ICSE 2015 The International Conference on Computing in Civil and Building Engineering Paris, France July 20 - 21, 2015 Biogeography Based CO2 and Cost

ICSE 2015The International Conference on Computing in Civil and Building Engineering

Paris, France July 20 - 21, 2015

Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls

DR. IBRAHIM AYDOGDU & DR.A L PER AKI N

ICSE 2015, PARIS, FRANCE

Biogeography Based CO2 and Cost Optimization of RC Cantilever Retaining Walls, Aydogdu and AKIN

Introduction Opt.Problem hTLBO-HS Example Conclusion

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In this study The development of minimizing the cost and the CO2 emission of the RC

retaining wall design has been performed by Biogeography Based Optimization (BBO) algorithm.

Computer programs are developed which minimizes the cost and the CO2 emission of the RC retaining walls.

Program Language: Fortran

Standards: ACI 318-14

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Optimization ConceptOptimization is a mathematical process (method) used to find optimum value (design) of a problem defined in specific objective(s) and constraints.

Components of optimization problemObjective functionDesign or decision variablesConstraints

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Optimization Problem Objective Functions: Minimize cost, CO2 and weighted aggregate of the cost and the CO2 of RW

Design Constraints: American Concrete Institute (ACI 318-05)

stability constraints (overturning, sliding and bearing ) Moment and shear capacity constraints Reinforcement arrangement constraints Geometric constraints

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Design Variables:total base width (X1)toe projection (X2)bottom and thickness of the stem (X3 and X4)thickness of the heel and the toe (X5)key distance from the toe (X6)thickness and the height of the key (X7 and X8)

Optimization Problem

first stem reinforcement together (R1), The second stem reinforcement together (R2)The toe reinforcement together (R3)The heel reinforcement together (R4)The key reinforcement together (R5)

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ICSE 2015, PARIS, FRANCE07.21.2015

OPTIMIZATION TECHNIQUES Deterministic Techniques(Mathematical Programming Techniques)

Integer Programming TechniqueBranch and Bound Method

Stochastic TechniquesGenetic Algorithm Simulated AnnealingArtificial Immune SystemParticle Swarm OptimizationAnt Colony OptimizationHarmony Search MethodFirefly AlgorithmIntelligent Water Drops

Algorithm

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Biogeography-Based OptimizationThe BBO algorithm was developed by simulating the theory of island biogeography which describes the extinction and migrations of species between islands. The method is considered in two complementary components:Migration part : Solutions are modified based on the immigration rateMutation part: Solutions are renewed according to their mutation probability.

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Biogeography-Based Optimization Steps of BBO algorithm:

Step-1: Initialize the method parameters and define the optimization problem.

Step-2: Initialize the population. initial RW designs of the population are generated randomly. The designs evaluated. Immigration and emigration rates of the designs are calculated

Step-3: Migration: The designs in the populations are modified calculated according to their immigration and emigration rates

Step-4: Mutation: If the design has high mutation probability the design is updated using random search. The procedure from step 2 to 4 is repeated until maximum iteration is reached.

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Design Example3.5 m height retaining wall

MaterialSTRENG

TH Unit Price CO2emission

Concrete 24 MPa 59.76 $/m3 304.75 CO2/m3

27 MPa 62.50 $/m3 324.76 CO2/m3

30 MPa 65.65 $/m3 344.54 CO2/m3

Steel 400 MPa 0.742 $/kg 0.3857 CO2/kg 500 MPa 0.770 $/kg 0.3962 CO2/kg

Unit CO2 emissions and Unit Price of the Structural

Materials

DV L.BOUNDU.

BOUNDX1 0.4H 0.8HX2 0.1H 0.6HX3 0.20 m 0.50 mX4 0.20 m 0.40 mX5 0.20 m 0.3HX6 0.5H 0.8HX7 0.20 m 0.40 mX8 0.20 m 0.90 m

Lower and Upper Bounds of Cross Sectional Design Variables

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population size=50 mutation probability=2 elitism parameter=2 maximum iteration=100,000.

