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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The state of the art for neutron irradiation experiments from the perspective of the High Flux Isotope Reactor (HFIR)

Irradiation experiment campaigns are critical to advancing nuclear energy technologies by providing data on material performance under relevant radiation conditions. Successful irradiation experiments require integrated design efforts that balance technical goals with facility constraints. Here, this paper presents an expert-informed overview of irradiation experiment design at the High Flux Isotope Reactor. It addresses the nuclear materials research and irradiation experiment communities to guide them toward developing technically sound, facility-compatible campaigns. The High Flux Isotope Reactor is a multipurpose reactor supporting isotope production, neutron scattering, and materials testing. Its high, steady-state neutron flux is ideal for irradiation experiments, but successful execution demands coordinated thermal, structural, and reactor physics analyses. The paper outlines the complete development workflow from concept definition and design optimization to safety qualification and post-irradiation examination. Standardized capsule platforms are also discussed in terms of flexibility, specimen capacity, and thermal performance. Common failure modes such as unanticipated geometric variations, can impact temperature-dose profiles and compromise data reliability. Therefore, detailed thermal modeling and accurate as-built characterization are essential for meaningful post-irradiation data interpretation. Key recommendations include early engagement all stakeholders, clearly defined design expectations, and alignment of specimen geometries with post-irradiation examination capabilities. This approach reduces design iterations, enhances data quality, and supports more efficient use of irradiation resources. Strategic and well-planned irradiation testing not only improves individual campaign success but also accelerates the deployment of advanced nuclear technologies. By closing critical data gaps and reducing development risks, the nuclear materials community can more effectively contribute to the future of clean, resilient energy systems.

Experiments↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2021

Design and implementation of the AMIGA embedded system for data acquisition

The Auger Muon Infill Ground Array (AMIGA) is part of the AugerPrime upgrade of the Pierre Auger Observatory. It consists of particle counters buried 2.3 m underground next to the water-Cherenkov stations that form the 23.5 km 2 large infilled array. The reduced distance between detectors in this denser area allows the lowering of the energy threshold for primary cosmic ray reconstruction down to about 1017 eV. At the depth of 2.3 m the electromagnetic component of cosmic ray showers is almost entirely absorbed so that the buried scintillators provide an independent and direct measurement of the air showers muon content. This work describes the design and implementation of the AMIGA embedded system, which provides centralized control, data acquisition and environment monitoring to its detectors. The presented system was firstly tested in the engineering array phase ended in 2017, and lately selected as the final design to be installed in all new detectors of the production phase. The system was proven to be robust and reliable and has worked in a stable manner since its first deployment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Influence of Diffuse and Ground-Reflected Irradiance on the Spectral Modeling of Solar Reference Cells

Thermal Energy Storage (TES) is a key component for solar thermal applications to bridge the gap between the demand for thermal energy and the supply of solar energy, whose availability depends on the time of day and season. Thus, cost-effective packed-bed thermal containers filled with a solid storage medium have been proposed for high-temperature sensible heat storage as materials are abundant and relatively cheap. Thus, it is necessary to investigate their performance and temperature profiles during the charge-discharge cycle. Several models are available for this purpose. Typically, the more detailed a model, the greater the computational effort required to solve it, and hence a time-efficient model is needed to prevent excessively long computation times for long-term analysis. At the more basic level, the common Hughes E-NTU model and the less realistic simplified Infinite-NTU model are very important for their less time and computational effort. In this paper, the appropriateness of employing the Infinite-NTU model was evaluated to investigate the performance of a typical and scalable rock-bed TES as a case study. The results presented provide a methodology to quickly test the validity of the model and predict the temperature profile for the case under study. Accordingly, such simple charge-discharge cycle thermal performance predictions are important to plan, design, and rapidly deploy a reliable and economical solar thermal system for the supply of valuable heat to high-temperature demanding applications of power generation and industrial processes as part of a rapid shift towards non-polluting renewable energy. Keywords: Solar Thermal, TES, Packed-bed, NTU model, Temperature profile

