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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids: Preprint

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. Different types of DERs such as Photovoltaics (PV), energy storage, electric vehicles (EVs), etc. have varying effects on the grid based on how and where they are deployed. Again, the DER deployment and its impact are network-dependent, while the traditional electric grids were not designed to host DERs. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper investigates the impacts of integrating a mix of DERs in the utility distribution network in Colorado, U.S. Firstly, BTM DERs at the residential scale including distributed PV; battery energy storage systems (BESS); heating, ventilation, and air-conditioning (HVAC) load; electric water heater (EWH) load; and EVs are modeled. The impacts of integrating these resources on the distribution network are evaluated by conducting time-series simulations for different scenarios considering different days to capture the worst-case conditions. Monte Carlo simulations are conducted to generate the realistic EV charging profile. The voltage issues, substation transformer loadings, and critical nodes in the network are identified with the incorporation of uncoordinated EV charging loads and other DER in the network. This analysis helps visualize the DER impact on the grid, identify the challenges, and provides an insight into the new distribution management and control needs to enable reliable and resilient distribution grid operations. Additionally, further analysis is performed to estimate the daily residential electricity cost with the inclusion of DERs under time-of-use tariffs. The result shows the daily residential electricity cost reduced by 20:7% on average with DERs compared to the case without DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2024

Achieving an 80% Renewable Portfolio in Alaska's Railbelt: Cost Analysis

This study examines the system-level costs and benefits of increased renewable energy deployment in the Railbelt grid, in the context of a proposed 80% renewable portfolio standard (RPS). This work studies the period from 2024 to 2040 and uses a model that simulates the planning, evolution, and operation of the power system to identify the mix of resources that maintains system reliability at the lowest electricity system cost over the period of analysis. The model tracks several reliability metrics, including the ability to serve demand during all hours of the year, even when normal power system failures occur. The model includes several measures (and associated costs) to address the variable output of renewable resources, including additional operating reserves, fuel storage, cycling of fossil plants, and additional equipment needed to maintain system stability. The Reference (least-cost) scenario results in substantial deployment of renewable energy and cost savings, reaching about 76% of Railbelt generation derived from renewables in 2040. Annual savings average about $105 M/year from 2030 to 2040. About 50% of this generation is from wind by 2040. Enforcing an 80% RPS results in about a 2% cumulative reduction in net savings. Demand is met in all scenarios, relying heavily on use of existing hydropower and fossil-fueled generators during periods of low renewable output. Meeting the increase in variability will require substantial changes in how the system is operated, with inverter-based resources providing nearly 100% of electricity during some periods.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Fundamentals of a modified model of the distribution of neutron-resonance widths and results of its application in the mass-number range of 35 {<=} A {<=} 249

A modified model is developed for describing the distribution of random resonance width for any nuclei. The model assumes the coexistence in a nucleus of one or several partial radiative and neutron amplitudes for respective resonance widths, these amplitudes differing in their parameters. Also, it is assumed that amplitude can be described by a Gaussian curve characterized by a nonzero mean value and a variance not equal to unity and that their most probable values can be obtained with the highest reliability from approximations of cumulative sums of respective widths. An analysis of data for 157 sets of neutron widths for 0 {<=} l {<=} 3 and for 56 sets of total radiative widths has been performed to date. The basic result of this analysis is the following: both for neutron and for total radiative widths, the experimental set of resonance width can be represented with a rather high probability in the form of a superposition of k {<=} 4 types differing in mean amplitude parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Weak data do not make a free lunch, only a cheap meal

