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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.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

System Safety Analysis of Complex NASA Systems with Model Based Engineering

The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System

Model Based Engineering↗
DOE OSTI2023

Using Co-Optimized Machine Learned Manifolds for Modeling Chemically Reacting Flows

Chemically reacting flows play a key role in a wide range of engineered systems, from chemical and polymer processing to combustion-based energy conversion technologies. Simulations of these flows involve solving a coupled set of partial differential equations for mass, momentum, energy, and all relevant chemical species in the system. Chemical reaction pathways may be extremely complex and involve hundreds or more intermediate species, with reactions that occur over timescales varying by several orders of magnitude - presenting a significant numerical stiffness challenge. The combination of these factors makes simulation of chemically reacting flows vastly more expensive than nonreactive simulations, and often makes direct solution of the governing equations intractable. It is necessary to apply lower-fidelity models in place of the detailed governing equations in order to reduce computational cost to enable reacting flow simulation tools to be used in the engineering design process. Many of the models employed for this purpose are based on reducing the dimension of the thermochemical state, motivated by the observation that the observed thermochemical states in a system lie on a low-dimensional manifold in thermochemical state space. This behavior occurs due to the fast equilibration of certain reactive and transport processes, and physics-based manifold models rely on idealized assumptions about the balance of timescales and the way in which chemistry and transport are coupled. In this work, we apply a novel method for data-driven manifold-based modeling that can leverage data from high-fidelity reacting flow simulations to improve model accuracy in cases where the physics-based modeling assumptions break down. The approach is designed to be broadly applicable across chemically reacting flow systems but is applied here to turbulent combustion modeling.

machine learning↗
DOE OSTI2023

A complementarity-based vapor-liquid equilibrium formulation for equation-oriented simulation and optimization

Vapor-Liquid Equilibrium (VLE) is a cornerstone of computer aided process engineering (CAPE). Embedded within process system models, VLE calculations are inherently procedural with non-smooth behavior that frequently require discrete decisions. Traditionally, these features resist the incorporation of VLE within efficient, large-scale equation-oriented (EO) process simulation and optimization strategies. On the other hand, recent reformulation of VLE models through the incorporation of complementarity constraints has broadened its scope to deal seamlessly with phase transitions and even supercritical excursions in process simulation and optimization. In this study, we extend these VLE complementarity models to EO frameworks where procedural thermodynamic property libraries are still required. Here, we develop an efficient, non-intrusive, and intuitive “square-flash” equation system that has been implemented within the IDAES Integrated Platform (IDAES-IP). Further, the effectiveness of this modular approach is demonstrated on case studies for non-ideal flash calculations and distillation optimization with disappearing phases and supercritical transitions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

14 SOLAR ENERGY↗
DOE OSTI2022

Physical Modeling of Coupled Thermohydraulic Behavior of Compacted MX80 Bentonite during Heating

Abstract This paper describes a tank-scale test setup and experimental methodology used to investigate coupled heat transfer and water flow processes during heating of compacted MX80 bentonite to high temperatures. Specifically, a temperature of 200°C was maintained by a cylindrical heating element at the center of a compacted bentonite layer containing an array of temperature, dielectric, and relative humidity sensors. In addition to providing an evaluation of the spatiotemporal variations in temperature, relative humidity, degree of saturation, and global volume, the coupled thermohydraulic properties of the bentonite were assessed. A wetting front was initially observed to move away from the central heater, followed by a drying process until reaching thermohydraulic equilibrium. The soil–water retention curve (SWRC) of the bentonite followed a wetting scanning path before following the primary drying path exhibiting a shift in water retention with elevated temperature. Results from the tank-scale test can be used for validation of numerical simulations of drying processes in the engineered barrier system of a high-level radioactive waste geological disposal repository and confirm that a temperature-dependent hysteretic SWRC with scanning paths is required to accurately capture the bentonite response.

Engineering↗
DOE OSTI2024

Highly Efficient Regeneration Module for Carbon Capture Systems in NGCC Applications

