Search NASA⌕ Search

SEARCH · Search NASA

Results for “Heating elements”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Acid digestion processes for recovery of rare earth elements from coal and coal byproducts

A system for recovering rare earth elements from coal ash includes a leaching reactor, an ash dryer downstream of the leaching reactor, and a roaster downstream of the ash dryer that is cooperatively connected to both the leaching reactor and the ash dryer. Coal ash is mixed with an acid stream such that rare earth elements present in the coal ash are dissolved in the acid stream, thereby creating (i) a leachate containing the rare earth elements and (ii) leached ash. The leachate is heated to obtain acid vapor and an acid-soluble rare earth concentrate. Mixing of the coal ash with the acid stream can occur in a leaching reactor and heating of the leachate can occur in a roaster. The acid-soluble rare earth concentrate can be fed to a hydrometallurgical process to separate and purify the rare earth elements.

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

Wireless Instrumented RB Experiment Preliminary Design and Analysis

The ability to deploy new nuclear fuels for current or future reactor concepts requires carefully designed experiments to generate data to support fuel qualification. Ideally these experiments would include state of-the-art sensing to maximize the amount of in situ data that can be collected during operation. Furthermore, advanced reactor systems can take advantage of integrated in-core sensing technologies to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator’s understanding of limiting peaking factors. Before any novel sensing technologies can be readily adopted for nuclear applications, they must first demonstrate acceptable performance in test reactors. This report summarizes the preliminary design and analysis of the most highly instrumented irradiation experiment ever performed in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Wireless Instrumented RB Experiment 2021 (WIRE-21) will test a wide range of sensors including wireless sensors being developed by Westinghouse Electric Company (WEC) that could provide in situ measurements of peak fuel temperatures and fuel rod pressurization due to fission gas release. The ability to wirelessly transmit a signal through the fuel rod’s cladding is critical to improving fuel monitoring capabilities without requiring signal penetrations through the cladding pressure boundary, which would significantly impact fuel fabrication, handling, and operation. Other sensors that will be tested in WIRE-21 include an array of thermocouples, self-powered neutron detectors (SPNDs), and spatially distributed fiber-optic temperature sensors. More generally, WIRE-21 will establish a flexible irradiation vehicle design to allow accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. This report summarizes the mechanical design for WIRE-21, the experimental test matrix, initial neutronic and thermal design analyses, and the active monitoring and control system enhancements necessary to support testing of advanced sensor technologies. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) relevant to light water reactors (LWRs), but the flexible design of the experiment vehicle allows much higher operating temperatures (>1,100°C). Neutronic calculations determine the neutron flux conditions as well as the nuclear heating within the experiments. These results are used as inputs to detailed thermal finite element calculations, which are required to evaluate the complex, three-dimensional heat transfer that occurs within WEC’s wireless sensor enclosures. Initial results show that the temperatures of the sensors’ enclosures and the metal bellows can be operated near the temperature range of LWR coolants and cladding while simultaneously increasing the temperature of a surrogate fuel material to values in the range of 800–1200°C to simulate centerline fuel temperatures during LWR operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Thermal conductivity modeling of monodispersed microspheres using discrete element method

Particle beds are widely used in various systems and processes, such as particle heat exchangers, granular flow reactors, and additive manufacturing. Accurate modeling of the thermal conductivity of particle beds and understanding of their heat transfer mechanisms are important. However, previous models were based on simple cubic packing of particles, which could not accurately represent the actual heat transfer processes under certain conditions. Here, we examine the effect of the packing structure on the thermal conductivity of particle beds. We use monodispersed silica microspheres with average particle sizes ranging from 23 to 330 μm as a model material. We employ a transient hot-wire technique to measure the thermal conductivity of the particle beds with packing density of 43%–57% within a temperature range of room temperature to 500 °C and under N2 gaseous pressures of 20–760 Torr. We then use a discrete element method (DEM) to obtain the realistic packing structure of the particles, which is then fed into a finite-element model (FEM) to calculate the thermal conductivity, with the consideration of solid conduction, gas conduction, and radiation heat transfer. Our results show that the thermal conductivity model based on the more realistic random packing structure derived from the DEM shows better agreement with the experimental data compared to that based on the simple cubic-packing structure. The combined DEM and FEM methodology can serve as a useful tool to predict the effective thermal conductivity of particle beds and to quantify different heat transfer mechanisms under various conditions.

