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Results for “Reliability Specifications”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗
DOE OSTI2020

Modeling Flexible Generator Operating Regions via Chance- constrained Stochastic Unit Commitment

Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.

42 ENGINEERING↗
DOE OSTI2021

Propagation of Input Uncertainties in Numerical Simulations of Laser Powder Bed Fusion

Laser powder bed fusion has the potential of redefining state-of-the-art processing and production methods, but defect formation and inconsistent build quality have limited the implementation of this process. Numerical models are widely used to study this process and predict the formation of these defects. Presently, the uncertainties of model input parameters and thermophysical properties used by these numerical simulations have not been investigated. In the present study, the uncertainty in these input parameters and material properties are quantified for laser powder bed fusion, with and without a simulated powder bed, to determine their influence on the predictive accuracy of an experimentally validated numerical model. Accounting for all possible sources of uncertainty quickly becomes computationally expensive on account of the curse of dimensionality. Uncertainty in laser absorption, solid, and liquid specific heat of the metal were found to have the largest effect on model prediction reliability with or without the use of a powder bed. Results also illustrate that accounting for these three uncertain parameters still captures the majority of model prediction uncertainty. Furthermore, the methodology of this study may be used to understand the uncertainty in as-built microstructure through propagation to microstructure prediction models, or applied under processing conditions where high Péclet numbers are observed and the thermal convection and fluid flow within the molten pool are substantial.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Standard operating procedures for the comprehensive and reliable analysis of cannabis terpenes

Terpenes are the primary determinants of cannabis flower aroma, and ongoing research tests their potential for impacting the overall experience. Frustratingly, despite the importance of terpenes in cannabis physiology and commercial uses, literature reports vary widely regarding the major constituents of volatile blends and the concentrations of individual terpenes. Here, in this article, we provide detailed descriptions of complementary approaches that will allow researchers to determine the identity and quantity of cannabis terpenes unequivocally and reliably. These standard operating procedures will guide decisions about which method to employ to address specific analytical goals. We are including two application examples to illustrate the utility of different approaches for tackling the analysis of terpenes in cannabis flower samples.

Polito, Joshua↗
DOE OSTI2026

“One Table to Rule Them All”: How a Single Table can Enable Extensive Insights, Analytics and Assessment on Human Mobility Data

While much research has been conducted in Human Mobility Science, most studies on the analytics/insights part generally focus on one of the following: processing and analytics on human stop-trip behavior, design of individual mobility metrics (often in silos), calculation and characterization of only a handful (typically 5-6) of human mobility metrics on geospatial-temporal human mobility data of interest. Although human mobility research offers a vast and diverse array of available metrics, most individual studies typically compute only a small subset of five or six metrics at a time when analyzing trajectory datasets of human mobility across different areas of interest. This paper is motivated by the critical need to repeatedly compute an extensive array of human mobility metrics across several trajectory datasets and perform individual metric-level benchmarking to establish a new, standardized Test and Evaluation (T&E) suite for the field of Human Mobility Science. We first present our findings on the minimal yet sufficient pre-processing required to reliably and efficiently compute a wide range of human mobility metrics. The key findings are specifically related to the proposed Composite Stop Locations table, which serves as a core pre-processing data layer. Subsequently, we present a case study demonstrating how the Composite Stop Locations table facilitates computation of at least 14 distinct human mobility metrics (unlike 5-6 different set of metrics used for studies in the literature) using the popular and open-source OpenPFLOW dataset. Finally, we have also presented an example of our benchmarking methodology to evaluate the quality and performance of the trajectory dataset of interest, assessed across multiple human mobility metrics.

De, Debraj [ORNL] (ORCID:0000000233630020)↗
DOE OSTI2026

Flash electropolishing for TEM: Reducing FIB‐induced defects in tungsten with protocols for new materials