Refinement and analysis of four structures with various data resolution cutoffs suggests that at present there are no reliable criteria for judging the diffraction data resolution limit and the condition I/σ(I) = 2.0 is reasonable. However, extending the limit by about 0.2 Å beyond the resolution defined by this threshold does not deteriorate the quality of refined structures and in some cases may be beneficial. Four data sets were processed at resolutions significantly exceeding the criteria traditionally used for estimating the diffraction data resolution limit. The analysis of these data and the corresponding model-quality indicators suggests that the criteria of resolution limits widely adopted in the past may be somewhat conservative. Various parameters, such as R{sub merge} and I/σ(I), optical resolution and the correlation coefficients CC{sub 1/2} and CC*, can be used for judging the internal data quality, whereas the reliability factors R and R{sub free} as well as the maximum-likelihood target values and real-space map correlation coefficients can be used to estimate the agreement between the data and the refined model. However, none of these criteria provide a reliable estimate of the data resolution cutoff limit. The analysis suggests that extension of the maximum resolution by about 0.2 Å beyond the currently adopted limit where the I/σ(I) value drops to 2.0 does not degrade the quality of the refined structural models, but may sometimes be advantageous. Such an extension may be particularly beneficial for significantly anisotropic diffraction. Extension of the maximum resolution at the stage of data collection and structure refinement is cheap in terms of the required effort and is definitely more advisable than accepting a too conservative resolution cutoff, which is unfortunately quite frequent among the crystal structures deposited in the Protein Data Bank.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures

In material science microfocus X-ray computed tomography (micro-CT) is one of the most popular non-destructive techniques to visualise and quantify the internal structure of materials in 3D. Despite constant system improvements, state-of-the-art micro-CT images can still hold several artefacts typical for X-ray CT imaging that hinder further image-based processing, structural and quantitative analysis. For example spatial resolution is crucial for an appropriate characterisation as the voxel size essentially influences the partial volume effect. However, defining the adequate image resolution is not a trivial aspect and understanding the correlation between scan parameters like voxel size and the structural properties is crucial for comprehensive material characterisation using micro-CT. Therefore, the objective of this study was to evaluate the influence of the spatial image resolution on the micro-CT based morphological analysis of three-dimensional (3D) open porous structures with a high surface complexity. In particular the correlation between the local surface properties and the accuracy of the micro-CT-based macro-morphology of 3D open porous Ti6Al4V structures produced by selective laser melting (SLM) was targeted and revealed for rough surfaces a strong dependence of the resulting structure characteristics on the scan resolution. Reducing the surface complexity by chemical etching decreased the sensitivity of the overall morphological analysis to the spatial image resolution and increased the detection limit. This study showed that scan settings and image processing parameters need to be customized to the material properties, morphological parameters under investigation and the desired final characteristics (in relation to the intended functional use). Customization of the scan resolution can increase the reliability of the micro-CT based analysis and at the same time reduce its operating costs. - Highlights: • We examine influence of the image resolution on μCT-based morphological analysis. • Surface properties influence accuracy of μCT-based morphology of porous structures. • Total porosity was the least sensitive to surface complexity and scan voxel size. • The beam thickness analysis was overestimated by the surface roughness. • Voxel size customization can significantly reduce a cost of the μCT-based analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Eucalyptus – An Analysis Suite for Fault Trees with Uncertainty Quantification

Eucalyptus is a novel code developed at Lawrence Livermore National Laboratory to incorporate uncertainty quantification into Fault Tree Analysis (FTA). This tool addresses the challenge of imperfect knowledge in “grey-box” systems by allowing analysts to incorporate and propagate uncertainty from component-level assessments to system-level effects. Eucalyptus facilitates a consistent evaluation of the impact of subject matter expert judgment and knowledge gaps on overall system response by Monte Carlo generation of possible system fault trees, sampling probabilities of the existence of subsystems and components. Here, the code supports the specification of fault trees through text and allows export to various formats, including auto-generated images, easing analysis and reducing errors. It has undergone extensive verification testing, demonstrating its reliability and readiness for deployment, and leverages on-node parallelism for rapid analysis. Example analyses are shown that include the identification of system failure paths and quantification of the value of further information about system components.

