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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources: Preprint

This study addresses the compliance of Inverter-based Resources (IBRs) with the IEEE Std 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a comprehensive controller development framework. This framework caters to maintaining ride-trhough operation or implementing strategic disconnections in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller framework is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

IEEE Std 2800↗
DOE OSTI2025

Importance of Sample Handling and Preparation for Surface Analysis: A Summary of ISO Standard 20579 Part 1, Documenting and Reporting the Handling of Specimens Prior to Analysis

Reliable and reproducible analysis of surfaces is critically dependent on how samples have been collected, handled, and prepared before analysis. Although there are important, well-established general guidelines to minimize unintended alteration of the surfaces to be analyzed, specific handling steps depend on the nature of the samples and information desired. Assessments of the validity and reliability of the results require adequate information about sampling, handling, and processing. ISO standard 20579 part 1 describes the information to be recorded and reported for samples that are prepared or submitted for surface analysis. This paper summarizes elements of the standard, which includes annexes that justify and inform the sample handling processes. Also included is a checklist of information that needs to be recorded and reported and an appendix containing an example of a form that might be used to report the information.

AES↗
DOE OSTI2024

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources

This study addresses the compliance of Inverter-based Resources (IBRs) with IEEE Standard 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a controller development framework for abnormal grid conditions. This framework caters to maintaining ride-through operation in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller frame-work is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

IEEE Std 2800↗
DOE OSTI2021

ENERGY STAR Residential Water Heater Specification and Test Method for Connected Residential Water Heaters

Electric water heaters have long been used as a tool for demand response due to their inherent thermal storage and large electric load. Traditionally, electric water heaters have been controlled by external load control switches, but that type of control does not work well with more efficient heat pump water heaters and cannot ensure that consumers have adequate hot water. Water heater manufacturers are adding more sophisticated controls that allow utilities or consumers to control their water heaters in new ways that can provide demand response without impacting consumer comfort. Further, the electric utility grid has seen a rapid increase the availability of renewable energy, which, depending on the type of renewable energy, can provide large amounts of energy for a portion of the day, but reduced or no energy at other times. In response to these advances in controls, availability of periodic renewable energy, and in an effort to have a standard which can be applied at a national level, ENERGY STAR and the Department of Energy have developed a Product Specification and Test Method for Connected Residential Water Heaters. In this session, we will discuss the new specification and test method, as well as show some initial results from running the new test method with two different HPWHs at NREL.

connected water heater↗
DOE OSTI2025

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗
DOE OSTI2022

Metallic support films reduce optical heating in cryogenic correlative light and electron tomography

Super-resolved cryogenic correlative light and electron tomography is an emerging method that provides both the single-molecule sensitivity and specificity of fluorescence imaging, and the molecular scale resolution and detailed cellular context of tomography, all in vitrified cells preserved in their native hydrated state. Technical hurdles that limit these correlative experiments need to be overcome for the full potential of this approach to be realized. Chief among these is sample heating due to optical excitation which leads to devitrification, a phase transition from amorphous to crystalline ice. Here, in this work, we show that much of this heating is due to the material properties of the support film of the electron microscopy grid, specifically the absorptivity and thermal conductivity. We demonstrate through experiment and simulation that the properties of the standard holey carbon electron microscopy grid lead to substantial heating under optical excitation. In order to avoid devitrification, optical excitation intensities must be kept orders of magnitude lower than the intensities commonly employed in room temperature super-resolution experiments. We further show that the use of metallic films, either holey gold grids, or custom made holey silver grids, alleviate much of this heating. For example, the holey silver grids permit 20× the optical intensities used on the standard holey carbon grids. Super-resolution correlative experiments conducted on holey silver grids under these increased optical excitation intensities have a corresponding increase in the rate of single-molecule fluorescence localizations. This results in an increased density of localizations and improved correlative imaging without deleterious effects from sample heating.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

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

A comprehensive study on three typical photoacid generators using photoelectron spectroscopy and ab initio calculations

Conducting a comprehensive molecular-level evaluation of a photoacid generator (PAG) and its subsequent impact on lithography performance can facilitate the rational design of a promising 193 nm photoresist tailored to specific requirements. In this study, we integrated spectroscopy and computational techniques to meticulously investigate the pivotal factors of three prototypical PAG anions, p-toluenesulfonate (pTS - ), 2-(trifluoromethyl)benzene-1-sulfonate (TFMBS - ), and triflate (TF - ), in the lithography process. Our findings reveal a significant redshift in the absorption spectra caused by specific PAG anions, attributed to their involvement in electronic transition processes, thereby enhancing the transparency of the standard PAG cation, triphenylsulfonium (TPS + ), particularly at ~193 nm. Furthermore, the electronic stability of PAG anions can be enhanced by solvent effects with varying degrees of strength. Here we observed the lowest vertical detachment energy of 6.6 eV of pTS - in PGMEA solution based on the polarizable continuum model, which prevents anion loss at 193 nm lithography. In addition, our findings indicate gas-phase proton affinity values of 316.4 kcal/mol for pTS - , 308.1 kcal/mol for TFMBS - , and 303.2 kcal/mol for TF - , which suggest the increasing acidity strength, yet even the weakest acid pTS - is still stronger than strong acid HBr. The photolysis of TPS + -based PAG, TPS + ·pTS - , generated an excited state leading to homolysis bond cleavage with the lowest reaction energy of 83 kcal/mol. Overall, the PAG anion pTS - displayed moderate acidity, possessed the lowest photolysis reaction energy, and demonstrated an appropriate redshift. These properties collectively render it a promising candidate for an effective acid producer.

