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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan↗
DOE OSTI2022

Evaluation of crystalline quality of traveling heater method (THM) grown Cd0.9Zn0.1Te0.98Se0.02 crystals

Because of its excellent opto-electronic properties, CdZnTe (CZT) has been the material of choice for x- and gamma-ray detectors operable at room temperature. CZT is the leading commercially available room-temperature radiation detector material today. Although much progress has been made over the past three decades, today's CZT crystals still face certain challenges, especially the presence of the performance-limiting materials defects and the associated relatively high production cost. In this regard, CdxZn1−xTeySe1−y (CZTS) is emerging as a next-generation compound semiconductor, which overcomes some of the limitations of CZT technology for the stated applications. Here, we conducted a study to evaluate the crystalline quality of the traveling heater method grown CZTS with an optimized alloy composition, i.e., Cd0.9Zn0.1Te0.98Se0.02. The as-grown samples were evaluated by low-temperature photoluminescence (PL) spectroscopy and high-resolution x-ray diffraction using the synchrotron light source at Brookhaven National Laboratory. The full width at half maximum of both the PL and x-ray rocking curves was observed to be broadened due to the lattice disorder of the quaternary compound, eventually degrading the crystalline quality. This was consistent with density functional theory calculations.

Roy, U. N. (ORCID:0000000282089680)↗
DOE OSTI2022

New Hybrid Model for Evaluating the Frequency-Dependent Leakage Inductance of a Variable Inductance Transformer (VIT)

Skin and proximity effects can cause a significant drop in the effective leakage inductance of a transformer when the operating frequency is increased. Although the magnetic image method-based double-2-D model can calculate the lowfrequency leakage inductance with sufficient accuracy, it is inherently a frequency-independent model. While Dowell’s 1-D model uses frequency-dependent relations to account for both skin and proximity effects, its accuracy is severely affected by the assumed winding geometry. In this paper, a hybrid model is proposed that uses superposition to combine a modified Dowell’s model with the double-2-D model. The proposed model is investigated on a variable inductance transformer (VIT)—a partially-filled transformer whose leakage inductance can be varied by moving one of the windings mechanically. The frequency-dependent leakage inductances of the VIT evaluated using the hybrid model are in excellent agreement with the corresponding finite element method (FEM) simulated and experimentally measured values, thereby validating the proposed hybrid model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Evaluating Methods for Measuring Grid Frequency in Low-Inertia Power Systems: Preprint

Accurate measurement of grid frequency is a critical component of reliable grid control. Traditionally, methods such as phase locked loops (PLLs) and discrete Fourier transforms (DFTs) have been used in inverters and phasor measurement units (PMUs) to measure frequency. However, as the percentage of inverter-based resources (IBRs) such as solar and wind has increased, these conventional frequency measurement methods are proving unable to guarantee reliable control in some cases. One challenge is measuring frequency during transient events, where there is a disruption in the steady state sinusoidal voltage. During these events, the underlying frequency of the grid may barely change, but measurement methods report a large spike in frequency due to the disrupted waveform. New methods must balance between suppressing spikes in frequency during faults, and providing fast, accurate, measurements in all other grid operation conditions, especially during events with high rate-of-change-of frequency (ROCOF), which are more prevalent in high-IBR power systems. This paper first surveys frequency measurement methods that have been proposed to reduce measurement errors during transient events. Then, both conventional and more novel frequency measurement methods are tested against an IEEE standard and industry recommendations, and their performance is evaluated for events simulated in PSCAD. Results quantify the trade-offs in performance during different grid conditions and lead to suggestions for the most appropriate frequency and ROCOF measurement methods for low inertia grids.

frequency↗
DOE OSTI2024

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle↗
DOE OSTI2022

Evaluation of Horizon of Viability Optimization Engine for Sustained Power to Critical Infrastructure: Preprint

