This program has been archived.
Engineering and Systems Design (ESD)
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Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.
The Engineering and Systems Design (ESD) program supports fundamental research leading to new engineering and systems design methods and practices for specific global contexts. In particular, ESD seeks intellectual advances in which the theoretical foundations underlying design and systems engineering are operationalized into rigorous and pragmatic methods for a specific context. In addition, the program funds the rigorous theoretical and empirical characterization of new or existing methods for design and systems engineering, identifying in which global contexts and under which assumptions these methods are effective and efficient. Such a global context includes both a domain (such as energy systems, consumer products, cyber-physical systems) and an economic, socio-political, environmental and technological context.
Application of existing design methods or tools to new domains is out of scope. Research in ESD should advance the state of knowledge of design methodology, for instance, by adapting existing methods to a new context or by carefully characterizing existing or new design methods in a new context. Research focused on the theoretical foundation of design and systems engineering in a generic, domain-independent fashion should be submitted to the Systems Science program (SYS).
Research topics of interest in ESD include, but are not limited to:
- Design for X, where X is either a specific domain (e.g., energy systems, consumer products, or additive manufacturing) or a specific concern (e.g., resilience, sustainability, usability, or manufacturability). New design-for-X methods should be carefully characterized: What are the assumptions being made? What are the boundaries of the domain over which the method is applicable? In addition, for concern-focused methods, it is important to frame the problem holistically. A specific concern should not be considered just by itself at the exclusion of other concerns.
- Novel information and communication technologies
Design and systems engineering are supported and enabled by information and communication technologies. As these technologies evolve, design and systems engineering methods need to be adapted to best take advantage of them. Examples of technologies of interest include: immersive visualization and human-computer interaction, social networking and net-enabled collaboration, modeling frameworks and languages, data mining and analytics, high-performance computing and cloud-computing. The improvements resulting from the introduction of such new technologies should be carefully characterized by gathering theoretical and/or empirical evidence.
- Novel modeling formalisms and algorithms
Modeling is an integral part of design and systems engineering. ESD supports research towards new modeling formalisms and improvements in algorithms to support design and systems engineering. Examples include: formalisms and algorithms for representing and manipulating form, function and behavior; algorithms for analysis, simulation, optimization, or reasoning; algorithms for prediction, uncertainty quantification and propagation. The improvements resulting from the introduction of such new formalisms or algorithms should be carefully characterized by gathering theoretical and/or empirical evidence.
- Novel integrated frameworks for design and systems engineering
Although advances in design and systems engineering can be made by improving individual models, modeling formalisms, algorithms, methods or tools, significant further advances are likely to result from integrating multiple such capabilities into an integrated framework. ESD supports research towards novel integrated frameworks that combine preference and belief elicitation, concept generation, gradual specification refinement, modeling at different levels of abstractions, uncertainty characterization, optimization, HPC, visualization, etc. The improvements resulting from the introduction of such a new framework should be carefully characterized by gathering theoretical and/or empirical evidence.