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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Utility-Scale Solar, 2023 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2023 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developments in 2022, this report explores trends in deployment, technology, capital and operating costs, capacity factors, the levelized cost of solar energy (LCOE), power purchase agreement (PPA) prices, wholesale market value, and interconnection queue data.

analysis↗
DOE OSTI2022

Utility-Scale Solar, 2022 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2022 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developments in 2021, this report explores trends in deployment, technology, capital and operating costs, capacity factors, the levelized cost of solar energy (LCOE), power purchase agreement (PPA) prices, wholesale market value, and interconnection queue data.

2022↗
DOE OSTI2024

Utility-Scale Solar, 2024 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2024 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developments in 2023, this report explores trends in deployment, technology, capital and operating costs, capacity factors, the levelized cost of solar energy (LCOE), power purchase agreement (PPA) prices, wholesale market value, net value, and interconnection queue data.

analysis↗
DOE OSTI2023

An empirical method for geometric calibration of a photon counting detector-based cone beam CT system

BACKGROUND: Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited areas. OBJECTIVE: This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. METHODS: Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. RESULTS: Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. CONCLUSION: Apart from the computational cost, we concluded that the method was easy to implement and robust.

Instruments & Instrumentation↗
DOE OSTI2024

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the $\mathcal{X}$$^{2}_{dof}$ between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to 0.1 $\mathcal{h}$ –1 Mpc. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

An empirical DNA-based identification of morphologically similar snappers (Lutjanus campechanus, Lutjanus purpureus) using a versatile bioinformatics workflow for the discovery and analysis of informative single-nucleotide polymorphisms

The commercially important speciesLutjanus campechanus(Northern/Gulf red snapper) andLutjanus purpureus(Southern/Caribbean red snapper) are the protagonists of a decade’s long taxonomic debate over their species delimitation, due in part to partial habitat overlap, extensive morphological similarity, and the lack of resolution when applying canonically reliable DNA barcoding approaches. In this study, we leveraged publicly available RAD-Seq data forL. campechanusandL. purpureusto identify species-informative single‐nucleotide polymorphisms (SNPs) at the genome scale that were successful in distinguishing the Northern and Southern red snappers, while also detecting individuals exhibiting introgression. This 4-step empirical approach demonstrates the value of applying novel bioinformatics pipelines to existing genome-scale data to maximize the distillation of informative subsets. Our results facilitate economically relevant species identification in addition to confirming or challenging species identifications for specimens with data in public databases. These findings and their applications will benefit future sustainability strategies and broader research questions surrounding these overfished and evolutionarily entangled snapper species.

Environmental Sciences & Ecology↗
DOE OSTI2024

Empirical Investigation of Properties for Additive Manufactured Aluminum Metal Matrix Composites

Laser additive manufacturing with mixed powders of aluminum alloy and silicon carbide (SiC) or boron carbide (B4C) is investigated in this experiment. With various mixing ratios of SiC/Al to form metal matrix composites (MMC), their mechanical and physical properties are empirically investigated. Parameters such as laser power, scan speed, scan pattern, and hatching space are optimized to obtain the highest density for each mixing ratio of SiC/Al. The mechanical and thermal properties are systematically investigated and compared with and without heat treatment. It shows that 2 wt% of SiC obtained the highest strength and Young’s modulus. Graded composite additive manufacturing (AM) of MMC is also fabricated and characterized. Various types of MMC devices, such as heat sink using graded SiC MMC and grid type three-dimensional (3D) neutron collimators using boron carbide (B4C), were also fabricated to demonstrate their feasibility for applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tuning Shinkarev’s Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ferrari, Nicholas [Louisiana State Univ., Baton Ro↗
DOE OSTI2023

The Symmetry Energy: Current Status of Ab Initio Predictions vs. Empirical Constraints

Infinite nuclear matter is a suitable laboratory to learn about nuclear forces in many-body systems. In particular, modern theoretical predictions of neutron-rich matter are timely because of recent and planned experiments aimed at constraining the equation of state of isospin-asymmetric matter. For these reasons, we have taken a broad look at the equation of state of neutron-rich matter and the closely related symmetry energy, which is the focal point of this article. Its density dependence is of paramount importance for a number of nuclear and astrophysical systems, ranging from neutron skins to the structure of neutron stars. We review and discuss ab initio predictions in relation to recent empirical constraints. We emphasize and demonstrate that free-space nucleon–nucleon data pose stringent constraints on the density dependence of the neutron matter equation of state, which essentially determines the slope of the symmetry energy at saturation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Bias correcting regional scale Earth system model projections: novel approach using empirical mode decomposition

