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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Failure diagnosis and trend‐based performance losses routines for the detection and classification of incidents in large‐scale photovoltaic systems

Abstract Fault detection and classification in photovoltaic (PV) systems through real‐time monitoring is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating systems. Different statistical and comparative approaches have already been proposed in the literature for fault detection; however, accurate classification of fault and loss incidents based on PV performance time series remains a key challenge. Failure diagnosis and trend‐based performance loss routines were developed in this work for detecting PV underperformance and accurately identifying the different fault types and loss mechanisms. The proposed routines focus mainly on the differentiation of failures (e.g., inverter faults) from irreversible (e.g., degradation) and reversible (e.g., snow and soiling) performance loss factors based on statistical analysis. The proposed routines were benchmarked using historical inverter data obtained from a 1.8 MWp PV power plant. The results demonstrated the effectiveness of the routines for detecting failures and loss mechanisms and the capability of the pipeline for distinguishing underperformance issues using anomaly detection and change‐point (CP) models. Finally, a CP model was used to extract significant changes in time series data, to detect soiling and cleaning events and to estimate both the performance loss and degradation rates of fielded PV systems.

14 SOLAR ENERGY↗
DOE OSTI2025

Resolution dependence of the turbulent atmospheric boundary layer in global storm-resolving climate simulations

The current generation of state-of-the-art global climate models are being run at increasingly higher horizontal resolutions, with the goal of resolving organised deep convection explicitly. How a kilometre-scale resolution impacts the representation of the atmospheric boundary layer is, however, not well known. Using statistical analysis on global fields as well as high-frequency data at selected locations, produced with the Integrated Forecasting System (IFS) model for the Next Generation Earth-system Models (nextGEMS) project, we investigate the horizontal resolution dependence of some boundary-layer processes. We find that a change in resolution from 9 to 2.8 km causes no substantial changes to boundary-layer properties and processes at most of the locations studied, although some global changes are detected that indicate circulation changes. Small changes to the boundary-layer depth and structure are found in the Tropics. The short simulation length and lack of data for optimal boundary-layer analysis limits the conclusions, especially in relation to the connection between the boundary layer and the atmosphere general circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evidence of Directional Structural Superlubricity and Lévy Flights in a van der Waals Heterostructure

Abstract Structural superlubricity is a special frictionless contact in which two crystals are in incommensurate arrangement such that relative in‐plane translation is associated with vanishing energy barrier crossing. So far, it has been realized in multilayer graphene and other van der Waals (2D crystals with hexagonal or triangular crystalline symmetries, leading to isotropic frictionless contacts. Directional structural superlubricity, to date unrealized in 2D systems, is possible when the reciprocal lattices of the two crystals coincide in one direction only. Here, directional structural superlubricity a α‐bismuthene/graphite van der Waals system is evidenced, manifested by spontaneous hopping of the islands over hundreds of nanometers at room temperature, resolved by low‐energy electron microscopy and supported by registry simulations. Statistical analysis of individual and collective α‐bismuthene islands populations reveal a heavy‐tailed distribution of the hopping lengths and sticking times indicative of Lévy flight dynamics, largely unobserved in condensed‐matter systems.

Le Ster, Maxime↗
DOE OSTI2020

Safety Design of Water Infrastructures in A Modern Era

In this chapter, we review the current practice of engineering safety design of large water management infrastructures. Those large infrastructures are designed using probable maximum precipitation (PMP) to withstand extreme conditions, but climate change has been posing challenges on the conventional PMP estimation approach. We discuss multiple limitations of the current approaches, and propose a few possible solutions based on the advancement of atmospheric modeling and statistical analysis of extreme precipitation mechanisms.

Chen, Xiaodong↗
DOE OSTI2026

Combination of searches for heavy vector boson resonances in proton-proton collisions at $\sqrt{s}=13$ TeV