14 SOLAR ENERGY↗
DOE OSTI2021

Sockeye: A One-Dimensional, Two-Phase, Compressible Flow Heat Pipe Application

Sockeye is a heat pipe analysis application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework. The primary purpose of Sockeye is to provide a transient heat pipe simulation tool to be used in the analysis of nuclear microreactor designs. Sockeye provides the capability to perform one-dimensional, two-phase, compressible flow simulation of a heat pipe working fluid and two-dimensional, axisymmetric heat conduction for the heat pipe cladding and its surroundings. Sockeye is demonstrated against analytical solutions and experimental data from the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Custom-designed heat treatment simultaneously resolves multiple challenges facing 3D-printed single-crystal superalloys

Single-crystal Ni-based superalloys are currently the material of choice for turbine blade applications, especially with the emerging additive manufacturing (AM) that facilitates the manufacture/repair of these single crystals. This promising AM route, however, comes with a dilemma: in the fusion and heat affected zones after e-beam or laser induced melting, one needs a solutionizing annealing to relieve the residual stresses and homogenize the chemical/microstructure. The super-solvus solutionizing temperature is usually adopted from the protocol for the cast superalloys, which almost always causes recrystallization and stray grain growth, resulting in a polycrystalline microstructure and degrading the high-temperature mechanical performance. Here, in this paper, we demonstrate a custom-designed post-printing heat treatment to replace the conventional super-solvus one. The recovery and relatively low temperature diminish the driving force for recrystallization and the movement of stray grain boundaries, without suffocating the chemical/microstructural homogenization thanks to the narrow dendrite width and short element segregation distance. The optimal duration of the heat treatment is proposed to achieve atomic-diffusion mediated chemical homogenization while limiting γ'-particle coarsening in the interdendritic regions. Our strategy makes it practically feasible to resolve several bottleneck problems with one processing/treatment, removing a seemingly formidable obstacle to effective additive manufacturing of superalloy single crystal products.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Foams in Hohlraums

Foam materials are starting to find application in laser-heated hohlraums used to drive inertial confinement fusion (ICF) implosions. The disparate scales of the solid foam elements (nm) compared to the typical problem scale (mm) make it expensive to resolve the individual foam elements in hydrodynamic calculations. In this project we developed two new models for treating foam materials – a 3D hydrodynamic model that treats the foam as bits of pre-expanded solid material separated by voids, and a subgrid model that captures the essential physics of laser-heated foams without requiring resolution of the individual solid elements. We also explored the microphysics of the transition from interpenetrating kinetic behavior to fully-collisional fluid-like behavior during the early time heating and expansion of foam elements through a combination of single-fluid and multi-fluid hydrodynamics calculations and particle-in-cell calculations. The model was benchmarked against these calculations and against experimental data on laser-heated chemical and additive-manufactured (AM) foams. Since there was no existing data on laser-heated AM foams, we performed the first experiments on such foams at the Jupiter Laser Facility. Samples of three different types of printed AM foams were heated using a single 0.5 micron laser. The foam densities ranged from 10 to 100 mg/cc (supercritical for 0.5 micron light). We measured the backscattered light (power and spectrum), the transmitted light, and the time-integrated temperature of the foam samples. This benchmarked subgrid foam model is a new capability that should allow routine calculation of ICF designs using foam elements, potentially opening up a new design space.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Integrating three plan evaluation approaches for coordinated heat resilience in cities across the Arizona urban corridor

Increasing heat poses a growing threat to cities worldwide due to both climate change and the urban heat island effect. While heat planning and governance are still emergent, research suggests that silos and conflicts within cities' networks of plans often impede heat resilience. Integrated heat resilience planning, therefore, requires a systematic and comprehensive analysis of the silos and conflicts relevant to heat resilience within networks of plans. This study is the first to combine three complementary plan evaluation methods to assess how cities' networks of plans address heat resilience. We applied 1) plan cross-referencing, 2) Plan Quality Evaluation for Heat Resilience, and 3) Plan Integration for Resilience Scorecard™ (PIRS™) for Heat to 19 plans from seven Arizona cities. We find similarities and differences in how these cities' networks of plans address heat hazards. The plans have consistently high-quality participation and coordination principles but lack details on vulnerability and climate change uncertainty, suggesting a need to move beyond immediate heat risks. We also identify opportunities to diversify policy mechanisms, spatially target high heat risk areas, and enhance the connection between planning efforts. These results validate that plan elements are interlinked and the importance of integrative plan development processes to improve heat resilience.

