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DOE OSTI2026

Seasonal performance evaluation of zero-superheat active refrigerant charge control for variable-speed heat pumps

Heat pumps account for a significant portion of electricity consumption in buildings, making their energy efficiency a critical area of research. Control optimization is recognized as an effective approach for enhancing the efficiency of building HVAC systems. Specifically, since the efficiency of heat pumps increases with reduced superheat and the optimal refrigerant charge level varies with operating conditions, zero-superheat active charge control is a promising strategy to maximize the system’s COP. However, due to its complexity, this control strategy remains in the research phase and has only been tested under limited operating conditions. This paper proposes a methodology to evaluate the seasonal performance improvement of zero-superheat active charge control across a full range of heating conditions in buildings. The methodology includes the development of an optimal controller that utilizes an accumulator to store excess refrigerant and manages the active charge level at zero superheat through subcooling control, as well as the creation of a detailed physics-based heat pump model. Targeted a 3-ton variable-speed heat pump with R410A refrigerant, we selected ten U.S. cities representing different climate regions for seasonal performance evaluation. Our simulations indicate that, depending on the climate conditions, the optimal control strategy could achieve energy savings ranging from 5.8 % to 8.0 % over the entire heating season. These results suggest that zero-superheat active charge control, combined with coordinated compressor and fan speeds, could substantially improve the energy efficiency of heat pump systems while maintaining the required heating capacity.

Guo, Fangzhou↗

DOE OSTI2025

Transient fuel performance analysis for the preliminary fuel concept of general atomics fast modular reactor

This study investigates the transient fuel performance of General Atomics Fast Modular Reactor (GA-FMR) during accident scenarios, focusing on the behavior of its innovative fuel system that combines high-assay low enriched uranium dioxide (HALEUO2) fuel with SiGA® ceramic matrix composite silicon carbide cladding. The preliminary fuel design’s response was analyzed during reactivity-initiated accidents (RIA) and loss of coolant accidents (LOCA) using BISON fuel performance analysis code, which included both the diffusion enhanced and BISON-FASTGRASS coupled UO 2 models. The RIA analysis demonstrated that effective reactivity control reduced fuel temperature, though with transient fission gas release resulting in additional tensile stress state on the cladding. LOCA simulations revealed differing predictions between the two models: the BISON UO 2 model showed more transient fission gas release but minimal pellet expansion, while the BISON-FASTGRASS UO 2 model predicted less pronounced fission gas release but more fuel swelling and thermal expansion, potentially leading to pellet-cladding mechanical interaction. Here, these findings highlight critical areas for fuel design optimization and identify knowledge gaps requiring further experimental and computational investigation to advance GA-FMR fuel development.

Lee, Soon K. [Argonne National Laboratory (ANL), A↗

DOE OSTI2021

Methodology for interpretable reinforcement learning model for HVAC energy control

Deep reinforcement learning (DRL) approaches have been used in various application areas to improve efficiency, optimization, or automation. However, very little is known about how the DRL algorithms make decisions and what features affect their performance. Using a case study of a DRL based Heating, Ventilation and Air Conditioning (HVAC) optimization methodology, we demonstrate how we can address these challenges by applying interpretability tools and systematically exploring the model inputs for better understanding the DRL behaviour and decision making process. We developed a methodology for interpretable reinforcement learning and evaluated our approach in real-world house located in Knoxville, TN. Our findings explain the reasoning behind DRL-based optimization decisions under different circumstances which has been discussed and confirmed by the experts in the field.

Kotevska, Olivera↗

DOE OSTI2021

Iterative Linearization for Phasor-Defined Optimal Power Dispatch

Optimal power flow (OPF) problems, which dispatch power targets to controllable generating units across a network, must generally account for non-convex constraints on power flow. Furthermore, adapting those problems so as to make them solvable with convex optimization techniques is an area of much academic and operational interest. In this paper, we present a method for solving OPF as a quadratic program by iteratively refining and re-initializing a linearized model of power flow based on the outputs of an associated nonlinear solver. The linear model on which we demonstrate this method is an adapted version of an approximation designed for use with unbalanced distribution networks. As an important benefit, the model allows for the explicit inclusion of nodal voltage phasor values in both the OPF problem's objective and its constraints, which opens the door to the idea of phasor-based control (PBC) design. We show in simulations on the IEEE 13-node test feeder that our method quickly converges to a set of phasor targets that are sufficiently precise for use in operations at the distribution level.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool

Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Summer Proceedings 2019

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers and heterogeneous computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program includes the organization of a weekly seminar series and the publication of this summer proceedings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

CSRI Summer Proceedings 2020

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program is organized by CSRI and typically includes the organization of a weekly seminar series and the publication of a summer proceedings. In 2020, the CSRI summer program was executed completely virtually; all student interns worked from home, due to the COVID-19 pandemic.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

CSRI Summer Proceedings 2021

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

High Efficacy, Long Lifetime Flexible White OLED Lighting Panels

In this project, OLEDWorks and partners made significant progress in advancing OLED light extraction technology. Improving light extraction efficiency remains one of the most important research topics for OLEDs. Current state-of-the-art white OLED products extract only about 50% of the photons that are generated within the device. Promising new light extraction concepts, such as those based on sub electrode micro lens arrays (SEMLAs), were explored in this project with the potential to achieve extraction efficiency of 60% or higher. Flexible thin glass substrates with integrated SEMLAs were successfully fabricated and scaled to large area. When combined with optimized high efficiency stacked white OLED structures, we achieved the program goals of 120 LPW efficacy and long lifetime more than 100,000 hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

SPARTAN (Scalable Probabilistic Application Reconfigurable Tensor Autonomous Network)

