본문

서브메뉴

Computational Modeling of Fracture Behavior of Rubber-Like Materials
Computational Modeling of Fracture Behavior of Rubber-Like Materials
Computational Modeling of Fracture Behavior of Rubber-Like Materials

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20260202105625
ISBN  
9798265427885
DDC  
306
저자명  
Arunachala, Prajwal Kammardi.
서명/저자  
Computational Modeling of Fracture Behavior of Rubber-Like Materials
발행사항  
[Sl] : Stanford University, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
253 p
주기사항  
Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
주기사항  
Advisor: Linder, Christian.
학위논문주기  
Thesis (Ph.D.)--Stanford University, 2024.
초록/해제  
요약Rubber-like materials are an evergreen and ubiquitous class of materials renowned for their wideranging practical utility. Their exceptional properties, including remarkable stretchability, low modulus, and high toughness, render them indispensable across various engineering domains such as automotive, packaging, petroleum, and aviation industries. Moreover, they find extensive applications in emerging fields like stretchable electronics, soft robotics, and implantable sensors. Among them, certain materials like natural rubber stand out for their superior qualities compared to their counterparts. Numerous efforts have been made to elucidate the underlying mechanisms behind its exceptional properties, with strain-induced crystallization (SIC) emerging as a key phenomenon believed to enhance fracture resistance. Moreover, SIC is also observed in polymer melts during industrial processing, where it can be harnessed to tailor the properties of finished products. Therefore, understanding and modeling the behavior of these materials hold significant importance. Given that their toughness and stretchability are their hallmark advantages, comprehending their fracture behavior is essential for designing applications resilient to failure. However, due to the complexity of the phenomenon, there is a lack of studies focusing on this aspect. Hence, this thesis aims to fill this gap by focusing on computationally modeling the fracture behavior of rubber-like materials, with particular emphasis on those exhibiting strain-induced crystallization.To simplify the modeling of this complex phenomenon, we approach it systematically by dividing the problem into manageable parts and addressing them individually. Initially, we focus on modeling the effect of strain-crystallization in delaying fracture initiation. This is achieved by proposing an internal energy-based failure criterion that incorporates the energy required for crystallite distortion. However, to extend the model to predict fracture propagation, a robust multiscale fracture model becomes necessary. Therefore, we couple a multiscale polymer model for non-crystallizing rubbers with the phase field fracture approach, wherein we assume that macroscale damage is driven by the breaking of microscale molecular bonds. Nevertheless, like many existing models in the literature,this model also predicts isotropic network deformation at the microscale, which is not physically realistic and poses challenges in capturing crystal orientations. Consequently, we propose a novel framework to capture anisotropic network deformations at the microscale for non-crystallizing rubbers. Given the importance of capturing the incompressible behavior of rubber-like materials, we introduce a mixed formulation and enforce the constraint using the augmented Lagrangian method. Finally, combining the model capturing the effects of strain-crystallization on fracture initiation and the robust multiscale model developed earlier, we present a simple fracture model for straincrystallizing rubbers, while also accounting for the weak anisotropy resulting from the evolution of crystallites.All of these studies employ a microscale polymer chain model, which assumes that the chains are made up of a number of freely jointed elastic chain segments, thus enabling the consideration of both entropy and molecular bond distortions within the chains. The deformations occurring at the microscale level in these chains are then linked to the macroscale loading using an appropriate network model. Finally, the macroscale model is proposed by incorporating the effects from the chains, bulk and the other necessary quantities. To validate the effectiveness of these models, rigorous comparisons are conducted with experimental data, thus ensuring that the models accurately capture the behavior of rubber-like materials under various complex conditions, thereby enhancing their predictive capabilities and applicability in real-world scenarios.
일반주제명  
Families & family life
일반주제명  
Crystallization
일반주제명  
Rubber
일반주제명  
Social support
일반주제명  
Visualization
일반주제명  
Personality
일반주제명  
Individual & family studies
일반주제명  
Social psychology
기타저자  
Stanford University.
기본자료저록  
Dissertations Abstracts International. 87-05B.
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

