Motivated by the growth of the commercial space economy and renewed focus on the disaggregation of military space systems, this work develops a method for conceptual design of federated satellite systems as a collaborative system of systems (SOS). Objectives seek to improve the likelihood of successful SOS formation and pursue constituent system utility robustness. The proposed metaheuristic optimization trade-space exploration method accounts for technical and economic design variables and multi-decision-maker strategy dynamics. Constituent system designs are ranked on their simulated net present value. A game-theoretic measure of risk dominance is used in concert with the net present value to assess the robustness and utility of candidate SOS designs. The method is validated with a notional application case that assesses potential collaboration between Earth-observing and telecommunications systems. The proposed methodology reduces the threshold probability of partner collaboration for which SOS participation is economically rational by up to 18% for the most efficient designs as compared to a typical conceptual design method, thereby increasing the likelihood of successful SOS formation. The results highlight the importance of accounting for strategy dynamics when designing systems for collaboration.
Robust designs protect system utility in the presence of uncertainty in technical and operational outcomes. Systems-of-systems, which lack centralized managerial control, are vulnerable to strategic uncertainty from coordination failures between partially or completely independent system actors. This work assesses the suitability of a game-theoretic equilibrium selection criterion to measure system robustness to strategic uncertainty and investigates the effect of strategically robust designs on collaborative behavior. The work models interactions between agents in a thematic representation of a mobile computing technology transition using an evolutionary game theory framework. Strategic robustness and collaborative solutions are assessed over a range of conditions by varying agent payoffs. Models are constructed on small world, preferential attachment and random graph topologies and executed in batch simulations. Results demonstrate that systems designed to reduce the impacts of coordination failure stemming from strategic uncertainty also increase the stability of the collaborative strategy by increasing the probability of collaboration by partners; a form of robustness by environment shaping that has not been previously investigated in design literature. The work also demonstrates that strategy selection follows the risk dominance equilibrium selection criterion and that changes in robustness to coordination failure can be measured with this criterion.
A new research paper co-authored by Leigha Capra, Jay Hilton, Sarah Bentley, Theodore Sherman, Aaron Alfaro, Ryan Savin, Olivier de Weck and Paul Grogan appears in the AIAA ASCEND 2021 conference proceedings. The paper will be presented on November 10, 2021.
The advancing digital engineering landscape generates a need for modern human space exploration logistics planning tools. The goal of the SpaceNet Cloud project is to build a tool to satisfy this need through a dynamic web-based application based on the existing SpaceNet space logistics tool. SpaceNet Cloud condenses the process of organizing, constructing, and analyzing a mission scenario into a user-friendly web-based application. A simplistic interface, coupled with powerful backend capabilities allows SpaceNet Cloud to harness the accessibility of cloud-based computing, creating a modern take on mission logistics. The effectiveness of a user’s mission is clearly defined using an incremental mission outline process, and a clear visualization of demand analysis upon completion. The dynamic nature of the application also allows for rapid prototyping of missions based on final analysis results, and the potential for collaborative design opens opportunities for public and private sectors alike.
This chapter focuses on strategies for technical design of engineering systems. The strategies allow designers to manage the complexity arising from the interconnected nature of engineering systems, while achieving both technical and business objectives. The design strategies discussed in the chapter include hierarchical decomposition, modularity, design for emergent behaviors, modeling and simulation, and optimization-based strategies. Hierarchical decomposition forms the basis for traditional top-down systems engineering processes where the overall system is decomposed into quasi-independent modules which can be developed concurrently and integrated into the overall system. While decomposition-based approaches are ideally suited for achieving functional properties of the system, they do not provide guidance for achieving emergent properties. The strategies for design of emergent properties include design for quality, design for changeability, and, more generally, design for X. To support both top-down functional design and design for emergent properties, commonly used modeling and simulation approaches, and optimization-based approaches are discussed. The chapter discusses challenges and trade-offs in designing complex engineering systems for technical behavior, such as complexity vs. robustness, requirements vs. value, modularity vs. performance, and the interactions between social and technical aspects.
