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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳志鴻 | zh_TW |
| dc.contributor.advisor | Chih-Hung Chen | en |
| dc.contributor.author | 黃品豪 | zh_TW |
| dc.contributor.author | Pin-Hao Huang | en |
| dc.date.accessioned | 2024-03-21T16:13:52Z | - |
| dc.date.available | 2025-02-01 | - |
| dc.date.copyright | 2024-03-21 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-02-01 | - |
| dc.identifier.citation | Meyers, M. A., Chen, P.-Y., Lin, A. Y.-M. & Seki, Y. Biological materials: structure and mechanical properties. Progress in materials science 53, 1–206 (2008).
Wegst, U. G., Bai, H., Saiz, E., Tomsia, A. P. & Ritchie, R. O. Bioinspired structural materials. Nature materials 14, 23–36 (2015). Pro, J. W. & Barthelat, F. The fracture mechanics of biological and bioinspired materials. MRS Bulletin 44, 46–52 (2019). Wilkerson, R. P. Biomimetic” Nacre-Like”, Metal-Compliant-Phase Ceramics Pro duced via Coextrusion (University of California, Berkeley, 2018). Zhong, Z., Tian, Y. & Xie, T. Investigation of subsurface damage of ground glass edges. The International Journal of Advanced Manufacturing Technology 87, 3261– 3269 (2016). Mayer, G. Mechanical energy dissipation in natural ceramic composites. Journal of the Mechanical Behavior of Biomedical Materials 76, 21–29 (2017). Yuan, Q., Chen, B., Chen, B., Wang, Z., et al. New insight into the toughening mechanisms of seashell: From arch shape to multilayer structure. Journal of Nanomaterials 2016 (2016). Mayer, G. Rigid biological systems as models for synthetic composites. Science 310, 1144–1147 (2005). Sun, J. & Bhushan, B. Hierarchical structure and mechanical properties of nacre: a review. Rsc Advances 2, 7617–7632 (2012). Sarikaya, M., Gunnison, K., Yasrebi, M. & Aksay, I. Mechanical property-microstructural relationships in abalone shell. MRS Online Proceedings Library 174, 109–116 (1989). Yin, Z., Hannard, F. & Barthelat, F. Impact-resistant nacre-like transparent materials. Science 364, 1260–1263 (2019). Liu, F., Li, T., Jia, Z. & Wang, L. Combination of stiffness, strength, and toughness in 3D printed interlocking nacre-like composites. Extreme Mechanics Letters 35, 100621 (2020). Gao, H.-L. et al. Mass production of bulk artificial nacre with excellent mechanical properties. Nature communications 8, 287 (2017). Griffith, A. A. VI. The phenomena of rupture and flow in solids. Philosophical transactions of the royal society of london. Series A, containing papers of a mathematical or physical character 221, 163–198 (1921). Rice, J. Thermodynamics of the quasi-static growth of Griffith cracks. Journal of the Mechanics and Physics of Solids 26, 61–78 (1978). Vasudevan, A., Lubomirsky, Y., Chen, C.-H., Bouchbinder, E. & Karma, A. Oscillatory and tip-splitting instabilities in 2D dynamic fracture: The roles of intrinsic material length and time scales. Journal of the Mechanics and Physics of Solids 151, 104372 (2021). Acocella, V., Gudmundsson, A. & Funiciello, R. Interaction and linkage of extension fractures and normal faults: examples from the rift zone of Iceland. Journal of Structural Geology 22, 1233–1246 (2000). Fender, M. L., Lechenault, F. & Daniels, K. E. Universal shapes formed by two interacting cracks. Physical Review Letters 105, 125505 (2010). Koivisto, J., Dalbe, M.-J., Alava, M. & Santucci, S. Path (un) predictability of two interacting cracks in polycarbonate sheets using Digital Image Correlation. Scientific reports 6, 32278 (2016). Mesgarnejad, A., Imanian, A. & Karma, A. Phase-field models for fatigue crack growth. Theoretical and Applied Fracture Mechanics 103, 102282 (2019). Tsai, H.