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Results for “Reliability Prediction”

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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Prediction of high-speed aerodynamic characteristics using the Aerodynamic Preliminary Analysis System (APAS)

An exercise was performed which illustrates the prediction of high-speed aerodynamic coefficients using the Aerodynamic Preliminary Analysis System. Two generic transatmospheric vehicle configurations are used as examples on which various inviscid and viscous estimation techniques are applied. As a means of evaluating the reliability of the Aerodynamic Preliminary Analysis System results, comparisons of predictions using this preliminary-level approach are compared with Shuttle-derived data, hypersonic helium tunnel data for several configurations, and computational fluid dynamics results. Overall, predictions using the Aerodynamic Preliminary Analysis System agree well with the other calculations and data.

Cruz, Christopher I.↗
DOE OSTI2020

Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements

New sets of CMS underlying-event parameters ("tunes") are presented for the PYTHIA8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO) orders in perturbative quantum chromodynamics, and the strong coupling evolution at LO or NLO. Measurements of charged-particle multiplicity and transverse momentum densities at various hadron collision energies are fit simultaneously to determine the parameters of the tunes. Comparisons of the predictions of the new tunes are provided for observables sensitive to the event shapes at LEP, global underlying event, soft multiparton interactions, and double-parton scattering contributions. In addition, comparisons are made for observables measured in various specific processes, such as multijet, Drell-Yan, and top quark-antiquark pair production including jet substructure observables. The simulation of the underlying event provided by the new tunes is interfaced to a higher-order matrix-element calculation. For the first time, predictions from PYTHIA8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2003

System and Software Reliability (C103)

Within the last decade better reliability models (hardware. software, system) than those currently used have been theorized and developed but not implemented in practice. Previous research on software reliability has shown that while some existing software reliability models are practical, they are no accurate enough. New paradigms of development (e.g. OO) have appeared and associated reliability models have been proposed posed but not investigated. Hardware models have been extensively investigated but not integrated into a system framework. System reliability modeling is the weakest of the three. NASA engineers need better methods and tools to demonstrate that the products meet NASA requirements for reliability measurement. For the new models for the software component of the last decade, there is a great need to bring them into a form that they can be used on software intensive systems. The Statistical Modeling and Estimation of Reliability Functions for Systems (SMERFS'3) tool is an existing vehicle that may be used to incorporate these new modeling advances. Adapting some existing software reliability modeling changes to accommodate major changes in software development technology may also show substantial improvement in prediction accuracy. With some additional research, the next step is to identify and investigate system reliability. System reliability models could then be incorporated in a tool such as SMERFS'3. This tool with better models would greatly add value in assess in GSFC projects.

Wallace, Dolores↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2020

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

Abstract The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λ s ). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λ s from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.

Baer, Kathryn C.↗
DOE OSTI2019

Magnetocaloric Effect and Critical Behavior Investigations in La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} Manganite Oxide

Structural, magnetic, and magnetocaloric effect (MCE) properties and the critical behavior of the La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} sample prepared by the sol–gel method have been investigated. The X-ray diffraction characterization reveals that our sample crystallizes in the orthorhombic structure with Pnma space group. Magnetization versus temperature measurement shows that our compound exhibits a ferromagnetic–paramagnetic transition. The Curie temperature is found to be 348 K. Close to this temperature, the maximum values of the magnetic entropy change (ΔS{sub M}) and the relative cooling power (RCP) are found to be 2.84 J/kg/K and 230 J/K under µ{sub 0}H = 5 T, respectively. The Arrott plots revealed that this compound exhibits a second-order magnetic phase transition at T{sub C}. The critical behavior has been investigated by several techniques which are the modified Arrott plot method, the Kouvel–Fisher method, and the critical isotherm analysis. The obtained critical exponents β, γ, and δ are consistent with those predictions of the mean-field model. Their reliability was confirmed by Widom’s scaling relation, as well as the universal scaling hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2017