Extreme heat↗
DOE OSTI2020

Heat Flux Analysis From IR Imaging on Proto-MPEX

The Prototype Material Plasma Exposure eXperiment (Proto-MPEX) is a linear device used to develop the source and heating concept for MPEX, an experiment to study plasma–material interactions for future fusion reactors. This paper highlights recent analysis and results on Proto-MPEX using an infrared (IR) camera, a key tool for imaging heat fluxes measured at the material target. The target heat fluxes are crucial to understanding the source and heating concepts. The recent analysis includes the application of homography and 3-D finite-element methods to provide between-shot measurements of the 2-D target heat flux profile. The IR camera inferred heat flux is shown to correlate with Langmuir probe inferred heat fluxes for a range of parameters in helicon only and helicon + electron cyclotron heated discharges. Results show both desirable central and undesirable edge heat flux for helicon source and electron heating on the target. These heat flux measurements are shown to be important for better understanding of the source and heating physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Prediction of PbLi fluid flow and temperature field in a thermal convection loop for qualification of fusion materials

Two modeling tools, a thermohydraulics code and a computational model in COMSOL Multiphysics, have been developed, tested and then applied to the analysis of fluid flow and heat transfer in a thermal convection loop (TCL). Such a device has recently been used to experimentally evaluate corrosion compatibility of APMT (Fe–21Cr–5Al–3Mo) steel with high-temperature molten eutectic lead-lithium (PbLi) alloy at Oak Ridge National Lab, TN, USA. Here, the 1-D thermohydraulics code allows for rapid calculations of the loop parameters as a function of the applied heat flux. The supplemental COMSOL finite-element computations provide detailed 3-D velocity and temperature field data but are much more time consuming. Both modelling tools demonstrate an excellent agreement in the computed circulation velocity as well as maximum and minimum temperatures. The performed TCL analysis focuses on flow development in the “hot” and “cold” legs, formation of Dean vortices in corner regions, blocking effect of the immersed samples, and radiative and convective cooling effects under the experiment-relevant conditions for Prandtl number Pr = 0.015, Grashof numbers Gr ~10 7 , and Reynolds numbers Re ~10 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Systems-wide analysis revealed shared and unique responses to moderate and acute high temperatures in the green alga Chlamydomonas reinhardtii

Different intensities of high temperatures affect the growth of photosynthetic cells in nature. To elucidate the underlying mechanisms, we cultivated the unicellular green alga Chlamydomonas reinhardtii under highly controlled photobioreactor conditions and revealed systems-wide shared and unique responses to 24-hour moderate (35°C) and acute (40°C) high temperatures and subsequent recovery at 25°C. We identified previously overlooked unique elements in response to moderate high temperature. Heat at 35°C transiently arrested the cell cycle followed by partial synchronization, up-regulated transcripts/proteins involved in gluconeogenesis/glyoxylate-cycle for carbon uptake and promoted growth. But 40°C disrupted cell division and growth. Both high temperatures induced photoprotection, while 40°C distorted thylakoid/pyrenoid ultrastructure, affected the carbon concentrating mechanism, and decreased photosynthetic efficiency. We demonstrated increased transcript/protein correlation during both heat treatments and hypothesize reduced post-transcriptional regulation during heat may help efficiently coordinate thermotolerance mechanisms. During recovery after both heat treatments, especially 40°C, transcripts/proteins related to DNA synthesis increased while those involved in photosynthetic light reactions decreased. We propose down-regulating photosynthetic light reactions during DNA replication benefits cell cycle resumption by reducing ROS production. Our results provide potential targets to increase thermotolerance in algae and crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Electrified vapour deposition at ultrahigh temperature and atmospheric pressure for nanomaterials synthesis

Vapour-phase synthesis methods have shown promise for the scalable synthesis of nanomaterials and coatings. However, the vaporization of different precursors for the synthesis of a broad nanomaterial space, particularly at atmospheric pressure, while maintaining compositional and structural control of the final product is challenging. Here we report the generation of an ultrahigh-temperature atomic vapour at atmospheric pressure based on electrified heating, for the growth of multi-elemental nanomaterials and thin films. This process relies on a reactor design whereby solid-state precursors are vaporized within a semi-confined space beneath an electrified heater that can reach ~3,000 K. The proximity of the heater rapidly breaks down the bonds of metal salt precursors and decomposes them into an atomic vapour that expands into a high-temperature (>2,000 K), highly reactive and high-flux vapour (10 21 –10 22 atoms per cm 2 per second) that travels upwards in a directional flow. When mixed with entrained ambient gases, the highly reactive atomic species rapidly nucleate and grow into the desired final products, including alloys, oxides, sulfides and thin films, which can be deposited on a low-temperature substrate. This EVD approach can synthesize a broad range of functional nanomaterials at atmospheric pressure, including single-phase multi-elemental nanomaterials formed under thermodynamically non-equilibrium conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing putative orbital differentiation effects via Eu 2+ spin dynamics in Sr 1-x Eu x Fe 2 As 2