PV modeling↗
DOE OSTI2020

An Analytical Model of Erosive Wear of BioMass Comminution Components

An analytical erosion model that relates critical process parameters (speed and impingement angle) to critical material attributes of inorganic mineral species in feedstock (density, size, aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear in pretreatment milling operations. Results of the model were compared to experimental measurements of wear produced using the Accelerated Wear Test (AWT) rig at Idaho National Laboratory (INL). Results showed that there is good agreement between predicted and measured performance, and that a quality-by-design (QbD) tool can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

09 BIOMASS FUELS↗
DOE OSTI2025

ICALEPCS 2025: Managing Technical Debt Across Large-Scale Control Systems

This presentation provides an overview of technical debt in the context of control systems for large-scale physics facilities. We explore various forms, common causes, and potential consequences on system reliability, maintainability, and extensibility. Drawing on experiences from multiple projects, including the ACORN control system modernization at Fermilab, we present a range of strategies for proactively managing technical debt, including best practices in design, development, testing, and documentation, as well as reactive approaches for identifying and mitigating existing issues.

Watts, Adam [Fermilab]↗
DOE OSTI2025

American WAKE Experiment (AWAKEN) Field Campaign Report

The American WAKE experimeNt (AWAKEN) was a large-scale, international collaborative field campaign funded primarily by the U.S. Department of Energy (DOE) Wind Energy Technologies Office. Its main purpose was to gather detailed observations of wind farm-atmosphere interactions to improve understanding of wind farm physics, validate and improve simulation tools, lower uncertainties in wind farm modeling, understand environmental impacts, and ultimately reduce the cost and increase the reliability of wind energy systems. The campaign specifically focused on seven testable hypotheses that include characterizing wind turbine and wind farm wake effects, wind farm blockage, turbulent mixing, structural loading impacts, local environmental impacts, and testing wind farm control technologies. AWAKEN was a highly collaborative effort involving numerous agencies, including: DOE, through the Wind Energy Technologies Office and the Office of Science Atmospheric Radiation Measurement (ARM) User Facility, the U.S. Department of Commerce through the National Oceanic and Atmospheric Administration, many American universities, and internationally funded collaborators from Germany and Brazil.

17 WIND ENERGY↗
DOE OSTI2026

Thermal Studies of CMS High-Granularity Calorimeter (HGCAL) Cassettes for the HL-LHC Upgrade

The CMS High Granularity Calorimeter (HGCAL) is a key endcap upgrade for the High-Luminosity LHC, designed to operate in an environment of extreme radiation and high particle rates. Each HGCAL cassette integrates silicon and scintillator modules, front-end ASICs, and a copper cooling plate that provides both mechanical integrity and thermal coupling using two-phase CO₂ cooling. Stable and uniform temperature control is essential to ensure reliable performance of the front-end electronics and to limit radiation-induced leakage currents in the silicon sensors. We present results from thermal characterization studies of pre-series HGCAL cassettes assembled and tested at Fermilab. Embedded RTD/PT1000 temperature sensors were used to measure gradients across copper cooling plates, module layers, and cassette edges under powering conditions representative of operation. The measured thermal behavior demonstrates effective heat transport through the cassette stack and highlights small but systematic variations correlated with geometry and assembly tolerances. These results validate the cooling performance of HGCAL cassettes.

Wang, Jinglu [Northwestern U.]↗
DOE OSTI2023

A Hot‐Swappable, Fault‐Tolerant, Modular Power Converter System for Solar Photovoltaic Plants

