A method of representing design solutions in complex systems through model-parametric spaces

Abstract

On the side of highly complicated systems, it is necessary to have powerful frameworks that can present solution design integration and visualization in the best possible manner, dealing with clarity, scalability, and adaptability. This work aims to formulate an innovative approach for modeling design solutions using model-parametric spaces to create a systematically structured yet convenient method for dealing with multidimensional design complexities. This investigation is conducted within a mixed-method research design combining qualitative assessments of system architecture with quantitative modeling techniques to formulate parametric spaces where design variables and their interrelations are parameterized systematically. The validation of that methodology was done in a way that involves simulated operational scenarios and expert-driven evaluation, which shows the robustness and versatility of the understanding achieved using the approach in different fields of study. Results reveal the utility of model-parametric spaces in vastly increasing the interpretability, modularity, and optimization capability of complex design processes. Therefore, the study argues that this methodology framework is a solid and reasoned basis for decisions in the systems engineering domain and positively explains both research and industrial applications. These future research trajectories determined by this study include further extensive validation within actual project settings to make the developed software more applicable and impactful in the physical world.