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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Multiphysics Multiscale Simulation Platform for Damage, Environmental Degradation, and Life Prediction of CMCs in Extreme Environments

This project successfully developed a multiphysics, multiscale computational framework to enhance the design and development of CMCs, with a focus on modeling highly nonlinear, time-dependent damage mechanisms and material degradation under extreme conditions, such as those experienced in turbine service environments. The project made significant advances in improving our understanding of progressive damage, oxidative degradation, and time-dependent inelastic deformation in CMCs, with particular attention to the role of uncertainties in predictions. Key outcomes include the integration of advanced material characterization, uncertainty quantification, and multiphysics constitutive models to predict the behavior of CMCs over their service life. A novel multiscale methodology was employed, which integrated microscale constituent behaviors with structural-scale responses, enabling the manufacturing defects in the microstructure that are prone to damage nucleation. Through the development of DL algorithms, the project advanced the prediction of damage initiation and crack propagation, taking into account the defect morphology and statistical variations across multiple scales. The framework was rigorously validated using thermomechanical experiments, which tested CMCs under various mechanical loadings at elevated temperatures, further enhancing the model's predictive capability. Overall, the research outcomes have provided a more accurate, reliable method for predicting CMC component life, significantly advancing material design, and improving component reliability in extreme environments. This work has strong implications for the optimization of turbine components and other high-performance applications where CMCs are used.

03 NATURAL GAS↗
NASA NTRS1989

Time dependent inflow-outflow boundary conditions for 2D acoustic systems

An analysis of the number and form of the required inflow-outflow boundary conditions for the full two-dimensional time-dependent nonlinear acoustic system in subsonic mean flow is performed. The explicit predictor-corrector method of MacCormack (1969) is used. The methodology is tested on both uniform and sheared mean flows with plane and nonplanar sources. Results show that the acoustic system requires three physical boundary conditions on the inflow and one on the outflow boundary. The most natural choice for the inflow boundary conditions is judged to be a specification of the vorticity, the normal acoustic impedance, and a pressure gradient-density gradient relationship normal to the boundary. Specification of the acoustic pressure at the outflow boundary along with these inflow boundary conditions is found to give consistent reliable results. A set of boundary conditions developed earlier, which were intended to be nonreflecting is tested using the current method and is shown to yield unstable results for nonplanar acoustic waves.

Watson, Willie R.↗
NASA NTRS2005

Comet/Asteroid Protection System: Concept Study Executive Summary

Many of the major issues have been identified for a futuristic capability to protect against impacting comets and asteroids, and a preliminary space-based concept has been envisioned. Some of the basic concept elements, approaches, methodologies, and features have been identified. When contemplating the ability to monitor comets and asteroids continuously, there are many trade-offs between orbiting observatories and detection systems on planetary bodies without an atmosphere. Future orbit modification techniques have the potential for rapid and controlled alteration of NEO orbits, provided that high-power, compatible thermal management systems are developed. Much additional work and analysis are required to identify a final system concept, and many trade studies need to be performed to select the best mix of system capability, reliability, maintainability, and cost. Finally, it is fully appreciated that at the present time space systems are much more costly than terrestrial-based systems. Hopefully, this will change in the future. Regardless, understanding what it would take to defend against a much wider range of the impact threat will foster ideas, innovations, and technologies that could one day enable the development of such a system. This understanding is vital to provide ways of reducing the costs and quantifying the benefits that are achievable with a system like CAPS.

Mazanek, Daniel D.↗
NASA NTRS2018

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid contradictions such as having to choose one sub-component to generate performance diagnostics to another, possibly not fully consistent, component.

Todling, Ricardo↗
NASA NTRSDate not supplied

Streamlining GNC Architecture Development and FSW Integration forthe Mars Ascent Vehicle

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface ofanother atmospheric planetary body outside of the Earth-Moon system. Significant light-time delayrequires complete autonomy of flight throughout ascent, and naturally a high level of reliability isdesired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls(GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiencyof algorithm integration onto the MAV flight processor, and to increase confidence that said integrationis successful and without human error. An interface architecture is proposed for the GNC suite thatallows both the guidance and navigation subsystems to provide code algorithms directly in C++, and thecontrols subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code fromthe GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendlywrapper which abstracts the integration of the GNC algorithm code into an interface-level API that iscompatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSWteam’s partnership, and this strong interface between these two teams have allowed the GNC/FSWteams to greatly increase confidence of efficient and error-free implementation of the GNC code ontoMAV for a successful flight.

