not reduce the required shelter time. Whatwould be expected, however, is that the decrease in theoverall schedule would result in a decrease in overheadexpenses that occur over the entire project duration. Thesecond consideration must be given to whether compressionof the schedule will result in additive direct labor andmaterial costs. These compression costs would then onlyserve to decrease anticipated profit.

32


82/252


83/252

CHAPTER IVCONCLUSION

As can be seen in the previous discussions, there aredistinct advantages in working during anticipated adverseconditions. However, there are numerous distinct disadvan-tages that have not been discussed.

In estimating productivity during periods of adverseclimatic conditions, one can only predict the outcome basedon occurrences to date. In the previous discussions, it isassumed that a contractor would be able to work continuous-ly through periods of adverse climatic conditions basedsolely on temperature predictions. Realistically, however,one can expect that the contractor will experience occur-rences of work stoppages and delays in delivery of materi-als during this same time due to not only unusual tempera-tures but also due to oncoming weather systems (i.e., snow,ice, high winds).

For the example project site, the primary differencebetween the actual project schedule (Scenario A) and theschedule based on mean temperature data (Scenario C) repre-sents an decrease in profit of $6,168, or a difference of1.19% of the actual direct costs. However, even this de-crease indicates that it probably will be economically

33


84/252


85/252

non-advantageous to conduct construction operations twelvemonths of the year for this specific project at this specif-ic site.

Other factors must be considered in working duringadverse conditions which would also reduce a contractor'santicipated profit. For example, in the case of winteraccident costs, it has been clearly shown that the frequen-cy as well as the severity of accidents is substantiallyhigher in the winter, and therefore the additional cost ofwinter accidents must be considered in the overall costconsiderations [8] . Additionally, one must concern them-selves with the loss of personnel during periods of adverseweather conditions. On one hand, if the contractor contin-ues work through periods of adverse weather, he or she mustalso anticipate loss of experienced personnel as a resultof accidents or the employees desire to work under betterconditions. On the other hand, if the contractor shutsdown during long periods of adverse weather, he or she canalso anticipate loss of personnel prior to start-up due tothe desire to remain employed during that period.

The construction project is essentially an investmentfor the contractor from which a certain amount of return orprofit is generated. Therefore, as a prudent investor, acontractor would tend to limit bids to low risk projects.In the case of adverse weather conditions, the probabilityfor unforeseen conditions is high. Unless the contractoranticipates these unforeseen conditions and plans and docu-

34


86/252


87/252

ments accordingly, there is little chance for the contrac-tor to recover from damages [9],

In the case of the example project, only proper plan-ning and documentation during the construction projectwould result in a successful execution of the project.This prior planning would require estimations of weatherconditions similar to what has been done in this report.Then the contractor would be required to document the actu-al occurrences and note the differences. Without thisinformation, the contractor would have no basis to recoverdamages

Without proper planning and documentation, the contrac-tor is only subjecting himself to high risks if pursuingwork during periods of adverse weather conditions. If thiswere determined to be the case with the actual execution ofthe example project, it is only logical that the contractorwould choose to utilize a winter shutdown period.

In conclusion, this report presents one procedure forestimating productivity based on temperature and humidityand traces the impact that these conditions have on schedul-ing and cost. In addition, this report provides some ofthe analysis required in making a decision as to whether ornot a contractor should work during periods of adverseclimatic conditions. While these analyses may be prelimi-nary in nature, it is suggested that they may be sufficientenough to evaluate risks when initially bidding on pro-jects. With this in mind, if the alternative of working

35


88/252


89/252

through adverse weather conditions is selected, furtherrefinement of these estimates, together with constantmonitoring and adjustment, will be necessary to ensuresuccessful execution of the project and attainment of one'sprofit objectives.

36


90/252


91/252

APPENDIX ADESCRIPTION OF THE EXAMPLE PROJECT

The Marine Corps Mountain Warfare Training Center(MWTC), Pickel Meadows, is located on a portion of theToiyabe National Forest in a region defined by the SierraNevada Mountains to the west, the Sweetwater Mountains tothe northeast. Mono Lake to the southeast, and Lake Tahoeto the north. It is in northwestern Mono County, Califor-nia, approximately 20 miles northwest of Bridgeport, thecounty seat, and 17 miles southwest of Walker. Both townsare located on the major north-south access through theregion. Interstate 395. Between Walker and Bridgeport,California, Highway 108 intersects with Interstate 395, andthe Center is four miles west along the east-west route tothe Sonora Pass, one of the few passes through the moun-tains .

The climate of the region varies considerably withelevation, which ranges from 4,400 feet to 12,512 feetabove sea level. The yearly average temperature in theBridgeport area is 25 'F minimum and 61 *F maximum, with thelowest temperature recorded approximately -31 *F in Januaryand the highest temperature recorded approximately 96 *F inAugust. The Pickel Meadows base camp represents subalpineconditions with an average annual precipitation

37


92/252


93/252

of 20 to 40 inches occurring from midwinter through latespring. Snow can remain on the ground from December untilMay.

The 45,635 acres of land that compromise the Centerare rugged and and contain steep slopes ranging between 15to 50 percent. The topography generally slopes from westto east with the highest peaks forming the western boundaryof the training area and the lowest elevations along StateHighway 108 and the West Walker River. The base camp has atotal of 420 acres and has an elevation of 6,760 feet over-looking the West Walker River floodplain.

The Fire Station project was one of a nine-project,$20 million military construction program started in 1983.This program replaced all "temporary" structures construct-ed in 1952. Construction of the fire station commenced inSeptember 1984 and was completed in December 1985 [10].