The objective of this project is to design, fabricate, and test a highly efficient regeneration module capable of providing an ultra-lean absorption solution that is required for capturing CO 2 from dilute sources at 95% or better efficiency. By integrating this advanced regenerator module with SRI International’s Mixed Salt Process (MSP) absorption modules, SRI expects to demonstrate significant progress toward a reduction in cost of capture versus the DOE reference natural gas combined cycle (NGCC) plant with carbon capture. SRI designed, built, and tested an advanced stripper to enhance the performance of SRI’s MSP for CO 2 capture – a transformational ammonia-based solvent technology – for natural gas (NG) power sources. The testing of the advanced stripper for MSP was conducted at an SRI site using a simulated flue gas stream equivalent to about 10 kWe. The research work included modeling of the advanced stripper and integrating it with the MSP absorbers; studying the strategies for producing very highly alkaline lean solvent with minimized emissions; operating the stripper with advanced heat integration to improve process efficiencies; and collecting critically important data for a detailed techno-economic analysis (TEA). The project tasks were designed to address concerns relating to scale-up and integration of the technology to NG power plants—more specifically, to maximize the carbon capture efficiency achievable with MSP and identify pathways to achieve higher capture efficiencies and ultimately zero net carbon emissions. SRI teamed up with a process modeling company (OLI Systems), a process and chemical engineering company (Trimeric Corporation), and a cost-sharing commercial partner (Baker-Hughes – a leading multinational company that designs, manufactures, and services transformative energy technologies) to execute the project. The research findings will accelerate the MSP development and pave the way for the technology to reach the DOE’s goal, and ultimately commercialization of the MSP technology for low-cost CO 2 capture from NGCC flue gas and other dilute CO 2 sources.

03 NATURAL GAS↗
DOE OSTI2025

Engineered Barrier System Research Activities at SNL: FY25 Report

This report describes research and development (R&D) activities conducted at Sandia National Laboratories (SNL) during Fiscal Year 2025 (FY25) specifically related to the Engineered Barrier System (EBS) Properties & Processes Work Package in the Spent Fuel and High-Level Waste Disposition (SFHLWD) Campaign supported by the United States (U.S.) Department of Energy (DOE). SNL activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. The team represented in this report consists of individuals from SNL, Argonne National Laboratory (Advanced Photon Source), and Vanderbilt University. The activities represented in this report include development of anion sorbent materials for buffer formulations, properties of pure bentonite and bentonite mixtures, and characterization of cement interfaces relevant to the EBS. The SNL EBS activities also leverage interactions with EBS teams from other national laboratories, and international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1977

Reliability analysis of forty-five strain-gage systems mounted on the first fan stage of a YF-100 engine

The reliability of 45 state-of-the-art strain gage systems under full scale engine testing was investigated. The flame spray process was used to install 23 systems on the first fan rotor of a YF-100 engine; the others were epoxy cemented. A total of 56 percent of the systems failed in 11 hours of engine operation. Flame spray system failures were primarily due to high gage resistance, probably caused by high stress levels. Epoxy system failures were principally erosion failures, but only on the concave side of the blade. Lead-wire failures between the blade-to-disk jump and the control room could not be analyzed.

Holanda, R.↗
NASA NTRS1985

Collected software engineering papers, volume 3

Topics addressed include: software technology evaluation programs; collection of valid software engineering data; test processes using structural coverage; prototype expert system for software engineering management; use of an environment characteristic software metric set; software modulation; software development by analysis of change; and independent verification and validation.

Source record↗
NASA NTRS1992

Intelligent diagnostics systems

Intelligent systems have been applied to today's problems and could also be applied to space operations integrity. One of these systems is the XMAN tool designed for 'troubleshooting' jet engines. XMAN is the eXpert MAiNtenance tool developed to be an expert information analysis tool which stores trending and diagnostic data on Air Force engines. XMAN operates with a 'network topology' which follows a flow chart containing engine management information reports required by the governments technical order procedures. With XMAN technology, the user is able to identify engine problems by presenting the assertions of the fault isolation logic and attempting to satisfy individual assertions by referring to the databases created by an engine monitoring system. The troubleshooting process requires interaction between the technician and the computer to acquire new evidence form auxiliary maintenance tests corroboration of analytical results to accurately diagnose equipment malfunctions. This same technology will be required for systems which are functioning in space either with an onboard crew, or with an unmanned system. The technology and lessons learned developing this technology while suggesting definite applications for its use with developing space systems are addressed.

Mcquiston, Barbara M.↗
NASA NTRS2004

Video Image Tracking Engine

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

Howard, Richard T.↗
NASA NTRS2007

Monitoring by Use of Clusters of Sensor-Data Vectors

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

Iverson, David L.↗
NASA NTRSDate not supplied

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Systems Engineering↗
NASA NTRS1988

The TAME Project: Towards improvement-oriented software environments

Experience from a dozen years of analyzing software engineering processes and products is summarized as a set of software engineering and measurement principles that argue for software engineering process models that integrate sound planning and analysis into the construction process. In the TAME (Tailoring A Measurement Environment) project at the University of Maryland, such an improvement-oriented software engineering process model was developed that uses the goal/question/metric paradigm to integrate the constructive and analytic aspects of software development. The model provides a mechanism for formalizing the characterization and planning tasks, controlling and improving projects based on quantitative analysis, learning in a deeper and more systematic way about the software process and product, and feeding the appropriate experience back into the current and future projects. The TAME system is an instantiation of the TAME software engineering process model as an ISEE (integrated software engineering environment). The first in a series of TAME system prototypes has been developed. An assessment of experience with this first limited prototype is presented including a reassessment of its initial architecture.

