Numerical models for casting solidification: Part I. The coupling of the boundary element and finite difference methods for solidification problems

1984 ◽  
Vol 15 (1) ◽  
pp. 91-99 ◽  
Author(s):  
C. P. Hong ◽  
T. Umeda ◽  
Y. Kimura
2013 ◽  
Vol 34 (4) ◽  
pp. 161-173 ◽  
Author(s):  
Dawid Taler ◽  
Piotr Cisek

Abstract The analyzed heat accumulator is a key element in a hybrid heating system. In this paper, analytical and numerical models of the ceramic heat accumulator are presented.The accuracy of finite difference methods will be assessed by comparing the results with those obtained from the exact analytical solution.


Robotica ◽  
2021 ◽  
pp. 1-12
Author(s):  
Xu-Qian Fan ◽  
Wenyong Gong

Abstract Path planning has been widely investigated by many researchers and engineers for its extensive applications in the real world. In this paper, a biharmonic radial basis potential function (BRBPF) representation is proposed to construct navigation fields in 2D maps with obstacles, and it therefore can guide and design a path joining given start and goal positions with obstacle avoidance. We construct BRBPF by solving a biharmonic equation associated with distance-related boundary conditions using radial basis functions (RBFs). In this way, invalid gradients calculated by finite difference methods in large size grids can be preventable. Furthermore, paths constructed by BRBPF are smoother than paths constructed by harmonic potential functions and other methods, and plenty of experimental results demonstrate that the proposed method is valid and effective.


Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 206
Author(s):  
María Consuelo Casabán ◽  
Rafael Company ◽  
Lucas Jódar

This paper deals with the search for reliable efficient finite difference methods for the numerical solution of random heterogeneous diffusion reaction models with a finite degree of randomness. Efficiency appeals to the computational challenge in the random framework that requires not only the approximating stochastic process solution but also its expectation and variance. After studying positivity and conditional random mean square stability, the computation of the expectation and variance of the approximating stochastic process is not performed directly but through using a set of sampling finite difference schemes coming out by taking realizations of the random scheme and using Monte Carlo technique. Thus, the storage accumulation of symbolic expressions collapsing the approach is avoided keeping reliability. Results are simulated and a procedure for the numerical computation is given.


Sign in / Sign up

Export Citation Format

Share Document