3.5 m height retaining wall

Input Parameter Unit ValueHeight of stem m H 3.50Concrete cover mm cc 50Shrinkage and temporary reinforcement percent

- st 0.002

Surcharge load kPa q 10Backfill slope degree β 30Internal friction angle of retained soil degree 36Internal friction angle of base soil degree ’ 0.01Unit weight of retained soil kN/m3 γs 17.50Unit weight of base soil kN/m3 γbs 18.50Unit weight of concrete kN/m3 γc 23.50Cohesion of base soil kPa c 65Design load factor - LF 1.7Depth of soil in front of wall m D 0.50Factor of safety for overturning stability - FSo 1.5Factor of safety for against sliding - FSs 1.5Factor of safety for bearing capacity - FSb 3.0

Input Parameters

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3.5 m height retaining wall

Optimum Values Des. Var. HS BioG CFFA AFFA Des. Var. HS BioG CFFA AFFA

X1 2.7 2.654 3.258 2.906 R1 1010 222 2f26 5f16X2 1.6 1.569 1.473 1.461 R2 710 912 8f16 8f16X3 0.35 0.315 0.462 0.463 R3 110 - - -X4 0.2 0.2 0.2 0.2 R4 1012 912 9f14 9f12X5 0.35 0.313 0.348 0.342 R5 710 710 7f10 7f10X6 1.9 2.45 2.88 2.607 X7 0.2 0.2 0.201 0.2 X8 0.6 0.7 0.204 0.644

Cost Details HS BioG CFFA AFFA

Vol.Conc.(m3) 2.03 1.871 2.17 1.93

Weightst.(kg) 92.20 97.78 110.05 93.24

CostConc.($) 81.10 74.82 86.78 77.17

Costst. ($) 36.88 39.11 44.02 37.29

CostTotal ($) 117.98 113.93 130.8 114.46

Optimum Values of Design Variables and Cost Details

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Variations of optimum values with respect to different materials

C24 C27 C30580

600

620

640

660

680

700

Obj:Cost/S400 Obj:Cost/S500Obj:CO2/S400 Obj:CO2/S500Obj:Weighted/S400 Obj:Weighted/S500

CO2

(Objective function: Minimize the CO2 emission)

C24 C27 C30180182184186188190192194196

Obj:Cost/S400 Obj:Cost/S500Obj:CO2/S400 Obj:CO2/S500Obj:Weighted/S400 Obj:Weighted/S500

Cost

($)

(Objective function: Minimize the cost)

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Variations of concrete and steel amounts of optimum designs with respect to different materials

(Concrete amount of optimum designs) (Steel amount of optimum designs)

C24/S400

C27/S400

C30/S400

C24/S500

C27/S500

C30S5001.7

1.751.8

1.851.9

1.952

Objective: CostObjective: CO2Objective: Weighted

Conc

rete

Am

ount

m3

C24/S400

C27/S400

C30/S400

C24/S500

C27/S500

C30S5007580859095

100105110

Objective: CostObjective: CO2

Stee

l Am

ount

kgf

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Conclusions1. BBO resulted in better performance than those obtained

in all previous research studies. The presented algorithm is powerful and efficient in finding the optimum solution for optimum cost design of RW problems.

2. The minimizing CO2 emission objective function does not have a material influence on the optimum cost of the retaining wall. Therefore, the minimizing CO2 emission objective function can be used in the cost optimization problem.

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Conclusions3. if lower class materials are used, lower cost and

CO2 emissions are obtained4. Higher steel amount is obtained in the

minimization of CO2 emission problem5. Higher steel class reduces the steel amount and

steel cost percentage

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07.21.2015

Documents

ICSE 2015 The International Conference on Computing in Civil and Building Engineering Paris, France July 20 - 21, 2015 Biogeography Based CO2 and Cost