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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗
DOE OSTI2023

Voltage regulation in distribution grids: A survey

Environmental and sustainability concerns have caused a recent surge in the penetration of distributed energy resources into the power grid. This may lead to voltage violations in the distribution systems making voltage regulation more relevant than ever. Owing to this and rapid advancements in sensing, communication, and computation technologies, the literature on voltage control techniques is growing at a rapid pace in distribution networks. In particular, there is a paradigm shift from traditional offline centralized approaches to distributed ones leveraging increased and varied types of actuators, real-time sensing, fast and efficient computations, and an overall distributed situational awareness. This paper reviews state-of-the-art voltage control algorithms, summarizes the underlying methods, and classifies their coordination mechanisms into local, centralized, distributed, and decentralized. The underlying solution methodologies are further classified into two categories, open-loop and feedback-based. Two specific example workflows are provided to illustrate these solutions for voltage regulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Crystal structures and functional analysis of the ZnF5-WWE1-WWE2 region of PARP13/ZAP define a distinctive mode of engaging poly(ADP-ribose)

PARP13/ZAP (zinc-finger antiviral protein) acts against multiple viruses by promoting degradation of viral mRNA. PARP13 has four N-terminal zinc (Zn) fingers that bind CG-rich nucleotide sequences, a C-terminal ADP ribosyltransferase fold, and a central region with a fifth Zn finger and tandem WWE domains. The central PARP13 region, ZnF5-WWE1-WWE2, is implicated in binding poly(ADP-ribose); however, there are limited insights into its structure and function. We present crystal structures of ZnF5-WWE1-WWE2 from mouse PARP13 in complex with ADP-ribose and in complex with ATP. The crystal structures and binding studies demonstrate that WWE2 interacts with ADP-ribose and ATP, whereas WWE1 does not have a functional binding site. Binding studies with poly(ADP-ribose) ligands indicate that WWE2 serves as an anchor for preferential binding to the terminal end of poly(ADP-ribose) chains. The composite ZnF5-WWE1-WWE2 structure forms an extended surface to engage ADP-ribose chains, representing a distinctive mode of recognition that provides a framework for investigating the impact of poly(ADP-ribose) on PARP13 function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Catabolism of lignin-related methoxylated compounds in white-rot fungi utilizes non-canonical oxidoreductases

White-rot fungi (WRF) are the most effective lignin-degrading organisms in nature, making them essential to Earth’s carbon cycle. Lignin is a highly methoxylated, heterogeneous biopolymer derived from plants. However, the pathways WRF use to metabolize methoxylated aromatic monomericcompounds as carbon sources remain unidentified. Here, we employ a systems biology approach to elucidate the intracellular catabolism of vanillate – a monomethoxylated aromatic compound – in two white-rot fungi (WRF), Gelatoporia subvermispora and Trametes versicolor. We identified and biochemically validated a four-enzyme pathway that converts vanillate into ß-ketoadipate – a metabolite that enters central carbon metabolism. This pathway deviates from typical bacterial pathways, where vanillate is initially demethylated and ring-cleaved by intradiol dioxygenases; instead, oxidative decarboxylation occurs prior to ring cleavage by extradiol dioxygenases. Thus, we conducted an in-depth investigation of ring cleavage and further downstream catabolism by the identified fungal enzymes using biochemical and structural approaches. This revealed non-canonical enzymes, including a highly substrate-specific extradiol dioxygenase and a metal-free, promiscuous reductase, the latter capable of acting on catabolic intermediates derived from both methoxylated and non-methoxylated aromatic compounds. This work emphasizes the potential of WRF and their enzymes to advance lignin valorization and enhance our understanding of their role during wood decay.

dioxygenase↗
DOE OSTI2023

Toward implementation of carbon-conservation networks in nonmodel organisms

Decarboxylation — the release of carbon dioxide (CO 2 ) from a substrate — reduces the carbon yield of bioproduced chemicals. When overlaid onto central carbon metabolism, carbon-conservation networks (CCNs) that reroute flux around CO 2 release can theoretically achieve higher carbon yields for products derived from intermediates that traditionally require CO 2 release, such as acetyl-CoA. Recently, CCNs have started to be implemented in model organisms to produce compounds at higher carbon yields. However, implementation of CCNs in nonmodel hosts may have the greatest impact given their ability to assimilate a larger array of feedstocks, greater environmental tolerance, and unique biosynthetic pathways, ultimately enabling access to a wider range of products. Here, we review recent advances in CCNs with a focus on their application to nonmodel organisms. The differences in central carbon metabolism among different nonmodel hosts reveal opportunities to engineer and apply new CCNs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Vidyut3d: A GPU accelerated fluid solver for non-equilibrium plasmas on adaptive grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure three-electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate ~ 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Evolving Electricity Supply and Demand to Achieve Net-Zero Emissions: Insights from the EMF-37 Study