The project itself was to construct a two story build-ing of approximately 4,800 square feet for fire stationtype use. The facility included an apparatus room, a dormi-tory, a living/dining area, an alarm/reception area, andadministrative areas. Foundations were constructed usingspread footings and columns with concrete block foundationwalls. Interior and exterior walls were mostly concreteblock with gypsum board on metal studs being used in limit-ed areas. Interior supports were steel beams and purlins.The lower level floor consisted of a 6 inch concrete slabreinforced with wire mesh on a 4 inch base. The upper

38


94/252


95/252

level floor consisted of a 3-1/4 inch concrete slab rein-forced with wire mesh on a 3 inch steel deck. Roofingconsisted of a standing seam metal roof on a structuralsteel deck. Doors consisted of hollow metal and wood inhollow metal frames. Windows consisted of steel frames withtinted insulated glass. Interior finishes consisted of acombination of exposed concrete floors, painted walls,exposed ceilings, vinyl asbestos tile floor coverings, andacoustical tile ceilings. The mechanical system consistedof a forced area heating system and the building was fullyfire sprinkled.

As seen in Table A-1 (Page 40), List of Activities,the contractor utilized a total of 69 activities. TableA-2 (Page 41), Example Project CPM Network Based on Contrac-tor's Actual Schedule (Listed by Activity Number, AscendingOrder) , indicates that the actual contract was performedover a period of 463 calendar days. Of particular note inthis network is Activity 4, Winter Shutdown, where thecontractor terminated all construction operations (otherthan caretaker maintenance) for a period of 177 calendardays. Of additional note are the temperatures that couldhave been expected. As indicated in Appendix E (Page 67),mean minimum monthly temperatures for this period rangedfrom 8-21 *F. Mean maximum monthly temperatures rangedfrom 42-66 *F. Mean mean monthly temperatures ranged from25-43 'F.

39


96/252


97/252

(A

Ul I-0. T

>- Oh- OfO Oo a:z oO COi-i cct- EGCQ _1Z U3 :ô oU. CD

Z iZO Oi UJ1^ zzo t-v> enz cn

(CX oI- CJcc oUJ ttiz a:CO zU. (/io u.o >->en UJ

CO COz z

COUJzccUl3Oz3

COK UlX -UJ UJ

Nc_lCO3OZ3I-XUJ

-" u.

UJ COz z(E >-oc Ll00 oE OUJ QE

-JU. (EO I-O UJ(h eCrt Crtz z

aQi.cc _iO 3oa COzE *^3CO t-0. t-> TCO CQ

I- z

E(Eu. ctoQ O3 QHCO QZ_i cn\- > OZ I-CO COz zU. "-"

aOiQ. CO

I- zCO u.

CDzCO HZ -> zUJu zCO a:3 ZCO uOd CAt- zen -

i-i UJa. -ICD I- CO _Jz u

l-H UJ UlC Q J0. >- UJu.Z XCO I- enz z zU. 0. u.

UJ

uE 01>- Z CQ cc CLZ U E QC OM Ul _j UJ O

CO 3Z O>-i UJ UJ-J ul-H ZUJ UJo zoen3 I-"

ZCCCO

:>o.cjoco:)>j3vo>joIE I c^

uUJ-)ooca.UJ-ia.ECXUJocoCOUJ

o

CO

IcUl_lCD(E

(A(D UJZ -ti I-Q tiUJ =>O I-IUJ 1-OC U0. C

zoH QCC 3DC V3Q

Z> 0--H IK DCo oo-4CMmT^lnô^.coaô-


98/252


99/252

d > I(Vl

Ul

:>I I I II I I Iu u u u o I- I I I I I ItK U I I I I I IO I

I I I

I I Io o oI t II I I

uI

IuI

I I I II I I Iu u u uI I I II I I I

z_l (/>en. >-i-> >~> '->>-> *r) (T >->

I I 1 I I T I00 00 w wI I I I I I I I I I IO""-" CO o> o g> CT> a a a-P3333535a)4t.i.LL3>3>3>3>33cccs- a a a a-p -paaaan)n)iT)iT)njrtj3rtj533333333333333ili*a)iliUUa:(Eirczzzzzz'->z'-'-)>->'->'^'->'->'^a:'->cEII__ .._ . woocoffivi)CJiMinooooojinco(^CvJCTiOiaaaaa3 3 3I I I

3 01 a> 111 Of Of(Z I I I I I I

I ^Tf^TftnininininuiininininininininininininininmuTinininininininuiininI 000000000000000000000000000000000009000000000000000000000000000003000000>H'IIIIIIIIIIIIIIIIIIIIII~l aaa-P!LL(.LLCC3>3^>^'->^^'-)'->>->>->a:a:a:ccir(n(oi:ocrtujo)iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiT

111111111111111i-^^4i-H^Mi-H Gio*doioiaaaa3333333333iK3riiaI I I I*oinvfi-


100/252


101/252

CMU.o- :>

g ^ V) fl) ^ '^(M (VI M m imI I I I I

I I I^ :> 3>o o oT I I^-ln 2'I I I I I I I I I I I I I I II'""'""""""IIIII

I I I I I I I I I I I I I

t I I I I I I t I I I T ffTf .Sininininwwcooooo^O'^^^^^'^^ioinininmmmivimiviivimo0000


102/252


103/252

Based on the contractor's Schedule of Prices, pricingdata obtained from Defense Contract Audit Agency (DCAA)audits, and a base bid of $721,055, direct costs (labor andmaterial) equalled $520,406, field overhead costs totaled$117,384, home office overhead costs totaled $57,245, andleaving $26,020 attributable to profit. It is noted thatas determined by the DCAA audits, home office overhead wasestimated based on an estimated eleven percent of directcosts. Therefore, in the analyses done in this report, itis assumed that direct costs remain constant throughout thecomparisons. Only the duration over which the expendituresare incurred change. Therefore, all costs comparisons areperformed with no consideration given to home overheadcosts only for the purpose of simplifying the comparisons.

