Insight最新文献

Systems engineering today faces a wide array of challenges, ranging from new operational environments to disruptive technological — necessitating approaches to improve research and development (R&D) efforts. Yet, emphasizing the Aristotelian argument that the “whole is greater than the sum of its parts” seems to offer a conceptual foundation creating new R&D solutions. Invoking systems theoretic concepts of emergence and hierarchy and analytic characteristics of traceability, rigor, and comprehensiveness is potentially beneficial for guiding R&D strategy and development to bridge the gap between theoretical problem spaces and engineering-based solutions. In response, this article describes systems–theoretic process analysis (STPA) as an example of one such approach to aid in early-systems R&D discussions. STPA—a ‘top-down’ process that abstracts real complex system operations into hierarchical control structures, functional control loops, and control actions—uses control loop logic to analyze how control actions (designed for desired system behaviors) may become violated and drive the complex system toward states of higher risk. By analyzing how needed controls are not provided (or out of sequence or stopped too soon) and unneeded controls are provided (or engaged too long), STPA can help early-system R&D discussions by exploring how requirements and desired actions interact to either mitigate or potentially increase states of risk that can lead to unacceptable losses. This article will demonstrate STPA's benefit for early-system R&D strategy and development discussion by describing such diverse use cases as cyber security, nuclear fuel transportation, and US electric grid performance. Together, the traceability, rigor, and comprehensiveness of STPA serve as useful tools for improving R&D strategy and development discussions. Leveraging STPA as well as related systems engineering techniques can be helpful in early R&D planning and strategy development to better triangulate deeper theoretical meaning or evaluate empirical results to better inform systems engineering solutions.

This paper hypothesizes that a system-of-systems (SoS) that is not fit for purpose is so because it cannot implement the correct, timely, and complete transfers of material, energy, and information (MEI) between its constituents and with its external environment that are necessary to achieve a particular result. This research addresses the problem of maintaining a SoS fit for purpose after unpredictable changes in operation, composition, or external factors by creating a method, implemented as an engineering process, and supported by an analysis technique to enhance the affordance {“Features that provide the potential for interaction by affording the ability to do something” (Norman 1999)} of SoS constituents for MEI transfer and reveal potential undesirable transfers.

The introduction of automation into technical systems promises many benefits, including performance increase, improved resource economy, and fewer harmful accidents. In particular, in the automotive sector, automated driving is seen as one key element in Vision Zero by eliminating common accident causes such as driving under the influence, reckless behavior, or distracted drivers. However, this is contrasted by new failure modes and hazards from the latest technologies. In this article, we address the problems of finding common sources of criticality for specific application classes and identifying and quantitatively assessing new sources of harm within particular automated driving systems.

This article summarizes the development of a System of Systems Analytic Workbench (SoS AWB) that provides a set of computational tools to facilitate better-informed decision-making on evolving SoS architectures. The workbench motif is adopted since SoS practitioners typically generate archetypal technical queries that can be mapped to appropriate analysis methods best suited to provide outputs and insights directly relevant to posed questions. After an overview of the workbench framework, four distinct methods currently available for use are presented along with their distinctive aspects in the concept of use.

Engineered Resilient Systems (ERS) is a Department of Defense (DoD) program focusing on the effective and efficient design and development of complex engineered systems across their lifecycle. An important area of focus is the evaluation of early-stage design alternatives in terms of their modeled operational performance and characteristics. The work in this paper ties together differentiated operational needs with requirements specification and maturation of previous analytical constructs toward a more operationally relevant viewpoint. We expand on the concept of Broad Utility as a high-level aggregated measure of robustness of fielded system capabilities with respect to operational requirements. The relation to requirements is more explicit, and systems are failing to achieve threshold requirements are penalized. The impact of this approach and how it offers a foundation from which to more fully explore sensitivity to Pre-Milestone A requirements are discussed.

Modern design of nuclear facilities represents unique challenges: enabling the design of complex advanced concepts, supporting geographically dispersed teams, and supporting first-of-a-kind system development. Errors made early in design can introduce silent errors. These errors can cascade causing unknown risk of complex engineering programs. The Versatile Test Reactor (VTR) Program uses digital-engineering principles for design, procurement, construction, and operation to reduce risk and improve efficiencies. Digital engineering is an integrated, model-based approach which connects proven digital tools such as building information management (BIM), project controls, and systems-engineering software tools into a cohesive environment.

The VTR team hypothesizes using these principals can lead to similar risk and cost reductions and schedule efficiencies observed in other engineering industries. This research investigates the use of a digital engineering ecosystem in the design of a 300-MWt sodium-cooled fast reactor. This ecosystem was deployed to over 200 engineers and used to deliver the conceptual design of the VTR. We conclude that initial results show significant reductions in user latency (1000x at peak use), the possibility of direct finite-element-analysis (FEA) integrations to computer-aided design (CAD) tools, and nuclear reactor system design descriptions (SDDs) that we can fully link throughout design in data-driven requirements-management software. These early results led to the VTR maintaining milestone performance during the COVID-19 pandemic.

Resilience is a much-needed characteristic in systems that are expected to operate in uncertain environments for extended periods with a high likelihood of disruptive events. Resilience approaches today employ ad hoc methods and piece-meal solutions that are difficult to verify and test, and do not scale. Furthermore, it is difficult to assess the long-term impact of such ad hoc “resilience solutions.” This paper presents a flexible contract-based approach that employs a combination of formal methods for verification and testing and flexible assertions and probabilistic modelling to handle uncertainty during mission execution. A flexible contract (FC) is a hybrid modelling construct that facilitates system verification and testing while offering the requisite flexibility to cope with non-determinism. This paper illustrates the use of FCs for multi-UAV swarm control in, partially observable, dynamic environments. However, the approach is sufficiently general for use in other domains such as self-driving vehicle and adaptive power/energy grids.