Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Systems Engineering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Overview of the Systems Engineering Process as It Applies to The National Spherical Torus Experiment - Upgrade (NSTX-U)

This paper addresses the systems engineering (SE) processes used for the National Spherical Torus Experiment-Upgrade (NSTX-U). It focuses on SE across the life cycle of the system, including requirements management, interface control, risk management, integration, and verification/validation. This is particularly significant as NSTX-U includes new systems and an existing plant and reused systems from past projects such as the Tokamak Fusion Test Reactor (TFTR). The implementation of SE provides the ability to control complexity, improve communications, identify risks early, and prevent defects. Systems engineering principles are applied to enhance the integration while maintaining relevance in plasma research. Furthermore, these principles define a deliberate process to identify and resolve issues early in the development cycle, thus reducing risks and optimizing outputs. They also establish relationships to gather knowledge from experts and stakeholders, supporting the continued ability of NSTX-U in building and maintaining an operational system able to adapt to changing environments and emerging requirements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2016

Systems Engineering Awareness

The presentation will provide an overview of the fundamentals and principles of Systems Engineering (SE). This includes understanding the processes that are used to assist the engineer in a successful design, build and implementation of solutions. The context of this presentation will be to describe the involvement of SE throughout the life-cycle of a project from cradle to grave. Due to the ever growing number of complex technical problems facing our world, a Systems Engineering approach is desirable for many reasons. The interdisciplinary technical structure of current systems, technical processes representing System Design, Technical Management and Product Realization are instrumental in the development and integration of new technologies into mainstream applications. This tutorial will demonstrate the application of SE tools to these types of problems..

technical management↗
NASA NTRS2002

Engine System Loads Analysis Compared to Hot-Fire Data

Early implementation of structural dynamics finite element analyses for calculation of design loads is considered common design practice for high volume manufacturing industries such as automotive and aeronautical industries. However with the rarity of rocket engine development programs starts, these tools are relatively new to the design of rocket engines. In the NASA MC-1 engine program, the focus was to reduce the cost-to-weight ratio. The techniques for structural dynamics analysis practices, were tailored in this program to meet both production and structural design goals. Perturbation of rocket engine design parameters resulted in a number of MC-1 load cycles necessary to characterize the impact due to mass and stiffness changes. Evolution of loads and load extraction methodologies, parametric considerations and a discussion of load path sensitivities are important during the design and integration of a new engine system. During the final stages of development, it is important to verify the results of an engine system model to determine the validity of the results. During the final stages of the MC-1 program, hot-fire test results were obtained and compared to the structural design loads calculated by the engine system model. These comparisons are presented in this paper.

Frady, Gregory P.↗
DOE OSTI2023

Bayesian, Multifidelity Operator Learning for Complex Engineering Systems–A Position Paper

Abstract Deep learning has significantly improved the state-of-the-art in computer vision and natural language processing, and holds great potential to design effective tools for predicting and simulating complex engineering systems. In particular, scientific machine learning seeks to apply the power of deep learning to scientific and engineering tasks, with operator learning (OL) emerging as a particularly effective tool. OL can approximate nonlinear operators arising in complex engineering systems, making it useful for simulating, designing, and controlling those systems. In this position paper, we provide a comprehensive overview of OL, including its potential applications to complex engineering domains. We cover three variations of OL approaches: deterministic OL for modeling nonautonomous systems, OL with uncertainty quantification (UQ) capabilities, and multifidelity OL. For each variation, we discuss drawbacks and potential applications to engineering, in addition to providing a detailed explanation. We also highlight how multifidelity OL approaches with UQ capabilities can be used to design, optimize, and control engineering systems. Finally, we outline some potential challenges for OL within the engineering domain.

Computer Science↗
NASA NTRSDate not supplied

Systems Engineering Best Practices Workshop

This presentation reflects discussion points made by participants during the Systems Engineering Best Practices workshop held during the 2024 In-Person LEARN Forum at NASA Ames Research on September 25, 2024. Points covered include those related to systems engineering in terms of best practices as applied to technical documentation, engineering activities, and risk management.

Jeff Homan↗
NASA NTRS2005

NASA Project Constellation Systems Engineering Approach

NASA's Office of Exploration Systems (OExS) is organized to empower the Vision for Space Exploration with transportation systems that result in achievable, affordable, and sustainable human and robotic journeys to the Moon, Mars, and beyond. In the process of delivering these capabilities, the systems engineering function is key to implementing policies, managing mission requirements, and ensuring technical integration and verification of hardware and support systems in a timely, cost-effective manner. The OExS Development Programs Division includes three main areas: (1) human and robotic technology, (2) Project Prometheus for nuclear propulsion development, and (3) Constellation Systems for space transportation systems development, including a Crew Exploration Vehicle (CEV). Constellation Systems include Earth-to-orbit, in-space, and surface transportation systems; maintenance and science instrumentation; and robotic investigators and assistants. In parallel with development of the CEV, robotic explorers will serve as trailblazers to reduce the risk and costs of future human operations on the Moon, as well as missions to other destinations, including Mars. Additional information is included in the original extended abstract.

