Search NASA⌕ Search

SEARCH · Search NASA

Results for “system level”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Phase change material-to-refrigerant heat exchangers: Experimental validation and uneven melting analysis

Thermal energy storage (TES) using phase change materials (PCMs) enables load shifting and reduces mismatches between the building's thermal demand and the heat pump (HP) system's thermal capacity. While most TES studies have focused on single-phase heat transfer fluids, PCM-to-refrigerant heat exchangers (PRHX), in which the refrigerant undergoes liquid-vapor phase change, remain largely underexplored. Here, to address this gap, this study systematically investigates a shell-and-tube PRHX operating as the condenser in an HP through experiments and simulations. A two-dimensional enthalpy-based finite-volume PRHX model was developed and validated against experimental data, including refrigerant and PCM temperature profiles, PRHX capacity, and system-level performance. Results show three characteristic stages: Stage I, the condenser temperature rapidly increases with PCM in the solid state absorbing sensible heat; Stage II, stable operation during PCM phase change; and Stage III, performance decline once part of the PCM becomes fully melted. Heat transfer analysis revealed that uneven PCM melting along the condenser length was driven primarily by variations in the refrigerant-side heat transfer coefficient, rather than local approach temperature differences. Further study demonstrated that minimizing refrigerant outlet subcooling led to more uniform PCM melting and extended Stages I and II by up to 89%. This paper provides a validated PRHX model, clarifies the mechanisms of uneven PCM melting, and highlights subcooling control as an effective strategy to improve TES performance in HP systems without requiring secondary loops.

Graphite matrix↗
DOE OSTI2024

Hydroxide Exchange Membrane Carbon Capture (HEMCC) Using Nickel Hydroxide Batteries and Flow-through Membranes

Proposed is an electrochemical nickel hydroxide based hydroxide exchange membrane carbon capture (HEMCC) device for Direct Air Capture (DAC) of CO2. DAC has been identified as one of the key net negative carbon technologies to achieve net zero carbon emissions. Net negative carbon technologies are required to offset continued emissions from dilute CO2 sources such as agriculture and construction. The majority of current DAC technologies at scale (>1 KT∙yr-1) are adsorbent based technologies with significant energy cost. The traditional DAC energy cost is primarily driven by the temperature swing required to regenerate the sorbent and has been shown to be 1.8 MWh·ton-1 at the system level. Electrochemical pH swing devices are a growing research area for carbon capture devices with the goal of lowering the energy cost required for DAC. A pH gradient is built by generating OH- at the cathode and consuming OH- at the anode. An acid-base equilibrium with CO2 allows for the capture of CO2 at the cathode and release at the anode. This extends from other electrochemical CO2 capture devices based on pKa shifts of an electrochemically active organic species allowing for the capture and release of CO2. Electrochemical CO2 capture is considered promising based on potentially low energy costs to capture CO2 in comparison with current temperature swing adsorption technologies. This work explores Ni(OH)2 electrodes to produce the pH gradient for CO2 capture and release. At the cathode NiOOH is reduced to Ni(OH)2 while at the anode Ni(OH)2 is oxidized to NiOOH. The symmetrical electrodes allow for a low voltage requirement; the thermodynamic potential difference of standard electrochemical reactions is zero. Most of the voltage observed is to produce the pH gradient with the remainder driving the polarization of the electrodes. There is a resistance component as well, but this is small in comparison due to the low current densities used in the device, nominally 2 mA·cm-1. Two similar devices are presented, a traditional MEA (membrane electrode assembly) and a flow-through MEA. The traditional MEA separates the two Ni(OH)2 electrodes with an 80μm Piperion® membrane. While the flow-through membrane separates the electrodes with a three piece membrane consisting of two 80μm Piperion® membranes with a porous membrane between them. In the traditional MEA system air is passed over the cathode for capture, while the flow-through MEA the air is passed through the porous membrane isolated from the electrodes. The traditional MEA has been used to establish a baseline performance of the device and has been shown to capture CO2 at an energy cost of 1 MWh·ton-1 at the device level. An understanding has been built around the components of that energy cost including the relationship of flux to current density, effect of a regeneration process, transient battery behavior, and gas losses coinciding with changing the polarization of the batteries. The flow-through MEA looks to address of transient battery behavior and gas losses. It allows for denser, higher capacity electrodes, which can lean on traditional Ni-MH battery technology used in alkaline batteries used today. The higher capacities, limit the transient battery effect on flux in the device. Gas losses are addressed by having a continuous inlet air stream to the device and continuous outlet product.