The technical founder of Ludwig Computing Inc has been competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Ludwig Computing Inc, supported by the U.S. Department of Energy's Advanced Manufacturing Office through the Cyclotron Road program, has investigated the advantages of probabilistic computing for real-world compute-intensive applications. This research adds to the understanding of alternative computing paradigms by exploring a unique hardware-software co-design that integrates quantum computing methods with nature-inspired problem-solving techniques. The project's focus on areas such as combinatorial optimization, graph analytics, and machine learning demonstrates the potential for significant advancements in computational efficiency and performance. By harnessing natural randomness to streamline large circuits into fewer devices, Ludwig's approach enables massive parallelism, potentially offering higher throughput, speed, and energy efficiency compared to conventional hardware solutions. This work benefits the public by paving the way for more efficient computing solutions that could address complex real-world problems while potentially reducing energy consumption in data-intensive industries.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Effect of Si Content on Extreme Fast Charging Behavior in Silicon–Graphite Composite Anodes

Commercial Li-ion batteries typically incorporate a small amount of high-capacity silicon (Si)-based materials in the composite graphite-based anode to increase the energy density of the battery. However, very little is known about the effects of Si on the fast-charging behavior of composite anodes. Herein, we examine the effects of the Si/graphite ratio in the composite anode on the fast-charging behavior of full cells. We show that addition of Si increases the rate capability from 1C to 8C and improves the capacity retention in early cycles at 6C due to reduced overpotential in constant current charging cycles. The impacts of Si content on fast-charging aging were identified by Post-Test characterization. Despite realizing benefits of available capacity and reduced Li plating at 6C, silicon–electrolyte interactions lead the time-dependent cell performance to fade quickly in the long term. The Post-Test analysis also revealed the thickening of the electrode and nonuniform distribution of electrolyte decomposition products on the Si-containing anodes, as well as the organic-rich solid electrolyte interphase (SEI), which are the factors behind cell degradation. Our study sheds insight on the advantages and disadvantages of Si/graphite composite anodes when they are used in fast-charging applications and guides further research in the area by designing an optimized composition of Si incorporated in a mature graphite matrix.

25 ENERGY STORAGE↗

DOE OSTI2021

Consumer Preferences and Willingness to Pay for Potting Mix with Biochar

Biochar is a co-product of advanced biofuels production from feedstocks including food, agricultural, wood wastes, or dedicated energy crops. Markets for soil amendments using biochar are emerging, but little is known about consumer preferences and willingness to pay (WTP) for these products or the depth of the products’ market potential for this product. This research provides WTP estimates for potting mix amended with 25% biochar, conditioned on consumer demographics and attitudes about product information labeling. Data were collected with an online survey of 577 Tennessee home gardeners. WTP was elicited through a referendum contingent valuation. Consumer WTP for an 8.81 L bag of 25% biochar potting mix is $8.52; a premium of $3.53 over conventional potting mix. Demographics and attitudes toward biofuels and the environment influence WTP. Biochar amounts demanded are projected for the study area’s potential market. Optimal prices, profits, and market shares are estimated across different marginal costs of producing biochar potting mix.

09 BIOMASS FUELS↗

DOE OSTI2025

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗

NASA NTRS1971

On optimal scheduling and air traffic control in the near terminal area

A scheme is proposed for automated air traffic control of landing aircraft in the vicinity of the airport. Each aircraft is put under the control of an airport-based computer as soon as it enters the near-terminal area (NTA). Scheduling is done immediately thereafter. The aircraft is given a flight plan which, if followed precisely, will lead it to the runway at a prespecified time. The geometry of the airspace in the NTA is chosen so that delays are executed far from the outer marker, and violations of minimum altitude and lateral separations are avoided. Finally, a solution to the velocity mix problem is proposed.

Sarris, A. H.↗

NASA NTRS1976

Hydrogen-fueled scramjets: Potential for detailed combustor analysis

Combustion research related to hypersonic scramjet (supersonic combustion ramjet) propulsion is discussed from the analytical point of view. Because the fuel is gaseous hydrogen, mixing is single phase and the chemical kinetics are well known; therefore, the potential for analysis is good relative to hydro-carbon fueled engines. Recent progress in applying two and three dimensional analytical techniques to mixing and reacting flows indicates cause for optimism, and identifies several areas for continuing effort.

Beach, H. L., Jr.↗

NASA NTRS1979

Automated Array Assembly, Phase 2

The Automated Array Assembly Task, Phase 2 of the Low Cost Silicon Solar Array Project is a process development task. The contract provides for the fabrication of modules from large area tandem junction cells (TJC). During this quarter, effort was focused on the design of a large area, approximately 36 sq cm, TJC and process verification runs. The large area TJC design was optimized for minimum I squared R power losses. In the TJM activity, the cell-module interfaces were defined, module substrates were formed and heat treated and clad metal interconnect strips were fabricated.

Carbajal, B. G.↗

NASA NTRS1979

Optimization of multi-layer front-contact grid patterns for solar cells

In a front-contact grid pattern for a solar cell there is a trade-off necessary between shadowing loss and excessive power loss due to voltage drop in the metalization itself. If the metalization is too little there may be excessive contact resistance to the underlying semiconductor and insufficient coverage to control losses in the thin front-surface layer of the solar cell. Optimization of grid pattern area and geometry is considered analytically to minimize total losses. Worthwhile performance advantages are shown to be possible, particularly in concentrator systems, if multi-layer grid patterns are used. The current carrying fingers should be approximately square in metal cross section and the main current feedout bars should not only be wider but also thicker than the primary collecting fingers. This is termed multi-level metalization. Effective use of multi-level grid metalization allows much greater concentration-to-loss ratio for a cell of large area and permits good performance from cells of high front-layer sheet resistance.

Flat, A.↗