Focused ion beam (FIB) milling has become the dominant approach for site-specific transmission electron microscopy (TEM) specimen preparation; however, FIB damage remains a critical limitation for reliable microstructural characterisation, particularly in radiation effects studies. Tungsten is especially susceptible to FIB damage due to its high nuclear stopping power, which promotes the formation and strong diffraction contrast of FIB-induced ‘black spot’ defects that are indistinguishable from very fine irradiation-induced loops/defects resulting from low to intermediate temperature neutron irradiation. In this work, flash electropolishing is systematically evaluated as a post-FIB treatment for minimising preparation-induced artefacts for TEM analysis of tungsten-based alloys. Using a range of non-, ion-, and neutron-irradiated tungsten materials, the effectiveness of flash electropolishing has been assessed through direct comparison with conventional FIB and plasma-FIB preparation including low-energy Ga, Ar, Xe ion cleaning. The results demonstrate that flash electropolishing effectively removes FIB-damaged layers and ‘black spot’ defects, thereby enabling reliable observation of irradiation-induced dislocation structures. Key processing parameters governing flash electropolishing quality – including lamella thickness, applied voltage, polishing duration, electrolyte chemistry, and cathode geometry – have been systematically evaluated, and clear criteria were established for determining when flash electropolishing is required to ensure reliable microstructural analysis. This work also provides practical guidance for implementing flash electropolishing as an artefact-controlled specimen-preparation approach for TEM characterisation of FIB-produced specimens. The systematic protocol can be extended to other, non-tungsten materials.

TEM sample preparation↗
DOE OSTI2020

Bistatic Synthetic Aperture Radar - Issues Analysis and Design

The physical separation of the transmitter from the receiver into perhaps separate flight vehicles (with separate flight paths) in a bistatic Synthetic Aperture radar system adds considerable complexity to an already complex system. Synchronization of waveform parameters and timing attributes become problematic, and notions of even the synthetic aperture itself take on a new level of abstractness. Consequently, a high-performance, fine-resolution, and reliable bistatic SAR system really needs to be engineered from the ground up, with tighter specifications on a number of parameters, and entirely new functionality in other areas. Nevertheless, such a bistatic SAR system appears viable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Differentiable Channels Are All You Need

Mobile wireless communication systems must adapt to and compensate for time-varying propagation paths. The process of performing compensation in the receiver for said effects is known as equalization. We seek an improved method for optimizing the reliability of said wireless links to minimize outage probability. A method based on machine learning, specifically deep learning, has the potential to allow for greater flexibility and robustness against unforeseen channel conditions. In this report we investigate the performance of a prior method in the literature with minor modifications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sample Cybersecurity Clauses for EV Charging Infrastructure Procurements

This is the final version of PNNL-34373, with sponsor updates. The proposed sample cybersecurity clauses for EVCI procurements are designed to assist in managing the risk of cyberattacks that may degrade the safety, security, and reliability of EVCI. The sample clauses are intended to be tailored and incorporated into procurement specifications for equipment and services related to the National EV Infrastructure Formula Program deployments. Widespread adoption of the sample cybersecurity procurement language will integrate cybersecurity throughout the life cycle of the infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Management of Risks Associated with Application of Novel Materials in Novel Operating Environments in Novel Reactor Designs

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. These challenges are discussed in the paper, and a potentially applicable modeling approach based on cumulative damage rather than failure rates is briefly illustrated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Direct Metallization with Reactive Inks – Assessment of Reliability and Process Sensitivities

This project will reduce silver consumption in photovoltaic cells by a factor of almost ten – from 95 mg/cell (the median across technologies) to 10 mg/cell. To achieve this goal, we will replace screen-printed silver pastes with contact dispensed reactive inks that produce lower resistivity metallizations at lower temperatures and with thinner films. This project will generate the understanding necessary to scale this reactive ink technology from the bench-scale to commercial throughputs. Specifically, it will combine fundamental understanding on physics and chemistries involved in contact printing of reactive inks with detailed performance and reliability studies to quantify how tightly processing parameters need to be controlled in order to reliably metallize high efficiency solar cells at commercial throughputs of 36,000 cells/hour.

14 SOLAR ENERGY↗
DOE OSTI2021

Geometric Tail Approximation for Reliability and Survivability

A common problem in developing high-reliability systems is estimating the reliability for a population of components that cannot be 100% tested. The radiation survivability of a population of components is often estimated by testing a very small sample to some multiple of the required specification level, known as an overtest. Given a successful test with a sufficient overtest margin, the population of components is assumed to have the required survivability or radiation reliability. However, no mathematical justification for such claims has been crafted without making aggressive assumptions regarding the statistics of the unknown distribution. Here we illustrate a new approach that leverages geometric bounding arguments founded on relatively modest distribution assumptions to produce conservative estimates of component reliability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Challenges for density functional theory: calculation of CO adsorption on electrocatalytically relevant metals

