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Results for “reliability study”

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 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS1978

Analysis and design of the Multimission Modular Spacecraft hydrazine propulsion module

The translational velocity increment, stabilization and control requirements, vehicle weight, and geometric considerations of the Multimission Modular Spacecraft (MMS) provided the basic data on which to initiate the analysis and design of the hydrazine propulsion modules. The Landsat D was used as the mission model. Tradeoff studies were conducted on thrust level, thruster location, and clustering arrangement together with tankage volume and location. The impact of the use of single and dual seat thruster valves on plumbing configuration, reliability, and overall system cost was studied in detail. Conceptual designs of a recommended propulsion module configuration for both the Delta 3910 and Shuttle were prepared.

Etheridge, F. G.↗

DOE OSTI2025

Assessing Dynamic Behaviors in Converter- Dominated Power Systems via RMS and EMT Simulations: A Study of Hawaii’s NELHA Microgrid

The transition from conventional power systems to converter-based microgrids has significantly advanced sustainability, clean energy integration, and operational reliability. However, this paradigm shift introduces operational challenges due to the intermittent nature of renewable energy sources and the non-linear characteristics of power electronic loads, inducing voltage fluctuations and harmonic distortions that complicate voltage and frequency regulation. Accurate dynamic modeling is hypothesized to be critical for capturing such effects, enabling reliable simulation and control strategy development. This study introduces an innovative dynamic modeling framework for a real-world converter-based microgrid, utilizing both root mean square (RMS) and electromagnetic transient (EMT) simulation methods. The microgrid was modeled in DIgSILENT PowerFactory, with simulations calibrated against high-resolution field measurements from SEL-735 power quality meters. Results show that RMS simulations effectively characterize steady-state dynamics, while EMT simulations are essential for capturing high-frequency transients and non-linear effects from photovoltaic inverters and variable frequency drives (VFDs). This complementary approach provides a comprehensive understanding of microgrid behavior, providing critical insights for improving simulation accuracy, advancing protection schemes, and improving resilience in future low-inertia power networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Test–retest reliability for a social discounting of personal information task

Increasing cybercrime rates means identifying potential victims is critically important. Social discounting tasks show that individuals share less personally identifying information as social distance increases. However, the test–retest reliability and uniqueness of this measure is unclear. The current study assessed social discounting for personally identifying information (SDPII), delay discounting, risk taking, and personality at two measurement waves 30 days apart for 64 undergraduate students. Test–retest reliability was statistically significant for the SDPII and all other measures, replicating previous studies. SDPII rates were not significantly correlated with other measures during both measurement waves, showing discriminant validity. SDPII rates were lower than those reported in a previous study but were still well described by a hyperbolic discounting function, suggesting replicability across studies. Furthermore, the high test–retest reliability, uniqueness, and replicability of the SDPII suggests that it may quantitatively identify cybercrime victimization. Future research should test which measure or combination of measures can accurately predict scam and cybercrime victimization to inform data-based interventions.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Atomically Precise Graphene Nanoribbon Transistors with Long-Term Stability and Reliability

Atomically precise graphene nanoribbons (GNRs) synthesized from the bottom-up exhibit promising electronic properties for high-performance field-effect transistors (FETs). The feasibility of fabricating FETs with GNRs (GNRFETs) has been demonstrated, with ongoing efforts aimed at further improving their performance. However, their long-term stability and reliability remain unexplored, which is as important as their performance for practical applications. In this work, we fabricated short-channel FETs with nine-atom-wide armchair GNRs (9-AGNRFETs). We revealed that the on-state (/ ON ) current performance of the 9-AGNRFETs deteriorates significantly over consecutive full transistor on and off logic cycles, which has neither been demonstrated nor previously considered. To address this issue, we deposited a thin ~10 nm thick atomic layer deposition (ALD) layer of aluminum oxide (Al 2 O 3 ) directly on these devices. The integrity, compatibility, electrical performance, stability, and reliability, of the GNRFETs before and/or after Al 2 O 3 deposition were comprehensively studied. The results indicate that the observed decline in electrical device performance is most likely due to the degradation of contact resistance over multiple measurement cycles. We successfully demonstrated that the devices with the Al 2 O 3 layer operate well up to several thousand continuous full cycles without any degradation. Our study offers valuable insights into the stability and reliability of GNR transistors, which could facilitate their large-scale integration into practical applications.

