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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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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Small angle scattering of diblock copolymers profiled by machine learning

We outline a machine learning strategy for quantitively determining the conformation of AB-type diblock copolymers with excluded volume effects using small angle scattering. Complemented by computer simulations, a correlation matrix connecting conformations of different copolymers according to their scattering features is established on the mathematical framework of a Gaussian process, a multivariate extension of the familiar univariate Gaussian distribution. We show that the relevant conformational characteristics of copolymers can be probabilistically inferred from their coherent scattering cross sections without any restriction imposed by model assumptions. This work not only facilitates the quantitative structural analysis of copolymer solutions but also provides the reliable benchmarking for the related theoretical development of scattering functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2011

Multidisciplinary Modeling Software for Analysis, Design, and Optimization of HRRLS Vehicles

The concept for Highly Reliable Reusable Launch Systems (HRRLS) under the NASA Hypersonics project is a two-stage-to-orbit, horizontal-take-off / horizontal-landing, (HTHL) architecture with an air-breathing first stage. The first stage vehicle is a slender body with an air-breathing propulsion system that is highly integrated with the airframe. The light weight slender body will deflect significantly during flight. This global deflection affects the flow over the vehicle and into the engine and thus the loads and moments on the vehicle. High-fidelity multi-disciplinary analyses that accounts for these fluid-structures-thermal interactions are required to accurately predict the vehicle loads and resultant response. These predictions of vehicle response to multi physics loads, calculated with fluid-structural-thermal interaction, are required in order to optimize the vehicle design over its full operating range. This contract with ResearchSouth addresses one of the primary objectives of the Vehicle Technology Integration (VTI) discipline: the development of high-fidelity multi-disciplinary analysis and optimization methods and tools for HRRLS vehicles. The primary goal of this effort is the development of an integrated software system that can be used for full-vehicle optimization. This goal was accomplished by: 1) integrating the master code, FEMAP, into the multidiscipline software network to direct the coupling to assure accurate fluid-structure-thermal interaction solutions; 2) loosely-coupling the Euler flow solver FEFLO to the available and proven aeroelasticity and large deformation (FEAP) code; 3) providing a coupled Euler-boundary layer capability for rapid viscous flow simulation; 4) developing and implementing improved Euler/RANS algorithms into the FEFLO CFD code to provide accurate shock capturing, skin friction, and heat-transfer predictions for HRRLS vehicles in hypersonic flow, 5) performing a Reynolds-averaged Navier-Stokes computation on an HRRLS configuration; 6) integrating the RANS solver with the FEAP code for coupled fluid-structure-thermal capability; and 7) integrating the existing NASA SRGULL propulsion flow path prediction software with the FEFLO software for quasi-3D propulsion flow path predictions, 8) improving and integrating into the network, an existing adjoint-based design optimization code.

Spradley, Lawrence W.↗

DOE OSTI2026

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗

DOE OSTI2022

Analysis Program 2021 Annual Progress Report

During fiscal year 2021 (FY 2021), the U.S. Department of Energy Vehicle Technologies Office (VTO) funded analysis projects supportive of VTO’s goals to pursue early-stage research in vehicle and mobility system technologies to reduce petroleum dependence, increase energy reliability and security, improve transportation affordability, and promote economic growth. VTO analysis projects result in a foundation of data, analytical models, and applied analyses that provide insights into critical transportation energy problems and assist in research investment prioritization and portfolio planning. This document presents a brief overview of VTO analysis efforts and progress for projects funded in FY 2021. Each of the progress reports includes project objectives, approach, and highlights of the technical results that were accomplished during the fiscal year (FY).

