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The issue of digitalization in chemical technology production is currently quite pressing, and the available computational infrastructure is insufficient for assessing the technological properties of the products obtained through mathematical modeling tools. This problem is particularly relevant for polymer synthesis processes, where standard empirical evaluations require enormous computational resources, and existing methods and algorithms prove ineffective when organizing multiple computational trials to select optimal production scenarios. The aim of this study is to develop a cloud-based digital service that enables comprehensive research into complex physicochemical processes occurring via polymerization mechanisms. The implementation of all algorithms is based on the use of kinetic and statistical approaches to modeling, and the embedded calculation methods are adapted to the specifics of polymerization processes. The conceptual framework of the developed cloud service is represented by a three-tier network architecture, and the established mechanism of network interaction allows the service to operate in a 24-hour multi-user mode. Task execution in the remote environment and the distribution of computational resources are handled using Docker containerization technology, which provides software-level virtualization within the operating system. The storage subsystem is managed by the MongoDB database management system, which supports distributed information storage functions. The organization of test computational experiments in evaluating the detailed properties of polymer products allowed for the assessment of the system’s core logic in web interface mode and the adequacy of the obtained calculation results. Doi: 10.28991/ESJ-2024-08-06-023 Full Text: PDF
Miftakhov et al. (Sun,) studied this question.