43


104/252


105/252

APPENDIX BUSE OF LOTUS 1-2-3 FORCPM NETWORK CALCULATIONS

As indicated previously in Chapter III, the contrac-tor's actual schedule was duplicated on a Lotus 1-2-3spreadsheet in order that impact on activity duration andslippage of activities could be evaluated instantaneously.

The spreadsheet critical path network utilizes basicformulas found in any network analysis .[ 11 ] These basicformulas are as follows:

Early Start = ES = the earliest time that an activitycan startEarly Finish = EF = ES + Duration = ES + DLate Finish = LF = the latest time that an activitycan finishLate Start = LS = LF - DFloat = LS - ES

In addition, basic calculations indicate that whenFloat = 0, then the activity is considered critical.

Information on the spreadsheet used for the CPMnetwork occupied the following ranges of columns and rows:

1) Duration for Activities 1-36 - Columns C, Rows 6-412) Duration for Activities 37-69 - Columns C,

Rows 48-83

44


106/252


107/252

3) Early Start Dates for Activities 1-36 - Columns G,Rows 6-41

4) Early Start Dates for Activities 37-69 - Columns G,Rows 48-83

5) Late Start Dates for Activities 1-36 - Column H,Rows 6-41

6) Late Start Dates for Activities 37-69 - Column H,Rows 48-83

7) Early Finish Dates for Activities 1-36 - Column I,Rows 6-41

8) Early Finish Dates for Activities 37-69 - Column I,Rows 48-83

9) Late Finish Dates for Activities 1-36 - Column J,Rows 6-41

10) Late Finish Dates for Activities 37-69 - Column J,Rows 48-83

11) Float for Activities 1-36 - Column K, Rows 6-4112) Float for Activities 37-69 - Column K, Rows 48-8313) Critical Activity Flag for Activities 1-36 -

Column L, Rows 6-4114) Critical Activity Flag for Activities 37-69 -

Column L, Rows 48-83Therefore, combining basic network calculations and

the column/row notation used in Lotus 1-2-3, networkcalculations for the example project as they would be foundon the spreadsheet are as follows:

45


108/252


109/252

1) Early Start/Early Finish Cell FormulaEarly EarlyStart Early Start Finish Early FinishAct Cell Formula/Value Cell Formula/ValueDescrptn Used in Cell Descrptn Used in Cell

1 G6 DATE (84, 9, 4) 16 +G6+E62 G7 + 16 17 +G7+E73 G8 + 17 18 +G8+E84 G9 + 18 19 +G9+E95 GIO + 19 110 +G10+E106 Gil + 110 111 +G11+E117 G12 + 110 112 +G12+E128 G13 MAX(I11,I12) 113 +G13+E139 G14 MAX (11 1,1 12) 114 +G14+E1410 G15 + 112 115 +G15+E15

11 G16 + 112 116 +G16+E1612 G17 + 115 117 +G17+E1713 G18 + 115 118 +G18+E1814 G19 eMAX(I13,I14,116,117) 119 +G19+E1915 G20 @MAX(I13,I14,116,117) 120 +G20+E2016 G21 MAX(I18,I19, 120) 121 +G21+E2117 G22 @MAX(I18,I19, 120) 122 +G22+E2218 G23 MAX(I18,I19, 120) 123 +G23+E2319 G24 + 122 124 +G24+E2420 G25 + 121 125 +G25+E2521 G26 + 121 126 +G26+E2622 G27 + 121 127 +G27+E2723 G28 MAX(I23,I24, 125) 128 +G28+E2824 G29 MAX(I23,I24, 125) 129 +G29+E2925 G30 MAX(I23,I24, 125) 130 +G30+E3026 G31 MAX(I26,I28) 131 +G31+E3127 G32 + 130 132 +G32+E3228 G33 MAX(I31,I32) 133 +G33+E3329 G34 + 133 134 +G34+E3430 G35 + 133 135 +G35+E3531 G36 MAX(I27,I29,

134,135)136 +G36+E36

32 G37 @MAX(I27,I29,134,135) 137 +G37+E3733 038 +136 138 +G38+E3834 G39 + 136 139 +G39+E3935 G40 + 136 140 +G40+E4036 G41 + 136 141 +G41+E4137 G48 + 136 148 +G48+E4838 G49 + 136 149 +G49+E4939 G50 + 136 150 +G50+E5040 G51 + 136 151 +G51+E5141 G52 + 136 152 +G52+E5242 G53 MAX(I37,I38) 153 +G53+E5343 G54 @MAX(I37,I38) 154 +G54+E54

46


110/252


111/252

Early EarlyStart Early Start Finish Early FinishAct Cell Formula/Value Cell Formula/ValueNo. Descrptn Used in Cell DescrDtn Used in Cell44 G55 + 139 155 +055+E5545 G56 + 139 156 +G56+E5646 G57 +139 157 +G57+E5747 058 MAX( (155,156,157) 158 +G58+E5848 G59 + 154 159 +G59+E5949 G60 + 159 160 +G60+E6050 G61 + 153 161 +G61+E6151 G62 + 153 162 +G62+E6252 G63 + 153 163 +G63+E6353 G64 + 153 164 +G64+E6454 G65 + 161 165 +065+E6555 066 + 161 166 +G66+E6656 067 MAX(I40,I41,I48149,165) 167 +G67+E6757 G68 MAX( (140. . .149,165) 168 +068+E6858 069 eMAX((I40. . .149,

165)169 +069+E69

59 G70 eMAX( (140. . .149,165) 170 +O70+E7060 071 MAX(I63,I66,I67) 171 +G71+E7161 072 MAX(I63,I66,I67) 172 +072+E7262 073 MAX(I63,I66,I67) 173 +G73+E7363 074 MAX(I63,I66,I67) 174 +074+E7464 075 @MAX(I63,I66,I67) 175 +075+E7565 076 MAX(I63,I66,I67) 176 +076+E7666 077 @MAX(I63,I66,I67) 177 +077+E7767 078 MAX(I63,I66,I67) 178 +G78+E7868 079 @MAX(I50. .152,158,160,162. .164,168. .178)