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

availability↗

DOE OSTI2020

Approximation Framework of Embodied Energy of Safety: Insights and Analysis

Transportation safety, as a critical component of an efficient and reliable transportation system, has been extensively studied with respect to societal economic impacts by transportation agencies and policy officials. However, the embodied energy impact of safety, other than induced congestion, is lacking in studies. This research proposes an energy equivalence of safety (EES) framework to provide a holistic view of the long-term energy and fuel consequences of motor vehicle crashes, incorporating both induced congestion and impacts from lost human productivity resulting from injury and fatal accidents and the energy content resulting from all consequences and activities from a crash. The method utilizes a ratio of gross domestic product (GDP) to national energy consumed in a framework that bridges the gap between safety and energy, leveraging extensive studies of the economic impact of motor vehicle crashes. The energy costs per fatal, injury, and property-damage-only (PDO) crashes in gasoline gallon equivalent (GGE) in 2017 were found to be 200,259, 4442, and 439, respectively, which are significantly greater than impacts from induced congestion alone. The results from the motor vehicle crash data show a decreasing trend of EES per crash type from 2010 and 2017, due primarily in part to a decreasing ratio of total energy consumed to GDP over those years. In addition to the temporal analysis, we conducted a spatial analysis addressing national-, state-, and local-level EES comparisons by using the proposed framework, illustrating its applicability.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Data Mining and Machine Learning for Power System Monitoring, Understanding, and Impact Evaluation

This chapter presents results from the Big Data analysis framework to improve power system situational awareness and system reliability. For this purpose, a dataset with real-world phasor measurement unit data and historical transmission system outage data has been created and used to carry out the analysis. Several statistical analysis and machine learning methods have been developed and implemented for event and anomaly detection and modeling. Detection and analysis results for actual examples of power system events are presented. Finally, data-driven characterization and risk assessment methods for weather-related extremes in power systems are developed and demonstrated on the Bonneville Power Administration system. These applications demonstrate the capability of Machine Learning (ML) methods to monitor system abnormalities, to predict system events, and to characterize the impact of extreme events on power grid

data mining, power grid, machine learning, anomaly↗

DOE OSTI2024

Summary of Alloy 617 and Alloy 709 Elevated Temperature Crack Growth Test Results from the Planned FY24 Crack Growth Test Activities

This report covers the results from crack growth rate testing performed at Idaho National Laboratory in the fiscal year 2024. It includes two creep crack growth rate tests and two creep-fatigue crack growth rate tests. Results are shown for each of these tests, included crack growth measured during the test using direct current potential drop, and measurements based off of the fracture surface. Load line displacement, as well as load, were also collected during the tests. Detailed analysis of the results will continue into the next fiscal year, however, a number of potential improvements to the equipment and testing procedures were identified that will increase testing reliability and throughput, as well as decrease complications with the analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2008

A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

Human space exploration is by its very nature an uncertain endeavor. Vehicle reliability, technology development risk, budgetary uncertainty, and launch uncertainty all contribute to stochasticity in an exploration scenario. However, traditional strategic analysis has been done in a deterministic manner, analyzing and optimizing the performance of a series of planned missions. History has shown that exploration scenarios rarely follow such a planned schedule. This paper describes a methodology to integrate deterministic and probabilistic analysis of scenarios in support of human space exploration. Probabilistic strategic analysis is used to simulate "possible" scenario outcomes, based upon the likelihood of occurrence of certain events and a set of pre-determined contingency rules. The results of the probabilistic analysis are compared to the nominal results from the deterministic analysis to evaluate the robustness of the scenario to adverse events and to test and optimize contingency planning.

Merrill, R. Gabe↗

NASA NTRS1995

Neurofilament protein defines regional patterns of cortical organization in the macaque monkey visual system: a quantitative immunohistochemical analysis

