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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 91 records · Page 5

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗

Designing the Design Process for Early Problem Discovery for a Complex Aeronautics Systems Challenge

The earliest stage in the innovation lifecycle, problem formulation, is crucial for setting direction in an innovation effort. When faced with an interesting problem, engineers commonly assume the approximate solution area and focus on ideating innovative solutions. However, in this project, NASA and their contracted partner, Accenture, collaboratively conducted problem discovery to ensure that solutioning efforts were focused on the right problems, for the right users, and addressing the most critical needs—in this case, exploring weather tolerant operations (WTO) to further urban air mobility (UAM) – known as UAM WTO. The project team leveraged generative, qualitative methods to understand the ecosystem, players, and where challenges in the industry are inhibiting development. The complexity of the problem area required that the team constantly observe and iterate on problem discovery, effectively “designing the design process.” This report discusses the approach, methodologies, and selected results, including insights on the application of early-stage design methodologies to a complex, system-level problem.

Problem formulation↗

A study of the selection of microcomputer architectures to automate planetary spacecraft power systems

Performance and reliability models of alternate microcomputer architectures as a methodology for optimizing system design were examined. A methodology for selecting an optimum microcomputer architecture for autonomous operation of planetary spacecraft power systems was developed. Various microcomputer system architectures are analyzed to determine their application to spacecraft power systems. It is suggested that no standardization formula or common set of guidelines exists which provides an optimum configuration for a given set of specifications.

Nauda, A.↗

Theoretical investigation of the force and dynamically coupled torsional-axial-lateral dynamic response of eared rotors

Difficulties in solution methodology to be used to deal with the potentially higher nonlinear rotor equations when dynamic coupling is included. A solution methodology is selected to solve the nonlinear differential equations. The selected method was verified to give good results even at large nonlinearity levels. The transfer matrix methodology is extended to the solution of nonlinear problems.

David, J. W.↗

Protocol for maximizing energy savings and indoor environmental quality improvements when retrofitting apartments

The current focus on building energy retrofit provides an opportunity to simultaneously improve indoor environmental quality (IEQ). Toward this end, we developed a protocol for selecting packages of retrofits that both save energy and improve IEQ in apartments. The protocol specifies the methodology for selecting retrofits from a candidate list while addressing expected energy savings, IEQ impacts, and costs in an integrated manner. Interviews, inspections and measurements are specified to collect the needed input information. The protocol was applied to 17 apartments in three buildings in two different climates within California. Diagnostic measurements and surveys conducted before and after retrofit implementation indicate enhanced apartment performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Protocol for Maximizing Energy Savings and Indoor Environmental Quality Improvements when Retrofiting Apartments

The current focus on building energy retrofit provides an opportunity to simultaneously improve indoor environmental quality (IEQ). Toward this end, we developed a protocol for selecting packages of retrofits that both save energy and improve IEQ in apartments. The protocol specifies the methodology for selecting retrofits from a candidate list while addressing expected energy savings, IEQ impacts, and costs in an integrated manner. Interviews, inspections and measurements are specified to collect the needed input information. The protocol was applied to 17 apartments in three buildings in two different climates within California. Diagnostic measurements and surveys conducted before and after retrofit implementation indicate enhanced apartment performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Adsorptive behavior of poly (vinylidene fluoride) membranes for the recovery of lignin-derived hydrophobic deep eutectic solvents