A combined statistical analysis of searches for heavy vector boson resonances decaying into pairs of W, Z, or Higgs bosons, as well as into quark pairs $\left(\mathrm{q}\overline{\mathrm{q}},\mathrm{b}\overline{\mathrm{b}},\mathrm{t}\overline{\mathrm{t}},\mathrm{t}\overline{\mathrm{b}}\right)$ or lepton pairs ℓ + ℓ – , ℓ$\bar{v}$, with ℓ = e, μ, τ, is presented. The results are based on proton-proton collision data at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb −1 , collected by the CMS experiment from 2016 to 2018. No significant deviation from the expectations of the standard model is observed. The results are interpreted in the simplified heavy vector triplet (HVT) framework, setting 95% confidence level upper limits on the production cross sections and on the coupling strengths of the HVT bosons to standard model particles. The results exclude HVT resonances with masses below 5.5 TeV in a weakly coupled scenario, below 4.8 TeV in a strongly coupled scenario, and up to 2.0 TeV in the case of production via vector boson fusion. The combination provides the most stringent constraints to date on new phenomena predicted by the HVT model.

beyond Standard Model↗
DOE OSTI2026

Geometry, spin coupling, and dielectric control of redox potentials in [4Fe–4S] Clusters

Iron–sulfur (Fe–S) clusters are common biological cofactors that facilitate vital redox reactions. Despite extensive research, the molecular basis of redox potential tuning in ferredoxin-like proteins remains an active area of debate. In this study, we combine statistical analysis of over one thousand [4Fe–4S]-containing protein structures from the Protein Data Bank (PDB) with broken-symmetry and extended broken-symmetry density functional theory to examine how cysteine ligand orientations and environmental screening affect redox properties of the clusters. We identified five main ligand configurations, three of which are predominant in natural structures. Among these, the adiabatic electron affinity differs by less than 0.1 V, indicating that, while geometry plays a secondary role, it allows localized fine-tuning of redox properties. In contrast, electrostatic and solvation effects primarily determine the overall potential range.

Computational Chemistry↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2023

Relationship between Grain Size and Sample Thickness on the Creep-Rupture Performance of Thin Metallic Sheets of INCONEL Alloy 740H

A study was conducted on INCONEL® alloy 740H® to examine the role of grain size and sheet thickness on the alloy’s creep-rupture behavior. Three different starting sheet thicknesses were utilized and multiple heat-treatment conditions anticipated for compact heat exchanger (CHX) manufacturing were applied to produce a range of grain sizes. Creep-rupture testing was conducted at 750 °C for times up to about 6000 h and the results were compared to wrought databases. The data show that both creep strength and ductility were important factors in the overall creep performance of the sheets. Reductions in performance were observed due either to accelerated creep when grain size was fine or loss of rupture ductility when grain sizes approached the sheet thickness. Some combinations of heat-treatment and thickness were able to produce typical expected wrought creep properties. Historically a ‘rule-of-thumb’ requirement for creep testing suggests 3-5 grains per sample minimum dimension to ensure homogeneous behavior. This research shows that to ensure representative wrought creep performance (i.e. no effect of sample size), the sample minimum cross-section should be 10 times the average ASTM grain size. Statistical analysis of the microstructures suggests the population of larger grains as a controlling feature in creep failure.

14 SOLAR ENERGY↗
DOE OSTI2021

High-Throughput Statistical Interrogation of Mechanical Properties with Build Plate Location and Powder Reuse in AlSi10Mg

Abstract Additive manufacturing (AM) allows agile, rapid manufacturing of geometrically complex components that would otherwise be impossible through traditional manufacturing methods. With this maturing manufacturing technology comes the need to adopt testing methods that are commensurate with the speed of additive manufacturing and take advantage of its geometric flexibility. High-throughput tensile testing (HTT) is a technique that allows a large number of tensile bars to be tested in a short amount of time. In the present study, HTT is used to evaluate AM AlSi10Mg produced using powder bed fusion with a Renishaw AM250 machine. Three parameters were varied in this study: (1) powder reuse history, (2) location on the build plate, and (3) size of the tensile specimen. For all parameter combinations, at least 22 specimens were tested; in several cases, over 40 were tested. This large dataset, consisting of over 500 tensile tests, permits Weibull statistical analysis and provides sufficient fidelity to isolate subtle trends that would have likely been missed in smaller, traditional datasets. The observed trends are rationalized in terms of the role of porosity and surface crust on mechanical response.