Human exploration logistics rely on a launch vehicle to place supplies in orbit. Estimating launch vehicle delay helps mission planning ensure adequate supplies under uncertainty in replenishment schedule. This paper mines launch delay data for human exploration missions from the International Space Station (ISS) US operating segment (USOS) including NASA commercial cargo (Northrop Grumman and SpaceX), ESA and JAXA missions from March 2013 to February 2017 as a mix of established mission providers (ESA and JAXA) and commercial companies spanning launch vehicle system development and recurring cargo delivery missions. Continuous probability distributions are developed using maximum likelihood estimates for launch delays associated with near-term, intermediate and long-term mission planning dates. Additionally, an approach adapted from the signal processing domain to convert the continuous distribution into a discrete probability mass function is outlined for scenario tree analysis.
This paper draws on perspectives from co-design as an integrative and collaborative design activity and co-simulation as a supporting information system to advance engineering design methods for problems of societal significance. Design and implementation of the Sustainable Infrastructure Planning Game provides a prototypical co-design artifact that leverages the High Level Architecture co-simulation standard. Three role players create a strategic infrastructure plan for agricultural, water and energy sectors to meet sustainability objectives for a growing and urbaninzing population in a fictional desert nation. An observational study conducts 15 co-design sessions to understand underlying dynamics between actors and how co-simulation capabilities influence design outcomes. Results characterize the dependencies and conflicts between player roles based on technical exchange of resource flows, identifying tension between agriculture and water roles based on water demands for irrigation. Analysis shows a correlation between data exchange, facilitated by synchronous co-simulation, and highly ranked achievement of joint sustainability outcomes. Conclusions reflect on the opportunities and challenges presented by co-simulation in co-design settings to address engineering systems problems.
This paper develops a flexibility management framework for space logistics mission planning under uncertainty through decision rules and multistage stochastic programming. It aims to add built-in flexibility to space architectures in the phase of early-stage mission planning. The proposed framework integrates the decision rule formulation into a network-based space logistics optimization formulation model. It can output a series of decision rules and generate a Pareto front between the expected mission cost (i.e., initial mass in low Earth orbit) and the expected mission performance (i.e., effective crew operating time), considering the uncertainty in the environment and mission demands. The generated decision rules and the Pareto front plot can help decision makers create implementable policies immediately when uncertainty events occur during space missions. An example mission case study about space station resupply under rocket launch delay uncertainty is established to demonstrate the value of the proposed framework.
This paper evaluates perception of complexity in a novel explanatory model that relates product performance and engineering effort. Complexity is an intermediate factor with two facets: it enables desired product performance but also requires effort to achieve. Three causal mechanisms explain how exponential growth bias, excess complexity, and differential perception lead to effort overruns. Secondary data from a human subject experiment validates the existence of perception of complexity as a context-dependent factor that influences required design effort. A two-level mixed effects regression model quantifies differences in perception among 40 design groups. Results summarize how perception of complexity may contribute to effort overruns and outline future work to further validate the explanatory model and causal mechanisms.
This paper performs an observational human subjects study to investigate how design teams use an information system to exchange, store, and synthesize information in an engineering design task. Framed through the lens of decision-based design, a surrogate design task models an aircraft design problem with 12 design parameters across four roles and six system-level functional requirements. A virtual design studio provides a browser-based interface for four participants in a 30-minute design session. Data collected across 10 design sessions provides process factors about communication patterns and outcome factors about the resulting design. Correlation analysis shows a positive relationship between design iteration and outcome performance but a negative relationship between chat messages and outcome performance. Discussion explains how advances in information exchange, storage, and synthesis can support future design activities.
Strategy dynamics are hypothesized to be a fundamental factor that influences interactive decision-making activities among autonomous design actors. The objective of this research is to understand how strategy dynamics in characteristic engineering design problems influence cooperative behaviors and collective efficiency for pairs of design actors. Using a bi-level model of collective decision processes based on design optimization and strategy selection, we formulate a series of two-actor parameter design tasks that exhibit four strategy dynamics (harmony, coexistence, bistability, and defection), associated with low and high levels of structural fear and greed. In these tasks, actors work collectively to maximize their individual values while managing the trade-offs between aligning with or deviating from a cooperative collective strategy. Results from a human-subject design experiment indicate cognizant actors generally follow normative predictions for some strategy dynamics (harmony and coexistence) but not strictly for others (bistability and defection). Cumulative link model regression analysis shows a greed factor contributing to strategy dynamics has a stronger effect on collective efficiency and equality of individual outcomes compared to a fear factor. Results of this study establish a foundation for future work to study strategic decision-making in engineering design problems and enable new methods and processes to mitigate potential unfavorable effects of their underlying strategy dynamics through social constructs or mechanism design.