Abstract Recently, membrane technology has gained significant traction as an energy-efficient alternative to traditional thermal processes for solvent recovery. Deep eutectic solvents (DESs) have emerged as sustainable alternatives to conventional organic solvents, yet a systematic methodology for selecting compatible membrane materials for their recovery remains underdeveloped. This study established a predictive framework for membrane material selection in hydrophobic DES applications using Hansen Solubility Parameters (HSP) with inverted criteria targeting materials with relative energy difference (RED) values greater than 1.0. Flat sheet membranes were fabricated via the non-solvent induced phase separation (NIPS) technique. Four NIPS fabricated polymer membranes were evaluated: polysulfone, cellulose acetate, polyvinylidene fluoride (PVDF) fabricated with polyethylene glycol (PEG) as a pore-forming agent, and polybenzimidazole (PBI). The HSP approach successfully predicted membrane-solvent compatibility, with polysulfone (RED = 0.6) and cellulose acetate (RED = 0.9) dissolving completely within 24 h, while PVDF (RED = 1.9) and PBI (RED = 1.1) maintained structural integrity throughout a 7-day exposure period. Furthermore, PVDF demonstrated superior performance with minimal weight gain (3.0%), hydrophobic surface characteristics (122° water contact angle), and enhanced mechanical properties following DES exposure. Comprehensive chemical and morphological characterization confirmed PVDF’s chemical stability and revealed a surface-selective interaction mechanism involving simultaneous PEG (pore-forming agent) extraction and DES component adsorption. Adsorption kinetics followed pseudo-first-order behavior with reversible characteristics, best described by the Temkin isotherm model (R² = 0.9987). PVDF membranes-maintained separation functionality with average lignin rejection (75.2 ± 7.69%) and demonstrated filtration permeability of 2.0 ± 0.34 LMH/bar. This methodology provides a rational approach for membrane selection in emerging solvent systems, contributing to the advancement of sustainable separation technologies for DES-based biomass processing applications.

Science & Technology - Other Topics↗

Energy Saving Opportunity from Advanced LED Lighting Research

Pacific Northwest National Laboratory (PNNL) was asked by the U.S. Department of Energy (DOE) to estimate the energy saving opportunity made possible by certain lighting research planned by PNNL. This report describes the results of that effort. To complete this work, PNNL selected a methodology created for and used in the electric utility industry, called Non-Energy Benefits methodology, and a lighting market model created for DOE to estimate future energy savings potential from solid-state lighting. The study found that select planned PNNL lighting research could lead to annual energy savings of 10% of total lighting energy savings in the year 2035, or in absolute terms, 334 tBtu. Energy savings in earlier years are smaller, primarily due to the early years of low market uptake of the new technologies expected from PNNL lighting research. In 2030, annual energy savings are projected to be 4.5%, or 165 tBtu.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal Stop Word Selection for Text Mining in Critical Infrastructure Domain

Eliminating all stop words from the feature space is a standard practice of preprocessing in text mining, regardless of the domain which it is applied to. However, this may result in loss of important information, which adversely affects the accuracy of the text mining algorithm. Therefore, this paper proposes a novel methodology for selecting the optimal set of domain specific stop words for improved text mining accuracy. First, the presented methodology retains all the stop words in the text preprocessing phase. Then, an evolutionary technique is used to extract the optimal set of stop words that result in the best classification accuracy. The presented methodology was implemented on a corpus of open source news articles related to critical infrastructure hazards. The first step of mining geo-dependencies among critical infrastructures from text is text classification. In order to achieve this, article content was classified into two classes: 1) text content with geo-location information, and 2) text content without geo-location information. Classification accuracy presented methodology was compared to accuracies of four other test cases. Experimental results with 10-fold cross validation showed that the presented method yielded an increase of 1.76% or higher in True Positive (TP) rate and a 2.27% or higher increase in the True Negative (TN) rate compared to the other techniques.

97 MATHEMATICS AND COMPUTING↗

Inspecta Annual Technical Report

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

42 ENGINEERING↗

Prevention of Overcurrent and Admissible Voltage Limit Violation in Electrical Network Nodes

In a centralized emergency control system (CECS) with a third-generation algorithm, emergency control actions (CA) are selected under conditions of preventing disruption of dynamic stability, providing the required margin of stability in post-emergency condition, as well as preventing overcurrent and restricting voltage in network nodes to admissible limits. A methodology for selecting CAs for these last two conditions is described.