The performance metrics of the state-of-the-art commercial solar inverters, such as system cost, operation and maintenance (O&M) cost, service life, reliability, maintainability, and power density are much lower than the target metrics needed to achieve SunShot’s 2030 levelized cost of energy (LCOE) goals. To overcome the shortcomings of the existing solar inverters, this project proposed a novel Hot-Swappable, Fault-Tolerant, Modular Power Converter (HSFT-MPC) concept for solar photovoltaic (PV) plants and proved the concept through the design, fabrication, and laboratory test validation of a single-phase HSFT-MPC prototype. The HSFT-MPC has the following distinct advantages over the state-of-the-art: 1) elimination of harmonic/ electromagnetic interference (EMI) filter in the inverter stage due to the novel topology, 2) lower system cost and higher power density due to the modular design, elimination of harmonic/EMI filter, and lower cooling requirement, 3) higher efficiency due to lower switching frequencies, 4) higher reliability and longer (50 years) service life due to simpler cooling and fault tolerance capability, 5) easier installation, lower O&M cost, and improved maintainability due to the modular design and hot-swappable power electronic building blocks (PEBBs), and 6) improved manufacturability due to the modular design. This project developed a single-phase HSFT-MPC prototype with 25kW nominal output power, 2.4kV, 60Hz nominal AC output, lower than 5% AC output voltage total harmonic distortion, over 5 kW/L inverter power density, and 99.4% inverter peak efficiency, being tolerant to failure of single and multiple PEBBs, and capable of hot swapping of the failed PEBB(s). The HSFT-MPC enables uninterruptable operation of the solar PV plant when failure of single or multiple PEBBs or PV modules occurs. Compared with the existing solar inverters in the market, the HSFT-MPC is expected to reduce the inverter failure-caused downtime and energy losses of solar PV plants by more than 60% and 50%, respectively. Project findings have been presented at major conferences in the field and published in peer-reviewed papers, which added new knowledge to the field of power electronics for solar PV systems. A minicourse on Solar PV Systems was developed for outreach activities. The minicourse will help attract young individuals to the renewable energy profession which has a significant talent shortage. The HSFT-MPC is expected to overcome all of the shortcomings of the state-of-the-art solar inverters in terms of cost, efficiency, service life, reliability, maintainability, and manufacturability targets needed to achieve SunShot’s 2030 LCOE goals. Therefore, the proposed HSFT-MPC concept has the great potential to disrupt the current solar inverter market. This project created a pathway towards industry adoption of the HSFT-MPC to help achieve 50-year service life solar PV systems. Since the solar PV plants using the HSFT-MPC will feature with higher reliability, longer service life, and easier maintenance, they are particularly useful for the rural areas with underserved populations that demand reliable and affordable clean electricity. The outcomes of the project have the strong potential to address national needs in the field of renewable energy to reduce CO 2 emissions from the electricity sector, reduce imports of energy from foreign sources, and improve energy security, efficiency, and sustainability. Since electricity is used in almost all of society’s sectors, the outcomes of the project will benefit various sectors of society and economy.

14 SOLAR ENERGY↗
DOE OSTI2020

High-Temperature Particle Heat Exchanger for sCO2 Power Cycles [Award 30342]

