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Automatingand optimizing pile group design using a Genetic Algorithm
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Optimering ochautomatisering av pålgruppsdesign med en genetisk algoritm (Swedish)
Abstract [en]

In bridge design, a set of piles is referred to as a pile group. The design process of pile groups employed by many firms is currently manual, time consuming, and produces pile groups that are not robust against placement errors.

This thesis applies the metaheuristic method Genetic Algorithm to automate and improve the design of pile groups for bridge column foundations. A software is developed and improved by implementing modifications to the Genetic Algorithm. The algorithm is evaluated by the pile groups it produces, using the Monte Carlo method to simulate errors for the purpose of testing the robustness. The results are compared with designs provided by the consulting firm Tyrens AB.

The software is terminated manually, and generally takes less than half an hour to produce acceptable pile groups. The developed Genetic Algorithm Software produces pile groups that are more robust than the manually designed pile groups to which they are compared, using the Monte Carlo method. However, due to the visually disorganized designs, the pile groups produced by the algorithm may be di cult to get approved by Trafikverket. The software might require further modifications addressing this problem before it can be of practical use.

Abstract [sv]

Inom brodesign refereras en uppsättning pålar till som en pålgrupp. Vid design av pålgrupper tillämpar för tillfället många firmor manuella och tidskrävanade processer, som inte leder till robusta pålgrupper med avseende på felplaceringar.

Denna avhandling tillämpar en metaheuristisk metod vid namn Genetisk Algoritm, för att automatisera och förbättra designprocessen gällande pålgrupper. En mjukvara utvecklas och förbättras stegvis genom modifi kationer av algoritmen. Algoritmen utvärderas sedan genom att Monte Carlo simulera felplaceringar och evaluera de designade pålgruppernas robusthet. De erhållna resultaten jämförs med färdigdesignade pålgrupper givna av konsultföretaget Tyréns AB.

Den utvecklade mjukvaran avbryts manuellt och kräver generellt inte mer än en halvtimme för att generera acceptabla pålgrupper. Den utvecklade algoritmen och mjukvaran tar fram pålgrupper som är mer robusta än de designade pålgrupperna vilka dem jämförs med. Pålgrupperna som skapats av den utvecklade algoritmen har en oordnad struktur. Således kan ett godkännande av dessa pålgrupper från Trafikverket vara svårt att få och ytterligare modifikationer som åtgärdar detta problem kan behövas innan algoritmen är användbar i praktiken.

Place, publisher, year, edition, pages
2018.
Series
TRITA-SCI-GRU ; 2018:259
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-229976OAI: oai:DiVA.org:kth-229976DiVA, id: diva2:1215870
External cooperation
Tyréns AB
Subject / course
Systems Engineering
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2018-06-10 Created: 2018-06-10 Last updated: 2018-06-10Bibliographically approved

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