Carroll, Jay D. (ORCID:0000000258184709)↗
DOE OSTI2023

Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images

Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. Here this approach is time-consuming and restricts the number of images that can be processed. Her in this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A spatial-statistical investigation of surface expressions associated with cyclic steaming in the Midway-Sunset Oil Field, California

In the Midway Sunset Oil Field in Central California, operators inject steam into the shallow diatomite formation to enhance heavy oil recovery through imbibition, wettability alteration, and viscosity reduction, among other mechanisms. The injected steam, however, does not always remain in the reservoir or return through the wells. In two zones in the study area, the steam comes out at the surface, creating sinkholes, seeps, and steam outlets. These phenomena, called “surface expressions,” pose safety and environmental hazards. Even though these surface expressions are a widespread problem in Central California, they are not well documented and understood. Possible causes of the surface expressions include: high injection pressure, structurally controlled flow patterns, leakage of steam through old improperly abandoned wells, high injection volumes, or flow along naturally occurring faults, among other possible factors. This work examines attributes of the zones with surface expressions in order to determine factors that may contribute to their occurrence. Spatial statistical analysis using logistic regression, random forests, and classification trees is used to explore the relationship between the surface expressions and geological and production-related attributes. The results point to a significant spatial correlation between the surface expressions and two predictors: concentration of plugged wells and geologic seal thickness. The results guide follow-up studies to further investigate the role of well abandonment and seal thickness in the occurrence of surface expressions.

02 PETROLEUM↗
DOE OSTI2020

Mapping the kinetic evolution of metastable grain boundaries under non-equilibrium processing

The kinetic evolution of a multiplicity of metastable grain boundaries (GBs) under fast driving conditions are studied by atomistic modeling. Assisted with an enhanced statistical analysis, the energetic evolution of GBs over a broad metastability-temperature space is mapped out, wherein two distinct regimes—an ageing regime and a rejuvenating regime—are retrieved with high fidelity. By comparing the results under various conditions (e.g. random perturbations, isothermal annealing, and fast heating/cooling), it is shown that such ageing/rejuvenating mechanism map is universal, irrespective of the actual stimuli used to elicit the metastable GBs. Here, the ageing/rejuvenating phenomena are demonstrated to stem from the energy imbalance of uphill climbing and downhill dropping during sequential transitions in the system's potential energy landscape. Without the necessity of introducing free parameters, such model can reconcile experimentally measured hardness variation of nanocrystalline metals subjected to femto-second laser irradiation, and it therefore provides a novel perspective on achieving a plurality of interfacial states and facilitating previously inaccessible property regimes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Slip localization behavior at triple junctions in nickel-base superalloys

Incipient slip localization in the vicinity of hundreds of grain boundary triple junctions (TJs) in a lightly deformed nickel-base superalloy IN718 is studied using a combination of three-dimensional (3D) crystal plasticity finite element (CPFE) modeling, high resolution digital image correlation (HR-DIC) and 3D electron back-scatter diffraction tomography (3D EBSD). A 3D reconstruction method enables identification of thousands of TJs and correspondence of any observed slip bands with their originating TJ lines below the specimen surface. Here, we present a large-scale CPFE model of the experimental 3D microstructure composed of high-fidelity representation of the TJ lines and the boundaries and interiors of the parent grains and use it to calculate the local micromechanical response and slip activity of all TJs at the onset of macroscopic yielding. Statistical analysis of the calculated quantities reveal TJs develop larger stress concentration and grain-average re-orientation than grain interiors and grain boundaries, however no substantial differences in cumulative slip were found among these microstructural regions. We find that TJs with observed slip bands generate lower grain-average re-orientation, fewer active slip systems, and more localized slip on a single system than those without. The distinctions in the reorientation and slip activity are stronger in TJs that experience more intense slip.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A statistical approach to analyzing domain dynamics in ferroelectric crystals using X-ray photon correlation spectroscopy

Ferroelectric materials exhibit strong electromechanical coupling, largely influenced by their domain structures. Numerous microstructural studies indicate that smaller domains with higher domain wall density generally enhance domain wall motion, although some inconsistencies have been reported. In this work, we use X-ray photon correlation spectroscopy (XPCS) to probe dynamic response in Pb(Mg 1/3 Nb 2/3 )O 3 -29PbTiO 3 (PMN-29PT) single crystals under applied electric fields. We introduce a two-field correlation approach, adapted from conventional two-time correlation to quantify dynamics. Statistical analysis reveals that both [001]-oriented direct current (DC) and alternating current (AC) poled samples show Poisson-like behavior within specific electric field regions. The DC-poled samples exhibit more frequent domain wall jump events but with smaller amount of decorrelation per jump event, whereas the AC-poled samples show fewer jump events with larger decorrelation per jump event. This observation aligns with the prevalence of 109° domain walls in the AC-poled samples, which contribute to more domain wall motion. These findings provide experimental evidence of collective domain wall motion and establish a direct connection between mesoscale dynamics and electromechanical response.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A statistical and simulation-informed model for estimating permeability from pore size distribution in saturated geomaterials

