High‐Performance Computing in Structural Mechanics and Engineering

Adeli, Hojjat; Kamat, Manohar P.; Kulkarni, Girish; VanLuchene, R. D.

doi:10.1061/(asce)0893-1321(1993)6:3(249)

Cited by 34 publications

(30 citation statements)

References 51 publications

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“…A solution to this problem can be found in high-performance and cloud computing. Although high-performance computing provides new and interesting opportunities to solve large-scale structural engineering problems (Papadrakakis et al, 2011;Hori et al, 2018), the development of new computational models and algorithms that exploit the unique architecture of these machines still remains a challenge (Adeli and Soegiarso, 1998). Cloud Computing is a model for enabling convenient, ondemand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort (Mell and Grance, 2011).…”

Section: High-performance and Cloud Computingmentioning

confidence: 99%

Computational Structural Engineering: Past Achievements and Future Challenges

Plevris

Tsiatas

2018

Front. Built Environ.

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PAST ACHIEVEMENTS AND CURRENT TRENDSComputational methods are computer-based methods used to numerically solve mathematical models that describe physical phenomena. The purpose of computational modeling is to study the behavior of complex systems by means of computer simulations and it can be used to make predictions of the system's behavior under different conditions, often for cases in which intuitive analytical solutions are not available (Nature, 2018). Computational methods have emerged in engineering during the 1960s. Since then, structural engineers have been leaders in technological solutions to engineering analysis and design problems. The evolution of electronic computers together with the tremendous increase of computational power has triggered the continuous development of computational methods. Rapid advances in computer hardware have had a profound effect on various engineering disciplines. The applications are numerous and cover a broad field of engineering branches including civil, mechanical, naval, electrical, aerospace, material, biomolecular, among others. Computational structural engineering has evolved as an insightful blend combining both structural analysis and computer science.Among all computational methods, the Finite Element Method (FEM) and the Boundary Element Method (BEM) are the most prevalent ones. Both methods exhibit unique characteristics as well as advantages and disadvantages. The FEM, as a simulation tool, enables sophisticated methods of computational mechanics, computer technology and applied mathematics. It has been broadly adopted in scientific research and engineering applications and it can be considered as the most popular method used for structural analysis, tackling linear and nonlinear problems of systems with various geometries, material properties and loads (Reddy, 2005). In FEM, the solution domain is subdivided into a finite number of elements. Each element approximately reproduces the behavior of a small region of the body it represents, but continuity between the elements is only enforced in an overall minimum energy sense. The FEM is especially suitable for problems with complex geometries, but the whole-body discretization scheme that is utilized inevitably leads to a large number of finite elements and, thus, increased computational cost. Although Professor R. Clough coined the term "Finite Element Method" in his pioneer work dated back in 1960 (Clough, 1960), the answer to the question "who invented FEM in everyday use?" is possibly M. Jonathan (Jon) Turner at Boeing who generalized and perfected the Direct Stiffness Method, and convinced his company to commit resources to it, over the period 1952 -1964(Felippa, 2017. The FEM obtained its real impetus in the 1960s and 1970s by the developments of pioneers J. H. Argyris, R. W. Clough, H. C. Martin, O. C. Zienkiewicz and their co-workers who evolved the method and applied it to a wide range of structural problems and applications.In the years since its first use, FEM has grown and developed into a standard...

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Section: High-performance and Cloud Computingmentioning

confidence: 99%

Computational Structural Engineering: Past Achievements and Future Challenges

Plevris

Tsiatas

2018

Front. Built Environ.

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“…The reference label results from implementation of the constant-work algorithm to be discussed in greater detail later in this article. Equation (14) requires that the condensed stiffness matrix and the condensed reference nodal load vector be formulated. The condensed tangent stiffness matrix is computed via…”

Section: Substructuring and Inelastic Analysismentioning

confidence: 99%

“…12,48 Several additional sources of information summarizing the most recent advances in highperformance computing are available. 10,11,13,14 Although an abundance of research has been performed in a wide variety of areas related to high-performance computing in structural engineering, the inelastic nonlinear analysis of large structural steel frameworks using parallel processing, vectorization, and substructuring has yet to receive attention. Application of the divide and conquer analytical paradigm in conjunction with parallel processing shows promise in the realm of inelastic stability analysis.…”

Section: Introductionmentioning

confidence: 99%

“…However, excellent reviews of past research efforts in applications of substructuring, parallel processing, and vectorization in computational mechanics are available. 2,6,15,26,28,60 Much of the past research in applications of substructuring and parallel processing have emphasized large-structure design optimization, 3,7,49,51 the elastic analysis of large structures, 4,5,8,9,31,32 nonlinear transient analysis, 35,53 nonlinear finite-element analysis, 36 and implementation of parallel equation solvers. The neural dynamics model has been implemented recently in the optimal design of large structures.…”

Section: Introductionmentioning

confidence: 99%

“…A truncated Taylor series expansion of the subelement equilibrium equations can be used to develop the subelement tangent stiffness, given by (7) where the component matrices are the same as those given in Equation (6). It should be noted that the vectors of fixed end actions and plastification forces drop out of the incremental equations as a result of the partial differentiation.…”

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confidence: 99%

See 2 more Smart Citations

Advanced Analysis of Steel Frames Using Parallel Processing and Vectorization

Foley

2001

Computer aided Civil Eng

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Distributed finite element structural analysis using the client–server model

Hudli

Pidaparti

1995

Commun. Numer. Meth. Engng.

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SUMMARYThe paper presents a distributed computing approach for concurrent finite element analysis of truss structures. The client-server model of distributed computation is applied to the plane frame finite element algorithm and implemented on SUN workstations. The remote procedure call combined with the ability to create threads of computation allows one to efficiently implement distributed and concurrent programs. The present approach is demonstrated through a typical truss structure to illustrate the details of the implementation. This approach can be used for very large finite element systems.

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High‐Performance Computing in Structural Mechanics and Engineering

Cited by 34 publications

References 51 publications

Computational Structural Engineering: Past Achievements and Future Challenges

Computational Structural Engineering: Past Achievements and Future Challenges

Advanced Analysis of Steel Frames Using Parallel Processing and Vectorization

Distributed finite element structural analysis using the client–server model

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