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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Renewable Thermal Hybridization Framework for Industrial Process Heat Applications

Renewable thermal energy systems (RTES) could be hybridized with different renewable options (e.g., flat plate collectors (FPCs) with parabolic collectors), or combined with existing heat supplies (e.g., fossil fuels), to give options for targeted solar IPH applications, industrial decarbonization and the reduction of fuel consumption. Buildings and industrial thermal energy applications require different temperature ranges, quantities, and rates of thermal energy, and as such require flexible, cost competitive solutions, able to provide heat over various temperature ranges. Hybrid solutions and thermal energy storage (TES) will be important for the dispatch of heat at optimal times needed by the demand side of the buildings and industrial applications. A variety of tools and platforms, such as the System Advisor Model (SAM), can provide hourly thermal yield simulations from single renewable energy (RE) technology options, including FPCs or CSP for solar IPH. We have investigated a variety of approaches to hybrid system modeling for RTES at different temperatures or combinations of technologies and developed an initial framework. The hybridization framework starts by creating a heat stream and raising the temperature of that heat stream by various combinations of RE technologies and other sources such as fossil fuels, new fuels or electric heating in multiple stages, with options for TES and/or waste heat recovery (WHR).

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Multistage Surface-Heated Vacuum Membrane Distillation Process Enables High Water Recovery and Excellent Heat Utilization: A Modeling Study

Surface-heated membrane distillation (MD) enhances the energy efficiency of desalination by mitigating temperature polarization (TP). However, systematic investigations of larger scale, multistage, surface-heated MD system with high water recovery and heat recycling are limited. Here, we explore the design and performance of a multistage surface-heated vacuum MD (SHVMD) with heat recovery through a comprehensive finite difference model. In this process, the latent heat of condensation is recovered through an internal heat exchanger (HX) using the retentate from one stage as the condensing fluid for the next stage and an external HX using the feed as the condensing fluid. Model results show that surface heating enhances the performance compared to conventional vacuum MD (VMD). Specifically, in a six-stage SHVMD process, 54.44% water recovery and a gained output ratio (GOR) of 3.28 are achieved with a surface heat density of 2000 W m –2 , whereas a similar six-stage VMD process only reaches 18.19% water recovery and a GOR of 2.15. Mass and energy balances suggest that by mitigating TP, surface heating increases the latent heat trapped in vapor. The internal and external HXs capture and reuse the additional heat, which enhances the GOR values. We show for SHVMD that the hybrid internal/external heat recovery design can have GOR value 1.44 times higher than that of systems with only internal or external heat recovery. Furthermore, by only increasing six stages to eight stages, a GOR value as high as 4.35 is achieved. The results further show that surface heating can reduce the energy consumption of MD for brine concentration. As a result, the multistage SHVMD technology exhibits a promising potential for the management of brine from industrial plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dynamic optimization and economic evaluation of flexible heat integration in a hybrid concentrated solar power plant

Hybridization of concentrated solar power (CSP) plants provides flexibility in operation that can drastically improve the solar-to-electric (STE) efficiency and levelized cost of electricity (LCOE) relative to standalone CSP plants. Flexible heat integration (FHI) is a novel concept where the collection and integration of CSP within a power plant is modified relative to the amount of solar energy available. FHI improves the thermal efficiency of a hybrid solar tower steam Rankine cycle power plant but leads to increased pumping needs due to continuously elevated molten salt flow rates through the collection system, which can negatively impact STE efficiency. The present work is carried out to maximize the STE efficiency of a hybrid CSP plant utilizing FHI by employing a dynamic optimization framework where a genetic algorithm optimizes the operation of the plant over a given solar irradiance profile. The study concerns a plant hypothetically located in Salt Lake City, Utah. Here, the optimization results confirm the accuracy of a predictive heuristic where the preferred operation of the plant can be estimated relative to local peaks in the incident power generated by the heliostat collection field. The optimized FHI operation demonstrates a yearly STE efficiency of 13.8%, whereas the equivalent base-level hybrid and solar-only plants exhibit solar efficiencies of 13.4% and 11.2%, respectively. Economic analysis shows that FHI reduces yearly natural gas costs, leading to a $\$0.5$/MWh reduction in LCOE relative to the base-level hybrid configuration. Overall, the results show that hybrid FHI schemes exhibit economic benefits along with observed thermodynamic improvements.

