Sample Projects

Overview of SEAri's five research threads

The following are some sample SEAri projects, organized by specific topic and relevant research thread.

Specific Topic


Multi-Attribute Tradespace Exploration (MATE)

Multi-Attribute Tradespace Exploration (MATE) applies decision theory to model and simulation-based design. Its purpose is to help users generate insights into "what constitutes a good design solution" through enumeration (e.g. thousands or more) and evaluation (e.g. through performance, cost, and value models) of many possible solutions. Decoupling the design from the need through tradespace exploration, MATE is both a solution generating as well as a decision-making framework. The tradespace exploration paradigm discourages premature optimization and instead promotes investigation of underlying constraints, relationships between what is desired and what is technically feasible, and the degree of alignment of various stakeholder desires and the associated technical and cost implications.

Epoch-Era Analysis (EEA)

Epoch-Era Analysis (EEA) is a framework designed to clarify the effects of changing contexts over time on the perceived value of a system in a structured way. The base unit of time in EEA is the epoch, which is defined as a time period of fixed needs and context in which the system exists. Epochs are represented using a set of epoch variables, which can be continuous or discrete values. These variables can be used to represent any exogenous uncertainty that might have an effect on the usage and perceived value of the system; weather conditions, political scenarios, financial situations, operational plans, and the availability of other technologies are all potential epoch variables. Appropriate epoch variables for an analysis include key (i.e., impactful) exogenous uncertainty factors that will affect the perceived success of the system. A large set of epochs, differentiated using different enumerated levels of these variables, can then be assembled into eras, ordered sequences of epochs creating a description of a potential progression of contexts and needs over time. This approach provides an intuitive basis upon which to perform analysis of value delivery over time for systems under the effects of changing circumstances and operating conditions, an important step to take when evaluating large-scale engineering systems with long lifecycles.

Interactive Model-Centric Systems Engineering (IMCSE)

The IMCSE research program aims to develop transformative results through enabling intense human-model interaction, to rapidly conceive of systems and interact with models in order to make rapid trades to decide on what is most effective given present knowledge and future uncertainties, as well as what is practical given resources and constraints. IMCSE focuses at the intersection of four pillars: visual analytics, big data science, model-based systems engineering and the complex systems domain. The team has discovered key challenges for further investigation, including visual analytics of artificial (model-generated) data; trade-off and choice of models; and cognitive and perceptual considerations in human-model interaction.

IMCSE Pathfinder Project

The IMCSE Pathfinder project is investigating the current state of the art/practice in interactive model-centric systems engineering. Knowledge gathering and literature review are being used to establish a preliminary picture of what is being done in practice including current methods, processes and tools and what research has/is being performed. Periodic workshops and technical exchanges are used to identify research opportunities, gaps and issues.

Interactive Schedule Reduction Model (ISRM)

Intense human-model interaction through new design methods and tools may improve perception and reduce effort to realize descriptively-complex systems. Applied to system project management, models may help assess alternative system development processes and resource allocations. Traditional modeling environments do not effectively support a paradigm for collaborative modeling emphasizing model sharing and reuse, massive data generation and storage, and advanced visualizations-areas in which web- based technologies excel. ISRM addresses two challenges to advance collaborative modeling. First, it aims to identify how a browser-based environment can replicate existing features of a SD model. Second, it aims to adapt existing technologies to support sensitivity analyses and advanced visualizations of results.

Interactive Epoch-Era Analysis (IEEA)

Key challenges in application of EEA up to this point involve eliciting a potentially large number of relevant epochs and eras, conducting analysis across these epochs and eras, and extracting useful and actionable information from the analyses. For many problem formulations it is not feasible to evaluate systems across all or even a large fraction of potential eras. Research in the areas of big data analysis and visual analytics both have led to techniques that could be leveraged to mitigate these challenges. It is hypothesized in this research that augmenting the traditional EEA approach with new analytic and interactive techniques will fundamentally enable new capabilities and insights to be derived from EEA, resulting in superior dynamic strategies for resilient systems.

IVTea Suite

IVTea Suite (Interactive Value-Driven Tradespace Exploration and Analysis Suite) is a software package developed in MATLABĀ® at the MIT Systems Engineering Advancement Research Initiative (SEAri). It is intended to help engineering analysts, stakeholders, and decision makers uncover insights about their systems and support value robust decision making in the face of large, uncertain problems. The software is a research support tool, and not intended for broad circulation as a final product for users.

Tradespace Explorers

The summer 2011 project was entitled "Interactive Games for Accelerated Insights into Dynamic System Strategies." The project was conducted by six undergraduate EECS students along with four SEAri graduate students tasked with leveraging purposeful game design techniques to both teach and study the application of SEAri constructs. The outcome was a python-based game that layered a game engine on top of pre-existing research data set with the vision of creating a "playful" experience in the mind of the user while exploring actual datasets.

Space Tug Skirmish

Space Tug Skirmish (STS) was originally conceived in the summer of 2011 as a potential solution to the challenge of rapidly teaching SEAri research material using the medium of games. Over the years, it has become readily apparent that the lab's graduate students typically require a year of immersion before existing SEAri research methods and terminology begins to feel tangible, delaying their ability to contribute effectively with individual research. Given that SEAri's research is also placed at the interface of engineering and upper-management decision making, this slow learning curve is also problematic in demonstrating contributions to potential high-level adopters, particular those with less technical backgrounds. Educational games seemed to offer a great deal of promise as both an effective way of conveying complex ideas and relationships in a short period of time and also a fun distillation of the work that could be used to spark interest. This led to the need: can we use a game to teach a completely unsophisticated player (no social/technical/systems experience) a basic understanding of system design, particularly the benefits of -ilities given future uncertainty? This question became the catalyst for the central idea behind STS, a card game designed to evoke the tension between designing a system and operating it, all while other players and random uncertainties try to interfere with your goals.

Digital Space Tug Skirmish

The summer 2013 project was entitled "Interactive Games as a Research Medium to Improve Engineering Systems Thinking." In order to facilitate data collection on player behaviors this project was undertaken to implement STS as an online-multiplayer computer game, with the primary purpose of facilitating data collection. Specifically the goals were: to implement Space Tug Skirmish v3.0 as a software-based game (including operationalizing game mechanics, providing compelling visual and interactive experience); with tracking (including database to store game state and player actions with standard schema); and level design capabilities (including separate scripted (i.e. deck and possible player AI) game design functionality); to have a software platform that enables easy modification (e.g. change card properties, modify game rules); and most importantly: preserve engaging player experience with the game!