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Hydrogen/Metal Hydride Based Heat Pump System for Large HVAC Applications Utilizing an Ionic Liquid Desiccant Subsystem [Slides]
A multi-stage electrochemical hydrogen compressor incorporates membrane-electrode-assemblies (MEAs) separated by proton exchange membranes (PEMs) in series to reach higher pressures, when a current is passed through the MEA protons and electrons are generated at the anode. The protons are electrochemically driven across the membrane to the cathode, after which they combine with the rerouted electrons to form hydrogen, which is fed to the hydrogen compressor to be oxidized at the anode of each cell to form protons and electrons. This type of compressor has no moving parts and can be applied to refrigeration systems technologies. This project investigated the viability of commercialization of heat pumps based on electrochemical compressor technology.
SCALE Analyses of Scenarios in the TRISO-based Heat Pipe Microreactor Fuel Cycle
This report documents the application of the SCALE code to the analysis of a TRistructural-ISOtropic (TRISO)-based heat pipe microreactor (HPMR) within the context of its nuclear fuel cycle stages. The evaluation was conducted in support of the US Nuclear Regulatory Commission’s ongoing efforts to assess modeling capabilities for advanced non–light-water reactor technologies. The generic HPMR selected as a representative microreactor concept features a compact core design that incorporates TRISO fuel compacts, passive heat removal via heat pipes, and a transportable configuration intended for deployment in remote environments.
Techno-economic analysis and environmental benefits of solar industrial process heating based on parabolic trough collectors
In this work, detailed techno-economic and environmental analyses are conducted for employing a 5 MWt parabolic trough-based solar industrial process heat (SIPH) plant in Salt Lake City, Utah. According to the results, an optimum solar multiple of 1.5 was determined, allowing the plant to generate annual thermal energy of 15389.24 MWth with a capacity factor of 35.1% and levelized cost of heat (LCOH) of $\$ 26.3$/MWth. Considering a 30% investment tax credit and a 30% reduction in the total installed cost could reduce the LCOH to $\$ 19.30$/MWth and $\$ 18.52$/MWth, respectively. Employing parabolic trough collectors could avoid emissions of 3,582,422.47 kg, 147.99 kg, 3,341.66 kg, and 14.32 kg for CO 2 , PM, NOx, and SO 2 , respectively per year compared to a natural gas-based plant. Further, it also caused an annual external cost savings of between $\$ 99,900$ and $\$ 357,004$. Including the external costs in the LCOH analysis shows that the SIPH plant is economically competitive with a natural gas-based plant, further demonstrating its value. A further comparison demonstrated the economic superiority of a parabolic trough-driven IPH plant over a photovoltaic-driven electric boiler plant. In summary, with reducing installed costs and providing incentives, parabolic trough-driven IPH plants will be an economically and environmentally viable option.
Numerical simulation for the design of induction heating based radio frequency reactor for ethylene production
Ethylene is a vital petrochemical compound produced in vast amounts yearly by manufacturers that have enough scale to overcome the inherent thermodynamic inefficiencies of the process. In order to address the inefficiencies that prevent smaller scale or intermittent production ethylene, investigation of new production methods are required. In this work, we investigate the use of a radio frequency (RF) based reactor system that generates heat internally as opposed to applying heat externally via steam or direct combustion of fossil fuels. In order to guide the design of an electromagnetic based reactor system, we have created a macroscale model capable of capturing heat generation at the susceptors from a produced electromagnetic field and subsequent chemical reactions. Several susceptor and induction coil designs were investigated to better understand the performance of the system.
A CONDUCTION-BASED HEAT PIPE MODEL FOR ANALYZING THE ENTIRE PROCESS OF LIQUID-METAL HEAT PIPE STARTUP
The Heat Pipe-cooled Microreactor (HPM) is one of the micro nuclear reactor designs under active study at the U.S. Idaho National Laboratory. Among the major concerns of HPM research is to understand the startup behavior of the heat pipe-cooled system associated with the startup of the liquid-metal heat pipes initialing from frozen state. The startup of liquid-metal heat pipes typically involves a number of nonlinear mass and heat transport processes including the phase change from solid to liquid and vapor. Hence, it is still a huge challenge to simulate the liquid-metal heat pipe startup using conventional CFD methods and software. The major difficulties of numerical CFD modeling come from the phase-change process, multiphase interaction, microporous wick flow, and compressible gas dynamics that occur during startup of the liquid-metal heat pipes. This paper proposes a simplified conduction-based method to provide practical insights into the entire startup process of the liquid-metal heat pipes while mitigating the challenges of addressing all the complex physics. We discuss the theoretical basis and modeling assumptions to analyze the liquid-metal heat pipe startup from frozen state based solely on heat-conduction equations. Then, the proposed model is implemented into the commercial CFD software to verify the model performance. The model prediction results are discussed via the comparison with the experimental data obtained from sodium heat-pipe startup experiments.
