MDO

Multidisciplinary Design Optimization (MDO) is a field in engineering and systems design that aims to optimize a product or system by simultaneously considering multiple interacting disciplines. In MDO, design variables can pertain to aerodynamics, structures, propulsion, controls, manufacturing, and other domains, while the objective function (or set of objectives) and constraints reflect system-level performance, weight, cost, reliability, and other criteria. The goal is to find design choices that offer the best overall performance given trade-offs between disciplines, rather than optimizing each discipline in isolation.

MDO typically relies on coupled analyses or simulations, sometimes using co-simulation, surrogate models, and optimization algorithms. Architectures range from loosely coupled or sequential designs to strongly coupled or fully integrated frameworks, depending on the degree of interaction among disciplines and the available computational resources. Common methods include gradient-based optimization, surrogate-assisted optimization, and multiobjective techniques to explore compromises among competing goals.

Applications are widespread in aerospace engineering (aircraft and spacecraft design), automotive and energy systems, wind turbines, naval engineering, and industrial product design. The approach can reduce development time and weight, improve performance, and enable more robust trade studies, but it is computationally intensive and requires careful management of data, models, and workflows. Interdisciplinary collaboration and compatible modeling tools are essential to successful MDO implementations.

See also: systems engineering, optimization, multiobjective optimization. MDO as an acronym may have other domain-specific meanings outside this field.