-C., Chen, C.-H. & Shu, Y.-C. Crack behavior in nacre-like composites: a phase-field method in Bioinspiration, Biomimetics, and Bioreplication XI 11586 (2021), 1158608. Bourdin, B., Marigo, J.-J., Maurini, C. & Sicsic, P. Morphogenesis and propagation of complex cracks induced by thermal shocks. Physical review letters 112, 014301 (2014). Ambrosio, L. & Tortorelli, V. M. Approximation of functional depending on jumps by elliptic functional via t-convergence. Communications on Pure and Applied Mathematics 43, 999–1036 (1990). Hossain, M., Hsueh, C.-J., Bourdin, B. & Bhattacharya, K. Effective toughness of heterogeneous media. Journal of the Mechanics and Physics of Solids 71, 15–32 (2014). Raina, A. & Miehe, C. A phase-field model for fracture in biological tissues. Biomechanics and modeling in mechanobiology 15, 479–496 (2016). Khaderi, S., Murali, P. & Ahluwalia, R. Failure and toughness of bio-inspired composites: Insights from phase field modelling. Computational materials science 95, 1–7 (2014). Gültekin, O., Dal, H. & Holzapfel, G. A. Numerical aspects of anisotropic failure in soft biological tissues favor energy-based criteria: A rate-dependent anisotropic crack phase-field model. Computer methods in applied mechanics and engineering 331, 23–52 (2018). Niskanen, K., Kettunen, H. & Yu, Y. Damage width: a measure of the size of fracture process zone in 12th Fundamental Research Symposium, Oxford, UK (2001). Bonamy, D. et al. Experimental investigation of damage and fracture in glassy materials at the nanometre scale. International Journal of Materials and Product Technology 26, 339–353 (2006). Yang, C., Kim, Y., Ryu, S. & Gu, G. X. Prediction of composite microstructure stress-strain curves using convolutional neural networks. Materials & Design 189, 108–509 (2020). Irwin, G. R. Analysis of stresses and strains near the end of a crack traversing a plate (1957). Irwin, G. R. Onset of fast crack propagation in high strength steel and aluminum alloys tech. rep. (Naval Research Lab Washington DC, 1956). Wang, C. H. Introduction to fracture mechanics (DSTO Aeronautical and Maritime Research Laboratory Melbourne, Australia, 1996). Adumitroaie, A. Initiation and Evolution of Matrix Cracking in Non-Symmetric Laminates under in-Plane and Flexural Loading (West Virginia University, 2012). Srinivasan, M. & Seetharamu, S. Fracture toughness of metal castings. Science and technology of casting processes, 285–312 (2012). Roylance, D. Introduction to fracture mechanics (2001). Gdoutos, E. E. & Gdoutos, E. E. Crack growth based on energy balance. Fracture Mechanics Criteria and Applications, 112–161 (1990). Rozen-Levy, L., Kolinski, J. M., Cohen, G. & Fineberg, J. How fast cracks in brittle solids choose their path. Physical Review Letters 125, 175501 (2020). Sadd, M. H. Elasticity: theory, applications, and numerics (Academic Press, 2009). Solanki, K., Daniewicz, S. & Newman Jr, J. Finite element modeling of plasticityinduced crack closure with emphasis on geometry and mesh refinement effects. Engineering Fracture Mechanics 70, 1475–1489 (2003). Kristensen, P. K., Niordson, C. F. & Martínez-Pañeda, E. An assessment of phase field fracture: crack initiation and growth. Philosophical Transactions of the Royal Society A 379, 20210021 (2021). Kobayashi, R. A brief introduction to phase field method. AIP Conference Proceedings 1270, 282–291. eprint: https://aip.scitation.org/doi/pdf/10.1063/ 1.3476232 (2010). Steinbach, I. Phase-field models in materials science. Modelling and simulation in materials science and engineering 17, 073001 (2009). Murali, P. et al. Role of modulus mismatch on crack propagation and toughness enhancement