An experimental study on dehumidification and regeneration performance of a new nonporous membrane-based heat and mass exchanger using an ionic liquid desiccant
As a promising alternative to inefficient vapor-compression-based air conditioning, liquid desiccant dehumidification uses a liquid desiccant in contact with the humid air absorbing the moisture. However, it has not gained much market share due to the issues related to the carryover, corrosion, fouling, and crystallization of liquid desiccant. The research has developed a new membrane-based exchanger, which uses a non-corrosive ionic liquid desiccant and nonporous tubular membranes to address these issues. As the second generation of the prototype, the new exchanger was tested at various operating conditions. According to the experimental data, when it is used in the dehumidification loop, the new membrane-based exchanger achieves a specific vapor transportation rate of 778.6 g/(h–m 2 ) and an average water vapor flux of 0.316 g/(h-m 2 -Pa), which is a significant improvement compared with the previous designs using nonporous membranes. It also achieved a comparable or even better dehumidification performance compared with the dehumidifiers that use porous membrane and conventional liquid desiccants. However, the regeneration performance is not as good as its dehumidification. It is mainly caused by the high operating temperature required in the regeneration loop. The experimental data and findings provide first-hand experimental data and enhance the understanding of advanced membrane-based ionic liquid desiccant systems.
Heat Based Power Augmentation for Modular Pumped Hydro Storage in Smart Buildings Operation
In the U.S., building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground-level. This unique design eliminates the geographical limitation associated with existing state of the art energy storage technologies. It is easy to be scaled for building level, community level and grid level applications. Using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g. from thermal storage, Combined Cooling, Heat and Power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Several groups of comparison experiments have been conducted and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.
Design, optimization, and validation of a triply periodic minimal surface based heat exchanger for extreme temperature applications
Heat exchanger (HX) innovation offers potential for significant improvements in energy efficiency for a host of applications including but not limited to aviation and power generation cycles. Triply Periodic Minimal Surfaces (TPMS) have received significant attention in recent years due to their incredibly high surface area density, which makes them very attractive from a heat transfer point of view. Recent efforts have largely focused on thermal-hydraulic characterization of the many available TPMS and the testing of small-scale HX prototypes. However, practical implementation remains largely unexplored, partially due to the extreme computational cost associated with accurately simulating these complex structures. In this work, we present the design, simulation, and optimization of a TPMS-HX for high temperature (900 °C) and pressure (25 MPa) applications. Detailed analysis of HX sub-sections is conducted to define the smallest repeatable section which may be used to characterize the thermal-hydraulic performance of the entire HX, enabling rapid design and iteration with significantly reduced computational cost. Compared to preliminary results for a water-to-water experiment, calibrated heat transfer and pressure drop predictions were within ±5 % and ±10 %, respectively. Optimization results show a 10x increase in volumetric power density over the initial design, which is verified against a parametric exhaustive search of the HX design space. Furthermore, it was found that reducing the unit cell hydraulic diameter cell plays the largest role in increasing heat transfer, increasing the surface area density and enabling a more compact and efficient HX.
Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides
Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.
A Data-Driven Approach to Embed Advection-Based Heat Flux Into Conduction-Only Porous Heat Transfer Models
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Evaluation of Mechanical and Thermomechanical Water Vapor Compression Techniques for Enabling High Temperature Lift Hydration-Based Chemical Heat Pumps
Achieving high temperature lifts (>200 K) via a chemical heat pump based on salt hydration/dehydration reactions requires the transport of water vapor from low to high pressure. Alternative compression approaches require condensing of low-pressure water vapor, pumping of liquid water, and subsequent evaporation when the low-side pressure corresponds to sub-ambient water saturation temperatures. Thus, this study compares four steam compression methods for use within a chemical heat pump system based on a reversible calcium oxide hydration/dehydration reaction with a temperature lift from 350 °C heat to >600 °C. Purely mechanical and thermochemical/mechanical compression technologies are considered. A parametric study of maximum allowable temperature, the isentropic efficiency of mechanical compressors, the effectiveness of heat exchangers, and the assumed allowable heat exchanger pressure drop is conducted to determine the mechanical and thermal energy consumed per kilogram of compressed steam. The system complexity in terms of the number of main system components, maximum pressure ratio, and maximum allowable temperature is estimated. Model results show an absorption-based steam compressor has the highest exergetic efficiency for the required chemical heat pump required conditions. As a result, this system configuration was then experimentally demonstrated to illustrate the impact of system performance on component effectiveness.
Al-Ce Alloy-Based Compact Heat Exchanger for Refrigerant Charge Reduction and Unprecedented Durability (CRADA NFE-21-08888 Final Report)
Oak Ridge National Laboratory and Eck Industries produced and characterized durable and corrosion resistant Al-Ce-Mg alloy-based heat exchanger. Eck Industries successfully casted Al-Ce-Mg heat exchanger. ORNL characterized reaction bonding between Al-2Ce-6Mg alloy and stainless-steel tube in a heat exchanger header. Metallurgical bonds were achieved between stainless steel tubes and Al-Ce-Mg alloy cast headers. ORNL performed corrosion testing on Al-Ce-Mg alloy/stainless steel tube reactive bond interface. In most cases no significant changes to the reactive bond morphology or compositional distribution were observed in the samples after exposure to acid for 267h acid.