179 +079+E79

69 083 + 179 183 +083+E832) Late Start/Late Finish Cell Formula

LateStartct CellNo. Descrptn1 H62 H73 H84 H95 HIO6 Hll7 H128 H139 H14

Late StartFormula/ValueUsed in Cell+J6-E6+J7-E7+J8-E8+J9-E9+J10-E10+J11-E11+J12-E12+J13-E13+J14-E14

LateFinishCellDescrptnJ6J7J8J9JIOJllJ12J13J14

Late FinishFormula/ValueUsed in Cell+H7+H8+H9MIN(H10+H12MIN(H13MIN(H13MIN(H19

Hll)

.H14).H16).H20)MIN(H19. .H20)

47


112/252


113/252

Late LateStart Late Start Finish Late FinishAct Cell Formula/Value Cell Formula/ValueNo. Descrptn Used in Cell Descrptn Used in Cell10 H15 +J15-E15 J15 @MIN


114/252


115/252

Late LateStart Late Start Finish Late FinishAct Cell Formula/Value Cell Formula/ValueNo. Descrptn Used in Cell Descrptn Used in Cell58 H69 +J69-E69 J69 +H7959 H70 +J70-E70 J70 +H7960 H71 +J71-E71 J71 +H7961 H72 +J72-E72 J72 +H7962 H73 +J73-E73 J73 +H7963 H74 +J74-E74 J74 +H7964 H75 +J75-E75 J75 +H7965 H76 +J76-E76 J76 +H7966 H77 +J77-E77 J77 +H7967 H78 +J78-E78 J78 +H7968 H79 +J79-E79 J79 +H8369 H83 +J83-E83 J83 + 183

3)Float Cell FormulaFloat FloatAct Cell FormulaNo. DescrptnK6

Used in Cell1 @IF( H6-G6=0," ",II6-G6)2 K7 eiF (H7-G6=0," ",II6-G6)3 K8 IF(,H8-G6=0," " ,1I6-G6)4 E9 @IF [H9-G6=0," 'M16-G6)5 KIO IFI H10-G10=0," ,H10-G10)6 Kll IFI[H11-G11=0," ',H11-G11)7 K12 IF('H12-G12=0," '',H12-G12)8 K13 IFI[H13-G13=0," '',H13-G13)9 K14 IF( H14-G14=0," ,H14-G14)

10 K15 @IFI[H15-G15=0," '',H15-G15)11 K16 IF(,H16-G16=0," ,H16-G16)12 K17 IFI[H17-G17=0," '',H17-G17)13 K18 IF( H18-G18=0," ,H18-G18)14 K19 IF [H19-G19=0," ',H19-G19)15 K20 IFI H20-G20=0," ,H20-G20)16 K21 ' IFI[H21-G21=0," '',H21-G21)17 K22 IF( H22-G22=0," ',H22-G22)18 K23 eiF (H23-G23=0," '',H23-G23)19 K24 IF( H24-G24=0," ',H24-G24)20 K25 IF [H25-G25=0," '',H25-G25)21 K26 IF( H26-G26=0," '',H26-G26)22 K27 IF (H27-G27=0," ',H27-G27)23 K28 @IF( H28-G28=0," '',H28-G28)24 K29 IF (H29-G29=0," '',H29-G29)25 K30 IF('H30-G30=0," ',H30-G30)26 K31 IF (H31-G31=0," ,H31-G31)27 K32 IFI H32-G32=0," ,H32-G32)28 K33 IF (H33-G33=0," '',H33-G33)29 K34 IF< H34-G34=0," ',H34-G34)30 K35 IF [H35-G35=0," ',H35-G35)

49


116/252


117/252

FloatAct CellNo. Descrptn31 K3632 K3733 K3834 K3935 K4036 K4137 K4838 K4939 K5040 K5141 K5242 K5343 K5444 K5545 K5646 K5747 K5848 K5949 K6050 K6151 K6252 K6353 K6454 K6555 K6656 K6757 K6858 K6959 K7060 K7161 K7262 K7363 K7464 K7565 K7666 K77 -67 K7868 K7969 K83

FloatFormulaUsed in CelleiF@IFeiF@IFIFIF@IFIFIFIF@IFIF@IFIFIFIFIFIFIFIFIFIF@IFIFIFIFIFIFIFIFIFIFIFIFIFIFIFIFIF

(H36-(H37-(H38-(H39-(H40-(H41-(H48-(H49-(H50-(H51-(H52-(H53-(H54-(H55-(H56-(H57-(H58-(H59-(H60-(H61-(H62-(H63-(H64-(H65-(H66-(H67-{H68-(H69-(H70-(H71-(H72-(H73-(H74-(H75-(H76-(H77-(H78-(H79-(H83-

G36:G37:-G38:039:G40:G41:G48:G49:G50:G51:G52:G53:G54:G55:G56:G57:G58:G59:G60:G61:G62:G63:G64:G65:G66:G67:G68:G69:G70:G71:G72:G73:G74:G75:G76:G77:G78:G79 =G83:

tt tt

tl It

tt 11

tt tt

tt It

tt II

It It

tt It

tt 11

It II

t II

It It

tt 11

tt tt

II tl

0, If IIIt II

0, It tttt tl

0, tt ItIt II

0, tt It11 It

0, It Ittt It

0,11 It

II tt

0, II It0, It It0. It It0, tt It0, It It0, tt tt0, tt tl0, tt It0, 11 110, It It0, II 110, It It

,H36-,H37-,H38-,H39-,H40-,H41-,H48-,H49-,H50-,H51-,H52-,H53-,H54-,H55-,H56-,H57-,H58-,H59-,H60-,H61-,H62-,H63-,H64-,H65-,H66-,H67-,H68-,H69-,H70-,H71-,H72-,H73-,H74-,H75-,H76-,H77-,H78-,H79-,H83-