Accurate permeability estimation is essential across subsurface engineering applications but remains challenging due to the complex pore structures of natural geomaterials. Traditional empirical methods and simplified theoretical models often inadequately capture the role of pore size distribution and connectivity. Here, this study develops a statistical and simulation-informed permeability model that collapses pore-scale complexity into a compact scaling of the form k = αϕμ d 2 , where ϕ is porosity, μ d is mean pore size, and α is a weakly varying coefficient. By combining pore network simulations with statistical analysis of unimodal and bimodal pore size distributions, we identify three key findings: (i) permeability is much more sensitive to mean pore size than to porosity; (ii) across extensive datasets, the ratio σ d /μ d (standard deviation to mean) clusters around a characteristic value ∼0.4, allowing the effects of the full pore size distribution to be represented by μ d and a narrowly varying α ≈ 0.05; and (iii) for bimodal systems, there exists a critical fraction of small pores ∼0.78 above which flow becomes small-pore dominated, enabling the definition of an effective flow-controlling pore population and facilitating simplified permeability estimation for such systems. The resulting model, which requires only porosity and a representative mean pore size as inputs, is validated against comprehensive experimental datasets (>1700 samples) spanning diverse soils and rocks and achieves good predictive accuracy. Overall, this work provides a physically grounded yet practically simple permeability estimator suitable for subsurface engineering, environmental protection, and resource management applications.

Permeability↗
DOE OSTI2020

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Role of underlying surface, rainstorm and antecedent wetness condition on flood responses in small and medium sized watersheds in the Yangtze River Delta region, China

Floods are becoming more frequent and are hard to control due to the shortage of water conservancy projects in small and medium sized basins, especially in developing regions. Understanding the hydrologic responses and estimated flood characteristics to storm events can help to predict flood disasters and form better effective mitigation and adaptation strategies. Here, using observations of several representative watersheds and Artificial Neural Networks (ANN) and Principal Component Regression (PCR) models, we conducted data-driven analyses to examine the flood responding characteristics. We quantified the relative contributions of the influencing factors to the variation of each flood characteristic. Statistical analysis of the observations shows that the drainage area plays a key role in determining the distribution of lag time and peak discharge. Rainstorm variability has direct influence on floods, and typhoon-induced rainstorms with high total rainfall and rainfall intensity generate higher lag time, flood peak, unit discharge and runoff depth, but lower runoff coefficient. The ANN and PCR models accurately predicted the variations of flood features using the driving factors including physical geographical characteristics, rainstorm features, and antecedent condition. Physical geographic characteristics are key influential factors of lag time, flood peak and runoff coefficient, while the rainstorm features control the magnitude of unit discharge and runoff depth. These results indicate that floods are mainly affected by rainstorm features and physical geographic characteristics in the Yangtze River delta, and it might become more damaging with the increasing rainfall extremes and sprawling impervious surfaces in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Molecular dynamics study of carbon dioxide and nitrogen selectivity through poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) membrane

Here, a molecular dynamics simulation model was developed to comprehensively understand carbon dioxide over nitrogen (CO 2 /N 2 ) selectivity through polyphosphazene-based membrane comprising of poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) selective layer at the molecular level. The effects of temperature, pressure, and initial feed gas composition on the CO 2 transport on a polymer membrane were studied. The computed free energy and density profile of the permeating gas mixture exhibited that CO 2 molecules express higher interactions with the membrane than N 2 molecules, resulting in higher CO 2 /N 2 selectivity. Statistical analysis of gas molecules (CO 2 , water (H 2 O), and N 2 ) transportation suggested that hydro- and CO 2 -philic functional groups in the membrane significantly impact CO 2 permeability and CO 2 /N 2 selectivity. This study suggested that Lewis acid–base and hydrogen bonding combinations contribute to CO 2 permeation and CO 2 /N 2 selectivity. An equal CO 2 /N 2 selectivity was observed with and without water vapor in the feed gas suggesting that water does not hinder CO 2 transport through the membrane.

36 MATERIALS SCIENCE↗