14 SOLAR ENERGY↗
DOE OSTI2023

Cooling performance of an active-passive hybrid composite phase change material (HcPCM) finned heat sink: Constant operating mode

Here, the present study explores a hybrid thermal management technology based on air cooling and hybrid composite phase change material (HcPCM) filled finned heat sink for cooling performance of lower to medium heat flux dissipating electronic devices. Two-dimensional numerical simulations are conducted to study the conjugate heat transfer effects of three types of finned heat sink: air-cooled finned heat sink, HcPCM-cooled finned heat sink, and hybrid (air-HcPCM) cooled finned heat sink. A heat sink with a constant volume faction of plate-fins is designed in all cases and simultaneous effects of hybrid nanoparticles and air are investigated to keep the heat sink temperature at safe operating conditions between 40–60°C. The effect of air is incorporated into the heat sink by applying the convective heat transfer coefficient of h c = 10–100W /m 2 .K which tends to create the natural convection and forced convection heat transfer characteristics. The heat flux is varied from 25–40kW /m 2 in the current study. The hybrid nanoparticles of carbon additives (GO and MWCNTs) are dispersed into the RT-35HC, used as a PCM, with a volume fraction of 0% to 6%. Transient simulations are carried out using COMSOL Multiphysics to solve the governing equations for PCM based conjugate heat transfer model. The results showed that forced convection heat transfer improved the cooling performance of the hybrid heat sink compared to natural convection heat transfer. The addition of nanoparticles further enhanced thermal enhancement and uniform melting distribution of PCM inside the finned heat sink. The h c between 30 to 50W/m 2 .K shows optimized values for forced convection heat transfer operating conditions. The volume fraction of 2% of GO+MWCNTs nanoparticles in recommended or optimum concentration for uniform melting of PCM inside the finned heat sink.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Kusmec, Aaron (ORCID:000000032295385X)↗
DOE OSTI2024

High performance heat exchangers for next generation hybrid cooler (CRADA Final Report)

The evaporative cooling process has been successfully deployed in multiple energy conversion processes such as power generation, process cooling, heating, ventilation & cooling (HVAC), and commercial and industrial refrigeration. The heat exchanger is a very common yet extremely critical component of such systems. The device is important since the performance of the overall cooling system heavily relies on the thermal-hydraulic efficiency of the heat exchanger. The possible wet operation as evaporative cooling heat exchanger complicates the issue. Indeed, based on the hybrid nature of operation (fully dry, partially wet, fully wet) the efficiency can vary significantly and can cause performance variation for the whole system. Understanding the importance of the issue, Oak Ridge National Laboratory (Contractor) and Baltimore Aircoil Company (Participant) propose an activity focused on the analysis of the existing heat exchanger technology used in air and evaporative cooling processes and design, development and demonstration of a novel heat exchanger design based on porous materials. The potential candidates include metallic wire meshes and metal foams carefully designed for the proposed application. Prior research has indicated that these materials have great potential for deployment in thermal systems, particularly heat sinks and heat exchangers. It is expected that the successful completion of the project will lead to novel heat exchanger technology for hybrid systems (capable of dry and wet operation) by exploring newly emerging materials and their potential for heat transfer application. The overall goal is to develop a next generation heat exchanger technology which can be deployed in evaporative cooling systems. The impact of the such development is significant since, it will not only make the overall system highly efficient but will also, reduce the total refrigerant charge in the heat exchanger, a critical aspect for the deployment of refrigerants with lower Global Warming Potential (GWP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Hybrid metal-polymer heat exchanger

A heat exchanger includes a metal tube and a composite polymer fin in thermal contact with the metal tube. The fin is formed of a polymer and a thermally conductive filler such that the fin has a thermal conductivity greater than or equal to 0.5 Watts per meter Kelvin.

42 ENGINEERING↗
DOE OSTI2024

High performance heat exchangers for next generation hybrid cooler (CRADA NFE-19-07891 Final Report)

The evaporative cooling process has been successfully deployed in multiple energy conversion processes such as power generation, process cooling, heating, ventilation & cooling (HVAC), and commercial and industrial refrigeration. The heat exchanger is a very common yet extremely critical component of such systems. The device is important since the performance of the overall cooling system heavily relies on the thermal-hydraulic efficiency of the heat exchanger. The possible wet operation as evaporative cooling heat exchanger complicates the issue. Indeed, based on the hybrid nature of operation (fully dry, partially wet, fully wet) the efficiency can vary significantly and can cause performance variation for the whole system. Understanding the importance of the issue, Oak Ridge National Laboratory (Contractor) and Baltimore Aircoil Company (Participant) propose an activity focused on the analysis of the existing heat exchanger technology used in air and evaporative cooling processes and design, development and demonstration of a novel heat exchanger design based on porous materials. The potential candidates include metallic wire meshes and metal foams carefully designed for the proposed application. Prior research has indicated that these materials have great potential for deployment in thermal systems, particularly heat sinks and heat exchangers. It is expected that the successful completion of the project will lead to novel heat exchanger technology for hybrid systems (capable of dry and wet operation) by exploring newly emerging materials and their potential for heat transfer application. The overall goal is to develop a next generation heat exchanger technology which can be deployed in evaporative cooling systems. The impact of the such development is significant since, it will not only make the overall system highly efficient but will also, reduce the total refrigerant charge in the heat exchanger, a critical aspect for the deployment of refrigerants with lower Global Warming Potential (GWP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Renewable Thermal Hybridization Framework for Industrial Process Heat Applications