Density Functional Theory (DFT) is currently the most tractable choice of theoretical model used to understand the mechanistic pathways for electrocatalytic processes such as CO 2 or CO reduction. In this work, we assess the performance of two DFT functionals designed specifically to describe surface interactions, RTPSS and RPBE, as well as two popular meta-GGA functionals, SCAN and B97M-rV, that have not been a priori optimized for better interfacial properties. We assess all four functionals against available experimental data for prediction of bulk and bare surface properties on four electrocatalytically relevant metals, Au, Ag, Cu, and Pt, and for binding CO to surfaces of these metals. To partially mitigate issues such as thermal and anharmonic corrections associated with comparing computations with experiments, molecular benchmarks against high level quantum chemistry are reported for CO complexes with Au, Ag, Cu and Pt atoms, as well as the CO–water complex and the water dimer. Overall, we find that the surface modified RPBE functional performs reliably for many of the benchmarks examined here, and the meta-GGA functionals also show promising results. Specifically B97M-rV predicts the correct site preference for CO binding on Ag and Au (the only functional tested here to do so), while RTPSS performs well for surface relaxations and binding of CO on Pt and Cu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Directed Evolution of an Adenylation Domain Alters Substrate Specificity and Generates a New Catechol Siderophore in Escherichia coli

Nonribosomal peptide synthetases (NRPS) biosynthesize numerous natural products with therapeutic, agricultural, and industrial significance. Reliably altering substrate selection in these enzymes has been a longstanding goal, as this would enable the production of tailor-made peptides with desired activities. In this study, the NRPS EntF and the associated biosynthesis of the siderophore enterobactin (ENT) were used as a model system to interrogate substrate selection by an adenylation (A) domain. We employed a directed evolution pipeline that harnesses an in vivo genetic selection for siderophore production to alter A domain substrate selection. Surprisingly, this led to the formation of a new, physiologically active catechol siderophore in Escherichia coli. We characterized the enzyme variants in vitro and demonstrated transferability of our findings to the well-studied TycC and GrsB NRPSs. Furthermore, this work identifies critical binding pocket residues that allow for altered substrate selection in our model system and expands upon our understanding of iron acquisition in E. coli.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2023

Electronic specific heat capacities and entropies from density matrix quantum Monte Carlo using Gaussian process regression to find gradients of noisy data

In this work, we present a machine learning approach to calculating electronic specific heat capacities for a variety of benchmark molecular systems. Our models are based on data from density matrix quantum Monte Carlo, which is a stochastic method that can calculate the electronic energy at finite temperature. As these energies typically have noise, numerical derivatives of the energy can be challenging to find reliably. In order to circumvent this problem, we use Gaussian process regression to model the energy and use analytical derivatives to produce the specific heat capacity. From there, we also calculate the entropy by numerical integration. We compare our results to cubic splines and finite differences in a variety of molecules in which Hamiltonians can be diagonalized exactly with full configuration interaction. We finally apply this method to look at larger molecules where exact diagonalization is not possible and make comparisons with more approximate ways to calculate the specific heat capacity and entropy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modulating above-room-temperature magnetism in Ga-implanted Fe 5 GeTe 2 van der Waals magnets

The creation of van der Waals (vdW) ferromagnets with tunable Curie temperature (T C ) and magnetic anisotropy is essential in developing vdW magnet-based devices. Here, we report an effective and reliable method for modulating the magnetic properties of vdW Fe 5 GeTe 2 by site-specific Ga + implantation. In this study, we report an easy axis in the ab-plane for bulk Fe 5 GeTe 2 (T C = 310 K) and an axis out of the plane for thin Fe 5 GeTe 2 flakes (T C = 290 K). Combining element-resolved photoemission electron microscopy and spatially resolved magneto-optic Kerr microscopy, we find that the implantation of a tiny amount of 10 –3 Ga + ·Å –3 in Fe 5 GeTe 2 greatly enhances the T C from 290 to 360 K and switches the magnetic easy axis from the out-of-plane c axis to the ab-plane. The room-temperature x-ray magnetic circular dichroism signal is enhanced from 0% to 9% at an implantation level of 10 –2 Ga + ·Å –3 . These results provide new opportunities for tailoring the magnetic properties of vdW materials beyond room temperature.

36 MATERIALS SCIENCE↗