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Performance-Based Wind Engineering Through Stochastic Simulation and High-Fidelity Computational Modeling
Performance-Based Wind Engineering Through Stochastic Simulation and High-Fidelity Computa...
Performance-Based Wind Engineering Through Stochastic Simulation and High-Fidelity Computational Modeling

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자료유형  
 학위논문 서양
최종처리일시  
20250211153006
ISBN  
9798384043881
DDC  
620
저자명  
Arunachalam, Srinivasan.
서명/저자  
Performance-Based Wind Engineering Through Stochastic Simulation and High-Fidelity Computational Modeling
발행사항  
[Sl] : University of Michigan, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
198 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
주기사항  
Advisor: Spence, Seymour M. J.
학위논문주기  
Thesis (Ph.D.)--University of Michigan, 2024.
초록/해제  
요약With the burgeoning growth of tall building construction around the globe and heightened public expectations for safe and sustainable urban habitats in the face of extreme natural hazards, solutions for performance-oriented building systems are in great need. Conventional design for wind effects requires the satisfaction of a series of component-level elastic acceptance criteria under strength-level wind demands stipulated in building codes and standards. By ensuring building response is at or below the first significant yield point at a predefined load intensity, satisfactory performance is deemed to be achieved for significantly higher load intensities for which severe damage or even catastrophic collapse may occur. That is, not only are structural systems designed with no knowledge of their wind-induced inelastic behavior, but also how satisfactory the post-yield performance is (e.g., the margin of safety or reliability against structural collapse) remains unknown. The evolving paradigm of performance-based wind engineering (PBWE) seeks to achieve better structural performance (through reliable prediction and control of nonlinear behavior) and improved economy while treating uncertainty through reliability. The principal objective of this dissertation is to develop computational tools within reliability frameworks to efficiently assess the nonlinear behavior of uncertain dynamic structures subject to wind loads. Practical and efficient reliability approaches based on stratified sampling were developed that not only tackle optimal sample allocation for satisfying user-defined coefficient of variation (COV) targets in high-dimensional settings, but also extend applicability to a wider range of natural hazard risk assessment problems involving explicit hazard modeling (e.g., stochastic ground motion modeling or hurricane hazard modeling). This generalization is enabled by incorporating Markov Chain Monte Carlo methods for which COV expressions are rigorously derived of the failure probability estimators. Subsequently, a reliability-based framework was proposed for the characterization of the nonlinear behavior by integrating a high-fidelity fiber-based structural modeling approach capable of capturing progressive yielding, buckling, low-cycle fatigue (LCF), and variable damping, which are crucial for collapse simulation, with an appropriate stochastic wind load model. Through illustration on a 45-story archetype steel building, discussions on the types of observed collapse mechanisms, the difference in along-wind and across-wind response, and finally, reliabilities against first yield, component failure, and system collapse were presented. Presently, PBWE lacks a validated model for the stochastic simulation of non-stationary (NS) wind pressures that can be calibrated to stationary wind tunnel data. Such a model is essential for studying load-path-dependent phenomena of inelasticity and LCF in wind-induced responses subject to NS hurricane winds. This led to the experimental validation of the NS wind pressure simulation model, with its performance confirmed through analyses of spectrogram-based errors. Ultimately, a comparative study of the nonlinear behavior of the 45-story steel building, including collapse and associated reliabilities, was conducted to highlight the differences between NS and equivalent-stationary wind load applications on the peak/residual drifts, initiation of yielding, LCF-induced damage, and reliabilities against several system/component limit states. This dissertation advances the field of PBWE on multiple fronts with cutting-edge frameworks and insights from case studies, to accelerate the shift towards truly performance-based wind design.
일반주제명  
Engineering
일반주제명  
Computer engineering
일반주제명  
Statistics
키워드  
Performance-based wind engineering
키워드  
Reliability analysis
키워드  
Collapse assessment
키워드  
Stochastic simulation
키워드  
Low-cycle fatigue
기타저자  
University of Michigan Civil Engineering
기본자료저록  
Dissertations Abstracts International. 86-03B.
전자적 위치 및 접속  
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■020    ▼a9798384043881
■035    ▼a(MiAaPQ)AAI31631389
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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a620
■1001  ▼aArunachalam,  Srinivasan.
■24510▼aPerformance-Based  Wind  Engineering  Through  Stochastic  Simulation  and  High-Fidelity  Computational  Modeling
■260    ▼a[Sl]▼bUniversity  of  Michigan▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a198  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-03,  Section:  B.
■500    ▼aAdvisor:  Spence,  Seymour  M.  J.
■5021  ▼aThesis  (Ph.D.)--University  of  Michigan,  2024.