This report describes the design, development, and testing of a prototype 100 kWt particle-to-supercritical CO 2 (sCO2) heat exchanger. An analytic hierarchy process was implemented to compare and evaluate alternative heat-exchanger designs (fluidized bed, shell-and-plate moving packed bed, and shell-and-tube moving packed bed) that could meet the high pressure (≥ 20 MPa) and high temperature (≥ 700 °C) operational requirements associated with sCO2 power cycles. Cost, heat-transfer coefficient, structural reliability, manufacturability, parasitics and heat losses, scalability, compatibility, erosion and corrosion, transient operation, and inspection ease were considered in the evaluation. A 100 kWt shell-and-plate design was selected for construction and integration with Sandia’s falling particle receiver system that heats the particles using concentrated sunlight. Sandia worked with industry to design and construct the moving packed-bed shell-and-plate heat exchanger. Tests were performed to evaluate its performance using both electrical heating and concentrated sunlight to heat the particles. Overall heat transfer coefficients at off-design conditions (reduced operating temperatures and only three stainless steel banks in the counter-crossflow heat exchanger) were measured to be approximately ~25 - 70 W/m 2 -K, significantly lower than simulated values of >100 W/m 2 -K. Tests using the falling particle receiver to heat the particles with concentrated sunlight yielded overall heat transfer coefficients of ~35 – 80 W/m 2 -K with four banks (including a nickel-alloy bank above the three stainless steel banks). The overall heat transfer coefficient was observed to decrease with increasing particle inlet temperatures, which contrasted the results of simulations that showed an increase in heat transfer coefficient with temperature due to increased effective particle-bed thermal conductivity from radiation. The likely cause of the discrepancy was particle-flow maldistributions and funnel flow within the heat exchanger caused by internal ledges and cross-bracing, which could have been exacerbated by increased particle-wall friction at higher temperatures. Additional heat loss at higher temperatures may also contribute to a lower overall heat-transfer coefficient. Design challenges including pressure drop, particle and sCO2 flow maldistribution, and reduced heat transfer coefficient are discussed with approaches for mitigation in future designs. Lessons learned regarding instrumentation, performance characterization, and operation of particle components and sCO2 flow loops are also discussed. Finally, a 200 MWt commercial-scale shell-and-plate heat-exchanger design based on the concepts investigated in this report is proposed.

14 SOLAR ENERGY↗
DOE OSTI2026

Demonstration of Grid Services Using Mixed Grid-Forming and Grid-Following Technologies at the Wheatridge Renewable Energy Facility (Final Technical Report)

This Final Technical Report summarizes the analytical, modeling, and engineering work performed to evaluate grid-forming (GFM) inverter capabilities within a large hybrid renewable energy facility. The project focused on assessing the ability of advanced inverter-based resources to provide essential reliability services through coordinated operation of grid-forming (GFM) and grid-following (GFL) technologies. During Budget Period 1, the project developed a comprehensive framework of GFM performance metrics, including angle support, voltage regulation, frequency response, damping behavior, and current-limiting performance. Extensive electromagnetic transient (EMT) studies and hardware-in-the-loop (HIL) testing were conducted to validate GFM behavior under a range of operating conditions, including weak-grid scenarios, voltage disturbances, and multi-resource interactions. The project also established validated modeling approaches, plant-level control integration strategies, commissioning frameworks, and high-speed measurement infrastructure to support future field demonstration. Although the project concluded prior to field demonstration, the results provide a utility-scale foundation for evaluating, modeling, and deploying grid-forming technologies. The methodologies and tools developed contribute to industry understanding of inverter-based resource behavior and support future power system reliability under increasing renewable penetration.

14 SOLAR ENERGY↗
DOE OSTI2022

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Evaluation of Saccadic Component Measure on Smooth Pursuit Tests

ABSTRACT Introduction Despite the advancement of eye-tracking technology for smooth pursuit (SP) eye movement evaluation, qualitative observation offers much information that is not captured by computers; hence, both objective and qualitative information should be utilized to evaluate SP. This study examined the consistency among our clinicians when evaluating SP using normal (N), grossly normal (GN), mildly abnormal (MA), and abnormal (AB) as classifications. We then evaluated the effect of combining GN and MA into a single subclinical (SUBC) category. We also evaluated the computerized percent saccade (PS) metric by determining its sensitivity and specificity in classifying SP. Materials and Methods Retrospective horizontal and vertical SP test videos and numerical data for 70 participants were obtained from the Neuro Kinetics Neuro-Otologic Test Center and de-identified. From this, eye-tracking videos, time plots of eye-tracking positional data, and tables of SP eye-tracking performance data were generated for 0.1, 0.3, and 0.5 Hz in both horizontal and vertical planes, totaling 6 tests per subject. Three clinicians rated each subject’s SP performance as N, GN, MA, or AB for a total of 6 ratings (3 frequencies, horizontal and vertical). This process was repeated using N, SUBC, and AB as rating categories. Clinicians also provided an overall SP rating for each plane as follows: AB if the results were abnormal for 2 or more frequencies tested. Alternatively, if fewer than 2 frequencies presented with a rating of AB, then an overall rating of MA, GN, or N was determined at the respective clinician’s discretion. Results When the 3 clinicians were tasked with classifying SP videos using 4 clinical categories, fair overall agreement was demonstrated. However, when MA and GN categories were combined into an SUBC category, the overall agreement for the 3 clinicians improved slightly for both horizontal SP (HSP) and vertical SP (VSP). This pattern of agreement did not differ considerably when comparing HSP versus VSP, and good consistency and reliability was observed across clinicians. Again, inter-rater consistency was smaller for VSP versus HSP despite the reduction in clinical categories. Cut-off values were generated for the PS metric and demonstrated good specificity and sensitivity when they were exceeded for 2 or more frequencies in a particular plane when evaluating a subject’s SP test. Conclusions