IEA EBC annex 53: Total energy use in buildings—Analysis and evaluation methods

One of the most significant barriers to achieving deep building energy efficiency is a lack of knowledge about the factors determining energy use. In fact, there is often a significant discrepancy between designed and real energy use in buildings, which is poorly understood but are believed to have more to do with the role of human behavior than building design. Building energy use is mainly influenced by six factors: climate, building envelope, building services and energy systems, building operation and maintenance, occupants’ activities and behavior, and indoor environmental quality. In the past, much research focused on the first three factors. However, the next three human-related factors can have an influence as significant as the first three. Annex 53 employed an interdisciplinary approach, integrating building science, architectural engineering, computer modeling and simulation, and social and behavioral science to develop and apply methods to analyze and evaluate the real energy use in buildings considering the six influencing factors. Finally, outcomes from Annex 53 improved understanding and strengthen knowledge regarding the robust prediction of total energy use in buildings, enabling reliable quantitative assessment of energy-savings measures, policies, and techniques.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthal resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this article, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, our analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Determining the Conformation of Supported Complexes Using an 17 O TEDOR-like NMR Experiment

Dynamic nuclear polarization surface-enhanced nuclear magnetic resonance (NMR) spectroscopy has enabled the determination of the three-dimensional configuration of surface sites, in particular supported metal complexes of relevance to single-site heterogeneous catalysis. These approaches have chiefly leveraged the application of NMR double-resonance experiments that either reveal the complex conformation via point-to-point intramolecular distances between spin-labeled atoms or the complex-surface orientation via distances between the spins and the surface plane. Either method typically requires expensive isotope labeling and each reports on different structural features. The application of an experiment that simultaneously reveals both types of distances with chemical resolution would be ideal. Here, in this article, we describe an 17 O{ 1 H} pseudo-3D correlation experiment that achieves this goal. Specifically, Si–O–Si and Si–O–M oxygens are well-resolved by 17 O NMR; therefore, distances can be simultaneously measured radially, between Si– 17 O–M and the 1 H’s of the ligands, and vertically to the Si– 17 O–Si linkages of the silica support. We demonstrate the experiment using supported yttrium and zirconium complexes. Good agreement is obtained when comparing the experimental results to theoretical predictions from density functional theory calculations, highlighting the reliability of this relatively simple experiment.

alkyls↗
DOE OSTI2024

Solvent Isotherms and Structural Transitions in Nanoparticle Superlattice Assembly

Here, we introduce a Molecular Theory for Compressible Fluids (MOLT-CF) that enables us to compute free energies and other thermodynamic functions for nanoparticle superlattices with any solvent content, including the dry limit. Quantitative agreement is observed between MOLT-CF and united-atom molecular dynamics simulations performed to assess the reliability and precision of the theory. Among other predictions, MOLT-CF shows that the amount of solvent within the superlattice decreases approximately linearly with its vapor pressure and that in the late stages of drying, solvent-filled voids form at lattice interstitials. Applied to single-component superlattices, MOLT-CF predicts fcc-to-bcc Bain transitions for decreasing vapor pressure and for increasing ligand length, both in agreement with experimental results. We explore the stability of other single-component phases and show that the C14 Frank-Kasper phase, which has been reported in experiments, is not a global free-energy minimum. Implications for precise assembly and prediction of multicomponent nanoparticle systems are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

StressNet - Deep learning to predict stress with fracture propagation in brittle materials

Abstract Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fracture resistance and reliability of materials. Existing high-fidelity methods, such as the Finite-Discrete Element Model (FDEM), are limited by their high computational cost. Therefore, to reduce computational cost while preserving accuracy, a deep learning model, StressNet, is proposed to predict the entire sequence of maximum internal stress based on fracture propagation and the initial stress data. More specifically, the Temporal Independent Convolutional Neural Network (TI-CNN) is designed to capture the spatial features of fractures like fracture path and spall regions, and the Bidirectional Long Short-term Memory (Bi-LSTM) Network is adapted to capture the temporal features. By fusing these features, the evolution in time of the maximum internal stress can be accurately predicted. Moreover, an adaptive loss function is designed by dynamically integrating the Mean Squared Error (MSE) and the Mean Absolute Percentage Error (MAPE), to reflect the fluctuations in maximum internal stress. After training, the proposed model is able to compute accurate multi-step predictions of maximum internal stress in approximately 20 seconds, as compared to the FDEM run time of 4 h, with an average MAPE of 2% relative to test data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bayesian calibration of irradiated graphite property models under high temperatures

