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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 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Cell-level reliability testing procedures for CIGS photovoltaics

The reliability of photovoltaics is commonly studied at the module level. Many reliability problems originate from module attributes, such as metal interconnections to cells, junction boxes. However, significant work in reliability can also be done prior to module design. Testing for reliability earlier in the research cycle increases the probability of avoiding common module reliability problems before cell changes are implemented on a large scale. Cell-level reliability studies can thus lower the rates of module failures in the field and provide confidence to investors that new technologies will perform as advertised. This report summarizes how we investigated three reliability concerns in Cu(In,Ga)Se 2 (CIGS) photovoltaics at the cell level: metastability, shading-induced damage, and potential-induced degradation (PID). We find that examining these concerns required developing robust measurement protocols including the fabrication of novel testing structures. This information will allow readers to incorporate sound metrics for investigating reliability phenomena and aid their studies of cell and module reliability improvements.

14 SOLAR ENERGY↗

DOE OSTI2024

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle↗

DOE OSTI2024

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗

NASA NTRS2016

EVA Health and Human Performance Benchmarking Study

Multiple HRP Risks and Gaps require detailed characterization of human health and performance during exploration extravehicular activity (EVA) tasks; however, a rigorous and comprehensive methodology for characterizing and comparing the health and human performance implications of current and future EVA spacesuit designs does not exist. This study will identify and implement functional tasks and metrics, both objective and subjective, that are relevant to health and human performance, such as metabolic expenditure, suit fit, discomfort, suited postural stability, cognitive performance, and potentially biochemical responses for humans working inside different EVA suits doing functional tasks under the appropriate simulated reduced gravity environments. This study will provide health and human performance benchmark data for humans working in current EVA suits (EMU, Mark III, and Z2) as well as shirtsleeves using a standard set of tasks and metrics with quantified reliability. Results and methodologies developed during this test will provide benchmark data against which future EVA suits, and different suit configurations (eg, varied pressure, mass, CG) may be reliably compared in subsequent tests. Results will also inform fitness for duty standards as well as design requirements and operations concepts for future EVA suits and other exploration systems.

Abercromby, A. F.↗

NASA NTRSDate not supplied

Development and Initial Validation of HFBP-EM Short-Form Surveys

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite includes self-report surveys designed to assess Behavioral Medicine (BMed) and Team risks for future exploration class missions. Survey data was collected during the Human Exploration Research Analog (HERA) Campaign 4 (C4), HERA Campaign 5 (C5), and during SIRIUS19 missions in the Russian Ground Based Experiment Complex, NEK. Crew time in spaceflight analogs and in spaceflight is typically limited. Extensive self-report surveys can be a significant burden to participants and are not operationally acceptable for spaceflight. The purpose of this project was to comprehensively assess the reliability and validity of the standard-length HFBP-EM surveys, identify acceptable short forms to administer during HERA C6, examine initial validation evidence for the proposed short form measures, and identify key measurement gaps in HFBP-EM coverage. In this presentation, we will report reliability and validity metrics of standard form data, describe the proposed new short forms, and present initial psychometric analyses supporting the use of these short forms.

S T Bell↗

NASA NTRSDate not supplied

Oculometric Detection and Characterization of Sub-Clinical Visual/Visuomotor Impairment

It has long been known that qualitative abnormalities in eye movements can be used to diagnose overt brain pathologies (Diefendorf & Dodge, 1908; Fox & Holmes, 1926; Leigh & Zee, 2015). Here, we will examine the use of a set of quantitative measures of the human behavioral response (oculometrics) in a 5-minute radial ocular tracking task (Krukowski & Stone, 2005) with sufficient temporal, spatial, and directional uncertainty to minimize the contribution of a priori prediction or anticipation, and to emphasize the use of a posteriori visual processing of the stimulus trajectory (Liston & Stone, 2014). The derived oculometrics provide a largely independent, reliable set of metrics that are sensitive enough to detect mild sub-clinical impairment across a range of possible neural loci (Stone et al., 2019) with the pattern of impairment across the set providing specificity as to its nature (Tyson et al., 2023). We will review our earlier findings where oculometrics have been used to detect mild impairment due to traumatic brain injury, sleep loss, and low-dose alcohol (Liston et al., 2017; Stone et al., 2019; Tyson et al., 2021). We will also report on a recent clinical study of asymptomatic patients at risk of retinal pathology (Leung et al., 2022) and show that oculometrics can detect and characterize substantive loss of visual function in the absence of clinical indicators of pathology. We conclude that oculometric testing could be used as a routine non-invasive ophthalmological or neurological tool to aid in the early detection and diagnosis of neural injury, toxicity, or disease.