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

Drying of Spent Nuclear Fuel: Considerations and Examples

A recently revised American Society for Testing and Materials consensus standard guide for drying of spent nuclear fuel (SNF) provides considerations and guidance for preparing SNF for its safe storage in a sealed dry storage system. The standard discusses (1) needs for drying, (2) techniques to dry, and (3) demonstration of adequate dryness. No specific approach is prescribed since the effective techniques and needs for drying depend on the specifics of the fuel and dry storage system. Here, this paper discusses these topics using examples for both Zr-alloy-clad commercial SNF and for aluminum-alloy-clad research reactor SNF. Residual water can include free water (liquid and/or vapor), physisorbed water bound to internal surfaces, and chemisorbed water incorporated into surface films, such as (oxy)hydroxides. The potential impacts of these residual waters are corrosion/oxidation, radiolytic breakdown into gaseous and/or reactive species, and canister pressurization. For commercial SNF, inadvertent free water, even up to large amounts (e.g., 10+ mol), is not predicted to cause adverse corrosion degradation, except possible fuel oxidation for breached SNF. For aluminum-clad SNF, the production of radiolytic hydrogen with contribution from the chemisorbed water in its hydrated oxides is a primary consideration. For both SNF systems, canister pressurization is predicted to be well within the canister design, and flammability would not pose a safety concern using an oxygen limit of 5 vol % criterion. (Flammability control can be achieved by limiting either hydrogen or oxygen, and an oxygen limit is expected to be easier to meet in the presence of radiolytic H 2 generation.) The two primary technologies for SNF drying, vacuum drying and forced-gas dehydration, are described herein, and drying tests and campaigns using these methods are cited. Dryness criteria and the methods used to detect and measure residual (free) water are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Designing monitoring networks for local earthquakes

Abstract Seismic networks are essential for monitoring local earthquakes in connection to industrial activities, including wastewater injection and CO2 sequestration. Because these networks are typically deployed for short periods of time at specific sites, it is beneficial to develop best practices for efficient and effective installation and monitoring. Such standards are available for regional earthquake and microseismic monitoring, but not readily available for local scale (tens of kilometer scale) monitoring. Once the region of interest has been determined, the key parameters for establishing a network are available monitoring station locations, site noise, and site utility. Networks should be designed based on the project monitoring goals for earthquake magnitude and density. Herein, a network was established at the Patterson and Hartland Oil Fields in western Kansas in association with a US Department of Energy CarbonSAFE carbon capture and sequestration research project. We employed observations from an analog local network, the Wellington Earthquake Monitoring Network in south-central Kansas, to assess site noise and estimate earthquake detection thresholds for the Patterson and Hartland fields. Noise from oil production facilities was evaluated, concluding that oil lease sites are suitable for monitoring small local earthquakes (M1-M3). The network was designed to have a magnitude of completeness of M1 while using station locations on existing field operator leases. Fifteen months of continuous network operation demonstrates reliable and efficient local earthquake monitoring and provides best practices recommendations for similar operations.

58 GEOSCIENCES↗
DOE OSTI2021

Geometric deep learning of RNA structure

RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.

Townshend, Raphael J. L.↗
DOE OSTI2020

Quantum Fast Circuit Optimizer (qFactor) v1

Quantum programs are represented as circuits, or sequences of gates. A common problem during quantum compilation to find a circuit that implements a target program. This is an optimizer, it optimizes a circuit's distance to the target by solving for the best fit gates. It is not a standard optimizer, it only optimizes circuits. It is not a compiler or synthesizer, it cannot build circuits, but given a circuit structure, it will solve for the gates. Quantum compilers (qsearch, qfast) use standard numerical optimizers. This has advantages over those general-purpose optimizers since it is domain-specific.

