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.
This repository contains a simple Excel spreadsheet for creating oncoplots to illustrate genetic mutations in a patient population. It does not require or depend on any other software to use. Edit the gray-shaded cells with a designated mutation type ID (below) to identify the observed mutation (rows) for each patient (columns).
The default configuration identifies eight types of mutations (by type ID):
Missense Mutation (green)
Frame Shift Insertion (purple)
In Frame Insertion (dark red)
Frame Shift Deletion (blue)
Splice Site (orange)
Nonsense Mutation (bright red)
Multi Hit (dark blue)
In Frame Deletion (brown)
and specifies nine placeholder genes (rows) for 22 patients (columns).
A bar plot above indicates mutation type per patient and a bar plot to the right indicates mutation type per gene.
Add or remove genes by right-clicking on a row and selecting “Insert” or “Delete”. After inserting a new row, copy and paste the equations for the entire row from an adjacent row.
Add or remove patients by right-clicking on a column and selecting “Insert” or “Delete”. After inserting a new column, copy and paste the equations for the entire column from an adjacent column.
This repository contains a simple Excel spreadsheet for creating swimmer plots to illustrate patient stories. It does not require or depend on any other software to use. Edit any of the cells with blue text to customize the swimmer plots which are available in both horizontal and vertical orientations.
The default configuration allows for up to 100 data items in five categories:
Patient Information — sets the bounds for a swim lane bar (ID, History Start Date, History End Date)
“Treatment” Event — adds a red triangle to the swim lane (Patient ID and Date)
“Biopsy” Event — adds a black circle to the swim lane (requires Patient ID and Date)
“Transplant” Event — adds a green square to the swim lane (requires Patient ID and Date)
“Alive” Indicator — adds an arrow to the end of a swim lane (requires Patient ID)
If you add or remove patients, adjust the chart axis limits to ensure all are visible (left click to select patient axis, right click and select “Format Axis…”).
If you add or more events, edit the chart series (right click, select “Select data…”, click “Add” or “Remove”, similar to existing event series).
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.
On August 17, 2020 Paul Grogan presented an abstract titled “Risk Dominance as a Decision Criterion for Collective Systems Design” for the 32nd International Conference on Design Theory and Methodology (DTM) at the 2020 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC-CIE). Check it out below!