eye movements↗

NASA NTRS2024

Morphometric Characterization of Lunar Landing Sites

As ambitious surface exploration of the Moon commences in the 2020s, it is important to develop reliable and objective metrics for understanding the quality of future landing sites. A key prerequisite for any exploration and utilization of the lunar surface is a safe landing. One of the most important methods to provide understanding of potential metrics for landing site safety in the lunar context is the systematic comparison of candidate and historic landing sites. The goal of this project is to determine the morphometric parameters of the lunar surface at 16 successful lunar landing sites where adequate data exists to execute a quantitative comparison using various parameters. Quantitative analysis of Lunar Reconnaissance Orbiter (LRO) data should inform mission planning activities by providing morphologic metrics for landing sites including slope, Terrain Ruggedness Index (TRI), and rock abundance. These comparisons will assist mission planners and exploration scientists by providing “calibration points” for using Lunar Reconnaissance Orbiter (LRO) data to successfully plan and execute lunar powered descents in the future. The metrics included in this analysis describe the form of the terrain and can be calculated for any potential future landing site. Another objective of this project is to determine how the derived morphologic parameters for the same landing site change between common pixel scales. In ideal lighting conditions, 2m/px Narrow Angle Camera Digital Terrain Models (NAC DTMs) can be assembled using stereoscopic imagery from two or more concentric orbits of the LRO. However, due to low light conditions near the lunar poles, the highest quality data for many potential lunar landing sites comes from the Lunar Orbiter Laser Altimeter (LOLA). Therefore, we seek to assess how the derived slope and TRI values change as a function of changes in the DTM postings from 2m/px to 5m/px.

J M McCallion↗

NASA NTRSDate not supplied

Trends in Human Spaceflight: Analysis of Observed Propulsion Failure Modes Following NASA’s Artemis I Mission

In 2022, NASA’s Artemis program returned the agency to lunar space, propelled by the Orion European Service Module (ESM). Through rigorous ground test campaigns for Artemis I and II and the collection and transmission of operational data during the Artemis I flight, the Safety and Mission Assurance (S&MA) team created and maintained a robust database of component nonconformances. This study analyzes in-flight and ground processing findings on the Artemis ESM propulsion subsystem to track reliability and safety metrics, as well as comparing the data to that of previous human spaceflight programs, Apollo and Space Shuttle. In drawing a comparison to the Artemis I flight, recommendations can be made for the Artemis II crewed mission to ensure best practices for flight safety, including redundancy and failure tolerance in the system. The results reinforce a need for robust safety standards and caution against the complacency of a single successful test flight.

human spaceflight safety↗

NASA NTRSDate not supplied

Trends in Human Spaceflight: Analysis of Observed Propulsion Failure Modes Following NASA’s Artemis I Mission

human spaceflight safety↗

DOE OSTI2023

Reliability Improvement and Effective Switching Layer Model of Thin-Film MoS 2 Memristors