Bias correction is a crucial step in using Earth system model outputs for assessments, as it adjusts systematic errors by comparing the model to observations. However, standard methods – ranging from mean-based linear scaling to distribution-based quantile mapping typically treat bias correction as a single-scale process, overlooking the fact that biases can manifest differently across daily, seasonal, and annual timescales. In this study, we propose a novel, timescale-aware bias-correction approach built on Empirical Mode Decomposition. By decomposing the meteorological signal into multiple oscillatory components and aggregating them to represent distinct timescales, we apply targeted corrections to each component, thereby preserving both short- and long-term structure in the data. Experimental illustrations show that the timescale-aware EMDBC framework matches the performance of conventional quantile-delta mapping (QDM) at the native daily scale and achieves progressively larger bias reductions at bi-weekly, seasonal, and annual scales. As a result, the proposed approach offers a more robust path to accurate and reliable Earth system projections, strengthening their utility for resilience and adaptation planning.

Ganguli, Arkaprabha [Argonne National Laboratory (↗
DOE OSTI2025

Data for "Which plant traits increase soil carbon sequestration? Empirical evidence from a long-term poplar genetic diversity trial"

This archive contains all data and code used by the following publication: Field, J. L., Sloan, B. P., Craig, M. E., Calloway, P., Ottinger, S. L., Mead, T., Abramoff, R. Z., Venegas, M. P., Chhetri, H. B., Haiby, K., Kalluri, U. C., Muchero, W., Schadt, C. W., & Mayes, M. A. (2025). Which plant traits increase soil carbon sequestration? Empirical evidence from a long-term poplar genetic diversity trial (p. 2025.02.17.638464). bioRxiv. https://doi.org/10.1101/2025.02.17.638464 Our analysis combined several soil and root data sets collected by Oak Ridge National Laboratory (ORNL) researchers/collaborators from the Clatskanie Poplar Common Garden in Clatskanie, OR by from 2009-2024. The raw data data files are located */02-data/01-raw/* which we harmonized using the codes in */01-codes/01-harmonize-clatskanie-data-pub.qmd*. The final processed data set used in the paper is found at */02-data/02-processed/clatskanie-c-fit-data.csv* and its columns are described in the table below.

Sloan, Brandon [ORNL] (ORCID:0000000316304271)↗
DOE OSTI2020

EMPIRICAL VALIDATION OF MULTI-ZONE BUILDING AND HVAC SYSTEM MODELS UNDER UNCERTAINTY

This study implemented a framework of empirical validation of building energy models under uncertainty to a set of controlled experiments that aim to validate multi-zone building and HVAC system models. Energy models were created through iterative acquisitions of information and data and uses measurement data from various types of sensors as both inputs and as observations to validate predictions. Experimental and modeling uncertainties were quantified and propagated accordingly, and probabilistic accuracy metrics were used to evaluate the agreement between model predictions and observations under uncertainty. Sensitivity analysis was performed to identify the most influential uncertainties that will be prioritized to be addressed in the next steps. Current results of two cooling tests show an overall good agreement between predictions and observations on a set of HVAC system outputs despite considerable and influential uncertainty in DX cooling coil COP. Agreements on zone-level responses vary notably among individual rooms, likely because of significant uncertainties in room radiation heat gain and system supply air.

Li, Qi↗
DOE OSTI2021

Physics-informed, empirically constrained machine learning for designing Fe-9Cr alloys

<span style="font-family: Calibri, sans-serif; font-size: 12pt;">Materials data analytics can be used to significantly shorten development time of specialized alloys needed for next generation energy applications. Incorporation of the domain knowledge into deep-learning graph structure via fuzzy pre-training and causal process imitation presents a viable approach to developing accurate data-driven models and reliable alloy design tools, with limited datasets. It was demonstrated that the domain knowledge-based empirical constraints not only inhibit overfitting but also allow training more accurate and reliable ML models with improved transparency of the output interpretation. In this study, alloy tensile properties were interpreted with three competing virtual-microstructure models.</span>