Basili, Victor R.↗
NASA NTRS2006

G2 Flywheel Module Design

Design of a flywheel module, designated the G2 module, is described. The G2 flywheel is a 60,000 RPM, 525 W-hr, 1 kW system designed for a laboratory environment; it will be used for component testing and system demonstrations, with the goal of applying flywheels to aerospace energy storage and integrated power and attitude control (IPACS) applications. G2 has a modular design, which allows for new motors, magnetic bearings, touchdown bearings, and rotors to be installed without a complete redesign of the system. This design process involves several engineering disciplines, and requirements are developed for the speed, energy storage, power level, and operating environment. The G2 rotor system consists of a multilayer carbon fiber rim with a titanium hub on which the other components mount, and rotordynamics analysis is conducted to ensure rigid and flexible rotor modes are controllable or outside of the operating speed range. Magnetic bearings are sized using 1-D magnetic circuit analysis and refined using 3-D finite element analysis. The G2 magnetic bearing system was designed by Texas A&M and has redundancy which allows derated operation after the loss of some components, and an existing liquid cooled two pole permanent magnet motor/generator is used. The touchdown bearing system is designed with a squeeze film damper system allowing spin down from full operating speed in case of a magnetic bearing failure. The G2 flywheel will enable module level demonstrations of component technology, and will be a key building block in system level attitude control and IPACS demonstrations.

Jensen, Ralph H.↗
NASA NTRS1999

The Design of Future Airbreathing Engine Systems within an Intelligent Synthesis Environment

This paper describes a new Initiative proposed by the National Aeronautics and Space Administration (NASA). The purpose of this initiative is to develop a future design environment for engineering and science mission synthesis for use by NASA scientists and engineers. This new initiative is called the Intelligent Synthesis Environment (ISE). The paper describes the mission of NASA, future aerospace system characteristics, the current engineering design process, the ISE concept, and concludes with a description of possible ISE applications for the decision of air-breathing propulsion systems.

Malone, J. B.↗
NASA NTRS1994

Robotic Processing Of Rocket-Engine Nozzles

Automated manufacturing cell containing computer-controlled robotic processing system developed to implement some important related steps in fabrication of rocket-engine nozzles. Performs several tedious and repetitive fabrication, measurement, adjustment, and inspection processes and subprocesses now performed manually. Offers advantages of reduced processing time, greater consistency, excellent collection of data, objective inspections, greater productivity, and simplified fixturing. Also affords flexibility: by making suitable changes in hardware and software, possible to modify process and subprocesses. Flexibility makes work cell adaptable to fabrication of heat exchangers and other items structured similarly to rocket nozzles.

Gilbert, Jeffrey L.↗
NASA NTRSDate not supplied

Long Duration Medical System Foundation for Lunar Orbital and Lunar Surface Exploration Missions

For long-duration lunar orbital and lunar surface (LDLOS) exploration missions, the NASA Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a medical system foundation through which clinical considerations may be represented via a systems engineering-based model. Components of the Long Duration Medical System Foundation model include a concept of operations (ConOps), functional decomposition, medical conditions to be addressed, clinical capabilities and resources, technical requirements, and traces of requirements to NASA standards documents and parent-level (Program- and Vehicle habitat system-level) requirements. The Foundation model offers the means to present information in a readily accessible format that is understandable across all clinical, engineering, scientific, and managerial disciplines. Collectively, these components constitute a foundation that serves future programs with similar long duration mission profiles as a starting point for medical system design. The Foundation was developed by a multidisciplinary team of systems engineers, scientists, and clinicians across NASA. The process started with ConOps development, subsequently decomposed into the functionalities needed to diagnose, treat, and prevent medical conditions. The clinical team identified medical conditions most likely needed to be diagnosed and treated during a long-duration lunar exploration mission. Through these approaches, requirements were codified for the LDLOS medical system. These requirements were then traced to NASA standards, medical conditions, medical capabilities, and medical resources, facilitating stakeholders’ use of the Foundation model to analyze traces and to identify medical system interfaces with other vehicle systems or subsystems. In addition, the Foundation may be used as a basis for performing risk trades on medical system mass and volume allocation. This discussion will focus on the processes through which the LDLOS Medical System Foundation was developed, how the Foundation builds a bridge between the medical and engineering domains, and how these processes may be applied more broadly to a crew health and performance system and other system domains.

Jay Lemery↗