2D memristors have demonstrated attractive resistive switching characteristics recently but also suffer from the reliability issue, which limits practical applications. Previous efforts on 2D memristors have primarily focused on exploring new material systems, while damage from the metallization step remains a practical concern for the reliability of 2D memristors. Here, the impact of metallization conditions and the thickness of MoS 2 films on the reliability and other device metrics of MoS 2 -based memristors is carefully studied. The statistical electrical measurements show that the reliability can be improved to 92% for yield and improved by ≈16× for average DC cycling endurance in the devices by reducing the top electrode (TE) deposition rate and increasing the thickness of MoS 2 films. Intriguing convergence of switching voltages and resistance ratio is revealed by the statistical analysis of experimental switching cycles. An “effective switching layer” model compatible with both monolayer and few-layer MoS 2 , is proposed to understand the reliability improvement related to the optimization of fabrication configuration and the convergence of switching metrics. In conclusion, the Monte Carlo simulations help illustrate the underlying physics of endurance failure associated with cluster formation and provide additional insight into endurance improvement with device fabrication optimization.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗

NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

Reliability↗

DOE OSTI2023

Laboratory testing methods to evaluate the reliability of occupancy sensors for commercial building applications

The energy performance of commercial buildings is greatly influenced by occupants which are highly variable and among the most unpredictable components of a building's operation. While most building control systems use fixed, predetermined occupancy schedules, these fixed occupancy levels can be quite different from actual occupancy. This can cause unnecessary energy consumption, particularly from heating, ventilation, and air conditioning (HVAC) and lighting systems which are responsible for approximately 60% of commercial buildings' energy use. The use of occupancy counting sensor systems integrated with building management system controls is one method that can be used to improve the energy-consuming performance of buildings. However, there is no standardized universal methodology and metrics to evaluate their reliability. The aim of this research is to develop a uniform evaluation methodology to assess the reliability of occupancy counting sensor systems in a controlled laboratory environment. The developed testing methodology includes both “typical” scenarios representing the occupancy scenarios of a typical commercial building, and “failure” testing scenarios which represent a range of potential scenarios that may impact a sensor system's reliability. These methods were then implemented in a case study to evaluate the performance of two novel occupancy counting sensor systems (i.e., door-centric, and camera-based). Results suggest that typical testing results can be used to compare the overall performance of the occupancy counting sensor systems; however, failure testing is also important to understand the weaknesses of the sensor system in order to select the suitable one for the intended use of the commercial building. In addition, the proposed methodology includes a modified confusion matrix which enables the ability to identify if failures are caused by over or under counting occupants and to what extent this occurs over the testing period.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗

NASA NTRS2000

Comprehensive Design Reliability Activities for Aerospace Propulsion Systems

This technical publication describes the methodology, model, software tool, input data, and analysis result that support aerospace design reliability studies. The focus of these activities is on propulsion systems mechanical design reliability. The goal of these activities is to support design from a reliability perspective. Paralleling performance analyses in schedule and method, this requires the proper use of metrics in a validated reliability model useful for design, sensitivity, and trade studies. Design reliability analysis in this view is one of several critical design functions. A design reliability method is detailed and two example analyses are provided-one qualitative and the other quantitative. The use of aerospace and commercial data sources for quantification is discussed and sources listed. A tool that was developed to support both types of analyses is presented. Finally, special topics discussed include the development of design criteria, issues of reliability quantification, quality control, and reliability verification.

Christenson, R. L.↗

DOE OSTI2022

Optimizing Rate of Penetration and Tripping Decision-Making using Real-Time Bit Wear Monitoring While Drilling Geothermal Wells

Understanding bit wear while drilling is critical to minimizing non-productive time (NPT) and optimizing rate of penetration (ROP). Lengthening drilling runs with damaged bits does not only lower the ROP, but also elevates the risk of inducing severe bit damage, which could potentially lead to time-consuming fishing operations. When drillers believe the bit has worn off substantially, the bit is tripped out to be replaced. On geothermal wells, tripping can take up to 20% of the overall well construction time, and this is generally acknowledged as an opportunity for improvement. Ideally, a bit run should be terminated before the bit is damaged beyond repair. At the same time, premature bit pulls are to be avoided as well. This study aims to leverage bit and tooth wear metrics that can be obtained in real time to characterize bit condition in order to optimize ROP and determine the optimal time to pull the bit. Two metrics were explored in this study: a bit wear metric that incorporated depth-of-cut, and a tooth wear metric developed by Bourgoyne & Young characterizing the state of bit teeth dull. Both metrics were computed using recorded data from 12¼ inches roller cone insert bit runs in five geothermal wells targeting a granodiorite formation in the western United States. Together with the actual dull grades, determined after the bits were pulled to surface, the metric trends were interpreted to characterize the downhole bit condition and identify the point at which the bit should have optimally been tripped out. The insights from studying the actual dull grades and how they relate to the two metrics were used to establish a reliable bit pull criterion. The bit wear metric trend correctly showed a noticeable departure from baseline for bits experiencing major dulling behavior. Additionally, the tooth wear model predicted the cutter dull within two dull grades for most runs, with better performance in predicting the inner teeth dull. Moreover, the combination of the bit wear and tooth wear metrics was effective in revealing the cause of the bit performance impairment. Proactive tracking of these two metrics in real-time can facilitate geothermal drilling ROP optimization and better-informed tripping decision-making, thereby avoiding wasted time and cost.