Here, in this work, we report x-ray powder diffraction, elemental analysis, electrical resistivity, magnetic susceptibility, specific heat, and electron spin resonance (ESR) in single crystals of Sr 1-x Eu x Fe 2 As 2 . We observed a breakdown of the previously reported scaling between the Eu 2+ Korringa relaxation rate obtained from ESR and the spin density wave temperature evolution for Sr-rich samples. This result suggests a distinct evolution of the orbital differentiation of the Fe 3d bands along the Sr-based series when compared to the Ba counterpart. We argue that this difference is related to a larger splitting between the structural (tetragonal-to-orthorhombic) and the Fe-driven spin density wave transitions induced by Eu doping in this series. In fact, our results indicate that the two transitions follow an opposite x-Eu dependence for Sr-concentrated samples. Our work shows that Sr 1-x Eu x Fe 2 As 2 series and the comparison with their Ba-based counterparts are exciting platforms to be explored for understanding the interplay among orbital differentiation, magnetism, and structural distortions in the iron pnictides

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Investigating the Linear Thermal Expansion of Additively Manufactured Multi-Material Joining between Invar and Steel

This work investigated the linear thermal expansion properties of a multi-material specimen fabricated with Invar M93 and A36 steel. A sequence of tests was performed to investigate the viability of additively manufactured Invar M93 for lowering the coefficient of thermal expansion (CTE) in multi-material part tooling. Invar beads were additively manufactured on a steel base plate using a fiber laser system, and samples were taken from the steel, Invar, and the interface between the two materials. The CTE of the samples was measured between 40 °C and 150 °C using a thermomechanical analyzer, and the elemental composition was studied with energy dispersive X-ray spectroscopy. The CTE of samples taken from the steel and the interface remained comparable to that of A36 steel; however, deviations between the thermal expansion values were prevalent due to element diffusion in and around the heat-affected zone. The CTEs measured from the Invar bead were lower than those from the other sections with the largest and smallest thermal expansion values being 10.40 μm/m-K and 2.09 μm/m-K. In each of the sections, the largest CTE was measured from samples taken from the end of the weld beads. An additional test was performed to measure the aggregate expansion of multi-material tools. Invar beads were welded on an A36 steel plate. The invar was machined, and the sample was heated in an oven from 40 °C and 160 °C. Strain gauges were placed on the surface of the part and were used to analyze how the combined thermal expansions of the invar and steel would affect the thermal expansion on the surface of a tool. There were small deviations between the expansion values measured by gauges placed in different orientations, and the elongation of the sample was greatest along the dimension containing a larger percentage of steel. On average, the expansion of the machined Invar surface was 42% less than the expansion of the steel surface. The results of this work demonstrate that additively manufactured Invar can be utilized to decrease the CTE for multi-material part tooling.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Modeling Radiolysis and Chemical Reactions during Dry Storage of Aluminum-clad Spent Nuclear Fuel