This paper explores the role of electricity in achieving economy-wide net-zero CO2 emissions by 2050 in the United States based on results from 17 models as part of the 37th Stanford Energy Modeling Forum (EMF-37). In the study's Net-Zero scenario, the models use diverse pathways to achieve net-zero emissions by 2050, with gross energy-related residual emissions ranging from 17.2 to 66.6 % of 2020 levels. Electricity consistently emerges as central to achieving net-zero, with models projecting rapid electrification of end-uses and rapidly declining CO2 intensity of electricity. However, the extent of electrification and the technology mix to decarbonize the power sector vary considerably across models. In the Net-Zero scenario, electricity is projected to evolve from ~20 % of final energy in 2020 to 17-63 % in 2050 across the models driven by electrification in all sectors-buildings, industry, and transportation-and, to a lesser extent by direct air capture. By 2050, total electricity consumption increases by 24-176 % (relative to 2020), accompanied by significant expansion in renewable electricity production. Together, solar and wind generation grows by 175-834 %, supplying 45-90 % of total electricity in 2050, with wind achieving slightly higher shares than solar. Electricity storage technologies are deployed at scale to support wind and solar generation. The electricity generation mix varies across models: some project almost complete reliance on renewables, while others see a substantial role for natural gas, often with carbon capture and storage. This paper synthesizes the rich diversity of modeling approaches and results, highlighting differing views on how key drivers of electricity demand and supply might evolve.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Smarter building start – A distributed solution

A significant focus of research and new technologies for reducing energy use in buildings is on operating the systems more efficiently during the times when the systems are active. However, there is a large potential for energy savings in determining the periods when the systems should or should not be active. This scheduling aspect of operation is often overlooked even though relatively simple solutions can unlock substantial energy savings. In this paper we describe a smart building start (SBS) algorithm that considers multiple zones in a building to determine individual schedules for room controllers as well as the central systems based on solving a simple optimization problem. Application of the SBS algorithm to multiple interconnected systems enables a staggered start-up that minimizes peak loads and also ensures comfort is within a target range with minimal system run time. The SBS algorithm extends the capability of traditional optimal start and is designed to be simple to deploy and robust. Simulation results as well as results from tests in a real building with a VAV system are presented. The presented algorithm is applicable to any type of building with a zonal or multi-zone HVAC system. To function, it needs to be able to change setpoints in rooms and monitor room temperatures, as well as, if desired, turn the central system on or off.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage

Due to heat prosumers' dual roles of heat producer and heat consumer, the future district heating (DH) systems will become more flexible and competitive. However, the current heating price models have not yet supported the reverse heat supply from prosumers to the central DH system, which means the prosumers would gain no economic benefit from supplying heat to the central DH system. These unidirectional heating price models will reduce interest in prosumers, and thus hinder the promotion of prosumers in DH systems. This study aimed to optimize prosumers' economic performance under the current heating price models by introducing water tank thermal energy storage (WTTES). A dynamic optimization problem was formulated to explore prosumers' economic potentials. The size parameter of WTTESs was swept in prosumers to obtain the optimal storage size considering the trade-off between the payback period and the heating cost saving. The proposed method was tested on a campus DH system in Norway. The results showed that the prosumer's annual heating cost was saved up to 9%, and the investment of WTTES could be recovered in less than ten years. This study could provide guidelines on improving prosumers' economic performance and promote the development of prosumers during the transformation period of DH systems.

Li, H↗
DOE OSTI2023

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗
DOE OSTI2024

Optimizing bioenergy sorghum productivity and nutrient removal in Illinois: Impact of nitrogen fertilization under diverse marginal conditions

Bioenergy sorghum (Sorghum bicolor L. Moench) is a promising crop for contributing to the United States bioenergy supply. However, the varying limitations of the marginal lands targeted for its cultivation present a management challenge. This two-year study aimed to investigate how the limitations associated with marginal cropland impact the effects of nitrogen fertilization on the yield of bioenergy sorghum and the uptake of 11 macro- (N, P, K, Ca, Mg, and S) and micronutrients (Fe, Mn, Zn, Cu, and B). The study contrasted prime cropland in central Illinois (Urbana) with three marginal cropland sites in southern (Ewing) and central Illinois (Fairbury and Pesotum). These marginal cropland sites are characterized by varying limitations, including low soil fertility (P and K limitations), leaching and erosion, and flooding, respectively. Four nitrogen rates (0, 56, 112, and 168 kg N ha –1 ) were tested under eight environments. The average yields and ranges of sorghum biomass were 20.2 (17.0–23.2) Mg ha –1 in Urbana, 18.1 (13.1–19.8) Mg ha –1 in Ewing, 13.8 (9.0–17.3) Mg ha –1 in Fairbury, and 23.3 (14.6–33.0) Mg ha –1 in Pesotum. Optimal N rates were 56 N in Pesotum and 112 N in Urbana, Ewing, and Fairbury. Tissue macronutrient contents in Urbana were generally higher than in the marginal croplands, while micronutrient contents did not show discernible trends. Increasing N rate generally correlated with the macronutrient removal except in Ewing. Comparable sorghum biomass yields were observed between prime and marginal croplands (averaging 18.3 Mg ha –1 ), but optimal N rates varied between 56 N and 112 N. This suggests that yield gaps can be narrowed by applying the optimal N rates for the respective locations. However, increased removals of macronutrients, especially P and K, with increasing yields indicate the need to revise fertilizer recommendations, particularly for soils deficient in these nutrients.

