To improve accessibility and responsiveness of CAE tools within our organization, we developed a web-based simulation service using Plotly Dash, a Python-based web application framework. Traditional workflows required engineers to rely on specialized departments for complex analyses. In contrast, simple calculations were handled using standalone tools. These tools, however, lacked maintainability and scalability, and were highly dependent on local environments. To address these limitations, we introduced a browser-based simulation system that allows engineers to run analyses without installing dedicated software, thereby minimizing dependency on local environments. In addition, server-side computation provides consistent performance across users and enables centralized management of computational resources. The service provides spreadsheet-like input interfaces and interactive visualizations. To improve computational efficiency, performance-critical routines, such as FEM solvers, were reimplemented in C++ and Fortran, reducing processing time from several minutes to approximately one second. To further explore its capabilities, the system’s performance in parallel computation and real-time visualization using Plotly Dash was evaluated through a simulation of fluid flow in a laboratory-scale electroplating tank, employing the lattice Boltzmann method (LBM). This simulation revealed technical challenges related to concurrent execution and time-dependent rendering. Although further improvements are required, the results demonstrate the system’s practical utility for internal engineering support and its potential for broader application in web-based CAE tools.
TAKANO et al. (2025) studied this question.