Solar industrial process heat (SIPH) technologies, such as concentrating solar power collectors, could economically replace the steam or heat needs at many industrial sites by providing high-temperature heat transfer fluids (HTFs) such as pressurized water, synthetic-oil, or direct steam. Renewable thermal energy systems (RTES) could be hybridized with different renewable options e.g., flat plate collectors with parabolic trough collectors, or combined with existing heat supplies (e.g., fossil fuels), to give options for targeted SIPH applications, industrial decarbonization and the reduction of fuel consumption. Hybrid solutions and thermal energy storage will be important for the dispatch of heat at optimal times needed by the demand side of the buildings and industrial applications. At present, there is no integrated modeling tool for hybrid RTES, and this paper highlights the development of a renewable thermal hybridization framework for IPH use that is built from existing tools like System Advisor Model. The long-term vision for the framework (through significant further research) is to develop a coupled hybrid energy generation and cost analysis tool, where the tool could help the user in determining the most suitable and cost-effective technologies for their applications. Ongoing work will look to add costs for RTES options and further refinement on the selection of suitable technologies. This future tool could calculate the levelized cost of heat of various RTES hybrid options, by taking the user's solar resource, fuel costs, industrial heat demand profile, available land, and other factors into account to determine the applicability into their process.

concentrating solar power↗
DOE OSTI2021

Lawrence Livermore National Laboratory (LLNL) Hybrid-Energy Technology for Power and Industrial Heat with Near-Zero or Negative CO 2 Emissions

Major contributors to global CO 2 emissions include electricity (27%) and industry (23%), such as cement manufacturing (8%). Using post-combustion technology to reduce CO 2 emissions by 85-90% could increase the cost of generating electricity with fossil fuel by 40-70%, while increasing cement-manufacturing cost by 75-140%. Both sectors are under pressure to reduce CO 2 emissions and are seeking cost-effective, energy-efficient solutions to decarbonizing energy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Physics-based hybrid machine learning for critical heat flux prediction with uncertainty quantification

Critical heat flux (CHF) is a key quantity in nuclear system modeling due to its impact on heat transfer, safety margins, and reactor performance. This study develops and validates an uncertainty-aware hybrid modeling approach that combines machine learning with physics-based models to predict CHF in cases of dryout. The Biasi and Bowring empirical correlations were paired with three ML uncertainty quantification (UQ) techniques: deep neural network (DNN) ensembles, Bayesian neural networks (BNNs), and deep Gaussian processes (DGPs). A pure ML model without a base model was evaluated for comparison. Model performance was assessed under plentiful (7,350 points) and limited (9 points) training data scenarios using parity, uncertainty distributions, and calibration curves. Results show that the Biasi hybrid DNN ensemble achieved the best overall performance, with a mean absolute relative error of 1.846%, and well-calibrated uncertainty estimates. The BNN-based hybrids showed slightly higher error (2.14%) but superior uncertainty calibration. DGP models underperformed, with over 6% error and poor uncertainty calibration. All hybrid models outperformed pure machine learning configurations, demonstrating resistance against data scarcity. These findings indicate that hybrid modeling significantly improves predictive accuracy, interpretability, and resilience to data scarcity. The integration of uncertainty awareness provides actionable confidence in CHF predictions, which is vital for safety-critical decisions in nuclear applications. This hybrid approach offers a viable pathway for deploying ML models in reactor analysis tools while preserving domain knowledge and physical consistency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Plasma heating by electron cyclotron wave and the temperature effects on lower hybrid current drive on EAST