■520    ▼aWith  the  burgeoning  growth  of  tall  building  construction  around  the  globe  and  heightened  public  expectations  for  safe  and  sustainable  urban  habitats  in  the  face  of  extreme  natural  hazards,  solutions  for  performance-oriented  building  systems  are  in  great  need.  Conventional  design  for  wind  effects  requires  the  satisfaction  of  a  series  of  component-level  elastic  acceptance  criteria  under  strength-level  wind  demands  stipulated  in  building  codes  and  standards.  By  ensuring  building  response  is  at  or  below  the  first  significant  yield  point  at  a  predefined  load  intensity,  satisfactory  performance  is  deemed  to  be  achieved  for  significantly  higher  load  intensities  for  which  severe  damage  or  even  catastrophic  collapse  may  occur.  That  is,  not  only  are  structural  systems  designed  with  no  knowledge  of  their  wind-induced  inelastic  behavior,  but  also  how  satisfactory  the  post-yield  performance  is  (e.g.,  the  margin  of  safety  or  reliability  against  structural  collapse)  remains  unknown.  The  evolving  paradigm  of  performance-based  wind  engineering  (PBWE)  seeks  to  achieve  better  structural  performance  (through  reliable  prediction  and  control  of  nonlinear  behavior)  and  improved  economy  while  treating  uncertainty  through  reliability.  The  principal  objective  of  this  dissertation  is  to  develop  computational  tools  within  reliability  frameworks  to  efficiently  assess  the  nonlinear  behavior  of  uncertain  dynamic  structures  subject  to  wind  loads.  Practical  and  efficient  reliability  approaches  based  on  stratified  sampling  were  developed  that  not  only  tackle  optimal  sample  allocation  for  satisfying  user-defined  coefficient  of  variation  (COV)  targets  in  high-dimensional  settings,  but  also  extend  applicability  to  a  wider  range  of  natural  hazard  risk  assessment  problems  involving  explicit  hazard  modeling  (e.g.,  stochastic  ground  motion  modeling  or  hurricane  hazard  modeling).  This  generalization  is  enabled  by  incorporating  Markov  Chain  Monte  Carlo  methods  for  which  COV  expressions  are  rigorously  derived  of  the  failure  probability  estimators.  Subsequently,  a  reliability-based  framework  was  proposed  for  the  characterization  of  the  nonlinear  behavior  by  integrating  a  high-fidelity  fiber-based  structural  modeling  approach  capable  of  capturing  progressive  yielding,  buckling,  low-cycle  fatigue  (LCF),  and  variable  damping,  which  are  crucial  for  collapse  simulation,  with  an  appropriate  stochastic  wind  load  model.  Through  illustration  on  a  45-story  archetype  steel  building,  discussions  on  the  types  of  observed  collapse  mechanisms,  the  difference  in  along-wind  and  across-wind  response,  and  finally,  reliabilities  against  first  yield,  component  failure,  and  system  collapse  were  presented.  Presently,  PBWE  lacks  a  validated  model  for  the  stochastic  simulation  of  non-stationary  (NS)  wind  pressures  that  can  be  calibrated  to  stationary  wind  tunnel  data.  Such  a  model  is  essential  for  studying  load-path-dependent  phenomena  of  inelasticity  and  LCF  in  wind-induced  responses  subject  to  NS  hurricane  winds.  This  led  to  the  experimental  validation  of  the  NS  wind  pressure  simulation  model,  with  its  performance  confirmed  through  analyses  of  spectrogram-based  errors.  Ultimately,  a  comparative  study  of  the  nonlinear  behavior  of  the  45-story  steel  building,  including  collapse  and  associated  reliabilities,  was  conducted  to  highlight  the  differences  between  NS  and  equivalent-stationary  wind  load  applications  on  the  peak/residual  drifts,  initiation  of  yielding,  LCF-induced  damage,  and  reliabilities  against  several  system/component  limit  states.  This  dissertation  advances  the  field  of  PBWE  on  multiple  fronts  with  cutting-edge  frameworks  and  insights  from  case  studies,  to  accelerate  the  shift  towards  truly  performance-based  wind  design.
■590    ▼aSchool  code:  0127.
■650  4▼aEngineering
■650  4▼aComputer  engineering
■650  4▼aStatistics
■653    ▼aPerformance-based  wind  engineering
■653    ▼aReliability  analysis
■653    ▼aCollapse  assessment
■653    ▼aStochastic  simulation
■653    ▼aLow-cycle  fatigue
■690    ▼a0543
■690    ▼a0537
■690    ▼a0464
■690    ▼a0463
■71020▼aUniversity  of  Michigan▼bCivil  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-03B.
■790    ▼a0127
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164468▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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