Fault Tree Analysis↗
DOE OSTI2025

Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

comparison↗
DOE OSTI2019

Anomaly detection in scientific data using joint statistical moments

We propose an anomaly detection method for multi-variate scientific data based on analysis of high-order joint moments. Using kurtosis as a reliable measure of outliers, we suggest that principal kurtosis vectors, by analogy to principal component analysis (PCA) vectors, signify the principal directions along which outliers appear. The inception of an anomaly, then, manifests as a change in the principal values and vectors of kurtosis. Obtaining the principal kurtosis vectors requires decomposing a fourth order joint cumulant tensor for which we use a simple, computationally less expensive approach that involves performing a singular value decomposition (SVD) over the matricized tensor. We demonstrate the efficacy of this approach on synthetic data, and develop an algorithm to identify the occurrence of a spatial and/or temporal anomalous event in scientific phenomena. The algorithm decomposes the data into several spatial sub-domains and time steps to identify regions with such events. Feature moment metrics, based on the alignments of the principal kurtosis vectors, are computed at each sub-domain and time step for all features to quantify their relative importance towards the overall kurtosis in the data. Accordingly, spatial and temporal anomaly metrics for each sub-domain are proposed using the Hellinger distance of the feature moment metric distribution from a suitable nominal distribution. Finally, we apply the algorithm to two turbulent auto-ignition combustion cases and demonstrate that the anomaly metrics reliably capture the occurrence of auto-ignition in relevant spatial sub-domains at the right time steps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Absolute intensity calibration for carbon-edge soft X-ray scattering

Resonant soft X-ray scattering (RSOXS) has become a premier probe to study complex three-dimensional nanostructures in soft matter through combining the robust structural characterization of small-angle scattering with the chemical sensitivity of spectroscopy. This technique borrows many of its analysis methods from alternative small-angle scattering measurements that utilize contrast variation, but thus far RSOXS has been unable to reliably achieve an absolute scattering intensity required for quantitative analysis of domain compositions, volume fraction, or interfacial structure. Here, a novel technique to calibrate RSOXS to an absolute intensity at the carbon absorption edge is introduced. It is shown that the X-ray fluorescence from a thin polymer film can be utilized as an angle-independent scattering standard. Verification of absolute intensity is then accomplished through measuring the Flory–Huggins interaction parameter in a phase-mixed polymer melt. As a result, the necessary steps for users to reproduce this intensity calibration in their own experiments to improve the scientific output from RSOXS measurements are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗
DOE OSTI2014

The Development of a Demonstration Passive System Reliability Assessment

In this paper, the details of the development of a demonstration problem to assess the reliability of a passive safety system are presented. An advanced small modular reactor (advSMR) design, which is a pool-type sodium fast reactor (SFR) coupled with a passive reactor cavity cooling system (RCCS) is described. The RELAP5-3D models of the advSMR and RCCS that will be used to simulate a long-term station blackout (SBO) accident scenario are presented. Proposed benchmarking techniques for both the reactor and the RCCS are discussed, which includes utilization of experimental results from the Natural convection Shutdown heat removal Test Facility (NSTF) at the Argonne National Laboratory. Details of how mechanistic methods, specifically the Reliability Method for Passive Systems (RMPS) approach, will be utilized to determine passive system reliability are presented. The results of this mechanistic analysis will ultimately be compared to results from dynamic methods in future work. This work is part of an ongoing project at Argonne to demonstrate methodologies for assessing passive system reliability.

Bucknor, Matthew↗
DOE OSTI2013

In-depth quantitative analysis of the microstructures produced by Surface Mechanical Attrition Treatment (SMAT)

Electron BackScattered Diffraction (EBSD) maps are used to characterize quantitatively the graded microstructure formed by Surface Mechanical Attrition Treatment (SMAT) and applied here to the 316L stainless steel. In particular, the analysis of GNDs – coupled with relevant and reliable criteria – was used to depict the thickness of each zone identified in the SMAT-affected layers: (i) the “ultrafine grain” (UFG) zone present at the extreme top surface, (ii), the “transition zone” where grains were fragmented under the heavy plastic deformation and, finally, (iii) the “deformed zone” where initial grains are simply deformed. The interest of this procedure is illustrated through the comparative analysis of the effect of some SMAT processing parameters (amplitude of vibration and treatment duration). The UFG and transition zones are more significantly modified than the overall affected thickness under our tested conditions. - Highlights: • EBSD maps are used to characterize quantitatively the microstructure of SMAT treated samples. • Calculation of the GND density to quantify strain gradients • A new method to depict the different zone thicknesses in the SMAT affected layer • Effects of SMAT processing parameters on the surface microstructure evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Prospects for Pumped Storage Hydropower in Alaska