Ashari, Rahmat↗

DOE OSTI2026

New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization

Reliable climate predictions across multiple timescales are increasingly critical as climate-related risks continue to rise. With the growing number and diversity of climate prediction systems, systematic intercomparison has become essential. Here, we present a comprehensive evaluation framework based on the PCMDI Metric Package to assess the performance of multiple decadal climate prediction systems. Unlike uninitialized simulations, initialized predictions exhibit bias and predictive skill that evolve with forecast lead time. To address this, we introduce (1) model-by-lead-time portrait plots, which efficiently summarize metrics of global temperature, precipitation, and Arctic/Antarctic sea-ice extent, and (2) an HTML-based interactive visualization platform that provides detailed regional and seasonal diagnostics of model bias, skill scores, and ensemble spread for each model and lead time. Comparisons with uninitialized simulations further quantify the relative impacts of initialization and external forcing on prediction skill. The proposed framework provides a scalable and transparent approach for multi-model climate prediction assessments and can be readily extended to a wide range of operational and research forecasting systems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2026

Reliability Models and Demonstration of a Fault-Tolerant Motor Concept for Vertical Takeoff and Landing Vehicles

This report documents the completion of the Revolutionary Vertical Lift Technology Project Annual Performance Indicator 24-3.2.4.1: “Apply and document reliability prediction for high reliability motor concept.” Two modeling tools were completed for calculation of reliability of fault-tolerant (FT) motors, and key FT operations of a modular FT motor were demonstrated experimentally. The two models are complementary tools for the stakeholder and user community. Both models employ Markov chain theory. The first model is a time-homogeneous Markov chain model, and the second is a time-inhomogeneous Markov-Weibull model. This report’s main sections are as follows: 1.0 Introduction, 2.0 Theory, 3.0 Motor Reliability Models, 4.0 Validation of FT Operation by Hardware Demonstration, and 5.0 Concluding Remarks. Novel contributions to the field include development of a modular FT motor concept for electrified vertical takeoff and landing (eVTOL) application, solution methods to solve the reliability calculations, development of figures of merit, and the introduction of “linked chains” to formulate a building-block approach for time-inhomogeneous Markov-Weibull modeling of motor reliability. Example case studies have been completed, and results are provided and discussed herein. A four-module FT motor concept was developed to a preliminary-design level of detail. This eVTOL FT motor concept was designed for galvanic, magnetic, and thermal isolation of stator winding faults. The reliability of the concept motor was calculated using a time-inhomogeneous Markov chain model. Employing average failure rate as a metric, 570 times greater reliability was achieved as compared to a baseline motor without fault tolerance. A demonstrator motor was built and tested. The testing demonstrated the key features of FT operation and validated the essential premises of the FT motor concepts presented herein. The experiments included successful demonstration of the feasibility of the following four key FT features: (1) terminal open-circuit operation, (2) thermal isolation after fault, (3) terminal short-circuit operation, and (4) internal short-circuit operation. These works indicate that FT modular motor drives offer promise for addressing the daunting reliability gap that electric aircraft propulsor drives are facing relative to the best conventional motor drive technology that is available today.

Electric Motor↗