09 BIOMASS FUELS↗
DOE OSTI2021

First ITER CS module test results

The ITER Central Solenoid (CS) is under fabrication by the US ITER organization and its subcontractors. US ITER will supply seven modules to ITER IO, six of which will be assembled in a stack that forms the ITER Central Solenoid, with one as a spare. The first module fabrication has been completed by General Atomics (GA) at their facility and has begun testing including high voltage testing, Paschen testing in the vacuum and then testing at 4.5 K and up to 40 kA in order to demonstrate compliance of the coil to ITER requirements. In the paper we present the Test Plan and results of the CS Module performance tests, especially at 40 kA current. Herein, AC losses, joint resistances and hydraulic characteristics of the coil are all measured. Displacements of the coil height and hoop strain of the CS Module are also measured to verify structural and mechanical characteristics of the coil along with cooldown shrinkage of the coil. This information is used for verification of the stack behavior of CS in ITER operation. The test results and preliminary analyses results are presented, compared to expectations, and discussed. All measured parameters suggest that the CS module will perform well in ITER machine.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Assessing the sensitivity and repeatability of permanganate oxidizable carbon as a soil health metric: An interlab comparison across soils

Soil organic matter is central to the soil health framework. Therefore, reliable indicators of Soil organic matter is central to the soil health framework. Therefore, reliable indicators of changes in soil organic matter are essential to inform land management decisions. Permanganate oxidizable carbon (PDXC), an emerging soil health indicator, has shown promise for being sensitive to soil management. However, strict standardization is required for widespread implementation in research and commercial contexts. Here, we used 36 soils-three from each of the 12 USDA soil orders-to determine the effects of sieve size and soil mass of analysis on PDXC results. Using replicated measurements across 12 labs in the US and the EU (n = 7951 samples), we quantified the relative importance of 1) variation between labs, 2) variation within labs, 3) effect soil mass, and 4) effect of soil sieve size on the repeatability of PDXC. We found a wide range of overall variability in PDXC values across labs (0.03 to 171.8%; mean = 13.4%), and much of this variability was attributable to within-lab variation (median = 6.5%) independently of soil mass or sieve size. Greater soil mass (2.5 g) decreased absolute PDXC values by a mean of 177 mg kg -1 soil and decreased analytical variability by 6.5%. For soils with organic carbon (SOC) >10%, greater soil mass (2.5 g) resulted in more frequent PDXC values above the limit of detection whereas the lower soil mass (0.75 g) resulted in PDXC values below the limit of detection for SOC contents <5%. A finer sieve size increased absolute values of PDXC by 124 mg kg -1 while decreasing the analytical variability by 1.8%. In general, soils with greater SOC contents had lower analytical variability. These results point to potential standardizations of the PDXC protocol that can decrease the variability of the metric. We recommend that the PDXC protocol be standardized to use 2.5 g for soils <10% SOC. Sieve size was a relatively small contributor to analytical variability and therefore we recommend that this decision be tailored to the study purpose. Tradeoffs associated with these standardizations can be mitigated, ultimately providing guidance on how to standardize PDXC for routine analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Heat transfer augmentation of natural convection heat sink through notched fin design

A novel notched fin heat sink with a central opening is proposed in the present study to augment the heat transfer performance of the natural convection heat sink under horizontal configuration. Thermal and airflow behavior in the heat sinks were studied using both experimental and numerical methods. The results showed that the performance of the conventional heat sink can be enhanced by optimizing its fin design. The basic heat sink model provided a 17% reduction in thermal resistance when its fin height and fin spacing were doubled, and it was accompanied by a 21% increase in surface area. The heat sink with a notched fin design with a less surface area offered a 13% lower thermal resistance compared to the basic model by entraining more airflow into the interior fin region. Providing a central opening in the notched fin heat sink can further reduce the thermal resistance by about 13%. Further, this study also analyzed the influence of emissivity of the heat sink on natural convection conditions. The findings demonstrated that the heat sink with an emissivity of 0.9 can reduce the thermal resistance by nearly 23% compared to one with an emissivity of 0.15.

42 ENGINEERING↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