G36G37-G38G39G40G41G48G49G50G51G52G53G54G55G56G57G58G59G60G61G62G6 3G64G65G66G67G68G69G70G71G72G73G74G75G76G77G78G79G83

4) Critical Activity Flag Cell FormulaCrit Figct Cell

No. Descrptn1 L62 L73 LB4 L9

Critical Activity FlagFormulaUsed in CellIF(H6-G6=0," -- CIF(H7-G6=0," -- CIF(H8-G6=0," ~ CIF(H9-G6=0," C

tt It II \~ I /II II It \~ f }It It It \

II It It \~ I50


118/252


119/252

Crit Fig Critical Activity FlagAct Cell FormulaNo. Descrptn

LIOUsed .Ln Cell

5 IF(H10-G10=0 II C __ M II ")6 Lll IF(H11-G11=0 II C ___ II II ")7 L12 IF(H12-G12=0 II C II II ")8 L13 IF(H13-G13=0 II C II II ")9 L14 IF(H14-G14=0 II c II It ")10 L15 IF(H15-G15=0 II c II II ")11 L16 eiF(H16-G16=0 II c II tl ")

12 L17 @IF(H17-G17=0 II c __ II II ")13 L18 IF(H18-G18=0 II c II II ")14 L19 IF(H19-G19=0, II c __ II II ")15 L20 IF(H20-G20=0 II c __ It It ")16 L21 9IF(H21-G21=0, n c __ II II ")17 L22 IF(H22-G22=0 II c M II ")18 L23 IF(H23-G23=0, II c __ II It ")19 L24 IF(H24-G24=0 II c II II ")20 L25 IF(H25-G25=0, II c II II ")21 L26 eiF(H26-G26=0 II c __ II II ")22 L27 IF(H27-G27=0, II c II II ")23 L28 IF(H28-G28=0 II c 11 II ")24 L29 IF(H29-G29=0, II c II It )25 L30 IF(H30-G30=0, II c It II ")26 L31 IF(H31-G31=0, II c It It )27 L32 IF(H32-G32=0, II c ___ t1 II ")28 L33 IF(H33-G33=0, 11 c II It ")29 L34 IF(H34-G34=0 II c __ II II ")30 L35 IF(H35-G35=0,

II c _____ II II ")31 L36 IF(H36-G36=0, II c __ It It ")32 L37 IF(H37-G37=0, II c __ II II ")33 L38 IF(H38-G38=0 II c __ n II ")34 ^L39 IF(H39-G39=0, II c __ II It ")35 L40 IF(H40-G40=0, II c II II ")36 L41 IF(H41-G41=0, II c __ II II ")37 L48 @IF(H48-G48=0, II c II II ")38 L49 IF(H49-G49=0, II c II II ")39 L50 IF(H50-G50=0, II c II II )40 L51 - IF(H51-G51=0, II c II It ")41 L52 IF(H52-G52=0, II c II II ")42 L53 @IF(H53-G53=0, II c __ II II ")43 L54 IF(H54-G54=0, II c II II ")44 L55 IF(H55-G55=0, II c II II ")45 L56 eiF(H56-G56=0, II -- c __ II II ")46 L57 IF(H57-G57=0, II c II II ")47 L58 @IF(H58-G58=0, II c 11 II ")48 L59 IF(H59-G59=0, II c __ II II ")49 L60 IF(H60-G60=0, II c II It ")50 L61 IF(H61-G61=0, II c __ II II ")51 L62 IF(H62-G62=0,

II c II II ")52 L63 IF(H63-G63=0, II c II II ")53 L64 IF(H64-G64=0, II c II It ")54 L65 IF(H65-G65=0, II c __ II II ")51


120/252


121/252

Crt Fig Critical Activity FlagAct Cell FormulaNo. Descrptn

L66Used in Cell

55 eiF(H66-G66=0," C --", II II \56 L67 @IF(H67-G67=0," C --", ft ir V57 L68 IF(H68-G68=0," C --", 11 11 \58 L69 IF{H69-G69=0," -- C ", M II V59 L70 IF(H70-G70=0," -- C ", It It \60 L71 IF(H71-G71=0," C ", II II \61 L72 IF(H72-G72=0," C ", II It V62 L73 IF(H73-G73=0," -- C --", It tl \63 L74 IF(H74-G74=0," C ", II II \64 L75 IF(H75-G75=0," C ", It tl \65 L76 IF(H76-G76=0," C --", tl 11 \66 L77 IF{H77-G77=0," C ", II 11 V67 L78 IF(H78-G78=0," C ", It It \68 L79 IF{H79-G79=0," -- C ", II II V69 L83 @IF(H83-G83=0," C ", It It V

52


122/252


123/252

APPENDIX CDEVELOPMENT OF SCENARIOS C, D, & E

As indicated in Appendix B (Page 44), the contractor'sactual schedule was simulated on a Lotus 1-2-3 spreadsheetin order that different scenarios involving activity dura-tion changes could be instantaneously monitored during theprocess. For the sake of continuity within this Appendix,Table C-1 shows the contractors actual schedule in theLotus format.

With the basic (actual) schedule in place, it was thendecided to develop the ideal case. This case. Scenario B,assumed that all durations indicated on the actual schedulewere at an ideal productivity efficiency of 100 per cent.In addition, it was assumed that winter shutdown would beof no consequence in the ideal case resulting in the respec-tive activity duration to be reduced to zero. As indicatedin Chapter 3, total project time is reduced to 289 calendardays. The CPM network for Scenario B follows as Table C-2(Page 57)

With an ideal schedule assumed to be independent oftemperature influences, it was then decided to create anexpected mean, worst, and best case scenario to identifytrends and impact. Scenario C, based on mean climaticconditions, was created by using the calculated productiv-


124/252


125/252

ity efficiencies indicated in Table 2-3 (Page 14) to modifythe ideal case in Scenario B. This resulted in a totalproject duration of 306 calendar days. The CPM network forScenario C follows as Table C-3 (Page 59).