Buchen, James↗
DOE OSTI2026

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The dual role of iron in alkaline water electrolysis: A friend or a foe?

Trace iron (Fe) impurities pose a challenge in alkaline water electrolysis (AWE) and can significantly impact long-term performance, yet their comprehensive system-level effects remain poorly understood. Here, we present the mechanistic roles of Fe in AWE, using combined rotation disk electrode studies, zero-gap cell measurements, and durability tests up to 1,000 h. Fundamental electrochemistry shows that Fe deposition proceeds through a solution-mediated pathway, with dendritic growth triggered under specific mass-transport and potential conditions. In single-cell operation, Fe incorporation substantially enhances nickel (Ni)-based anode activity by forming highly active Ni-Fe oxyhydroxides, while cathodic Fe forms either thin films or dendrites, depending on potential, surface morphology, and electrolyte distribution. Although dendrites do not degrade hydrogen evolution performance up to 1,000 h, they reveal partial intrusion into the separator, indicating a potential durability risk. We identify five governing factors controlling Fe dendrite formation and provide design principles for impurity-resilient AWE systems.

Lyu, Xiang [ORNL] (ORCID:0000000208673248)↗
DOE OSTI2025

Theoretical foundations of waste factor and waste figure with applications to fixed wireless access and relay systems

The growing energy demands of next-generation wireless systems call for unified, system-level metrics to evaluate and optimize energy efficiency. This paper advances the concept of the Waste Factor (W), or Waste Figure (WF) in decibel scale, as a general framework for modeling power loss across cascaded communication components. By integrating W into the Consumption Factor (CF)–the ratio of data rate to consumed power–we reveal how component inefficiencies influence the minimum achievable energy per bit. Closed-form expressions are derived for energy-per-bit consumption in both direct and relay-assisted links, along with a decision rule for selecting the more energy-efficient path. While not explicitly modeled, Reflective Intelligent Surfaces (RIS) are shown to fit naturally within this framework. The analysis is further applied to a Fixed Wireless Access (FWA) scenario, where asymmetries in traffic direction and hardware inefficiencies are jointly considered, demonstrating the utility of the Waste Factor in guiding energy-aware system design.

Sevim, Nurullah [Texas A&M University, College Sta↗
DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
DOE OSTI2026

A Scalable, Distribution Network-Aware, Customer Privacy-Preserving Framework for Operation of Virtual Power Plants

This poster presents a hierarchical control framework for a virtual power plant that leverages behind-the-meter resources for grid services while maintaining customer privacy during setpoint disaggregation. Unlike many existing approaches, the virtual power plant model uses a hierarchical control strategy and an iterative approach to determine the optimal set point dis-aggregation without direct load control while maintaining system-level power flow and voltage constraints. The proposed approach is numerically validated on a synthetic distribution feeder in San Francisco, demonstrating the ability of the framework to provide privacy-preserving virtual power plant services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

System and Machine Learning-Guided Materials Design for High-Pressure Hydrogen Compression