In the aftermath of increasingly frequent catastrophic events, a typical scenario is Critical Infrastructure (CI) units being supported by available backup sources with a weak power grid that can be intermittent or absent. Such a scenario is significantly challenging in the sense of reliable supply of power to CI units. In this article, an intelligent optimization scheme termed as Horizon of Viability (HoV) engine is developed to guarantee the viability of a sustained reliable supply of power to the CI units over a time-horizon. The proposed HoV engine generates a cost-optimal portfolio of the locally available generation sources and the loads over a time horizon using a mixed-integer convex programming problem. A Controller hardware-in-the-loop (CHIL) platform is developed to evaluate the control performance of the HoV engine. The experimental results corroborates the efficacy in maintaining the viability of the CI units after a grid interruption event. Further, the proposed HoV optimization scheme performs better compared to existing net-load management schemes in the literature.

disaster resiliency↗
DOE OSTI2020

Performance Evaluation of Data-Enhanced Hierarchical Control for Grid Operations

This paper presents a hardware-in-the-loop (HIL) simulation to evaluate the performance of voltage regulation of Data-Enhanced Hierarchical Control (DEHC). This DEHC uses an advanced distribution management system (ADMS) for grid operations to control legacy and grid-edge devices and coordinate with distributed energy management systems (DERMS) to manage high penetrations of photovoltaics (PV) on a utility distribution system. The HIL platform provides realistic laboratory testing, including accurate modeling (legacy devices, grid-edge devices, and PV) of the real-world distribution system from a utility partner, a real controller (ADMS), software controller DERMS, hardware grid-edge devices, and standard communications protocols. The test results demonstrate functionalities of the integrated platform and the performance of voltage regulation of the coordinated control systems. Based on laboratory testing, the utility can set up the same grid-automation system to manage DERs, legacy devices, and grid-edge devices to achieve their system-level control and operation objectives (e.g., voltage regulation), thus de-risking potential issues such as instability for field deployment.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗
DOE OSTI2018

Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds

We use the long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three Tropical Western Pacific (TWP) sites as a tropical testbed to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. We conducted a series of CAM5 simulations at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in the frequency of ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, feedback on clouds. Both the CAM5 model and ARM observations show distinct diurnal cycles in total, stratiform and convective cloud fractions; however, they are out-of-phase by 12 hours and the biases vary by site. Our results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. We also found that the modelled gridmean surface longwave fluxes are systematically larger than site measurements when the grid that the ARM sites reside in is partially covered by ocean. The modeled longwave fluxes at such sites also lack a discernable diurnal cycle because the ocean part of the grid is warmer and less sensitive to radiative heating/cooling compared to land. Higher spatial resolution is more helpful is this regard. Our testbed approach can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional model simulations at high spatial resolutions.

Wang, Hailong↗
DOE OSTI2026

Data for Multisite Field Evaluation of Oil Accumulation and Agronomic Performance in Grain and Sweet Sorghums Engineered for Lipid Hyperaccumulation

Oil sorghum (OS) has been developed by engineering grain (TX430) and sweet (Ramada) genetic backgrounds to accumulate triacylglycerols (TAG) in vegetative tissues as an energy-dense feedstock for sustainable aviation fuel (SAF) and other biofuels. This study evaluated two TX430 OS lines (TxHO-2, TxHO-3) and two Ramada OS lines (RmHO-1, RmHO-2) alongside wild-type (WT) lines in NE and IL over 2 years (2023–2024) to quantify genotype × environment effects on agronomic performance and TAG accumulation. Across four environments, TX430 OS lines showed average TAG concentrations of 15.0 g kg−1 in leaves and 12.8 g kg−1 in stems, approximately 19-fold higher than WT. Ramada OS lines accumulated 26.1 g kg−1 in leaves and 12.3 g kg−1 in stems, approximately 25-fold and 13-fold increases over WT, respectively. OS lines in TX430 exhibited an 18% reduction in biomass (8.4 vs. 9.9 Mg ha−1 for WT), while Ramada OS lines had similar WT biomass (18.3 vs. 19.9 Mg ha−1 for WT). Among TX430 OS lines, TxHO-2 achieved the highest TAG yield (190 kg ha−1), while RmHO-1 led the Ramada lines (335 kg ha−1) due to higher biomass and similar TAG concentration. Enhanced TAG accumulation increased N, P, and K removal in TX430 lines but not in Ramada lines. Structural carbohydrate and ash concentration were unaffected. Overall, results confirm vegetative lipid accumulation as a viable strategy for high-biomass sorghum, supporting its potential as a dual-purpose feedstock for SAF. Future work should focus on minimizing biomass yield penalties and improving nutrient use efficiency in oil sorghum systems.