Younis, Ed↗
DOE OSTI2020

Analysis of the sludge batch 9 (Macrobatch 10) DWPF pour stream glass sample

A pour stream (PS) sample taken during processing of Sludge Batch 8 (SB8, Macrobatch 10) was analyzed by Savannah River National Laboratory (SRNL) to verify compliance with the Defense Waste Processing Facility (DWPF) Glass Product Control Program. The following conclusions were drawn from these analyses; The sum of oxides for the SB8 PS glass (97.41 wt%) is within the Product Composition Control System (PCCS) limits (100 ± 5 wt%); The average Waste Dilution Factor (WDF) calculated from the Tank 40 dried sludge analysis results for SB8 is 1.9 ± 0.1. In general, the radionuclide concentration of the SB8 PS glass sample calculated using this WDF is in good agreement with the measured radionuclide content; The Product Consistency Test (PCT) results indicate that the SB8 PS glass meets the Waste Acceptance Product Specifications (WAPS) for durability, with normalized release rates for boron, lithium and sodium all at least two standard deviations lower than those of the Environmental Assessment (EA) glass; The average measured density of the SB8 PS glass is 2.72 g/cm 3 , consistent with previous PS samples; and, The average measured Fe 2+ /ΣFe ratio of the SB8 PS glass is 0.15, within the target range of 0.09- 0.33, and closely resembling the predicted REDOX value of 0.15.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Case Study: Applying the INL Resilience Framework to Iowa Lakes Electric Cooperative Distributed Wind Systems

Traditional metrics and evaluation methods for resiliency are not sufficient to evaluate the effect that distributed wind systems will have, particularly in light of the challenges described above. While the concept of resiliency is not new, its application to the electric grid is neither standardized nor well-defined, and there is little to no guidance on how to evaluate resilience specifically for distributed wind systems. To fill this gap, the Idaho National Laboratory (INL), as part of the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project, has developed a resilience framework for electric energy delivery systems (EEDS). The framework provides detailed steps for evaluating resiliency in the planning, operational, and future stages, and encompasses five core functions of resilience. It allows users to evaluate the resilience of distributed wind, taking into consideration the resilience of the wind systems themselves, as well as the effect they have on the resiliency of any systems they are connected to. In this study, we evaluate the resilience of the distributed wind systems at Iowa Lakes Electric Cooperative to cybersecurity hazards. We show that the wind resource can benefit the overall system resilience during some hazards. We show that the practices in place make the wind subsystems resilient against some cybersecurity hazards but that there are still significant risks associated with other cybersecurity hazards

17 WIND ENERGY↗
DOE OSTI2025

DER Inverter Control Fault Ride Through Model in Accordance with IEEE 1547-2018 Std

Distributed Energy Resources (DER) with smart inverters are becoming more prevalent as the need for renewable energy and grid stability increases. An important challenge arises when considering that inverterbased generation methods contribute less current during faults, rendering traditional overcurrent protection unsatisfactory. DERs have fault ride-through requirements when operating in high or low voltage, outlined by IEEE Std. 1547-2018. Faults cause the voltage to reach abnormal steady state magnitudes, depending on the fault resistance and fault type. There are several high voltage and low voltage ride-through zones defined by IEEE Std. 1547-2018. Each zone’s ride through duration decreases as the applicable voltage measurement, i.e., the phase RMS voltage, deviates from its nominal value. This presentation demonstrates the implementation of IEEE Std. 1547-2018 high and low voltage ridethrough grid support functions using a preexisting RSCAD model, discussing the challenges presented during this process. The implemented controls monitor the filtered phase voltages to have a more accurate reading of the applicable voltages. The controls sense the duration that the applicable voltage remains in a specific zone. The breaker trips and ceases energization to the grid when the duration is exceeded. The standard allows the operator to adjust the ride-through times and voltage zones from the default settings. These ranges are implemented into the runtime, which acts as the operator’s SCADA. The results show the accuracy of the voltage measurements, which remain within the IEEE Std. 1547-2018 for all cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗
DOE OSTI2020

Calculating Average Hot Water Mixes of Residential Plumbing Fittings Using the ANSI 301-2019 Hot Water Draw Model and National Residential Data to Estimate Hot Water Use in Showerheads and Lavatory Faucets

Available studies of hot water use percentages may not necessarily be generalized to a national level given regional differences, varying methodological approaches, and limited sample sizes. While some publicly available usage data, reports, and surveys estimate actual household usage, a lack of water use data specific to end uses make more precise savings calculations difficult. Additionally, most hot water draw models tend to focus on overall household use and may not readily estimate lavatory fixture use. However, reviewing more recent studies and standards enables the U.S. Environmental Protection Agency’s WaterSense program to update its estimates for hot water use and consumers’ corresponding energy and monetary savings to better reflect realworld conditions. This report specifically focuses on improving hot water use and savings estimates of lavatory faucets and showerheads. To estimate the hot water use of lavatory faucets and showerheads, we employed the 2015 Residential Energy Consumption Surveys (RECS) microdata alongside the ANSI 301-2019 Hot Water Draw Model. These estimates account for regional differences in hot water use, including regional cold water inlet temperatures. As a result, the refinements presented in this report are more robust, more recent, and better describe the geographic variation than previous inputs used by the WaterSense program. In addition, the approach described in this paper can be updated over time or tailored to regionally specific needs given available inputs. We conclude that hot water percentages for showers and faucets calculated using publicly available national data are close to the percentages found by regional studies and are consistent with household-level models of water use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection.

59 BASIC BIOLOGICAL SCIENCES↗