 008260126s2024        us                              c    eng  d
■001000017360831
■00520260202105625
■006m          o    d                
■007cr#unu||||||||
■020    ▼a9798265427885
■035    ▼a(MiAaPQ)AAI32316548
■035    ▼a(MiAaPQ)Stanfordng613vx2766
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a306
■1001  ▼aArunachala,  Prajwal  Kammardi.
■24510▼aComputational  Modeling  of  Fracture  Behavior  of  Rubber-Like  Materials
■260    ▼a[Sl]▼bStanford  University▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a253  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  87-05,  Section:  B.
■500    ▼aAdvisor:  Linder,  Christian.
■5021  ▼aThesis  (Ph.D.)--Stanford  University,  2024.
■520    ▼aRubber-like  materials  are  an  evergreen  and  ubiquitous  class  of  materials  renowned  for  their  wideranging  practical  utility.  Their  exceptional  properties,  including  remarkable  stretchability,  low  modulus,  and  high  toughness,  render  them  indispensable  across  various  engineering  domains  such  as  automotive,  packaging,  petroleum,  and  aviation  industries.  Moreover,  they  find  extensive  applications  in  emerging  fields  like  stretchable  electronics,  soft  robotics,  and  implantable  sensors.  Among  them,  certain  materials  like  natural  rubber  stand  out  for  their  superior  qualities  compared  to  their  counterparts.  Numerous  efforts  have  been  made  to  elucidate  the  underlying  mechanisms  behind  its  exceptional  properties,  with  strain-induced  crystallization  (SIC)  emerging  as  a  key  phenomenon  believed  to  enhance  fracture  resistance.  Moreover,  SIC  is  also  observed  in  polymer  melts  during  industrial  processing,  where  it  can  be  harnessed  to  tailor  the  properties  of  finished  products.  Therefore,  understanding  and  modeling  the  behavior  of  these  materials  hold  significant  importance.  Given  that  their  toughness  and  stretchability  are  their  hallmark  advantages,  comprehending  their  fracture  behavior  is  essential  for  designing  applications  resilient  to  failure.  However,  due  to  the  complexity  of  the  phenomenon,  there  is  a  lack  of  studies  focusing  on  this  aspect.  Hence,  this  thesis  aims  to  fill  this  gap  by  focusing  on  computationally  modeling  the  fracture  behavior  of  rubber-like  materials,  with  particular  emphasis  on  those  exhibiting  strain-induced  crystallization.To  simplify  the  modeling  of  this  complex  phenomenon,  we  approach  it  systematically  by  dividing  the  problem  into  manageable  parts  and  addressing  them  individually.  Initially,  we  focus  on  modeling  the  effect  of  strain-crystallization  in  delaying  fracture  initiation.  This  is  achieved  by  proposing  an  internal  energy-based  failure  criterion  that  incorporates  the  energy  required  for  crystallite  distortion.  However,  to  extend  the  model  to  predict  fracture  propagation,  a  robust  multiscale  fracture  model  becomes  necessary.  Therefore,  we  couple  a  multiscale  polymer  model  for  non-crystallizing  rubbers  with  the  phase  field  fracture  approach,  wherein  we  assume  that  macroscale  damage  is  driven  by  the  breaking  of  microscale  molecular  bonds.  Nevertheless,  like  many  existing  models  in  the  literature,this  model  also  predicts  isotropic  network  deformation  at  the  microscale,  which  is  not  physically  realistic  and  poses  challenges  in  capturing  crystal  orientations.  Consequently,  we  propose  a  novel  framework  to  capture  anisotropic  network  deformations  at  the  microscale  for  non-crystallizing  rubbers.  Given  the  importance  of  capturing  the  incompressible  behavior  of  rubber-like  materials,  we  introduce  a  mixed  formulation  and  enforce  the  constraint  using  the  augmented  Lagrangian  method.  Finally,  combining  the  model  capturing  the  effects  of  strain-crystallization  on  fracture  initiation  and  the  robust  multiscale  model  developed  earlier,  we  present  a  simple  fracture  model  for  straincrystallizing  rubbers,  while  also  accounting  for  the  weak  anisotropy  resulting  from  the  evolution  of  crystallites.All  of  these  studies  employ  a  microscale  polymer  chain  model,  which  assumes  that  the  chains  are  made  up  of  a  number  of  freely  jointed  elastic  chain  segments,  thus  enabling  the  consideration  of  both  entropy  and  molecular  bond  distortions  within  the  chains.  The  deformations  occurring  at  the  microscale  level  in  these  chains  are  then  linked  to  the  macroscale  loading  using  an  appropriate  network  model.  Finally,  the  macroscale  model  is  proposed  by  incorporating  the  effects  from  the  chains,  bulk  and  the  other  necessary  quantities.  To  validate  the  effectiveness  of  these  models,  rigorous  comparisons  are  conducted  with  experimental  data,  thus  ensuring  that  the  models  accurately  capture  the  behavior  of  rubber-like  materials  under  various  complex  conditions,  thereby  enhancing  their  predictive  capabilities  and  applicability  in  real-world  scenarios.
■590    ▼aSchool  code:  0212.
■650  4▼aFamilies  &  family  life
■650  4▼aCrystallization
■650  4▼aRubber
■650  4▼aSocial  support
■650  4▼aVisualization
■650  4▼aPersonality
■650  4▼aIndividual  &  family  studies
■650  4▼aSocial  psychology
■690    ▼a0628
■690    ▼a0451
■71020▼aStanford  University.
■7730  ▼tDissertations  Abstracts  International▼g87-05B.
■790    ▼a0212
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360831▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

미리보기

내보내기

chatGPT토론

Ai 추천 관련 도서


    신착도서 더보기
    최근 3년간 통계입니다.

    소장정보

    • 예약
    • 소재불명신고
    • 나의폴더
    • 우선정리요청
    • 비도서대출신청
    • 야간 도서대출신청
    소장자료
    등록번호 청구기호 소장처 대출가능여부 대출정보
    TF18374 전자도서 대출가능 마이폴더 부재도서신고 비도서대출신청 야간 도서대출신청

    * 대출중인 자료에 한하여 예약이 가능합니다. 예약을 원하시면 예약버튼을 클릭하십시오.

    해당 도서를 다른 이용자가 함께 대출한 도서

    관련 인기도서

    로그인 후 이용 가능합니다.