As seen in Table C-4 (Page 61), Scenario D, based ontemperatures ten (10) degrees below the calculated monthlymean temperatures, total project duration was calculated as327 calendar days.

Lastly, as seen in Table C-5 (Page 63), Scenario E,based on temperatures ten (10) degrees above the calculatedmonthly mean temperatures, total project duration was calcu-lated as 296 calendar days.


126/252


127/252

5^ I I I II I I I I I II I I-i:>iu(juoo ouuIt

g^

ztU COoc __l -u.

I I I I II I I I I

t I II I I

1u IuI

IoI I I II I I IU U U (J

I II I

uI

->->'-5->'-^'->'->^->a:'->cn'->irccir>^'->'->'->->^'-)'->'->'->'->ca:ir'r.'7>q:ir

rr\ rt ]n(MCVJ (fU "^ rv- COCVJ CJ C\J OV O -< . -oj rn m n 01(^ m ^ \p 'oro m rn


128/252


129/252

1

IaII

* ^ fO -< (V)vd in vA < m s* "> 1^ ** ^ vO * *

I

zUJ (0lominioininioinioinio0O0OQOCO00000O0OO90O0O

I

u u oo z1 I i

I I

o uz z oT I II I I

u o oz z1 I Iinir)Ooo^^'-ir'iriifn Z_l a*> _uaiu*yuyuu

I I I I T I I I I-. _ .... _ -^ ^ ^MfVJN-r fW cJ CV?W N oT TTf mmmfninininininininin'MnvoM S^ Pt M M O t^ (s. N N N TH r>- mUJ 1- m m m m * in ô

t \)i o ^ k *k as Vt ôc iLC sD iji ^ ^0 m egm m m m * in ^do a^ WK ah v^ Vh aî in in in in u^ cvj îvi |T| m m mm ô^ ^ vfi^J>mlnm-UJO'-iX

1 1 (T o: z o:; UJ UJ X UJ > il K- r^ r :^-Z)ZTi:^_j>-uj_juj~i~i>-i ^MLJ UJ Ul QL z lH z a. (r)(0OQ.wUJ2'Zll.OQ0-)it;S ^fH Q X Z Q _l Z u. J Q1 CDCDZU.Ot-l-l-1- ZI-H-h-l-l-ZI-l-ZI-l-Z Xt-ZIt-iiill-l- ij3Q D 3 n ii; CO Qi CO co co CO CO CO CO Oi CO CO CO OL CO lli 01 CO 1- CO CO CO 01 CO Z 01 01 01 ?* 1-OOOOTt-ZZZ z z Z Z 1- z z z KZI-ZZZZZZZZCZZUJ -4 uCO

ctctu.cnEcn'-i^-.H^ U. 1- lH H^ CO 1-^ Ll 1

i;ou.coi-iu.a.u.i-iu.u.i-iXu.i-ii- li.t- O NC0(TÔ'Hl^Jm


130/252


131/252

^^1 ! i I I !-I :> i u u u u u- - I I I I I I

g^ II . I .

I

I I II I I

u IoI

o a oI I II I Io CJ u u

I I I II I I I

Io

I- IC I31

UJ (0

> Ioc z

C Z I

^>:>^^ûua;uuuoooooooii;(nOÔOOZZZZZZZQO

I I I I I I I

I I I I I I IU C C C C j34i -P>3'^:>^?5uuuyuucccJ3Ci3i)X]i3rii.LLs.LL4fa>UUUUOOOOOOOaiafliwli4ii9'i)9iTiiliitiiLaia>>ll4)iT>i?i9Q.Q.Q.(0 (W o o pI I I I To in vA ^ iSj ->1 1 ?

I I I I I I I I I I I I I I I I I I

li.->'->-)li.LLU.LLSSirESI I I I I I I I I I I I I I I I I ITôu^^fl^Doo^^^r>rn^lJOln^*gooo- oI- t-> CLI- 0^

^

^(Mm'fl-TrinNNNNoowtMinininNvDôvooopiviinrvoooooo --'^^^^^rt ^ ^ ^ (vi cvi (vj eg^ff>rnrf>r> oococo **M f^vM .H ."^ tl^ 4 H (^J (M00 CO > n

(vj Nooj


132/252


133/252

CMU.OCM

t- - i- - IOC O Iu IuII

Iu Iu

s * * (T) -< fls in v < (n 3'3'3>3>i^n7n)>iinin)ina.a.Q.Q.Q.a.Q.a.a.Q.a.a.iTi(9iDin 5 00K0LLt-lJ.t-01-a.l-_JQt-


134/252


135/252

CVJ

a!^ ill!! 1 1 i 11 11 j 11 11 lit) 11 t 1 1 1O !--:> oo oo o ooo u O O o o o o u u uH -- H 1 1 1 1 1 > 1 1 1 1 1 1 1 lilt 1gj^.

till! 1 1 1 1 1 1 1 1 1 1 1 1 11- 1 m ^^ N. y-t m yO '->>->^U-Eli.ZU.LLlJ.lJ.1 1 1 1 1 1 1 1 1 1 1 1 1 1 I T

I3t 3>lU j5 "JEzsiTirsiss:

L L 1 J. J_ I I I

lilt.O . -H O O '->->I I I I I I I I I

I I I I I I I I I I IcnjiihiJ^Ji i. L, LI I I T

I I

I I I I I I I I

I I

i- ^ inininininCOCO00(CO(O0OiXiGO00iQ00003000000Q0000000QC>0003C0(0}C0CC>(OI I I I Ia 0. a-p -piD OT Ol u u0) 01 (O o oI I I I ITf o * N (> -p > i>u u o oo o z zI I I I

