Browser-Based Parametric Modeling: Bridging Web Technologies with CAD Kernels
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V1I3P107Keywords:
Browser-Based CAD, Parametric Modeling, WebAssembly, JavaScript, CAD Kernel, IndexedDB, WebGL, OpenCascade, Performance Optimization, Cloud CADAbstract
Parametric modeling has turned out to be a mandatory maxim in computer-aided design (CAD) that allows designers and engineers to build geometrically limited models that can be shaped or changed without problems by manipulating parameters. However, the conventional CAD systems are highly dependent on hardware-demanding software installation along with the platform-specific systems. This paper discusses the possibility of parametric modelling to work through browsers, incorporating CAD kernels with web technologies, specifically WebAssembly and JavaScript. WebAssembly makes web-capable execution fast (near-native performance), whereas JavaScript is the glue providing user interaction, presentation of a UI, and the ability to dynamically modify parameters of a design. This study explores the realities, challenges and problems associated with integrating CAD kernels like OpenCascade and Parasolid with web front-ends and the implications of dealing with performance bottlenecks, problems of persistent storage, responsiveness of user interfaces and management of data in the cloud. The idea is to assess the possibility of the existence of an alternative to conventional desktop-based modeling environments in the form of a web-based platform. One of the fundamental issues will be interactive performance, as the computational intensity is characteristic of the parametric operations. We look at WebAssembly optimizations and multi-threading (when possible), and compare the complexities of models with responsiveness trade-offs. The solutions we investigate in persistent model storage are local browser storage (IndexedDB) and remote storage through REST APIs and GraphQL. They provide details of a complete case study where a sophisticated parametric model is formulated, edited and saved entirely on the browser. Our results are compared with those of other existing traditional CAD platforms in terms of metrics such as load time, interaction delay, model regeneration rate, and user satisfaction, as measured through surveys. Our results show that parametric modeling with a browser can not only be done, but it can also be sufficient to cover a broad scope of design opportunities, especially in cases of collaborations, learning and lightweight design. Nevertheless, it has a problem in scaling up with very complex assemblies and in advanced integration of simulation. This paper lays the groundwork for future research into high-performance web-based CAD systems and their integration into broader digital engineering workflows
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