General & Internal Medicine↗
DOE OSTI2025

Estimating the State of Charge in Lithium Primary Batteries: Recent Advances and Critical Insights

Lithium primary batteries (LPBs) remain essential in critical applications such as military, aerospace, medical and emergency devices, and portable electronics. Their superior energy density over lithium-ion batteries offers a significant advantage for long-duration use. Therefore, accurate estimation of the state of charge (SoC) is essential for ensuring the reliable and safe operation of these batteries. While extensive research has been conducted on SoC estimation techniques for lithium-ion secondary batteries, LPBs present unique challenges that complicate accurate SoC estimation. Moreover, research on nondestructive testing techniques for SoC estimation in LPBs is significantly lacking. In this review article, it is aimed to provide a comprehensive overview of recent advancements in SoC estimation for LPBs and generates new insights and directions for future research. Herein, existing methods are discussed and their effectiveness and mechanisms are identified, and areas for further optimization are outlined. More theoretical/experimental efforts to advance SoC detection in LPBs is recommended due to challenges identified with existing techniques.

25 ENERGY STORAGE↗
DOE OSTI2022

Application of machine learning to evaluating and remediating models for energy and environmental engineering

Machine learning (ML) algorithms have been increasingly successful in their applications to solve energy and environmental engineering problems. ML algorithms have the advantage of being able to solve highly nonlinear issues effectively. Furthermore, considering the limited sample size of data collected in energy and environmental engineering, obtaining a ML model with reasonable accuracy is simple. Unfortunately, the vast majority of the current applications of ML algorithms lack effective screening of dominant factors and comprehensive model validation, which weakens the predictive ability of the models. The present study takes the minimum miscible pressure (MMP) of CO 2 - oil systems as an example. It establishes a systematic and robust predictive model to address this issue. Based on 147 sets of slim tube tests, the predictive models of the MMPs are investigated by application of eight ML algorithms. The paper concludes that most of the published ML models in the field of energy and environmental engineering prediction are not reliable. Furthermore, it addresses the main reasons for the poor performance of some predictive models built by ML and provides guidelines on how to make such models robust. Further, to the best of our knowledge, this is the first study to point out the defects of current ML modeling methods and propose countermeasures for their application in energy and environmental engineering problems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

A review on the sizing and selection of control valves for thermal hydraulics for reactor system applications

This study presents an overview regarding how to model/size, choose, and maintain control valves (CVs) for a reactor system thermal hydraulics experimentation—specifically simulating pipe break(s) and a loss of coolant accident (LOCA) analysis. In a thermal hydraulics test loop, CVs modulate fluid flow according to the control signal generated by the controller to control the process parameter. The selection of a CV in industrial applications involves many factors, including process diversity, safety, and reliability. Further, the key issues and challenges for performing proper mathematical modeling, installation, servicing, and calibration are also discussed for the benefit of operators and end-users. Additionally, this research includes case studies illustrating major plant-level accidents associated with the malfunctioning of valves. Therefore, the study will serve as a knowledge base or reference guide for young professionals and operators who wish to better understand process control applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Experimenting in the cloud: The digital divide's impact on innovation

This paper builds on a recent National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. We estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Here, findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