42 ENGINEERING↗

Evaluation of printability methodologies and feasibility to down select LBPF steel and other materials for nuclear applications

In this work, new research is underway to produce alloys beyond well-known alloys with modified compositions that are better suited to be produced with additive manufacturing. These alloys can only possess improved radiation tolerance but also improved high temperature strength, creep resistance while also using elements that reduce the amount of activation after irradiation. This work package supports the vision and goals of the Advanced Materials and Manufacturing Technology (AMMT) program relevant to accelerate the development and deployment of advanced manufacturing processes. This work focuses on evaluating the methodology for designing alloys best suited for AM processes based on “printability”, literature research to evaluate and down select steel alloy systems. In this work, microstructural characterization and testing activities have been performed on certain steel alloys to support the efforts from collaborating laboratories during the evaluation and printing of the test articles. The final recommendation will be performed by all four participating laboratories.

316L↗

A risk index for multicriterial selection of a logging system with low environmental impact

Setting up the working stages in forest operations is conditioned by environmental protection and forest health requirements. This paper exposes a method for improving the decision-making process by choosing the most environmentally effective logging systems according to terrain configuration and stand characteristics. Such a methodology for selecting machines or logging systems accounting for environment, safety as well as economics, becomes mandatory in the context of sustainable management of forest with multiple functions. Based on analytic hierarchy process analysis the following classification of the environmental performance for four considered alternatives was obtained: skyline system (42.43%), forwarder system (20.22%), skidder system (19.92%) and horse logging system (17.43%). Further, an environmental risk matrix for the most important 28 risk factors specific to any work equipment used in forest operations was produced. In the end, a multicriterial analysis generated a risk index RI ranging between 1.0 and 3.5, which could help choosing the optimal combination of logging system and logging equipment with low environmental impact. In order to demonstrate the usefulness of the proposed approach, a simple application in specific conditions of a harvesting site is presented. - Highlights: • We propose a decision-making algorithm to select eco-friendly logging systems. • Analytic hierarchy process was applied for ranking 4 types of logging systems. • An environmental risk matrix with 28 risk factors in forest operations was made up.

54 ENVIRONMENTAL SCIENCES↗

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗

Rocket Plume Scaling for Orion Wind Tunnel Testing

A wind tunnel test program was undertaken to assess the jet interaction effects caused by the various solid rocket motors used on the Orion Launch Abort Vehicle (LAV). These interactions of the external flowfield and the various rocket plumes can cause localized aerodynamic disturbances yielding significant and highly non-linear control amplifications and attenuations. This paper discusses the scaling methodologies used to model the flight plumes in the wind tunnel using cold air as the simulant gas. Comparisons of predicted flight, predicted wind tunnel, and measured wind tunnel forces-and-moments and plume flowfields are made to assess the effectiveness of the selected scaling methodologies.

Brauckmann, Gregory J.↗

Uncertainty reduction in residual stress measurements by an optimised inverse solution using nonconsecutive polynomials

Many destructive methods for measuring residual stresses such as the slitting method require an inverse analysis to solve the problem. The accuracy of the result as well as an uncertainty component (the model uncertainty) depends on the basis functions used in the inverse solution. The use of a series expansion as the basis functions for the inverse solution was analysed in a previous work for the particular case where functions orders grew consecutively. The present work presents a new estimation of the model uncertainty and a new improved methodology to select the final basis functions for the case where the basis is composed of polynomials. Including nonconsecutive polynomial orders in the basis generates a larger space of possible solutions to be evaluated and allows the possibility to include higher-order polynomials. The paper includes a comparison with two other inverse analyses methodologies applied to synthetically generated data. With the new methodology, the final error is reduced and the uncertainty estimation improved.

36 MATERIALS SCIENCE↗

Probabilistic fracture mechanics and optimum fracture control of the solid rocket motor case of the shuttle

Development of a procedure for the reliability analysis of the solid rocket motor case of the space shuttle is described. The analysis is based on probabilistic fracture mechanics and consideration of a probability distribution for the initial flaw sizes. The reliability analysis can be used to select design variables, such as the thickness of the SRM case, projected design life and proof factor, on the basis of minimum expected cost and specified reliability bounds. Effects of fracture control plans such as the non-destructive inspections and the material erosion between missions can also be considered in the developed methodology for selection of design variables. The reliability-based procedure can be easily modified to consider other similar structures and different fracture control plans.

Hanagud, S.↗