Dumbacher, Daniel L.↗
DOE OSTI2017

How systems engineering and human factors can assist SMR vendors with the licensing process - 345

There is growing interest in the development of small modular reactors (SMRs) as a cost-effective renewable source of energy. Most of the current conceptual designs propose advanced and automated control and monitoring technologies which would require complex human system interfaces. The proposals also include a reduction in the number of staff, and partial or full remote control of the facilities. The human factors challenges of such a design philosophy range from identification of information requirements of users to assessing workload to deciding on best information visualization techniques to ensure situation awareness is maintained in a remote control facility. Addressing these challenges will require a systems engineering approach where user requirements are identified through a systematic approach for various contexts, including normal, abnormal, and accident conditions. A systems engineering process will integrate human factors as well as other specialty disciplines such as reliability and design optimization in a coherent fashion that would lead to realization of a successful system that addresses user requirements. The licensing model in Canada is based upon a graded approach and is largely technology neutral. A key factor in ensuring effective licensing effort is identification of regulatory requirements. This paper discusses how adopting a systems engineering approach and early consideration of human factors principles and requirements will not only ensure an efficient design process, but will also help with developing a design that meets the regulatory requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2004

Innovative Design of Complex Engineering Systems

The document contains the proceedings of the training workshop on Innovative Design of Complex Engineering Systems. The workshop was held at the Peninsula Higher Education Center, Hampton, Virginia, March 23 and 24, 2004. The workshop was jointly sponsored by Old Dominion University and NASA. Workshop attendees came from NASA, other government agencies, industry and universities. The objectives of the workshop were to a) provide broad overviews of the diverse activities related to innovative design of high-tech engineering systems; and b) identify training needs for future aerospace work force development in the design area. The format of the workshop included fifteen, half-hour overview-type presentations, a panel discussion on how to teach and train engineers in innovative design, and three exhibits by commercial vendors.

Noor, Ahmed K.↗
DOE OSTI2021

Perceived Conflicts of Systems Engineering in Early-Stage Research and Development 1

Early Systems Research and Development (ESR&D) is one of the most crucial phases in the product development process. It both blends and blurs the lines between science and engineering, and requires a risk-based, disciplined, and graded approach to effectively manage scope, cost, and complexity of the final product. Many leaders, program managers, and scientists are unwilling to involve systems engineering because of the perception that systems engineering is heavily process oriented, adds unnecessary costs, and should be applied only to mature technologies. The value of systems engineering as applied to ESR&D is unclear to these key individuals. The unfortunate result is that system engineering is not applied to ESR&D. This results in R&D efforts that may have solved the wrong problem, selected the wrong architecture, require technical rework, have difficulty transitioning later maturity levels, and result in higher R&D costs and extended development timelines. This work discusses the difficulty of introducing systems engineering to the research and early development process and their inclination perspectives of researchers, engineers, and managers. The article shall offer potential means to manage the cultural transformation of early adoption of right-sized systems engineering in ESR&D and reverse the attitudinal positions.

42 ENGINEERING↗
NASA NTRSDate not supplied

Lean Model-Based Systems Engineering on the NASA High-Density Vertiplex Subproject

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) in July of 2020, prior to subproject formulation. A small and lean team of HDV Systems Engineers (SE) are utilizing MagicDraw to execute NASA SE processes via MBSE. The SEs learned how to use MagicDraw from scratch and HDV is the first project for which the SEs have utilized MagicDraw. This presentation will demonstrate project technical execution via MBSE, utilizing the digital elements built into the SysML (Systems Modeling Language). SysML provides a model-centric means of carrying out the NASA SE common technical processes by providing tools for complete system modeling, including requirements and interface management and design capture. The authors also leverage and extend SysML to perform other SE tasks, such as Verification and Validation (V&V) tracking. MBSE has two main purposes for HDV: 1) documenting the subproject’s logical architecture for distribution outside of the subproject, 2) capturing the subproject’s physical architecture in a single-source-of-truth for use by the subproject’s members. This presentation details the challenges, lessons learned, and solutions that were encountered in implementing MBSE in the first iteration on a multi-iteration, full-lifecycle design, build, fly project.

systems engineering↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗
NASA NTRS2014

System Engineering of Autonomous Space Vehicles

Human exploration of the solar system requires fully autonomous systems when travelling more than 5 light minutes from Earth. This autonomy is necessary to manage a large, complex spacecraft with limited crew members and skills available. The communication latency requires the vehicle to deal with events with only limited crew interaction in most cases. The engineering of these systems requires an extensive knowledge of the spacecraft systems, information theory, and autonomous algorithm characteristics. The characteristics of the spacecraft systems must be matched with the autonomous algorithm characteristics to reliably monitor and control the system. This presents a large system engineering problem. Recent work on product-focused, elegant system engineering will be applied to this application, looking at the full autonomy stack, the matching of autonomous systems to spacecraft systems, and the integration of different types of algorithms. Each of these areas will be outlined and a general approach defined for system engineering to provide the optimal solution to the given application context.

Watson, Michael D.↗
NASA NTRS2009

The Case for Distributed Engine Control in Turbo-Shaft Engine Systems

The turbo-shaft engine is an important propulsion system used to power vehicles on land, sea, and in the air. As the power plant for many high performance helicopters, the characteristics of the engine and control are critical to proper vehicle operation as well as being the main determinant to overall vehicle performance. When applied to vertical flight, important distinctions exist in the turbo-shaft engine control system due to the high degree of dynamic coupling between the engine and airframe and the affect on vehicle handling characteristics. In this study, the impact of engine control system architecture is explored relative to engine performance, weight, reliability, safety, and overall cost. Comparison of the impact of architecture on these metrics is investigated as the control system is modified from a legacy centralized structure to a more distributed configuration. A composite strawman system which is typical of turbo-shaft engines in the 1000 to 2000 hp class is described and used for comparison. The overall benefits of these changes to control system architecture are assessed. The availability of supporting technologies to achieve this evolution is also discussed.

Culley, Dennis E.↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