Abstract
To increase the pace of the design of safer road infrastructure and raise the active and passive safety features of road structures on the global stage, innovative and smart virtual tools are essential. One of the basic steps for such ground breaking numerical simulation technology would be to develop advanced smart hybrid techniques with dynamic adaptation into mainstream design and simulation tools that are used by engineering offices. In the research work herein, a new numerical framework including dynamic zoning, advanced grid interfacing, new computationally-efficient solvers, and genetic algorithm symbolic-regression has briefly been presented to address long-standing problems of speed, accuracy, and reliability of numerical tools. The fundamental physical and mathematical aspects of the new simulation framework are concisely presented. In addition, some outcomes of real-world case studies utilized using the proposed hybrid analytical and data-driven (i.e., machine learning, ML) scheme have been shown, where the design rule for road gantry structures is interrogated using the developed virtual tool. One of the main contributions of this paper is to show the benefits of using hybrid simulation technologies to model engineering systems along with the ML-based method to optimize their designs.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
2 articles.
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