Visual function in monkeys is subserved at the cortical level by a large number of areas defined by their specific physiological properties and connectivity patterns. For most of these cortical fields, a precise index of their degree of anatomical specialization has not yet been defined, although many regional patterns have been described using Nissl or myelin stains. In the present study, an attempt has been made to elucidate the regional characteristics, and to varying degrees boundaries, of several visual cortical areas in the macaque monkey using an antibody to neurofilament protein (SMI32). This antibody labels a subset of pyramidal neurons with highly specific regional and laminar distribution patterns in the cerebral cortex. Based on the staining patterns and regional quantitative analysis, as many as 28 cortical fields were reliably identified. Each field had a homogeneous distribution of labeled neurons, except area V1, where increases in layer IVB cell and in Meynert cell counts paralleled the increase in the degree of eccentricity in the visual field representation. Within the occipitotemporal pathway, areas V3 and V4 and fields in the inferior temporal cortex were characterized by a distinct population of neurofilament-rich neurons in layers II-IIIa, whereas areas located in the parietal cortex and part of the occipitoparietal pathway had a consistent population of large labeled neurons in layer Va. The mediotemporal areas MT and MST displayed a distinct population of densely labeled neurons in layer VI. Quantitative analysis of the laminar distribution of the labeled neurons demonstrated that the visual cortical areas could be grouped in four hierarchical levels based on the ratio of neuron counts between infragranular and supragranular layers, with the first (areas V1, V2, V3, and V3A) and third (temporal and parietal regions) levels characterized by low ratios and the second (areas MT, MST, and V4) and fourth (frontal regions) levels characterized by high to very high ratios. Such density trends may correspond to differential representation of corticocortically (and corticosubcortically) projecting neurons at several functional steps in the integration of the visual stimuli. In this context, it is possible that neurofilament protein is crucial for the unique capacity of certain subsets of neurons to perform the highly precise mapping functions of the monkey visual system.

Non-NASA Center↗

NASA NTRS1991

A simulation model for risk assessment of turbine wheels

A simulation model has been successfully developed to evaluate the risk of the Space Shuttle auxiliary power unit (APU) turbine wheels for a specific inspection policy. Besides being an effective tool for risk/reliability evaluation, the simulation model also allows the analyst to study the trade-offs between wheel reliability, wheel life, inspection interval, and rejection crack size. For example, in the APU application, sensitivity analysis results showed that the wheel life limit has the least effect on wheel reliability when compared to the effect of the inspection interval and the rejection crack size. In summary, the simulation model developed represents a flexible tool to predict turbine wheel reliability and study the risk under different inspection policies.

Safie, Fayssal M.↗

NASA NTRSDate not supplied

Video Analysis for Surveillance of Spacecraft Parachute Systems

The Commercial Crew Program (CCP) has established a surveillance methodology to ensure the reliability of spacecraft parachute systems. The implemented methodology relies on an interconnected framework consisting of imagery analysis, hardware inspections, and vehicle data analysis. Imagery analysis serves as a foundation for these core activities which provide a robust approach to the surveillance of spacecraft parachute systems. As the surveillance framework has been developed, the role of imagery has become more prominent, and therefore imagery requirements have changed. To complete photogrammetric analysis, careful consideration must be made to the role of imagery, required data, imagery requirements, the analysis process, and mission planning. The role of imagery will drive the required data, which will in turn drive imagery requirements. Imagery requirements are likely to drive mission planning through consideration to camera selection and placement. If onboard imagery is required, the camera and data system must be implemented prior to launch. If external imagery is required, the photography package must be implemented such that it can be positioned for a return and free of potential debris fields. For these reasons, an integrated approach must be used to build an imagery package around the required analysis with careful coordination with mission planners.

parachutes↗

NASA NTRSDate not supplied

Video Analysis for Surveillance of Spacecraft Parachute Systems

parachutes↗

DOE OSTI2026

Design and Analysis of a 25 MWe Supercritical CO2 Turbo Machine

This paper presents the design and analysis of a turbo machine operating with supercritical carbon dioxide (sCO2) in a 25 MWe Recompression Brayton Cycle (RCBC). The work was performed under US Department of Energy (DoE) program DE-EE-0010318. The design process involves the aerodynamic design of the compressor and turbine, including the initial layout of flowpaths and stage configurations to achieve high efficiency and performance. Additionally, a comprehensive rotodynamic analysis is performed to ensure the stability and reliability of the system. Conceptual designs for a high-speed motor and synchronous generator that match turbomachinery requirements are also developed from first principles.