I

oz :.I I

I

z zI

I :>Q oz z|\.TfU.'->li.I I I I I I I I I I i

1J3 .} 1 i. 1 1 1i. 1Ol 4; n


136/252


137/252

I> !CMu.oCVi g cco rn fn ro Q fivo in vo p ^ N *i> * pPj I I I I

I I I I I I I t I

I I I I I I I I I I I(S.\OVOC"J(VJWCVJWCgCMN-*'-' (VIOWO I 3>5. nj It)- E E i:

I I TI I I I I

ID rt) 3 ^ 3^ ^ E ->I I I I

I I I I I I I t I I I I I I I I I I^ ID a a E IT E C ccI I I I I Iooco*N'rrv-NONOOOJOO*firv.--'-3^3>3>C3C" -iD35.iDiDirEEEE'->E'->I I I I I I I I I

k?^ I I I I I3.35^^S|'H^S>zr>3EEE'->S'-lI I I I I I I I I I I I I I I ^rn m m (T|h M a^ avin in C If'm m m m

H N m* in vjo m CM* in îX. OJ ^m m *xi

a>CMnoDuÊQ.OacO^*9X>-ZZ(-CDZI-t-ggg^gSggco1^ N^ il ll iI ^ ^^ HM ^

Q.ooa:40

QUZoQ. - I- :> I- t- Ipi o IoLl t

I I I I II I I I Iu u u u oI I ! i I

I I Iu u uI

uI

uI

Io

i OO - If)m w m S OJ CO

0O0O0O0O0O0O0OO00O0OCOQOCO0O0O0Ouu)jucucOw>llil'4finilJf9

I I I I I I To^flOOOO'^>J^j(Mooocvj(vjooj '^m-'d

I I r I I I I I I I I I I I I I I!5a>inii'wft*i5inina.Q.Q.Q.inin33I I I I I I I I I I I I T I T I I I*gomcoN(^J^filn^-comm(^\l fl^^J^^-^-OCVJfvj0J---O^ÔO373r


140/252


141/252

di

'^û

X(T Z I

IuII

IuI

IToU. I

f * (vj fy '->s'->'->'->->>->'->'->s:^'-)'-)'-)'->>->->'->^î->'->'->'-)>-)'-)> '-)i->- I I I I t I I I I I I I I I I I I I I 1 I I I I I I I I I I I I Iii. ^rv.r^rs.ooNmm(vN)r-o>rN.NN-I00

(VJ

> XIT Z

Ii.

I ininioininininininininininininintnininininininininininintfjinininia0CO00(0000COCO000O00000000O3CO00O)C000O0CO00es:ees'->->

i i i i i i i i '

I I I I I I I I I t i_ I I I I I I I I I I I I

S*5 S ?S S S S 3 333333333333S:'->^'-)E>->->'->->->'->'->->T>'-)>^'->'->'->>^'->r)'->T I I I I I I I I I I I I I I I I I I I I I I

I I ( I I ( I < I I I I I I I I I I I I t I I I I Immpoocc^'^lT>^^rlNgoQO3iC3>C3>3>3'3>3>3>CCCCCaQ.a5.ifliTiTliTJHi3"U3'^rt)i5rt)'5i533333(ra:(rirs:EEEE'->E'->s:2:EEs:s:'-'n->'->fTiTiiiiiiTI I T I I I I I I T I I I I I r I 1 I I Ia>(T>aâsiT.iT.2>*iivjjscwa)ooooioocop(--i>-if>-0CrCT>O'-'


142/252


143/252


144/252


145/252

ICC I- IO "- II 2> IK -> I1 I- I

U. I

IIX I

I- - i(TZ ILi. I

> I-J QC -u.

UJa: I-_l CO

IuII

Io

rr yt m ^ ff\vi3 IP VD m *p ID m ^ (\j CM w m cvj cj (vj IP * vOw m m ^ lO N lO vO * * vi) * ^ t

oooo&oocociooocooocoQooocociooocoooQococoooooatisooaoooaooooocowI I I I I I I I I I I I I I I I I t

oomiDU")N6-^-NioNir)voinioiooffaminioioioioinioiomin-C0Ca>00(C009Q0C00003C000C000iXI09C00pI J I I I I I I I I I t I I I I I I I I I I I I I I I I I I I I I

4CVICM-'^HfTlOm-ininin^in^fiRmmminininioininininTtinio

N fs. rn* in voO |V (VJ^ in vnOS (VI -- UJ Llii-i -I u

i-H LU Ul (C_J Crt O I 3> I QQ (T Cii O CZOEOiQCfiHai>-' UJ _l UJ O 3 >-'3>EQ.OQ(n:>:40t-IIH-CDIH-l-CO to Cfl CO Z Cn CO 0^ZZZZZZUJi-'tU.'-'XlJ.'-'H-cvim-

ozI-(JoX

(VJ

0. >-

OS


146/252


147/252

APPENDIX DMETHOD FOR DERIVING PRODUCTIVITY AS A FUNCTION OFTEMPERATURE AND RELATIVE HUMIDITY

For the purpose of this report, efficiencies in produc-tivity were solely based on the non-linear equations de-rived by E. Koehn and G. Brown [12]. In deriving theseproductivity efficiencies, the authors employed historicaldata for various activities and crafts encompassing a totalof 172 data points. From this data, two nonlinear relation-ships, shown below as Eqs . 1 and 2, were derived relatingproductivity with temperature and relative humidity - onefor cold or cool weather, and another for warm or hot weath-er. Eq. 1 is applicable from -20 *F to 50 'F and Eq. 2 from70*F to 120'F.