Key Takeaways: The resource mapping analysis confirmed that numerous locations in Alaska are suitable for the development of pumped storage hydropower (PSH) projects, both larger grid scale projects and smaller projects that could be suitable for remote communities; The resource assessment for larger, grid-scale projects showed the potential for more than 1,800 closed-loop systems in Alaska, with a total energy storage capacity of about 4 terawatt hours (TWh); Because of their small reservoir sizes and dam heights, many locations were identified as potentially suitable for small-scale PSH systems. Nearly 50% of the identified potentially suitable small-scale PSH sites are in Southeast Alaska; PSH candidate sites were part of the optimal capacity expansion solution in all scenarios analyzed for the Railbelt system. Depending on the scenario, the new PSH capacity that the model selected for the analysis period until 2046 ranged from 300 MW to 600 MW. The locations and timing of new PSH investments vary in different scenarios; Lithium-ion batteries were also selected a source of new generating capacity in all analyzed scenarios for the Railbelt system, indicating that the system will need a mix of short- and long-duration energy storage to support variable renewable energy sources and provide system reliability in the future; For rural communities, analysis results showed that PSH suitability is very site-specific; in addition to diesel fuel costs and PSH capital costs, suitability depends heavily on available renewable resources and existing infrastructure (e.g., reservoirs, transmission access and construction road access); The analysis for rural communities also showed that PSH projects with 10-hour energy storage are likely to be more economical for remote community applications in Alaska than those with larger reservoirs that could provide 10 days of energy storage; Lithium-ion batteries seem to be an economically more viable energy storage option for small, remote communities in Alaska.

13 HYDRO ENERGY↗
DOE OSTI2015

Investigation of electrochemical migration on Sn-0.7Cu-0.3Ag-0.03P-0.005Ni solder alloy in HNO{sub 3} solution

Current issue in lead-free solder in term of its reliability is still under investigation. This high impact research attempts to investigate the electrochemical migration (ECM) on Sn-0.7Cu-0.3Ag-0.03P-0.005Ni solder alloy by Water Drop Test (WDT) in different concentration of HNO{sub 3} solution. The concentration of HNO{sub 3} solution used in this research was 0.05, 0.10, 0.50 and 1M. Optical Microscope (OM), Field Emission Scanning Electron Microscope (FESEM) and Energy Dispersive X-Ray Analysis (EDX) were carried out in order to analysis the ECM behavior based on the growth of dendrite formation after WDT. In general, the results demonstrated that dendrite growth is faster in higher concentration compared with low concentration of HNO{sub 3}. The concentration of HNO{sub 3} solution used has a strong correlation with Mean-Time-To-Failure (MTTF). As the concentration of HNO{sub 3} increases, the MTTF value decreases. Based on the MTTF results the solder alloy in 1M HNO{sub 3} solution is most susceptible to ECM. SnO{sub 2} forms as a corrosion by-product in the samples proved by EDX analysis. The solder alloy poses a high reliability risk in microelectronic devices during operation in 1M HNO{sub 3} solution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world applicability remains uncertain due to discrepancies between simulated and actual machining environments. The primary goal of this study is to bridge the gap between simulation-based machine learning models and real-world applications by developing and validating a Random Forest-based chatter detection system. This research focuses on improving manufacturing efficiency through reliable chatter detection by integrating Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL). The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. The model is validated against 1600 real-world machining datasets, achieving an accuracy of 86.1%, with strong precision and recall scores. The results demonstrate the model’s robustness and potential for practical implementation in industrial settings, highlighting challenges such as sensor noise and variability in machining conditions. This work advances the use of predictive analytics in machining processes, offering a data-driven solution to improve manufacturing efficiency through more reliable chatter detection.

42 ENGINEERING↗
DOE OSTI2018

Modeling Imperfect Generator Behavior in Power System Operation Models

A key component in power system operations is the use of computer models to quickly study and analyze different operating conditions and futures in an efficient manner. The output of these models are sensitive to the data used in them as well as the assumptions made during their execution. One typical assumption is that generators and load assets perfectly follow operator control signals. While this is a valid simulation assumption, generators may not always accurately follow control signals. This imperfect response of generators could impact cost and reliability metrics. This paper proposes a generator model that capture this imperfect behavior and examines its impact on production costs and reliability metrics using a steady-state power system operations model. Preliminary analysis shows that while costs remain relatively unchanged, there could be significant impacts on reliability metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