Graphite under high temperatures and irradiation is central to advanced reactors. We develop a Bayesian calibration framework for graphite property models that explicitly represents model-data mismatch via a Gaussian-process discrepancy. The approach propagates uncertainty from parameters, experimental noise, and model form, with a hierarchical variance structure to capture group and cross-group noise. Using two predictive models across five grades (IG-110, NBG-18, PCEA, NBG-17, 2114) and four properties-irradiation-induced dimension change, creep, Young’s modulus change ratio, and coefficient of thermal expansion change ratio-we obtain average predictive-error reductions of 54%, 65%, 17%, and 17% when discrepancy is included. We illustrate engineering impact with a multiphysics model of a very-high-temperature reactor prismatic reflector brick, analyzing stresses under high fluence and temperature. Accounting for model discrepancy markedly improves predictive accuracy and provides a robust basis for reliable graphite component design in advanced reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2015

Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis

This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset. The absence or presence of radiation data alters long-term variation of solar radiation measurement values. Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher. The completeness of the observed variable dataset has significantly important for data analysis. Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However, the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset.

42 ENGINEERING↗
DOE OSTI2026

Development of an ultraprecise glue-free bimorph deformable mirror with a length of 460 mm

Lead zirconate titanate (PZT) bimorph mirrors are essential for performing multiple functions, such as beam shaping, wavefront correction, and dynamic focusing with adjustable beam sizes. They typically consist of a mirror substrate with PZT electrodes bonded to the substrate using a thin epoxy film. However, glue-bonded PZT mirrors exhibit low reproducibility in measurement results. One source of this variability is water absorption by the substrate’s epoxy adhesive during wet fabrication processes, such as elastic emission machining (EEM), which leads to swelling and deformation. Additionally, longer deformable bimorph mirrors require larger PZT electrodes, further complicating their design and fabrication, particularly during bonding and ultraprecise metrology. To address these challenges, silver nanoparticles were employed to bond PZT elements to the silicon (Si) mirror, eliminating the need for epoxy glue. Here, in this study, we developed an inorganic-glue-free PZT bimorph mirror with a length of 460 mm and 28 channels. The glue-free bonding method successfully ensured the high reproducibility of measurements after water immersion. This approach resulted in a shape error of only 0.41 nm root mean square after the figure correction process using an ultraprecise EEM process. Scanning acoustic tomography and basic response function tests confirmed the success of the bonding process, showing no critical voids. Furthermore, the shape changes induced by applying voltages to the PZT electrodes closely matched predictions obtained from simulations. These results demonstrate the reliability and precision of the proposed glue-free bonding technique, paving the way for improved performance of new PZT bimorph mirrors.

Ichii, Yoshio [SLAC National Accelerator Laborator↗
DOE OSTI2020

CI-MBPT line strengths and atomic probabilities for some transitions of neutral iodine

Iodine is a promising alternative to expensive xenon as a propellant for electric propulsion devices. Iodine optical spectroscopy is a valuable diagnostic tool for optimization of the iodine propellant. Recently, some measurements have been conducted with cells containing iodine plasma, and iodine atomic absorption at several wavelengths (911, 906, 206 and 1315 nm) was measured with a Ti:sapphire laser. Motivated by these experiments and future applications, here we have calculated line strengths and atomic probabilities for the transitions between different types of 5s 2 5p 5 , 5s 2 5p 4 6s, 5s 2 5p 4 6p and 5s 2 5p 4 5d states of atomic iodine, using configuration-interaction many-body perturbation theory. Since experimental transition data for atomic iodine are only available for a relatively small number of transitions, we also performed calculations for the bromine atom, to further validate our approach. We found good agreement between our theory and available experimental data for both elements in most cases. Therefore, we believe that our predicted line strengths and transition probabilities are quite reliable and will be useful for iodine spectroscopy.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Mesoscale to Microscale Coupling for Wind Energy Applications: Addressing the Challenges

The purpose of the US DOE's Mesoscale to Microscale Coupling (MMC) Project is to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales that determine wind plant performance and reliability. The project seeks to create a new predictive numerical simulation capability that represents a range of dynamic atmospheric flow conditions impacting wind plant performance.

17 WIND ENERGY↗