GNC↗
DOE OSTI2020

Enhancing Reliability of Classified Shipments Between the Nuclear Security Enterprise

The extent of this project, as related to by the Nuclear Security Enterprise (NSE), is related to the current shipping and logistical issues and optimization opportunities between several different NSE sites that are the basis of the enterprise. This current scope is part of every site’s, described as Design Agency (DA) and Production Agency (PA), normal operation to meet the needs and mission of the National Nuclear Security Administration (NNSA). The NSE has a broad mission scope encompassing several differing DA and PA sites to meet the NNSA’s mission. These sites require frequent interaction and shipments of material and items between one another in order to meet the mission needs of the enterprise. Currently, there is no methodology that integrates schedules, standards, orders, processes, and best practices to optimize transfers between the differing sites. A centralized location and standard shipping process will optimize and improve the systems behavior, reducing lag time and increasing throughput at sites today. Ultimately this project proposes a central logistical platform, tiered escalation process, and standardized shipping forms to reduce taxpayer costs to meet the NSE’s mission more efficiently. This increase in processing logistics and process accuracy of shipments will save the NSE, not only from a monetary value, but it will reduce the frustrations of individuals working these outdated and over processed systems to improve their quality of life.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

New Report Highlights LAMP's Role as a Robust and Reliable System for Wave Energy Converter Testing

Harnessing the power of waves requires more than just putting devices in the ocean - it takes tools that can refine and accelerate innovation before the first deployment. That's where NLR's largeamplitude motion platform, or LAMP, comes in. LAMP is a six-degree-of-freedom motion system designed to replicate the response of a wave energy converter (WEC) device in realistic ocean conditions. By letting researchers evaluate WEC performance in a safe, controlled lab environment before moving offshore, LAMP helps accelerate innovation while reducing risk. An NLR report, titled Initial Characterization of the NLR LargeAmplitude Motion Platform (https://www.nrel.gov/docs/fy26osti/93733.pdf), provides a deeper understanding of LAMP's capabilities and also lays the groundwork for future advancements in WEC testing methodologies. Researchers studied LAMP's amplitude and frequency limits across different payloads and collected data from 16 test profiles. Testing demonstrated that platform accuracy remained consistent across all payloads evaluated; researchers expect similar accuracy up to LAMP's 10,000-kilogram capacity limit. The measured position limits for single degrees of freedom experienced by WECs, including surge, sway, heave, roll, pitch, and yaw, also exceeded the original manufacturer specifications, providing new insight into the true boundaries of the system.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Multiplanar Stiffness of Commercial Carbon Composite Ankle-Foot Orthoses

The mechanical properties of an ankle-foot orthosis (AFO) can impact how a user's movement is either restricted or augmented by the device. However, standardized methods for assessing stiffness properties of AFOs are lacking, posing a challenge for comparing between devices and across vendors. Therefore, the purpose of this study was to quantify the rotational stiffness of thirteen commercial, nonarticulated, carbon composite ankle-foot orthoses. A custom, instrumented test fixture, for evaluating mechanical properties in rotating exoskeletons (EMPIRE), deflected an AFO through 20 deg of plantar/dorsiflexion motion about a specified, but adjustable, ankle axis. Sagittal, frontal, and transverse plane rotational stiffness were calculated, and reliability was assessed between cycles, sessions, and testers. The EMPIRE demonstrated good-to-excellent reliability between testers, sessions, and cycles (intraclass correlation coefficients all ≥0.95 for sagittal plane stiffness measures). Sagittal plane AFO stiffness ranged from 0.58 N·m/deg to 3.66 N·m/deg. AFOs with a lateral strut demonstrated frontal plane stiffnesses up to 0.71 N·m/deg of eversion while those with a medial strut demonstrated frontal plane stiffnesses up to 0.53 N·m/deg of inversion. Transverse plane stiffnesses were less than 0.30 N·m/deg of internal or external rotation. These results directly compare AFOs of different models and from different manufacturers using consistent methodology and are intended as a resource for clinicians in identifying a device with stiffness properties for individual patients.

