Adaptive phase-field modeling of brittle fracture using a robust combination of error-estimator and markers. (15th October 2022)
- Record Type:
- Journal Article
- Title:
- Adaptive phase-field modeling of brittle fracture using a robust combination of error-estimator and markers. (15th October 2022)
- Main Title:
- Adaptive phase-field modeling of brittle fracture using a robust combination of error-estimator and markers
- Authors:
- Krishnan, U. Meenu
Gupta, Abhinav
Chowdhury, Rajib - Abstract:
- Abstract: An error estimator is proposed to carry out adaptive mesh refinement (AMR ) for phase-field fracture (PFF ) simulation. The proposed error estimator works with the mesh-induced crack (MIC ) method for modeling initial cracks, resulting in significant gains in the AMR algorithm's computational efficiency. The error estimator is derived using the iterative change in the crack driving energy over each element in the mesh. A sensitivity analysis with variation in the control parameter of the marking methods is also carried out to present the robustness of the AMR algorithm with the proposed error estimator. We also study the accuracy of the proposed algorithm by implementing it to standard problems and comparing the responses to the non-adaptive (NA ) algorithm. The algorithm adaptively and accurately refines the mesh along the expected crack path to estimate the system's global force versus displacement response. Compared to the NA algorithm, a reduction of 84%–98% is obtained in the total CPU time with the proposed AMR algorithm. Highlights: A new error estimator is proposed based on the crack driving energy. The algorithm's applicability is studied for phase field-induced and mesh-induced initial crack. The algorithm can predict accurate crack topology and peak load. A sensitivity analysis is done with variation in the control parameter of the marking methods. The robustness and accuracy of the algorithm are studied for different problems for mesh induced crackAbstract: An error estimator is proposed to carry out adaptive mesh refinement (AMR ) for phase-field fracture (PFF ) simulation. The proposed error estimator works with the mesh-induced crack (MIC ) method for modeling initial cracks, resulting in significant gains in the AMR algorithm's computational efficiency. The error estimator is derived using the iterative change in the crack driving energy over each element in the mesh. A sensitivity analysis with variation in the control parameter of the marking methods is also carried out to present the robustness of the AMR algorithm with the proposed error estimator. We also study the accuracy of the proposed algorithm by implementing it to standard problems and comparing the responses to the non-adaptive (NA ) algorithm. The algorithm adaptively and accurately refines the mesh along the expected crack path to estimate the system's global force versus displacement response. Compared to the NA algorithm, a reduction of 84%–98% is obtained in the total CPU time with the proposed AMR algorithm. Highlights: A new error estimator is proposed based on the crack driving energy. The algorithm's applicability is studied for phase field-induced and mesh-induced initial crack. The algorithm can predict accurate crack topology and peak load. A sensitivity analysis is done with variation in the control parameter of the marking methods. The robustness and accuracy of the algorithm are studied for different problems for mesh induced crack method. … (more)
- Is Part Of:
- Engineering fracture mechanics. Volume 274(2022)
- Journal:
- Engineering fracture mechanics
- Issue:
- Volume 274(2022)
- Issue Display:
- Volume 274, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 274
- Issue:
- 2022
- Issue Sort Value:
- 2022-0274-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10-15
- Subjects:
- Phase field -- Brittle fracture -- Mesh adaptivity -- Error estimator -- FEniCS
Fracture mechanics -- Periodicals
Rupture, Mécanique de la -- Périodiques
Fracture mechanics
Periodicals
620.112605 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00137944 ↗
http://www.elsevier.com/journals ↗
http://www.elsevier.com/wps/find/homepage.cws_home ↗ - DOI:
- 10.1016/j.engfracmech.2022.108758 ↗
- Languages:
- English
- ISSNs:
- 0013-7944
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3761.350000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23971.xml