This paper presents the progress in the long—pulse operation of the electron cyclotron (EC) system and the achievements in high—electron temperature plasmas by the combined EC and lower hybrid (LH) waves heating since the EC system was built in 2015. An electron temperature of up to 12 keV with a duration over 100 s was realized by the simultaneous heating of EC and LH waves at the line-averaged density ${\bar n_{\text{e}}}$ ~1.8 × 10 19 m –3 . The plasma heating effect strongly depends on the location of EC power deposition. H-mode plasmas with solely EC wave auxiliary heating have been obtained on EAST for the first time. These H-mode discharges show an enhanced confinement factor H 98(y,2) around 1.0, which is higher than the previous H-mode using LH power alone (Xu et al 2011 Nucl. Fusion 51 072001). The total heating power is very close to the threshold value for L–H transition according to the international tokamak scaling. In addition to the temperature effects inside the separatrix, higher electron temperature produced by EC wave is found to reduce the LH power loss in the scrape-off layer due to collisional absorption, which is beneficial to further increase the LH current drive efficiency. Ray-tracing/Fokker–Planck modeling results indicate that higher electron temperature can shorten the LH wave propagation on EAST in a multiple-pass regime, thus decreasing the collisional dissipation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Deployment of Traditional and Hybrid Machine Learning for Critical Heat Flux Prediction in the CTF Thermal-Hydraulics Code

Critical heat flux (CHF) marks the transition from nucleate to film boiling, where heat transfer to the working fluid can rapidly deteriorate. Accurate CHF prediction is essential for efficiency, safety, and preventing equipment damage, particularly in nuclear reactors. Although widely used, empirical correlations frequently exhibit discrepancies when compared to experimental data, limiting their reliability in diverse operational conditions. Traditional machine learning (ML) approaches have demonstrated potential for CHF prediction but often suffer from limited interpretability, data scarcity, and insufficient knowledge of physical principles. Hybrid model approaches, which combine data-driven ML with base models, mitigate these concerns by incorporating prior knowledge of the domain. This study integrates an externally trained purely data-driven ML model and two hybrid models (using the Biasi and Bowring CHF correlations) within the CTF subchannel code via a custom Fortran framework. Performance was evaluated using two validation cases: a subset of the Nuclear Regulatory Commission (NRC) CHF database and the Bennett dryout experiments. In both cases, the hybrid models demonstrated significantly lower error metrics compared to conventional empirical correlations, with the best models often reducing relative error by about 5 percentage points. The pure ML model achieved comparable accuracy, outperforming the hybrid Biasi model in the NRC test case (3.3% versus 5.5% relative error) but exhibiting slightly higher error against the hybrid Bowring model in the Bennett test case (7.7% versus 6.1%). Trend analysis of error parity indicated that ML-based models reduced the tendency for CHF overprediction, improving overall accuracy. These results demonstrate that ML-based CHF models can be effectively integrated into subchannel codes and could potentially increase performance compared to conventional methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Hybrid-energy approach enabled by heat storage and oxy-combustion to generate electricity with near-zero or negative CO 2 emissions

We assess a hybrid-energy approach that modifies a steam-turbine power plant to use renewable energy sources (electricity, plus options for geothermal and solar heat), plus fossil fuel (natural gas and coal) and/or waste biomass (e.g., Douglas fir woodchips). Heat storage allows heat to be created during periods of excess energy supply and for that heat to be converted to electricity when demanded. Excess electricity, such as from variable renewable energy (VRE), is used to generate oxygen for oxy-combustion furnaces that create very-hot, high-purity CO 2 that heats granular rock beds in insulated vessels. Cool CO 2 leaving the beds is dried, sent to compressors powered by excess VRE electricity, before being sent by pipeline to geologic CO 2 storage. Very-hot CO 2 transfers high-grade heat from storage to the power plant in a closed loop that returns medium-grade heat back to storage, allowing low- and medium-grade renewable-heat sources to be stacked beneath combustion heat, with all heat sources being converted to electricity at the same (high) thermal efficiency. Reliable, on-demand power may be generated with near-zero CO 2 emissions with fossil fuel and with negative CO 2 emissions with waste biomass. Our analyses show that with fossil fuel, up to 35% of gross power can be derived from renewable sources, while for waste biomass, it can be entirely derived from renewable sources. Because our approach has the potential to ensure that grids have a continuous supply of clean energy and because electricity is only generated once, when demanded, it could serve as an efficient alternative to bulk energy storage.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission

This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.

Li, Zhenning↗
DOE OSTI2020

Lower-Hybrid Drift Waves Driving Electron Nongyrotropic Heating and Vortical Flows in a Magnetic Reconnection Layer

Here, we report measurements of lower-hybrid drift waves driving electron heating and vortical flows in an electron-scale reconnection layer under a guide field. Electrons accelerated by the electrostatic potential of the waves exhibit perpendicular and nongyrotropic heating. The vortical flows generate magnetic field perturbations comparable to the guide field magnitude. The measurements reveal a new regime of electron-wave interaction and how this interaction modifies the electron dynamics in the reconnection layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