in bioinspired composites. Physical Review E 84, 015102 (2011). Pons, A. J. & Karma, A. Helical crack-front instability in mixed-mode fracture. Nature 464, 85–89 (2010). Gurtin, M. E. Generalized Ginzburg-Landau and Cahn-Hilliard equations based on a microforce balance. Physica D: Nonlinear Phenomena 92, 178–192 (1996). Brencich, A. & Gambarotta, L. Isotropic damage model with different tensile– compressive response for brittle materials.International Journal of Solids and Structures 38, 5865–5892 (2001). Karma, A. & Lobkovsky, A. E. Unsteady crack motion and branching in a phase-field model of brittle fracture. Physical review letters 92, 245510 (2004). Chen, C.-H., Bouchbinder, E. & Karma, A. Instability in dynamic fracture and the failure of the classical theory of cracks. Nature Physics 13, 1186–1190 (2017). Smith, G. D., Smith, G. D. & Smith, G. D. S. Numerical solution of partial differential equations: finite difference methods (Oxford university press, 1985). Unni, M. P., Chandra, M. G. & Kumar, A. A. Memory reduction for numerical solution of differential equations using compressive sensing in 2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA) (2017), 79–84. Guardabasso, P., Bucci, L., Skoulidou, D. K., Letizia, F. & Lizy-Destrez, S. Massive GPU Parallelisation for Cislunar Debris Mitigation Analyses (2022). Sanders, J. & Kandrot, E. CUDA by example: an introduction to general-purpose GPU programming (Addison-Wesley Professional, 2010). Nvidia. CUDA C++ Programming Guide https://docs.nvidia.com/cuda/ pdf/CUDA_C_Programming_Guide.pdf. Kondratyuk, N., Nikolskiy, V., Pavlov, D. & Stegailov, V. GPU-accelerated molecular dynamics: State-of-art software performance and porting from Nvidia CUDA to AMD HIP. The International Journal of High Performance Computing Applications 35, 312–324 (2021). Ilievski, A., Zdraveski, V. & Gusev, M. How CUDA powers the machine learning revolution in 2018 26th Telecommunications Forum (TELFOR) (2018), 420–425. Geng, S. et al. Comparison of solidification cracking susceptibility between Al-Mg and Al-Cu alloys during welding: A phase-field study. Scripta Materialia 150, 120–124 (2018). Geng, S. et al. Effects of back-diffusion on solidification cracking susceptibility of Al-Mg alloys during welding: A phase-field study. Acta Materialia 160, 85–96 (2018). Baskaran, M. M., Ramanujam, J. & Sadayappan, P. Automatic C-to-CUDA code generation for affine programs in Compiler Construction: 19th International Conference, CC 2010, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2010, Paphos, Cyprus, March 20-28, 2010. Proceedings 19 (2010), 244–263. Lindholm, E., Nickolls, J., Oberman, S. & Montrym, J. NVIDIA Tesla: A unified graphics and computing architecture. IEEE micro 28, 39–55 (2008). Nukada, A., Ogata, Y., Endo, T. & Matsuoka, S. Bandwidth intensive 3-D FFT kernel for GPUs using CUDA in SC’08: Proceedings of the 2008 ACM/IEEE conference on Supercomputing (2008), 1–11. Ujaldón, M. CUDA achievements and GPU challenges ahead in Articulated Motion and Deformable Objects: 9th International Conference, AMDO 2016, Palma de Mallorca, Spain, July 13-15, 2016, Proceedings 9 (2016), 207–217. Liang, T.-Y. & Chang, Y.