ASDL is currently undertaking a broad range of research initiatives. These initiatives are designed to bring together common research being performed around the lab to create a comprehensive understanding that advances the state-of-the-art in each area. Because participants in each initiative have diverse research and experience backgrounds, the initiatives benefit from a multi-perspective approach, and are able to cross-fertilize between areas that historically have not shared information. Research initiatives are led by Research Engineers (REs) and are designed to explore fundamental concepts and ideas that will benefit multiple sponsored projects across multiple divisions, as well as spawn thesis research topics for Ph.D. students. Participants in each initiative include a mix of REs and students with an interest in the associated topic area.
The Relational Oriented Systems Engineering Technology Tradeoff Analysis (ROSETTA) Initiative is attempting to bridge the gap between qualitative subject matter expert driven techniques and quantitative modeling and simulation techniques. In the same way that the Rosetta stone provided a means to translate between the Greek, Hieroglyphics, and Egyptian demotic languages by having the same text (a decree) repeated in all three languages, the Relational-Oriented Systems Engineering and Technology Tradeoff Analysis (ROSETTA) Environment provides a means to translate between theoretical mathematics, subject-matter expert driven analysis, and modeling and simulation, by representing a single problem using all three types of analysis and highlighting the commonalities and differences between the different representations of the problem. Since these techniques are often used in different phases of the systems engineering process, these side by side comparisons will allow feedback to be provided as to how to improve the systems engineering process for future similar studies.
The Architecture-based Technology Evaluation and Capability Tradeoff (ARCHITECT) initiative is performing research in the area of architecture-based engineering. Much of the current focus is on enabling quantitative architecture level trades during early phases of design and developments. This initiative is also exploring the many systems engineering challenges presented by system of systems (SoS), including the complexity, the high level of stochastic behavior, the managerial and operational independence of elements, and the large and diverse alternative space available to decision makers. Several thrusts are presently being explored in parallel, including a high-level methodology for SoS architecture selection, techniques to enable analysis of alternatives for SoS, modeling and simulation techniques and challenges for SoS (in conjunction with the AGENT initiative), and how to measure and understand the impact of complexity in the context of SoS. In addition, this initiative is heavily focused on researching the development and use of executable architectures for a variety of applications, as well as expanding the abilities of executable architectures beyond the current state-of-the-art.
Project AGENT is exploring the broad range of non-physics-based modeling techniques to tackle key challenges in study for complex adaptive systems. While Agent-Based Modeling and Simulation (ABM/S) and System Dynamics (SD) remain at the core, other modeling techniques that are currently being leveraged and expanded as part of this effort include network models , discrete event simulations, constructive simulations as well as Markov models and stochastic Petri net models to name a few.
The Integrated Reconfigurable Intelligent Systems (IRIS) initiative is proposed as a response to the U.S. Navy’s challenges for designing next-generation surface combatants that meet operational goals for increased mission effectiveness, survivability, environmental compatibility, and reduced operating cost. An IRIS designed system is envisioned to integrate several intelligent systems onboard to collect the information about the environment and ship state, assess the situation and then take a best course of action to reconfigure the ship into the state most suitable to handle the situation at hand. This indicates that the IRIS designed system possesses three main functions: the ability to sense, assess and react.The main objective of this research initiative is to develop methods to support the U.S. Navy in the study, design, and operation of complex naval systems.
Unconventional and innovative methods and strategies are investigated in order to capture complex system in a highly dynamic and uncertain environment, including resilience assessment, dynamic modeling and co-simulation, graph-based modeling, hierarchical intelligent control, and human in the loop control. Total ship systems engineering approaches are explored for the development of a dynamic modeling and simulation environment, integrating multiple physics-based models (electrical power system, cooling network and hierarchical control system), to accurately simulate the dynamic behavior that the systems exhibit and represent the total operations of typical naval ship architecture. Following the envisioned core IRIS functionality, possible techniques are explored for designing control systems, in order to enable system reconfigurability, platform automation and intelligence. Given that control system design is tightly coupled with the physical system architecture, advanced design approaches (resilience-based design, flexible and adaptive controls) are explored for concurrently addressing system effectiveness, survivability and safety requirements.
The CASSANDRA initiative focuses on the elicitation, modeling, propagation of uncertainty, and how uncertainty can be used to help quantify and apply risk analysis during design.
The PROMETHEUS initiative is researching variable-fidelity physics-based modeling.
The ASM initiative is exploring Advanced Surrogate Modeling. The primary goal of the ASM initiative is to advance the capability of surrogate modeling so that surrogates can be used with more accuracy on a wider range of modeling types, including dynamic models, stochastic models, and highly non-linear models. Surrogate types being researched include neural networks (NN), Gaussian Processes, and Kriging Models. Current research topics for this area include dynamic surrogates, surrogates of stochastic models, and NN learning algorithms. In addition, selection of the correct design of experiments for a given surrogate and development of new types of design of experiments are being researched.
Continuum explores the full breadth of engineering problems, from the macro level of requirements development and operations analysis, to the micro level of material selection and sub-system design, and everything in between. This initiative explores how to drill down into a problem, what level of fidelity is required at each level of the drill down, and how the linkages between levels work.
Huddle (Human Unified Digital Design Laboratory Environment) is the next step for real time collaborative design environments like the CoDE and CoVE. While these facilities have advanced design processes through the co-location of people and tools, Huddle will extend these facilities by providing a user friendly data fusion framework. The framework serves as a common point between collaborators and tools where information from each source can be combined to expand the collective understanding of all of the stakeholders. Huddle allows engineers to share variables, functions, files, archives, and computational resources through an intuitive client-server architecture. The server sports a friendly web-based interface which is utilized by both a graphical-user-interface and Huddle libraries written for the following major engineering tools: Excel, JMP, Matlab, Python, ModelCenter, and Flex. By facilitating quick exchanges (milliseconds) of variable values or other media between these tools over a network engineers can quickly enhance knowledge propagation within a team.
The goal of the Huddle project is provide a framework which is easy enough to use to attract further research into collaborative design processes.