Romanov, Vyacheslav↗
DOE OSTI2023

SEMI-EMPIRICAL MODELING OF IRRADIATION-INDUCED DIMENSIONAL CHANGE IN H-451 NUCLEAR GRAPHITE

Nuclear graphite has been used as a moderator material in nuclear reactor designs dating back to the first reactor to reach criticality, Chicago Pile 1, in 1942. In addition, it is anticipated to be used in the conceptual Generation four (GenIV) Molten-salt reactors (MSRs) and the High-temperature gas-cooled reactors (HTRs). The macroscopic dimensional change observed in irradiated nuclear graphite is a property change of significant importance. Largely, volumetric change provides valuable insight into the in-service lifetime of graphite components used in nuclear reactors. The dimensional change behavior varies amongst each grade of nuclear graphite due to processing techniques and the resulting microstructure. In this work, historic data for nuclear graphite H-451 is revisited. A semi-empirical methodology is proposed to describe the dimensional change behavior as a function of temperature for nuclear graphite H-451. The turnaround dose, or when there is a reversal of the dimensional change from contraction to expansion, is proposed to be a thermally activated process and thus can be described by an Arrhenius model. On the atomic scale, H-451 is sp2-bonded carbon atoms with some degree of disorder regardless of orientation. Towards that end, the activation energy is assumed to be a constant irrespective of orientation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Empirical Bounding Analysis and User Recommendations for a Neutron Multiplicity Detector

Neutron multiplicity detectors are useful for a variety of applications including nuclear emergency response, nuclear nonproliferation, safeguards, and criticality safety. When measuring black-box problems (i.e., when the system being measured is completely unknown) with systems that have relatively low detection efficiency, expert analysis is frequently required to determine appropriate bounds for system parameters such as neutron multiplication and neutron leakage. This is because the detection efficiency can vary wildly, which also means that the resulting system parameters can have large variations. This work applies an empirical approach to provide bounds on system parameters (such as system multiplication, neutron leakage, and detector efficiency). The results of this bounding analysis are then used as inputs to provide recommendations to users regarding criticality safety. In addition to describing the method used, this work provides sample results from a measurement campaign performed at the National Criticality Experiments Research Center (NCERC).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems in MCNP6

Current aqueous plutonium processing models for criticality safety often contain significant bias due to material modeling assumptions. These solutions include plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution. Furthermore, there is no current predictive capability for modeling plutonium metal-water mixtures that is approved for use at Los Alamos National Laboratory (LANL). Recent density measurements for aqueous plutonium chloride systems (PuCl 3 -HCl-H 2 O) now allow for the development and application of a more realistic density law. This work develops a Python-based density law for this ternary solution using an empirical method. This code can be used in conjunction with an MCNP6 input to determine the density and composition of a solution based upon user inputs of plutonium concentration, hydrochloric acid concentration, and temperature. The tool allows users to input plutonium and acid content of a solution in terms of molality, molarity, or concentration, and predicts density within the current data range within 1.4% of experimental data. Current preliminary MCNP6 calculations utilizing this tool have demonstrated a minimum decrease in system reactivity of 5% in comparison to the current modeling conventions. Thus, this tool enables more accurate criticality safety operational limits by better crediting chorine content while still maintaining necessary conservatism.

Density Law↗
DOE OSTI2024

Empirical Validation of UBEM: An Assessment of Bias in Urban Building Energy Modeling for Chicago

Residential and commercial buildings currently account for 30% of total global final energy consumption. Urban-scale building energy modeling (UBEM) can enable scalable investments and unlock building improvements by quantifying energy, demand, emissions, and cost reductions of specific measures or packages for building-specific technologies in large geographic regions. While the sophistication of UBEM data sources and technologies have increased dramatically in the past decade, there remains a knowledge gap for empirical validation and sources of bias between building-specific energy models and measured data at varying geographic scales.As UBEM continues to develop, systemic analysis of accuracy, bias, and limitations of the resulting models is necessary to inform best practices and move toward standardization. These are characterized for the Automatic Building Energy Modeling (AutoBEM) software suite with an initial case study involving metered electricity consumption data from 247,188 buildings in Chicago, Illinois, USA - averaged across years 2019-2021 - compared to the following datasets: (1) the AutoBEM-generated nation-scale Model America version 2 (MAv2) data for 596,064 buildings, (2) tax assessor data for 579,829 buildings, (3) tax assessor data filled with MAv2, and (4) 102 representative dynamic archetypes. The accuracy is reported for every building type and vintage combination, along with multiple sources of bias for unique building descriptors. The AutoBEM simulation workflow produced energy consumption estimates that closely match aggregated metered electricity consumption data for different types of buildings constructed during various time periods at the city scale - with initial normalized mean bias error of 10.9%, and 1.1% after removing outliers. Contribution of statistically significant factors including building type, land use, age, and size to variance in UBEM bias is quantified.

Garg, Ankur↗