-W. GridCuda: a grid-enabled CUDA programming toolkit in 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications (2011), 141–146. Cheng, J., Grossman, M. & McKercher, T. Professional CUDA c programming (John Wiley & Sons, 2014). Mastrostefano, E. Large Graphs on multi-GPUs (2013). Ortega, J. M. & Rheinboldt, W. C. Monotone iterations for nonlinear equations with application to Gauss-Seidel methods. SIAM Journal on Numerical Analysis 4, 171–190 (1967). Konstantinidis, E. & Cotronis, Y. Accelerating the red/black SOR method using GPUs with CUDA in Parallel Processing and Applied Mathematics: 9th International Conference, PPAM 2011, Torun, Poland, September 11-14, 2011. Revised Selected Papers, Part I 9 (2012), 589–598. Choquette, J., Lee, E., Krashinsky, R., Balan, V. & Khailany, B. 3.2 the A100 datacenter GPU and Ampere architecture in 2021 IEEE International Solid-State Circuits Conference (ISSCC) 64 (2021), 48–50. Konstantinidis, E. & Cotronis, Y. A quantitative performance evaluation of fast on-chip memories of gpus in 2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP) (2016), 448–455. Nvidia. NVIDIA A100 Tensor Core GPU Architecture https://images.nvidia. com/aem-dam/en-zz/Solutions/data-center/nvidia-ampere-architecture-whitepaper.pdf. Inam, R. An introduction to gpgpu programming-cuda architecture (Mälardalen University, Mälardalen Real-Time Research Centre, 2010). Torres, Y., Gonzalez-Escribano, A. & Llanos, D. R. uBench: exposing the impact of CUDA block geometry in terms of performance. The Journal of Supercomputing 65, 1150–1163 (2013). Choquette, J. & Gandhi, W. Nvidia a100 gpu: Performance & innovation for gpu computing in 2020 IEEE Hot Chips 32 Symposium (HCS) (2020), 1–43. Tran, N.-P. & Lee, M. Parameter tuning model for optimizing application performance on gpu in 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS* W) (2016), 78–83. Torres, Y., Gonzalez-Escribano, A. & Llanos, D. R. Understanding the impact of CUDA tuning techniques for Fermi in 2011 International Conference on High Performance Computing & Simulation (2011), 631–639. Kirk, D. B. & Wen-Mei, W. H. Programming massively parallel processors: a hands-on approach (Morgan kaufmann, 2016). Ryoo, S. et al. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA in Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming (2008), 73–82. Yi, X., Stokes, D., Yan, Y. & Liao, C. CUDAMicroBench: Microbenchmarks to Assist CUDA Performance Programming in 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (2021), 397–406. Rosen, P. A visual approach to investigating shared and global memory behavior of CUDA kernels in Computer Graphics Forum 32 (2013), 161–170. Yang, Z., Zhu, Y. & Pu, Y. Parallel image processing based on CUDA in 2008 International Conference on Computer Science and Software Engineering 3 (2008), 198–201. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92243 | - |
| dc.description.abstract | 大自然在數萬年演化下，許多生物材料已經發展出其特殊優異的抵抗裂紋增生結構，像是骨頭、牙齒、珍珠質、海綿骨針、蟹類外骨骼等，其中某些生物材料像是珍珠質成分有著極高的脆性材料佔比，但卻能表現出超過該脆性材料數十倍的韌性，如此優異的增韌機制是目前人造材料無法達到的，許多學者與工程師希望能了解這些生物材料特殊結構抵抗裂紋的機制；相場法近幾年被大量用於許多裂紋研究中，並被證實在模擬裂紋方面具有相當可靠的準確性，同時相場法因具備獨有不須特別追蹤複雜裂紋邊界的性質，相當適合模擬生物材料中的裂紋生長行為，然而由於相場法在模擬尺度上使用材料破裂過程區作為尺度大小約為µm，而生物材為了描述其特殊結構，所設定的模型尺寸計算所需花費的時間會相當可觀。
近幾年隨著電腦高速運算的崛起，發展出許多有效率的計算架構，而本研究團隊透過Nvidia公司推出的CUDA架構來幫助我們提升計算效率，該方法雖然能有效提升計算效率，但在程式模型架構上須同時遵守硬體與軟體眾多規則才能完全發揮硬體資源效能，為了使相場法裂紋模型，能有效率的幫助我們進行模擬分析，我們透過對於平行計算架構的環境參數調整與測試，藉此來達到提升計算效率的方式，另一部分將模型加入共享記憶體使用，透過該記憶體能在計算時提供更低的資料傳輸延遲縮短模擬時間，達成對於團隊日後裂紋模擬效率上的提升。 | zh_TW |
| dc.description.abstract | Throughout thousands of years of natural evolution, various biological materials such as bones, teeth, nacre, sponge spicule, and crustacean exoskeletons have developed unique crack-resistant structures. Some biological materials, like nacre, possess high proportions of brittle components yet demonstrate toughness several times greater than the brittle material. This outstanding toughening mechanism remains beyond the capabilities of current synthetic materials. Scholars and engineers aspire to understand the specific structural mechanisms in these biological materials that resist crack propagation.
