Systems Engineering and Design Lab (SEDL)
Co-Directors Dr. Alejandro Salado and Dr. Hanumanthrao "Rao" Kannan
Summary: We focus on transdisciplinary fundamental and translational research that studies the design, development, acquisition, and sustainment of complex engineered systems. We develop engineering methods that we implement to a diverse portfolio of applications. We have extensive experience in the areas of problem formulation, applied decision analysis, system architecture and design, model-based systems engineering (MBSE), and verification and validation.
Current research areas:
· Requirements engineering: We develop techniques for improving the elicitation of requirements by means of achieving higher levels of coverage with lower amounts of requirements. These techniques include the development of true model-based requirements, the automated generation of contractual requirements out of model elements, and the incorporation of artificial intelligence as an engineering assistant to the requirements analyst, leveraging organizational knowledge and model structures.
· Preference representation and communication: We perform studies to effectively model stakeholder preferences and communicate them consistently across organizational hierarchies. We leverage formal logic in order to rigorously define preferences in a similar fashion to established definitions of knowledge and beliefs and apply this to development of complex engineered systems.
· Architecture and design: We develop quantitative approaches to improve system architecture and design. We seek improvement in two areas: 1) Realistic application of fundamental theories and 2) Aggregation of architectural perspectives, with a particular focus to assessing the impact of contractual structures to the system architecture. These approaches are based on decision-based design, value-based engineering, value-driven design, multidisciplinary optimization (MDO), and graph theory.
· Verification and validation (V&V): We study how engineers make V&V decisions and develop quantitative methods to improve those decisions. These methods leverage statistical tools such as Bayesian analysis, psychological methods such as cognitive mapping, and design approaches that we adapt to the V&V domain such as tradespace exploration, set-based design, decision-based design, and MBSE.
· Education: We develop instructional approaches to bridge the disconnect between professional practice and college education in engineering. These approaches are aimed at transforming students into decision-makers in ambiguous contexts rather than solvers of idealized problems.
Systems Engineering and Design Lab
206 Durham Hall
1145 Perry Street
Blacksburg, VA 24061