Pc = 0.0144T - 0.00313H - O.OOOIOTT^ - 0.000029H2- 0.0000357TH + 0.647 (1)

Pw = 0.0517T -I- 0.0173H - 0.00032T* - 0.0000985H2- 0.0000911TH - 1.459 (2)

wherePc = productivity factor for cool or cold weather;Pw = productivity factor for warm or hot weather;T = temperature in degrees Fahrenheit;

and H = relative humidity as a percent.


148/252


149/252

In order to represent the productivity as a percent ofstandard efficient operations, Eqs . 1 and 2 were then nor-malized as a function of their respective maximum values.Also, to obtain a smooth transition between the two curves,productivity at 60 *F and 70 *F was arbitrarily taken asunity. Applying the aforementioned expressions, the au-thors developed Table 2-1 which illustrates the resultingrelationships between productivity and temperature forvarious relative humidities. These relationships are graph-ically illustrated by way of Figure 2-1 found in the text.

For the example project, each month was individuallycalculated to derive the productivity efficiency for thespecific month and site. Again, calculations were madeusing a Lotus 1-2-3 spreadsheet.

For each month, values of Pc were calculated foreach temperature between absolute minimum temperature and50 'F. These values were then normalized by dividing eachefficiency value by the maximum value in the series. Theappropriate efficiency value was then selected based on thecalculated mean monthly temperature.

Procedures for calculating values of Pw are the samewith the exception that values were calculated for eachtemperature between 70 'F and the absolute maximum maximumtemperature


150/252


151/252

APPENDIX ECALCULATION OF AVERAGE MONTHLY TEMPERATURESUSING THE SIMPLE AVERAGE METHOD

For the purpose of this report, the Simple AverageMethod was used to estimate average monthly temperaturesbased on the available data over a twenty year period.Procedures used were as follows:

1) Calculate the mean (using the arithmetic mean)daily mean temperature for each day of the month in ques-tion.

2) Assuming a straight line trend, calculate the lin-ear trend occurring for each month. The least squares linefor a given series is obtained by using a set of normalequations. These equations are derived mathematically [13]but for working purposes they may be obtained bymultiplying the type equation through by the coefficientsof each unknown (a and b) . In this case, the typeequation, which is for a straight line, is

Y = a + bXwhere

a = the Y-interceptb = slope of the given lineX = X coordinateY = corresponding Y coordinate


152/252


153/252

The coefficient of the first unknown (a) is 1. Therefore,multiplying the type equation through by 1 we have

Y = a + bXThe formula must be summed up for all points.

The summation results inL(Y) = Ea + bE(X)

But, the sum of a equals the number of items times theconstant

Ea = NaTherefore

(I) S(Y) = Na + b S(X)The coefficient of the second unknown (b) is X.

Multiplying the type equation through by X we obtainXY = aX + bX

This sums up to(II) S(XY) = aS(X) + bE(X*)

By the use of these two equations the values of the twounknowns can be determined and the trend fitted.

As an example of the above equations, information forthe Table E-4 (Page 74) will be used to demonstrate trendcalculations. From Table E-4, the following information isobtained:

EX = 406EY =814.4EXY = 12013.75EX* = 7714


154/252


155/252

Combining with equations I and II above the following isobtained:

(I) 814.40 = 29a + 406b(II) 12013.75 = 406a + 7714b

(II) 12013.73 = 406a + 7714b(III) 11402.38 = 406a -t- 5684b (I x 14)(IV) 611.35 = 2030b (II - III)

b = 0.301163) Adjust the mean daily mean temperatures for

trend. Each of the averages just computed would then bedistorted by the secular trend of the data. If the trendis upward, the adjusted mean daily mean temperature at theend of the month would be higher than it should be inrelation to the rest of the days since it occurs lateralong the trend line.

The increase per month due to trend was determined byfitting a least squares line to the monthly figures anddividing the b value (slope) by the number of days in themonth. The resulting value represented the amount eachdaily average is distorted by the trend as compared to theprevious day. This trend adjustment was completed for eachmonth resulting in the listing of average temperatures forthe month as seen at the end of this section.

4) With these monthly values established, it was thendecided that the temperatures would also require adjustmentas the monthly average would also be distorted by the trend

69


156/252


157/252

as compared to the previous month. Therefore Steps 1 and 2were repeated using the monthly values. The results ofthese calculations follows.

With a line of regression used to estimate a theoreti-cal value of Y for a given value of X, if the relationshipis not perfect the actual values will not usually coincidewith the theoretical values because of scatter. If thescatter is definitely measured the variation may then beallowed for. For this purpose the standard error of esti-mate was used to measure the variation or scatter about theline of regression. This standard error of estimate isused similarly to the standard deviation.

Tables E-1 through E-37 utilize the above noted pro-cedures and provide data for the months of January throuhDecember. This data provides the basis for the productiv-ity efficiency estimates listed in Table 2-3 (Page 14).


158/252


159/252

TABLE E-1. JANUARY TEMPERATURE STATISTICSCORRECTDTREND DAILYX Y XY X2 Y' CORRECTN MEAN

18 0.00 23 0.0000 181 19 18.63 1 23 -0.0044 192 21 41.60 4 23 -0.0088 213 21 62.55 9 23 -0.0132 214 23 92.20 16 24 -0.0176 235 22 110.13 25 24 -0.0220 226 23 137.55 36 24 -0.0264 237 25 177.10 49 24 -0.0308 258 26 204.00 64 24 -0.0352 259 24 217.35 81 24 -0.0396 24

10 26 257.75 100 24 -0.0440 2611 28 303.05 121 24 -0.0484 2812 27 328.50 144 25 -0.0528 2713 28 363.03 169 25 -0.0572 2814 28 394.45 196 25 -0.0616 2815 29 439.13 225 25 -0.0660 2916 27 433.20 256 25 -0.0704 2717 28 471.75 289 25 -0.0748 2818 28 508.95 324 25 -0.0792 2819 27 514

adverse climatic c 00 sach

Documents