Cost-effective and reliable hydrogen compression remains a challenging barrier in the widespread adoption of hydrogen as an energy carrier. The prevailing technology of mechanical compression suffers from several drawbacks, some of which can be addressed by nonmechanical compression strategies (e.g., electrochemical or metal hydride-based thermal compression). Thermally driven metal hydride compression strategies typically rely on multistage metal hydride-based compressors; however, discovering or optimizing low-stability metal hydrides that can pressurize hydrogen upward of 1000 bar is difficult, both with respect to computational predictions and experimental validation. Here, in this study, we (1) demonstrate that simple machine learning-derived design rules can inform the rational design of alloying strategies yielding low-stability hydrides, (2) validate their experimental pressure–composition–temperature (PCT) isotherms up to 875 bar, and (3) utilize a dynamic system-level model of a metal hydride compressor design to evaluate their performance under realistic operating conditions. Importantly, this analysis yields predicted operational efficiencies of both 2-stage (90–875 bar) and 3-stage (20–875 bar) metal hydride compressors to enable further evaluation of this technology and its techno-economic outlook.

alloy optimization↗
DOE OSTI2025

The GREEN ‘omics of Nutrient Feedbacks to Soil Warming

The GREEN ‘omics of Nutrient Feedbacks in Soil project advanced the DOE Biological and Environmental Research (BER) mission by developing and applying isotope-enabled ’omics tools to understand how soil microbes regulate carbon and nutrient cycling. Guided by the Growth Rate, growth Efficiency, and stoichiometry of Essential Nutrients (GREEN ’omics) framework, the project aimed to build a predictive, systems-level understanding of microbial traits that control ecosystem biogeochemistry. In a collaboration among Northern Arizona University (lead), West Virginia University, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory, we combined quantitative stable isotope probing (qSIP), Chip-SIP, NanoSIMS, and genome-resolved metagenomics across long-term experiments in Arctic, boreal, temperate, and tropical ecosystems. The project produced three key outcomes: 1) We showed that community-weighted temperature sensitivities of bacterial growth (Q10) can predict ecosystem-scale soil respiration responses across diverse soils. 2) We provided the first in situ evidence for density-dependent population dynamics in soil bacteria and demonstrated that nutrient additions intensify competition, concentrating carbon use into fewer taxa. 3) We improved and extended isotope-enabled ’omics methods by quantifying qSIP measurement error to guide experimental design and coupling SIP with genome-resolved metagenomics to reveal cross-kingdom interactions among bacteria, fungi, and viruses. Together, these results show that a small number of microbial traits and taxa exert disproportionate control over soil carbon and nutrient cycling, providing critical data and methods to improve representation of microbial processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Representativity error scaling of models of the high temperature test facility

Error scaling is a critical step toward the validation of modeling capabilities for high-temperature gas-cooled reactors (HTGRs). Extensive effort is being made to bring HTGRs into the validation basis of numerous thermal-hydraulics codes. Here, this paper demonstrates how systems-level codes can be leveraged to perform error scaling analyses between an experimental facility and a plant-to-be facility. Specifically, we focus on two conduction cooldown experiments from the High Temperature Test Facility (HTTF) and the General Atomics 350 MW th modular high-temperature gas-cooled reactor (MHTGR-350). The error scaling methodology employed in this study is representativity, which in the context of this work was used to quantify how well experiments captured the physics of the plant facility by comparing sensitivity vectors between the two facilities. In addition, two different RELAP5–3D models of the HTTF were included in the comparison to determine if modeling methodologies notably impact the representativity results. The key figures of merit are the maximum block temperature and the coolant outlet temperature. The time-dependent maximum block temperature had a low representativity of below 0.1 for both models across both transients. The coolant outlet temperature had a higher representativity of around 0.6 for both models during the pressurized conduction cooldown, but it was below 0.2 for the depressurized conduction cooldown. Overall, the HTTF experiments were not representative of the transients in the MHTGR-350. However, these results can play a significant role in informing future potential experiments for HTGR systems that iterate on what the HTTF accomplished.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Minimum GHG emissions and energy consumption of U.S. PET and polyolefin packaging supply chains in a circular economy