42 ENGINEERING↗

NASA NTRS1997

A mathematical model of diurnal variations in human plasma melatonin levels

Studies in animals and humans suggest that the diurnal pattern in plasma melatonin levels is due to the hormone's rates of synthesis, circulatory infusion and clearance, circadian control of synthesis onset and offset, environmental lighting conditions, and error in the melatonin immunoassay. A two-dimensional linear differential equation model of the hormone is formulated and is used to analyze plasma melatonin levels in 18 normal healthy male subjects during a constant routine. Recently developed Bayesian statistical procedures are used to incorporate correctly the magnitude of the immunoassay error into the analysis. The estimated parameters [median (range)] were clearance half-life of 23.67 (14.79-59.93) min, synthesis onset time of 2206 (1940-0029), synthesis offset time of 0621 (0246-0817), and maximum N-acetyltransferase activity of 7.17(2.34-17.93) pmol x l(-1) x min(-1). All were in good agreement with values from previous reports. The difference between synthesis offset time and the phase of the core temperature minimum was 1 h 15 min (-4 h 38 min-2 h 43 min). The correlation between synthesis onset and the dim light melatonin onset was 0.93. Our model provides a more physiologically plausible estimate of the melatonin synthesis onset time than that given by the dim light melatonin onset and the first reliable means of estimating the phase of synthesis offset. Our analysis shows that the circadian and pharmacokinetics parameters of melatonin can be reliably estimated from a single model.

NASA Discipline Number 70-10↗

NASA NTRS2014

Conceptual Launch Vehicle and Spacecraft Design for Risk Assessment

One of the most challenging aspects of developing human space launch and exploration systems is minimizing and mitigating the many potential risk factors to ensure the safest possible design while also meeting the required cost, weight, and performance criteria. In order to accomplish this, effective risk analyses and trade studies are needed to identify key risk drivers, dependencies, and sensitivities as the design evolves. The Engineering Risk Assessment (ERA) team at NASA Ames Research Center (ARC) develops advanced risk analysis approaches, models, and tools to provide such meaningful risk and reliability data throughout vehicle development. The goal of the project presented in this memorandum is to design a generic launch 7 vehicle and spacecraft architecture that can be used to develop and demonstrate these new risk analysis techniques without relying on other proprietary or sensitive vehicle designs. To accomplish this, initial spacecraft and launch vehicle (LV) designs were established using historical sizing relationships for a mission delivering four crewmembers and equipment to the International Space Station (ISS). Mass-estimating relationships (MERs) were used to size the crew capsule and launch vehicle, and a combination of optimization techniques and iterative design processes were employed to determine a possible two-stage-to-orbit (TSTO) launch trajectory into a 350-kilometer orbit. Primary subsystems were also designed for the crewed capsule architecture, based on a 24-hour on-orbit mission with a 7-day contingency. Safety analysis was also performed to identify major risks to crew survivability and assess the system's overall reliability. These procedures and analyses validate that the architecture's basic design and performance are reasonable to be used for risk trade studies. While the vehicle designs presented are not intended to represent a viable architecture, they will provide a valuable initial platform for developing and demonstrating innovative risk assessment capabilities.

Launch Vehicle↗

DOE OSTI2023

Data Privacy for the Grid: Toward a Data Privacy Standard for Inverter-Based and Distributed Energy Resources

The traditional approach to planning the distribution grid has focused on reliability in the context of gradual and reasonably predictable load growth. Forecasts of load growth, combined with asset management practices, were used by system planners to identify upgrades to the system to maintain or improve reliability. The decisions, typically based within load flow analysis tools, included considerations about contingency scenarios and corporate forecasts (i.e., top-down predictions at a summary level of what would happen in a particular area that could impact load growth and behavior). As a result, today, this traditional approach no longer fits all purposes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2018

Thermal Modeling of an Advanced Geared Turbofan for Distributed Engine Control Application

Reliability and life-expectancy of gas turbine engine components is very much correlated to the temperature environment in which they operate. This is no different for control system components, especially those with electronic parts. In recent years, the concept of Distributed Engine Control (DEC) has emerged to address the limitations of the current centralized control implementation. This new approach involves relocating control system components from a relatively benign environment to the harsher thermal environment of the engine casing and its surrounding structures and cavities. In this paper, an approach to modeling the gas turbine thermal environment is described. The modeling approach is applied to a 3rd generation geared turbofan design with a focus on the engine locations where control instrumentation and actuation could be installed. The analysis was conducted with an eye toward component reliability and service life as it relates to the thermal environment. The results were found to be reasonable. Furthermore, the model is shown to execute in real-time within a multi-model simulation environment that demonstrates the capability to interact with hardware to drive test equipment.

Kratz, Jonathan↗