Biophysics↗
DOE OSTI2024

Applications of fuzzy logic and best-worst method for tritium sensor selection

Accurate assessment of tritium as a fuel source is critical in fusion reactions, necessitating effective sensor evaluation methods. This study investigates a multi-criteria decision-making framework for selecting tritium sensors, integrating fuzzy logic to enhance decision quality. Initial attempts at applying fuzzy logic were found to be too elementary and failed to capture the complexity of multi-criteria selection; this prompted a refined approach that incorporated expert insights and advanced ranking techniques for sensor evaluation. The research used a two-stage methodology. In the first stage, important criteria and sub-criteria for sensor performance were identified and defined. These criteria were then weighted and scored using a fuzzy best-worst method, drawing upon expert opinions to ensure relevance and validity. The second stage involved interpreting information about varying sensors to rank them based on their overall criteria scores, encouraging the selection of the most suitable options. The result of the study is a proposed method for effective sensor selection in fusion reactors, which in turn will significantly improve the reliability of tritium monitoring in fusion applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2013

Uncertainty Quantification in Remaining Useful Life of Aerospace Components using State Space Models and Inverse FORM

This paper investigates the use of the inverse first-order reliability method (inverse- FORM) to quantify the uncertainty in the remaining useful life (RUL) of aerospace components. The prediction of remaining useful life is an integral part of system health prognosis, and directly helps in online health monitoring and decision-making. However, the prediction of remaining useful life is affected by several sources of uncertainty, and therefore it is necessary to quantify the uncertainty in the remaining useful life prediction. While system parameter uncertainty and physical variability can be easily included in inverse-FORM, this paper extends the methodology to include: (1) future loading uncertainty, (2) process noise; and (3) uncertainty in the state estimate. The inverse-FORM method has been used in this paper to (1) quickly obtain probability bounds on the remaining useful life prediction; and (2) calculate the entire probability distribution of remaining useful life prediction, and the results are verified against Monte Carlo sampling. The proposed methodology is illustrated using a numerical example.

Sankararaman, Shankar↗
NASA NTRS2007

Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks

Geostationary Operational Environmental Satellite (GOES) Image Navigation and Registration (INR) performance is specified at the 3- level, meaning that 99.7% of a collection of individual measurements must comply with specification thresholds. Landmarks are measured by the Replacement Product Monitor (RPM), part of the operational GOES ground system, to assess INR performance and to close the INR loop. The RPM automatically discriminates between valid and invalid measurements enabling it to run without human supervision. In general, this screening is reliable, but a small population of invalid measurements will be falsely identified as valid. Even a small population of invalid measurements can create problems when assessing performance at the 3-sigma level. This paper describes an additional layer of quality control whereby landmarks of the highest quality ("platinum") are identified by their self-consistency. The platinum screening criteria are not simple statistical outlier tests against sigma values in populations of INR errors. In-orbit INR performance metrics for GOES-12 and GOES-13 are presented using the platinum landmark methodology.

Carr, James L.↗
NASA NTRS2011

Single-Event Gate Rupture in Power MOSFETs: A New Radiation Hardness Assurance Approach

Almost every space mission uses vertical power metal-semiconductor-oxide field-effect transistors (MOSFETs) in its power-supply circuitry. These devices can fail catastrophically due to single-event gate rupture (SEGR) when exposed to energetic heavy ions. To reduce SEGR failure risk, the off-state operating voltages of the devices are derated based upon radiation tests at heavy-ion accelerator facilities. Testing is very expensive. Even so, data from these tests provide only a limited guide to on-orbit performance. In this work, a device simulation-based method is developed to measure the response to strikes from heavy ions unavailable at accelerator facilities but posing potential risk on orbit. This work is the first to show that the present derating factor, which was established from non-radiation reliability concerns, is appropriate to reduce on-orbit SEGR failure risk when applied to data acquired from ions with appropriate penetration range. A second important outcome of this study is the demonstration of the capability and usefulness of this simulation technique for augmenting SEGR data from accelerator beam facilities. The mechanisms of SEGR are two-fold: the gate oxide is weakened by the passage of the ion through it, and the charge ionized along the ion track in the silicon transiently increases the oxide electric field. Most hardness assurance methodologies consider the latter mechanism only. This work demonstrates through experiment and simulation that the gate oxide response should not be neglected. In addition, the premise that the temporary weakening of the oxide due to the ion interaction with it, as opposed to due to the transient oxide field generated from within the silicon, is validated. Based upon these findings, a new approach to radiation hardness assurance for SEGR in power MOSFETs is defined to reduce SEGR risk in space flight projects. Finally, the potential impact of accumulated dose over the course of a space mission on SEGR susceptibility is explored. SEGR evaluation of gamma-irradiated power MOSFETs suggests a non-significant SEGR susceptibility enhancement due to accumulated dose from gamma rays. During SEGR testing, an unexpected enhanced dose effect from heavy-ion irradiation was detected. We demonstrate that this effect could be due to direct ionization by two or more ions at the same channel location. The probability on-orbit for such an occurrence is near-zero given the low heavy-ion fluence over a typical mission lifetime, and did not affect SEGR susceptibility. The results of this work can be used to bound the risk of SEGR in power MOSFETs considered for insertion into spacecraft and instruments.