After aluminum-clad spent nuclear fuel (ASNF) is removed from the reactor, it is initially stored in spent fuel pools, which are specially designed water-filled basins that provide temporary cooling to reduce the temperature of the fuel assemblies and provide radiation shielding. ASNF continues to generate heat due to the radioactive decay of elements within the fuel, which persists for many years post-shutdown as the residual radioactive products decay into more stable elements. During the wet storage period, an oxyhydroxide layer composed of boehmite/bayerite forms on the surfaces of the aluminum cladding from exposure to water in the pools. Road-ready packaging for long-term disposition of the ASNF involves dry storage in helium backfilled DOE standard canisters (DSCs). When the ASNF is removed from water storage and dried, most of the water is removed, but some physisorbed and chemisorbed water remains in the oxyhydroxide layers. This residual water can produce hydrogen when exposed to radiation from the ASNF during dry storage. Predicting hydrogen accumulation over time in the DSCs is critical for long-term storage considerations. Previous modeling efforts have developed coupled computational fluid dynamics (CFD)-chemical models to simulate temperature, pressure, and gas phase concentrations within the DSCs. These models use the thermal field predicted by CFD as input to a radiolysis model for the gas phase and the surface oxyhydroxide layer chemistry. Given the long storage period of the DSCs and the impracticality of long-term experiments, a simulation-based approach is necessary to assess chemical evolution within the canisters. This study advances the development of a modeling framework designed to simulate the chemical evolution of spent fuel canisters. Both thermal and radiation-driven reactions are considered, with radiation kinetics quantified using G-values. Sensitivity analysis identifies key parameters influencing species composition. Reaction pathway diagrams offer insight into dominant species formation routes, enabling more effective comparisons between model predictions and experimental observations, particularly regarding the production of hydrogen. Results show that the model predicts significant hydrogen gas production with minimal oxygen generation, primarily due to hydrogen formation via boehmite pathways. These findings underscore the importance of accurately characterizing surface-bound species and radiolysis kinetics. A deeper understanding of these mechanisms is critical for evaluating the long-term safety of nuclear waste storage.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2021

Simulation of the PBX 9501 Self-Ignited Heavily Confined Cookoff Test

The PBX 9501 self-ignited thermally damaged explosive (SITX) test was carried out by Holmes et al. A 6-inch diameter sphere made of the PBX 9501 was heated inside a steel confinement vessel until it underwent a thermal explosion. This test provided measured temperature data that was used to define a boundary condition to carry out post-experiment finite element (FE) thermal simulations and comparisons of the FE thermal response with the experimental time to thermal ignition and internal temperature measurements at the center of the PBX 9501 sphere. Finite element models of this experiment were constructed using the heat transfer code Aria. A cookoff model for PBX 9501 was used to simulate the thermal decomposition of PBX 9501 and to predict the time to thermal ignition. An inverse heat conduction scheme was designed and applied to estimate a 1D temperature boundary condition.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Implementation of the Glued Sphere Discrete Element Model for Non-Spherical Particles in MFiX Software

To enhance solver capabilities, simulation flexibility and model validation within the MFiX software, the U.S. Department of Energy (DOE) is funding efforts to develop and integrate the glued-sphere discrete element method into the latest version of MFiX as a dedicated computational module. The glued-sphere discrete element method is a numerical technique to depict the behavior of non-spherical particles in granular flows or particulate systems by representing them as a collection of component spheres. These spheres are bonded together to approximate the shape and mechanical/chemical properties of a more complex particle. The method effectively reuses the existing sphere-sphere collision algorithm, interphase momentum and heat transfer calculations utilized in the traditional discrete element method, extending these capabilities to non-spherical particles. Additionally, this method explicitly resolves intra-particle temperature and species distributions. The MFiX glued-sphere computational module includes tools for generating glued sphere configurations, a dedicated solver, and visualization capabilities in post-processing. More specifically within the computational module, collision detection and calculations were first performed on component spheres and then mapped onto non-spherical particles. The linear spring-dashpot model was utilized to simulate the sphere-sphere interactions.

Ke, Renjie↗
DOE OSTI2024

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING↗
DOE OSTI2022

A Machine Learning-Assisted Framework to Control Thermally Anisotropic Building Envelopes in Residential Buildings

To curb the energy consumption of buildings and their related CO2 emissions, Oak Ridge National Laboratory (ORNL) has developed the thermally anisotropic building envelope (TABE) —a multi-layer design comprising insulation materials and metal foils connected to thermal loops. In this study, a machine learning-assisted framework was developed to control the TABE in residential buildings to reduce the computation load for future optimal rule-based control and application. First, a 2D finite element model was established in COMSOL to calculate the hourly heat flux through exterior walls installed with the TABE. Then, TABE wall heat fluxes were simulated for various given indoor and outdoor boundary conditions, as well as thermal loops fluid temperatures and flow rates. Since the finite element simulations are computationally expensive, an artificial neural network (ANN) was then trained to use as a proxy of the finite element (COMSOL) modeling. Finally, the trained ANN model was coupled with the EnergyPlus model to predict the energy consumption of a US Department of Energy prototype single-family house installed with the TABE. An optimal simple rule-based control was determined from predefined rules for a case study. The results demonstrate that the developed machine learning–assisted framework can reduce 99.9% of the computation time while efficiently managing residential building energy for installed TABE walls.

Shen, Zhenglai↗