36 MATERIALS SCIENCE↗

NASA NTRS1997

The Interplay of Surface Mount Solder Joint Quality and Reliability of Low Volume SMAs

Spacecraft electronics including those used at the Jet Propulsion Laboratory (JPL), demand production of highly reliable assemblies. JPL has recently completed an extensive study, funded by NASA's code Q, of the interplay between manufacturing defects and reliability of ball grid array (BGA) and surface mount electronic components.

Spacecraft electronics electronic assemblies J-lea↗

NASA NTRS1982

Ion thruster charge-exchange plasma flow

The electron bombardment ion thruster has been under development for a number of years and during this time, studies of the plasmas produced by the thrusters and their interactions with spacecraft have been evaluated, based on available data. Due to diagnostic techniques used and facility effects, there is uncertainty as to the reliability of data from these early studies. This paper presents data on the flow of the charge-exchange plasma produced just downstream of the thruster's ion optics. The 'end-effect' of a cylindrical Langmuir probe is used to determine ion density and directed ion velocity. Results are compared with data obtained from a retarding potential analyzer-Faraday cup.

Carruth, M. R., Jr.↗

DOE OSTI2024

Advancing Molecular Weight Determination of Lignin by Multi-Angle Light Scattering

Due to the complexity and recalcitrance of lignin, its chemical characterization is a key factor preventing the valorization of this abundant material. Multi-angle light scattering (MALS) is becoming a sought-after technique for absolute molecular weight (MW) determination of polymers and proteins. Lignin is a suitable candidate for MW determination via MALS, yet further investigation is required to confirm its absolute MW values and molecular size. Studies aiming to break down lignin into a variety of renewable products will benefit greatly from a simple and reliable determination method like MALS. Recent pioneering studies, discussed in this review, addressed several key challenges in lignin’s MW characterization. Nevertheless, some lignin-specific issues still need to be considered for in-depth characterization. This study explores how MALS instrumentation manages the complexities of determining lignin’s MW, e.g., with simultaneous fractionation and fluorescence interference mitigation. Additionally, we rationalize the importance of a more detailed light scattering analysis for lignin characterization, including aspects like the second virial coefficient and radius of gyration.

differential refractive index increment↗

NASA NTRS2007

Nuclear Thermal Propulsion Mars Mission Systems Analysis and Requirements Definition

This paper describes the Mars transportation vehicle design concepts developed by the Marshall Space Flight Center (MSFC) Advanced Concepts Office. These vehicle design concepts provide an indication of the most demanding and least demanding potential requirements for nuclear thermal propulsion systems for human Mars exploration missions from years 2025 to 2035. Vehicle concept options vary from large "all-up" vehicle configurations that would transport all of the elements for a Mars mission on one vehicle. to "split" mission vehicle configurations that would consist of separate smaller vehicles that would transport cargo elements and human crew elements to Mars separately. Parametric trades and sensitivity studies show NTP stage and engine design options that provide the best balanced set of metrics based on safety, reliability, performance, cost and mission objectives. Trade studies include the sensitivity of vehicle performance to nuclear engine characteristics such as thrust, specific impulse and nuclear reactor type. Tbe associated system requirements are aligned with the NASA Exploration Systems Mission Directorate (ESMD) Reference Mars mission as described in the Explorations Systems Architecture Study (ESAS) report. The focused trade studies include a detailed analysis of nuclear engine radiation shield requirements for human missions and analysis of nuclear thermal engine design options for the ESAS reference mission.

Mulqueen, Jack↗

DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2015

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

simulation↗

DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Connected Thermostat Alternatives for Room Air Conditioners and Minisplit Heat Pumps

The availability of smart, connected thermostats has improved climate control, energy efficiency, and grid demand-response programs for central HVAC systems. However, a significant gap exists in addressing integrated control systems for point-source heating and cooling systems such as window air-conditioners (window ACs) and mini-split heat pumps (MSHPs). This report examines the emerging market of third-party connected thermostats tailored for these systems, focusing on their effectiveness, reliability, and potential barriers to adoption.This study evaluates several commercially available products designed for room ACs and MSHPs through a series of laboratory tests. While these infrared-based (IR-based) thermostats offer remote temperature control and scheduling via mobile apps, our findings reveal that none are seamless, with reliability of basic functions being a critical factor. Promising features include integration of indoor air quality metrics and time-of-use pricing, but the latter are not yet available in the U.S. Barriers to broad user acceptance include non-seamless setup processes, challenges in thermostat placement, and unclear product differentiation. There is a pressing need for research and development in enabling MSHPs and central thermostats to coordinate, enhancing energy savings and comfort in retrofit applications. This study underscores the importance of further innovation in connected thermostat technology to address the diverse needs of single-zone HVAC systems and promote efficient energy management in households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2017