In recent years, the phase-field method has been extensively employed in crack studies, proving its considerable accuracy in simulating crack behavior. The phase-field method is particularly suitable for simulating crack growth in biological materials due to its unique ability to avoid tracking complex crack boundaries. However, its use of material fracture processes at a scale of approximately µm poses a substantial computational time challenge when modeling the unique structures of biological materials. With the rise of high-speed computing, our research team utilized Nvidia’s CUDA architecture to enhance computational efficiency. While effective, achieving optimal hardware resource utilization requires adherence to numerous hardware and software rules in the programming model. To efficiently utilize the phase-field method for crack modeling and simulation analysis, we adjusted and tested environmental parameters for parallel computing architecture, aiming to enhance computational efficiency. Additionally, we incorporated shared memory usage into the model to reduce data transfer latency during computation, thereby shortening simulation time and contributing to the team’s future efficiency in crack simulations. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-03-21T16:13:52Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-03-21T16:13:52Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 致謝 i
摘要 ii Abstract iii 目次 v 圖次 vii 表次 xi 第一章 緒論 1 1.1 前言 1 第二章 研究方法 10 2.1 線彈性斷裂力學 10 2.2 應變能 15 2.3 相場法 16 2.4 系統總能 17 2.5 位移場、速度場與加速度場計算 20 2.6 離散化 21 2.7 平行計算 23 2.8 CPU與GPU差異 25 2.9 CUDA執行架構 26 第三章 研究結果與優化 30 3.1 CUDA硬體架構 30 3.2 CUDA軟體架構 32 3.3 軟體與硬體資源參數優化調整 33 3.4 共享記憶體 38 3.4.1 共享記憶體設定 40 3.4.2 共享記憶體測試結果 40 第四章 結論與未來展望 43 4.1 結論 43 4.2 未來展望 44 參考文獻 46 附錄A — 三維加速度場 54 附錄B — 熱傳模型程式碼 57 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 相場法 | zh_TW |
| dc.subject | 平行運算 | zh_TW |
| dc.subject | 高效能運算 | zh_TW |
| dc.subject | 生物材料 | zh_TW |
| dc.subject | 裂紋 | zh_TW |
| dc.subject | CUDA | zh_TW |
| dc.subject | phase-field | en |
| dc.subject | crack | en |
| dc.subject | biomaterials | en |
| dc.subject | CUDA | en |
| dc.subject | parallel computing | en |
| dc.subject | high performance computing | en |
| dc.title | CUDA架構下相場法裂紋模擬：平行化架構參數調整與效能分析 | zh_TW |
| dc.title | Crack simulation using phase-field method on CUDA architecture: parallelization framework parameter adjustment and performance analysis | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 詹楊皓;舒貽忠 | zh_TW |
| dc.contributor.oralexamcommittee | Yang-Hao Chan;Yi-Chung Shu | en |
| dc.subject.keyword | 相場法,裂紋,生物材料,CUDA,平行運算,高效能運算, | zh_TW |
| dc.subject.keyword | phase-field,crack,biomaterials,CUDA,parallel computing,high performance computing, | en |
| dc.relation.page | 67 | - |
| dc.identifier.doi | 10.6342/NTU202400099 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2024-02-04 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 應用力學研究所 | - |
| dc.date.embargo-lift | 2025-02-01 | - |
| 顯示於系所單位： | 應用力學研究所 | |
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