There is a wide agreement on the urgency of transforming linear management of plastics towards a circular economy model. However, no clear pathways exist as to required recycling technologies involved and system-wide environmental impacts. This study explores such pathways in the U.S. for the most commonly used packaging plastics through a combination of mechanical and emerging advanced recycling technologies. A system optimization model aimed at minimizing environmental impacts was developed to determine optimal end-of-life (EOL) management and locations of existing and emerging U.S. recycling infrastructures. Our study includes material flows from virgin resin production through semi-manufacturing processes to existing EOL disposal and recycling processes. An optimized circular plastics packaging system achieved greenhouse gas (GHG) emission savings of up to 28% and cumulative energy demand (CED) savings of up to 46%, compared to the linear economy. Moreover, these savings of GHG emissions and CED impacts represent a reduction of 0.16% and 0.49% compared to annual U.S. GHG emissions and energy consumption in 2022, respectively. The optimal recycling rates and systems-level circularity ranged from 78–99% and 57–75%, respectively. Increased energy savings led to increased GHG emissions showing a potential trade-off between GHG emissions and energy. Analysis of 40 scenarios showed the importance of material collection distances, blend limit of mechanically recycled resins, process yields, and mandated recycling rates for achieving a sustainable circular economy of plastics.

09 - BIOMASS FUELS↗
DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗
DOE OSTI2025

Transient Modeling and Simulation of a Generic Stable Salt Reactor

A SAM system-level model of a generic stable salt reactor has been developed to investigate thermal-hydraulic behavior and safety performance under steady and transient conditions. The model integrates information generated from a reactor physics analysis using PROTEUS and PERSENT, and a computation fluid dynamics (CFD) analysis using STAR-CCM+. A loose, iterative coupling scheme between PROTEUS and SAM is implemented to calculate the equilibrium power and temperature distributions in the steady-state critical core condition. The converged steady-state model is then used in PERSENT to calculate the four reactivity feedback temperature coefficients (Doppler, fuel density, coolant density, and core radial expansion) and kinetic parameters that are needed in SAM to model the temperature feedback effects in transient simulations. Within the fully enclosed liquid fuel pins, natural convection is the dominant heat transfer mechanism. The STAR-CCM+ model of the fuel pin considers conjugate heat transfer from the liquid fuel salt to the pin cladding and external reactor coolant. The CFD results of the axial and radial temperature profiles are used to empirically determine an effective fuel salt thermal conductivity in the SAM fuel pin model so that the temperatures predicted by the SAM model match as closely as possible the CFD results. In the central region of the fuel pin, the effective thermal conductivity is as high as similar to 60 times the physical fuel salt thermal conductivity. The whole-plant SAM model is then used to simulate an unprotected station blackout transient. The results of this simulation showed that the large negative fuel axial expansion reactivity feedback reduces fission power to similar to 2.4% nominal power. The core is cooled by natural circulation, which removes heat in the core to the emergency heat removal system, and ultimately, to the ambient. However, peak fuel salt and cladding temperatures can potentially reach as high as 1500 K, albeit briefly, if the shutdown mechanism fails to operate.

stable salt reactor; transient simulations; system↗
DOE OSTI2025

Progress Towards the Validation of a new RELAP5-3D model of the High Temperature Test Facility