Experimental Investigation of a Novel Membrane-Based Condensing Heat Exchanger for High Efficiency Furnaces
Building space heating consumes approximately one-third of all global natural gas end use. Higher-efficiency (i.e., condensing) furnaces constitute only about 30% of the annual furnace shipments in the United States because the condensing heat exchangers must use highly expensive, corrosion-resistant materials to be protected from acidic components in the furnace flue gas stream. Increasing the market share of high-efficiency furnaces will reduce greenhouse gas emissions. This study developed and tested a benchtop prototype of a novel membrane-based heat exchanger (MHX) for high-efficiency furnaces to achieve nonacidic condensation via nanoporous membranes. Test results show that both sensible and latent heat were recovered by the MHX, and the fraction of latent heat recovery ranged from about 25% to 45% over the range of operating conditions evaluated. The amount of water condensed through the MHX increased with the increase of flue gas flow rate and decreased with increasing coolant temperature. The fraction of latent heat recovery decreased with the increase of flue gas flow rate and coolant temperature. The pH value of condensed water from the MHX was only mildly acidic, varying from 5.3 to 5.6 without any additional treatment, about 2.0 to 2.3 pH points higher (i.e., less acidic) than typical values for the condensate from conventional condensing furnaces. Therefore, feasibility of the MHX was experimentally verified, and the MHX could enable wider market penetration of highly energy-efficient condensing furnaces by reducing costs associated with managing the acid condensation compared with conventional condensing furnaces, possibly enabling the use of existing vent systems when replacing noncondensing furnaces (due to higher flue gas exit temperatures), and possibly reducing furnace first costs.
Al-Ce Alloy-Based Compact Heat Exchanger for Refrigerant Charge Reduction and Unprecedented Durability
• Oak Ridge National Laboratory and Eck Industries produced and characterized durable and corrosion resistant Al-Ce-Mg alloy-based heat exchanger. • Eck Industries successfully casted Al-Ce-Mg heat exchanger. • ORNL characterized reaction bonding between Al-2Ce-6Mg alloy and stainless-steel tube in a heat exchanger header. • Metallurgical bonds were achieved between stainless steel tubes and Al-Ce-Mg alloy cast headers. • ORNL performed corrosion testing on Al-Ce-Mg alloy/stainless steel tube reactive bond interface. • In most cases no significant changes to the reactive bond morphology or compositional distribution were observed in the samples after exposure to acid for 267h acid.
Design screening and analysis of gas-fired ammonia-based chemisorption heat pumps for space heating in cold climate
Thermally-driven ammonia-based chemisorption heat pumps (CSHP) have the potential to provide high-efficiency space heating in cold climates. Using the reversible chemical bond between sorbent salt and ammonia, CSHP thermochemically pumps heat from the cold ambient to the end-uses of space heating at 50 °C. The heating coefficient of performance (COP) of a CSHP largely depends on the selection of the sorbent salts, cycle configuration, and the system operation. This study uses a thermodynamic model to investigate the performance of six CSHP system configurations, including four single-effect and two double-effect cycles. The feasibility and performance of 121 available NH 3 /salt reactions are studied for each configuration. The thermal COP of the cycles and the primary energy COP of the gas-fired CSHP systems are evaluated assuming 50 °C supply temperature for building space heating and the optimal system designs are identified. The highest thermal COP for single-effect and double-effect cycles under -25 °C ambient temperatures are predicted to be 1.22 and 1.57, respectively. The corresponding primary energy COPs are above 1.0 and 1.15, which are 30% higher than condensing furnaces and is sustained into the same cold temperatures.
Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)
RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.
Suitable low Global Warming Potential (GWP) refrigerants for two-speed Heat Pumps for residential applications based on speed Heat Pumps for residential applications based on simulated performance simulated performance
Cold climate Heat Pumps (CCHPs) using single-speed compressors in tandem have been successfully built and tested to reach its performance metrics with outdoor temperatures as low as -25°C. CCHPs must be designed to alleviate the problems of too high discharge temperatures, low suction pressure and high-pressure ratio at low ambient conditions and insufficient heating capacity relative to the heating capacity at 8.3°C. In this paper we recognize those concerns. Low-GWP refrigerants are screened based on the shape of their T-S saturation boundary. Simulations of the performance of low-GWP refrigerants (R32, R454B, R466A, and R452B) relative to R410A is done using the DOE/ORNL Heat Pump Design Model at the component level. Systemic inefficiency, the root cause of lost work, is addressed by component-level exergy analysis to refine design options. CCHPs using low-GWP refrigerants addresses issues of reducing energy consumption, lowering carbon footprint, and enabling environmentally sustainability. The CCHP was designed to meet a HSPF > 11.0 and SEER > 15.0 having adequate heat pump heating capacity down to -25°C. It is estimated that at least 2.6 million U.S homes using electric furnaces and heat pumps in cold or very old climates with an annual energy consumption of 0.17EJ would benefit by CCHPs.