Lauenstein, Jean-Marie↗
NASA NTRS2020

Bayesian Framework For Bioburden Density Calculations To Perform Planetary Protection Probabilistic Risk Assessment

The planetary protection discipline aims to minimize the microbial contamination on spacecraft to prevent the inadvertent contamination of other planetary bodies, known as forward planetary protection (PP). Planetary protection probabilistic risk assessment (PRA) relies on two core methodologies-the contamination probability event tree analysis and statistical parameter estimation. Planetary protection engineers combine several techniques to estimate the bioburden present on spacecraft components. A direct assay to enumerate CFU (colony forming units) is the preferred methodology, but given a similar processing environment the bioburden present on certain components is inferred using: (1) a NASA defined bioburden estimate based upon the biological cleanliness of the manufacturing/assembly environment or (2) sampled data from a similar spacecraft component. The paper presents an empirical Bayesian framework to systematically treat bioburden estimation and its uncertainties on different levels starting with measurement procedures to combining different components to subsystems and whole spacecraft. It is shown that the Bayesian approach can effectively handle estimations and their uncertainties at different levels and produce a reliable estimate for bioburden to be used to evaluate the probability of contamination.

Seuylemezian, Arman↗
DOE OSTI2020

LID and LeTID Impacts to PV Module Performance and System Economics: Draft Analysis

This webinar is a technical review of the measurements and causes of BO LID, UV LID and LeTID, as well as modeling their impacts to PV project financial metrics. We will first review how Boron-Oxygen complexes form and detail the range of impacts to PV module power ratings over time and across climates. Similarly, we will also discuss the measurements and extent of UV LID over time and across climates. Then, we will demonstrate a methodology for translating these effects to pro forma cash flow models and their impacts to PV project financial returns and levelized cost of electricity (LCOE). We will conclude with estimates of the value of solutions to these degradation mechanisms.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

End-To-End Decentralized Transmission Line Protection in IBR-Dominated Weak Grids Using Interpretable Data-Driven Methods

Traditional transmission line protection relies on predictable synchronous-based fault signatures, which frequently fail under the non-standard, current-limited fault characteristics of Inverter-Based Resources (IBRs). This study investigates how to achieve secure, communication-free fault isolation in IBR-dominated weak grids without relying on opaque, computationally heavy "black-box" machine learning algorithms. To address this, we propose a novel, standalone, and inherently interpretable data-driven protection framework. Unlike centralized methods requiring multi-terminal communication, this decentralized approach relies solely on local measurements using a hierarchical linear-kernel Support Vector Machine (SVM). The methodology decomposes the protection task into four sequential stages that mimic traditional protection elements: fault detection and fault direction identification, fault type classification, zone classification, and location estimation. This multi-stage architecture allows for specialized feature engineering at each stage, combining high computational efficiency with logic traceability. The framework's end-to-end performance was validated via C-code and PSCAD/EMTDC co-simulation, utilizing a real-world utility network and an OEM black-box IBR model. The proposed relay achieves 97.2% overall accuracy and provides a reliable trip decision within a 2.5-cycle window. The results confirm 100% accuracy in fundamental fault detection, reliable zone selectivity across low to moderate fault resistances, and robust security against non-fault transients, proving its immediate viability for integration into commercial numerical relays.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Benchmark probabilistic solar forecasts: Characteristics and recommendations

We illustrate and compare commonly used benchmark, or reference, methods for probabilistic solar forecasting that researchers use to measure the performance of their proposed techniques. A thorough review of the literature indicates wide variation in the benchmarks implemented in probabilistic solar forecast studies. To promote consistent and sensible methodological comparisons, we implement and compare ten variants from six common benchmark classes at two temporal scales: intra-hourly forecasts and hourly resolution forecasts. Using open-source Surface Radiation Budget Network (SURFRAD) data from 2018, these benchmark methods are compared using proper probabilistic metrics and common diagnostic tools. Practical implementation issues, such as the impact of missing data and applicability for operational forecasting, are also discussed. Furthermore, we make recommendations for practitioners on the appropriate selection of benchmark methods to properly showcase state-of-the-art improvements in forecast reliability and sharpness. All code and open-source data are available on Github for reproducibility and for other researchers to apply the same benchmark methods to their own data.

14 SOLAR ENERGY↗
NASA NTRS2010

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Chamis, Christos C.↗