Validation is a key step in the development of any type of systems model. As the next generation of reactors approaches, the need for codes that have been validated for these new types of systems continues to grow. An example of a prominent option is the Reactor Excursion Leak Analysis Program (RELAP5-3D), developed by Idaho National Laboratory. This code was developed for the purpose of systems level thermal-hydraulic modeling of light water reactors (LWRS) and postulated transients that can occur in LWRS.RELAP5-3D has been substantially validated against LWR data. Due to its long history as a reactor safety analysis tool, there has been an effort to adapt RELAP5-3D for the purposes of advanced reactor concepts such as prismatic high-temperature gas-cooled reactors (HTGRs). However, RELAP5-3D has not nearly been validated and verified for HTGRs to the degree of LWRs, warranting verification and validation opportunities with computational benchmarks and existing experimental facilities. Examples of such facilities include the modular high-temperature gas-cooled reactor (MHTGR) 350 and the high temperature engineering test reactor (HTTR) from Japan. The MHTGR 350 is a benchmark design concept for code-to-code verification purposes; therefore, it does not provide any experimental data for validation opportunities The HTTR provides useful multiphysics validation data but does not have the in-core instruments to generate thermal-hydraulic experimental data to help with RELAP5-3D validation. Consequently, a facility that could provide key in-core temperatures for thermal-hydraulic validation was still needed. The High Temperature Test Facility (HTTF) is an integral effects facility for HTGR thermal hydraulics developed and operated by Oregon State University. HTTF represents ¼ length scale of the General Atomics MHTGR and is rated for a total power of 2.2 MW. Axially, the core consists of an upper and lower reflector and 10 blocks, numbered from bottom to top (Block 1 is right above lower reflector). The core is heated via graphite resistive heater rods, with respective channels distributed throughout the core. The primary coolant is helium and heat can radiate out of the core to the reactor cavity cooling system (RCCS), which is cooled by water. The primary purpose of the facility is to investigate pressurized conduction cooldown (PCC) and depressurized conduction cooldown (DCC) transients, which are also referred to as the pressurized and depressurized loss of forced cooling respectively. Two experiments were chosen to perform the validation study with a RELAP5-3D model of HTTF. These experiments are PG-27 (PCC) and PG-29 (DCC). These were chosen based off of the quality of available experimental data before and during the experiment which led to their inclusion in the HTGR Thermal Hydraulics Benchmark.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

BlueCRAB Domain Overlapping Coupling: Theory & Verification

Coupling low- and high-fidelity codes is a useful way to model complex engineering systems. Thanks to the high-fidelity code, complex phenomena can be resolved in areas of the system where this is required, yet the efficiency of the lower-fidelity code is still retained in modeling the rest of the system. This document details the theory and implementation of coupling two different thermal-hydraulic codes: the system thermal-hydraulics (STH) code System Analysis Module (SAM) and the coarse-mesh computational fluid dynamics (CFD) code Pronghorn. Both applications are included in the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite and are based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. The domain overlapping (DO) coupling approach was adopted, as it offers proven advantages over more conventional domain decomposition methods. In the DO coupling, SAM provides Pronghorn with boundary conditions that depend on the system-level simulation of the entire plant. In return, the overlapping coupled SAM components–termed “surrogate components”–receive friction factors and source terms computed online based on the Pronghorn simulation. The framework is designed to be generic and enable coupling regardless of geometry and the number of inlet/outlet boundaries in the DO coupled domain. The developed method leads to consistent pressure drops, enthalpies, and scalar concentrations when comparing the coupled SAM and Pronghorn simulations. This document presents the DO coupling approach, along with two verification and two demonstration cases. The proposed problems explore different physical aspects relevant to nuclear reactor analysis, including buoyancy-driven flows, complex flow patterns, and multiple inlets and outlets. Periodically, new versions of this “BlueCRAB Domain Overlapping Coupling: Theory & Verification” report will be issued to reflect future developments and verification tests.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Radiation-Hard 8-Channel 15-Bit 40-MSPS ADC for the ATLAS Liquid Argon Calorimeter Readout

The custom design of a radiation-hardened, 8-channel, 40-MSPS, 15-bit resolution, 14.2-bit dynamic range, 11.4-ENOB ADC data acquisition ASIC fabricated in a commercial 65-nm triple-well CMOS technology is presented. The ADC is developed for and integrates seamlessly into the readout system for the ATLAS liquid argon (LAr) calorimeter in the high-luminosity large hadron collider (HLLHC) upgrade at CERN, which will require a total of 364 936 ADC channels. A three-stage MDAC+SAR pipelined ADC architecture was designed to meet the physics requirements and scientific goals of the ATLAS experiment. The ADC is a fully self-contained data acquisition system that includes foreground calibration, digital data processing, digital control, and supporting circuitry. The measured performance shows the ADC achieves a competitive dynamic range and SNDR, and it meets or exceeds the ATLAS analog requirements. Radiation tolerance and scalability design considerations were implemented at the device-, circuit-, and system-level. Radiation-hardening-by-design techniques used include redundancy for digital circuits, the use of MiM capacitors, and a hybrid RC-DAC for the ADC core. The ADC ASIC was demonstrated to be robust against the effects of the intense radiation expected in the HL-LHC experimental environment.

