Evaluation of Nonlinear Structural Dynamic Responses Using a Fast-Running Spring-Mass Formulation
It has been a fond desire of structural analysts to be able to calculate the dynamic responses of very large, highly nonlinear systems without expending a year’s allocation of computer funds with every run. In today’s world, accurate finite-element simulations of large nonlinear systems may require meshes composed of hundreds of thousands of degrees of freedom. Even with today’s fast computers and the promise of ever-faster ones in the future, central processing unit (CPU) expenditures for such problems could be measured in days. Many contemporary engineering problems, such as those found in risk assessment, probabilistic structural analysis, and structural design optimization, cannot tolerate the cost or turnaround time for such CPU-intensive analyses, because these applications require a large number of cases to be run with different inputs. For many risk assessment applications, analysts would prefer running times to be measurable in minutes. There is therefore a need for approximation methods which can solve such problems far more efficiently than the very detailed methods and yet maintain an acceptable degree of accuracy. For this purpose, we have been working on two methods of approximation: neural networks and spring-mass models.
KeywordsCentral Processing Unit Finite Element Code Sandia National Laboratory Lateral Impact Structural Design Optimization
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