1. Integrated Modeling and Simulation
This research area involves developing methods and tools to analyze the
interactions between phenomena, disciplines or subsystems in complex
systems and products such as spacecraft, aircraft and automobiles. These
models typically involve coupling various physics-based governing equations
with each other and potentially with empirical models such as response
surface models (RSM) or neural networks. The behavior of the systems of
interest can then be modeled and simulated in a single, integrated
environment. Research questions involve abstraction strategies, model
integration and reduction schemes, computational efficiency and model
validation with experimental data, among others.
2. Multidisciplinary Design Optimization
Multidisciplinary design optimization (MDO) focuses on optimizing the
performance and reducing the costs of complex systems involving multiple
interacting disciplines, such as those found in aircraft, spacecraft,
automobiles, industrial manufacturing equipment, various consumer products,
and on the development of related methodologies. MDO is a broad area that
encompasses design synthesis, sensitivity analysis, approximation concepts,
optimization methods and strategies, artificial intelligence, and
rule-based design in the context of integrated design dealing with multiple
disciplines and/or subsystem interactions. In some cases it is possible to
simply wrap an optimizer around an integrated model (such as the ones
developed in area 1.), in other cases the problem requires careful
decomposition of the system model and optimization at multiple levels.
3. System Architecture and Engineering
System Architecture involves the early process of identifying stakeholder
needs and mapping these to useful system functions and ultimately to
physical elements and instantiations of form. The description of a system
concept involves specification of an operating principle for the system, as
well as a mapping from form to function. For short-lived, simple systems
the functions and associated performance levels might be easily understood
and formulated as targets. For long-lived, capital-intensive systems
freezing requirements early might not be appropriate and designing modular,
flexible systems that can be deployed in stages, adaptively reconfigured,
and scaled in performance and capacity might be more appropriate. This
gives rise to research on product families and flexible platforms as well
as real options and modularity.
4. Engineering Systems Studies
An important aspect of graduate education in Engineering Systems in the
future will be the use of systems studies that combine historical data,
systems theory and simulations in unprecedented and effective ways . My
group has completed such an Industry Systems study entitled "Low Earth
Orbit Satellite Communication Constellations and Real Options Analysis",
commissioned by the Engineering Systems Learning Center (ESLC http://i2i.mit.edu ). Additional studies are underway.
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