EVA Human Health and Performance Benchmarking Study Overview and Development of a Microgravity Protocol

The primary objective of this study is to develop a protocol to reliably characterize human health and performance metrics for individuals working inside various EVA suits under realistic spaceflight conditions. Expected results and methodologies developed during this study will provide the baseline benchmarking data and protocols with which future EVA suits and suit configurations (e.g., varied pressure, mass, center of gravity [CG]) and different test subject populations (e.g., deconditioned crewmembers) may be reliably assessed and compared. Results may also be used, in conjunction with subsequent testing, to inform fitness-for-duty standards, as well as design requirements and operations concepts for future EVA suits and other exploration systems.

Norcross, Jason↗

DOE OSTI2025

Light-Matter Interaction in Ultrastable Tunneling Nanogaps

Light emission and detection through tunnel junctions have emerged as a promising platform for studying nanoscale light–matter interactions, including electroluminescence and photoassisted transport. However, controlling these interactions in the tunneling regime has been challenging due to complex underlying mechanisms that remain poorly understood. A major obstacle is the difficulty in forming stable junctions that can function reliably over extended periods. In this study, we fabricate ultrastable tunneling junctions consisting of epitaxial indium–tin-oxide, epitaxial lutetium oxide, and gold. With their stable and consistent tunneling currents, we investigate photon-assisted transport phenomena using simple direct-current detection. Our results demonstrate that optical rectification is the primary contributor to the laser-induced current, alongside thermal effects and hot-electron currents. Furthermore, owing to their epitaxial nature and high breakdown threshold, this ultrastable platform holds promise for future real-world applications, including nanoscale light sources and multifunctional photodetectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Sensory integration for neuroprostheses: from functional benefits to neural correlates

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Here, resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Testing the reliability of interpretable neural networks in geoscience using the Madden–Julian oscillation

Abstract. We test the reliability of two neural network interpretation techniques, backward optimization and layerwise relevance propagation, within geoscientific applications by applying them to a commonly studied geophysical phenomenon, the Madden–Julian oscillation. The Madden–Julian oscillation is a multi-scale pattern within the tropical atmosphere that has been extensively studied over the past decades, which makes it an ideal test case to ensure the interpretability methods can recover the current state of knowledge regarding its spatial structure. The neural networks can, indeed, reproduce the current state of knowledge and can also provide new insights into the seasonality of the Madden–Julian oscillation and its relationships with atmospheric state variables. The neural network identifies the phase of the Madden–Julian oscillation twice as accurately as a linear regression approach, which means that nonlinearities used by the neural network are important to the structure of the Madden–Julian oscillation. Interpretations of the neural network show that it accurately captures the spatial structures of the Madden–Julian oscillation, suggest that the nonlinearities of the Madden–Julian oscillation are manifested through the uniqueness of each event, and offer physically meaningful insights into its relationship with atmospheric state variables. We also use the interpretations to identify the seasonality of the Madden–Julian oscillation and find that the conventionally defined extended seasons should be shifted later by 1 month. More generally, this study suggests that neural networks can be reliably interpreted for geoscientific applications and may thereby serve as a dependable method for testing geoscientific hypotheses.

58 GEOSCIENCES↗

NASA NTRS1984

High performance fibers for structurally reliable metal and ceramic composites

Very few of the commercially available high performance fibers with low densities, high Young's moduli, and high tensile strengths possess all the necessary property requirements for providing either metal matrix composites (MMC) or ceramic matrix composites (CMC) with high structural reliability. These requirements are discussed in general and examples are presented of how these property guidelines are influencing fiber evaluation and improvement studies at NASA aimed at developing structurally reliable MMC and CMC for advanced gas turbine engines.

Dicarlo, J. A.↗

DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