DAQ↗
DOE OSTI2024

District heating utilizing waste heat of a data center: High-temperature heat pumps

Data centers are energy-intensive facilities with substantial low-grade waste heat. High-temperature heat pumps can be critical in boosting the data center’s waste heat for district heating, improving the system-level energy efficiency of data centers, and reducing CO 2 emissions in district heating. This study built thermodynamic models to assess high-temperature heat pumps with six configurations using low global warming potential refrigerants to supply heat up to 120 °C. The heat pump configurations include single-stage or two-stage cycles with advanced components, such as internal heat exchanger, economizer, flash tank, or parallel compressor. The refrigerants include R1234ze(Z), R1233ed(E), R1224yd(Z), R600, and R600a, and R245fa is used as a reference. A case study was carried out to recover the waste heat from the Frontier high-performance computing data center and provide hot water for district heating at the US Department of Energy’s Oak Ridge National Laboratory campus. The optimized performance of high-temperature heat pumps is characterized with various effectiveness of internal heat exchangers, and the operating parameters of economizer or flash tank, as well as their combination. The results show that the configurations of two-stage cycles with internal heat exchanger + flash tank and internal heat exchanger + economizer/parallel-compressor provide the highest coefficient of performance under scenarios of the maximum allowable value and a fixed value (0.3) of the internal heat exchangers’ effectiveness, respectively. R1234ze(Z) and R600a are the most promising refrigerants, considering trade-offs between the coefficient of performance and the volumetric heating capacity. The single-stage cycle with internal heat exchanger + economizer/parallel-compressor using R1234ze(Z) is recommended for utilizing Fronter’s waste heat in district heating. A one mega-watt high-temperature heat pump will reduce 33,100–33,200 metric tons of CO2 emission annually, corresponding to 85.4 %–85.6 % of equivalent CO2 emissions from natural gas boilers. Here, this study provides good guidelines for designing and deploying high-temperature heat pumps to support sustainable data centers and decarbonize district heating in the US.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Electronegativity-Guided Site Differentiation in High-Entropy Alloy for pH-universal Hydrogen Evolution Reactions

Enhancing the intrinsic activity of transition metal catalysts for the hydrogen evolution reaction (HER) remains a critical challenge in sustainable energy conversion. Herein, we report an electronegativity-guided site differentiation strategy in a single-phase CoNiCuMoW high-entropy alloy (HEA) via electrodeposition by incorporating high-electronegativity 4d/5d orbital transition metals (Mo, W) into the face-centered cubic (fcc) matrix (CoNiCu). The as-synthesized HEA demonstrates exceptional HER performance in all pH conditions, delivering an outstanding overpotential of 65 mV (alkaline), 28 mV (acidic), and 155 mV (neutral) at a current density of 100 mA cm−2, showing performance comparable to commercial Pt/C and has excellent long-term stability at high current density (1 A cm−2, 1000 h). X-Ray absorption spectroscopy (XAS) and density functional theory (DFT) calculations reveal that the incorporation of Mo/W simultaneously alters the local coordination environment and induces element-dependent charge redistribution, accompanied by a system-level d-band center downshift, thereby optimizing the hydrogen binding strength across multimetallic sites. Meanwhile, oxophilic Mo/W sites lower the water dissociation energy barrier. These synergistic effects collectively enable efficient and durable pH-universal HER performance.

Wu, Yutong↗