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            Development of Advanced Methods for Theoretical Prediction of Shakedown Stress States and Physically Based Enhancement of Experimental Data: Volume III
      

      
  Document Series
              Other Reports


      
  Author
          J. Kogut, J. Orkisz


      
Office
              RRD


      Subject
                    Evaluation


      
  Keywords
              Residual Stress, Neural Networks, Mathematical Modeling


      

      
      
              
                  
      
              
  Document
              2003_DEVELOPMENT OF ADVANCED METHODS FOR THEORETICAL PR.PDF (45.26 MB)

      
              A neural network approach to theoretical prediction of required residual stresses is considered here. Artificial neural networks trained well and long enough on residual stresses induced by various contact loads may provide very fast response. Results of numerical meshless finite difference analyses were pre- processed and introduced into the neural networks as input and output parameters. The study was performed for two different types of neural networks: a backpropagation neural network (BPNN) and a newly examined radial basis function neural network (RBF).
      
            
      
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              Last updated: Sunday, June 1, 2003 U.S. DEPARTMENT OF TRANSPORTATION

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