Agronomy↗
DOE OSTI2026

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗
DOE OSTI2026

Evaluation of accuracy and resolution of the electron beam profile scanner at the Fermilab Main Injector

The objective of this work is to assess the accuracy of measurements made by the Electron Beam Profile Scanner (EBPS), which captures the trajectory of an electron beam with and without a proton beam present. The proton beam induces deflection in the electron beam, which is influenced by proton charges.For high-resolution images, the probe beam needs to be of high intensity, small diameter, and small divergence, evaluated using a YAG screen and an optical transition radiation (OTR) screen. Additionally, the point spread function (PSF) will be calculated to characterize the optical system's properties using ZEMAX software. The capabilities of the Hamamatsu Charge-Injection Device (CID) camera and Kimball Physics electron gun (e-gun) will be considered for accuracy.

Mwaniki, Matilda [IIT, Chicago; Fermilab]↗
DOE OSTI2025

Evaluate data lake design for the accelerator control system

Increasing precision in automation for modern particle accelerators not only creates a requirement to gather data from all devices but also demands scalable and high-performance data infrastructure with the capability of handling vast incoming device data. A well architected data lake is suitable for such a system which integrates real-time data acquisition, transient data caching, and long-term storage. This paper evaluates data lake architecture for an Accelerator Control System (ACS), focusing on two critical components of a data lake, data cache and long-term storage.

Jaikar, Amol [Fermilab]↗
DOE OSTI2022

Evaluating the Impact of Residential Solar Contract Cancellations in the United States

The residential solar photovoltaic (PV) market in the United States is growing, despite frequent customer cancellations. Contract cancellations result in lost time and costs that must be borne by installers, often in the form of higher "soft costs" (i.e., non-equipment costs). These costs are often passed on to customers who successfully install PV systems. To date, few studies have attempted to estimate national cancellation rates or model the impacts on installed system costs. In this report, we utilize an installer-provided dataset of 199,665 residential PV-only projects representing about 10% of U.S. installs each year from 2017-2019. With this data, we evaluate cancellation rates and trends from contract signing to install. Next, by leveraging NREL's soft cost model for residential solar, we estimate installer spending through each phase of the pre-install process. Applying our findings on cancellation timelines and rates, we then estimate the potential cost impacts to successful installs from contract cancellations. Our work suggests that the rates and impacts of contract cancellations have been previously underestimated. Namely, we find that cancellations/unsuccessful project are; more common than previous estimates suggest; occur earlier in project timelines, though a significant number happen even after permit/ATB approvals; and contribute significantly to customer acquisition and other soft costs. We also find that cancellation do not appear to be driven by review delays in permitting and interconnection applications.

14 SOLAR ENERGY↗
DOE OSTI2022

Update on 17 O evaluation and fast neutron evaluation for 181 Ta [Slides]

Reliable fast-neutron evaluation can be entirely encapsulated in the reaction model and related input. Ta181 is a particularly relevant case due to extraordinary coverage of various observables by differential experiments that offer much help and relatively little headache. Differences from the similar ENDF/B-VIII evaluation are as follows: more advanced modeling (CC OMP, MSD, MSC, decay schemes), more careful selection of models and parameters, new experimental data, and isomers. Overall, there is improved agreement with differential data and hints of better performance in integral testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

An Evaluation of Energy Storage Cost and Performance Characteristics

The energy storage industry continues to expand globally as costs continue to fall and opportunities in consumer, transportation and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS) - lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium metal halide batteries, and zinc-hybrid cathode batteries - four non-BESS storage technologies - pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors - and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

Mongird, Kendall↗