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RISS 인기검색어
- 검색키워드
- 저자 : Fritz Sihombing (검색결과 3 건)
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Fritz Sihombing,Marco Torbol 국제구조공학회 2016 Smart Structures and Systems, An International Jou Vol.18 No.6
This study presents a new method to computes analytical fragility curves of a structure subject to tsunami waves. The method uses dynamic analysis at each stage of the computation. First, the smooth particle hydrodynamics (SPH) model simulates the propagation of the tsunami waves from shallow water to their impact on the target structure. The advantage of SPH over mesh based methods is its capability to model wave surface interaction when large deformations are involved, such as the impact of water on a structure. Although SPH is computationally more expensive than mesh based method, nowadays the advent of parallel computing on general purpose graphic processing unit overcome this limitation. Then, the impact force is applied to a finite element model of the structure and its dynamic non-linear response is computed. When a data-set of tsunami waves is used analytical fragility curves can be computed. This study proves it is possible to obtain the response of a structure to a tsunami wave using state of the art dynamic models in every stage of the computation at an affordable cost.
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Fritz Sihombing,Marco Torbol 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.2
The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.
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Parallel fault tree analysis for accurate reliability of complex systems
Sihombing, Fritz,Torbol, Marco Elsevier 2018 Structural safety Vol.72 No.-
<P><B>Abstract</B></P> <P>Fault tree analysis is one of the methods for the probabilistic risk assessment of components and subsystems of nuclear power plants. The algorithms that solve a fault tree have been until now serial. Instead, this study presents new algorithms that handle and solve a fault tree by taking advantage of the new state of the art in parallel computing: general purpose graphic processor unit (GPGPU). The subsystems of nuclear power plants are the target of this study. However, the method can be used on many others, complex, engineering systems. The different, developed, parallel algorithms are: one builder, which assembles the topology matrix of the fault tree and leads the computation of the three, developed, new solvers. A bottom-up solver, a cut sets solver, and a Monte Carlo simulation solver. The probability of the top event, and the probabilities of each cut sets are computed. The results shows that, given the same investment, a GPU can handle larger fault trees than a CPU implementation. The developed solvers are the foundation of the next generation parallel algorithms for the tree-based analysis of complex systems.</P> <P><B>Highlights</B></P> <P> <UL> <LI> New algorithms are proposed to solve fault trees on parallel general purpose GPU architecture. </LI> <LI> The obtained framework execute fault tree analysis faster and better than existing serial software. </LI> <LI> More cut sets than ever before can be identified. </LI> <LI> Existing fault trees can be solved by the new parallel algorithms. </LI> </UL> </P>
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