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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Separate sensible and latent cooling: Carnot limits and system taxonomy

Energy efficiency and thermal comfort can be improved by independent control of temperature and humidity. In recent work, an emerging class of cooling systems known as separate sensible and latent cooling (SSLC) systems have demonstrated 14 to 47% energy savings, while simultaneously providing better comfort control than conventional air conditioning. In this work, SSLC is defined as using two or more cooling processes with unequal sensible heat ratio (SHR) to control temperature and humidity independently and dynamically. Fundamental efficiency limits of SSLC systems are developed for the first time, demonstrating that the Carnot efficiency for SSLC is higher than that of conventional systems. It is revealed that SSLC has particularly high potential for moderate outdoor temperatures, high sensible building loads, and drier indoor conditions. Additionally, this work proposes a classification scheme for SSLC systems, revealing an enormous number of feasible cycle permutations. This provides a framework for the important research task of developing SSLC systems that will save energy, be practical to construct, and be controllable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Models of SIV rebound after treatment interruption that involve multiple reactivation events

In order to assess the efficacy of novel HIV-1 treatments leading to a functional cure, the time to viral rebound is frequently used as a surrogate endpoint. The longer the time to viral rebound, the more efficacious the therapy. In support of such an approach, mathematical models serve as a connection between the size of the latent reservoir and the time to HIV-1 rebound after treatment interruption. The simplest of such models assumes that a single successful latent cell reactivation event leads to observable viremia after a period of exponential viral growth. Here we consider a generalization developed by Pinkevych et al. and Hill et al. of this simple model in which multiple reactivation events can occur, each contributing to the exponential growth of the viral load. We formalize and improve the previous derivation of the dynamics predicted by this model, and use the model to estimate relevant biological parameters from SIV rebound data. We confirm a previously described effect of very early antiretroviral therapy (ART) initiation on the rate of recrudescence and the viral load growth rate after treatment interruption. We find that every day ART initiation is delayed results in a 39% increase in the recrudescence rate (95% credible interval: [18%, 62%]), and a 11% decrease of the viral growth rate (95% credible interval: [4%, 20%]). We show that when viral rebound occurs early relative to the viral load doubling time, a model with multiple successful reactivation events fits the data better than a model with only a single successful reactivation event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Performance Assessment of a Heat Pump Integrated with Thermal Energy Storage in Cooling & Heating Modes

Thermal Energy Storage (TES) systems have demonstrated significant potential to manage the fluctuating nature of energy demand and shifting peak loads. This technology has made significant recent advances, including new research on the integration of TES with residential and commercial Heating, Ventilation, and Air-Conditioning (HVAC) systems. In this paper, we present the use of a novel laboratory assessment framework for a prototype heat pump system integrated with latent heat phase change material-based TES. The assessment framework consists of 22 total test points (11 heating, 11 cooling) using psychrometric conditions from AHRI Standard 210/240 and includes transient conditions to evaluate TES charging and discharging modes. In addition, both continuous mode and cyclic mode were evaluated for charging and discharging to explore the benefits to TES heat transfer from repeated transient operation. The ambient conditions evaluated include heating mode charging at cold-climate heat pump conditions when winter-peaking utilities may most require demand reduction (H4Full conditions, 5°F/-15°C) and cooling mode charging at high ambient temperature that may occur during times of day when excess solar power generation results in low-cost electricity (105°F/40.6°C). The work demonstrates the demand reduction capabilities of integrating TES with HVAC, including up to 44% in cooling mode and 60% in heating mode compared to conventional HVAC equipment without TES.

25 ENERGY STORAGE↗
DOE OSTI2025

A simple introduction to the SiMPL method for density-based topology optimization

We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as “the simple method”) optimizes a design using only first-order derivative information of the objective function. The bound constraints on the density field are enforced with the help of the (negative) Fermi–Dirac entropy, which is also used to define a non-symmetric distance function called a Bregman divergence on the set of admissible designs. This Bregman divergence leads to a simple update rule that is further simplified with the help of a so-called latent variable. Because the SiMPL method involves discretizing the latent variable, it produces a sequence of pointwise-feasible iterates, even when high-order finite elements are used in the discretization. Numerical experiments demonstrate that the method outperforms other popular first-order optimization algorithms. In conclusion, to outline the general applicability of the technique, we include examples with (self-load) compliance minimization and compliant mechanism optimization problems.

Calculus of Variations and Optimization↗
DOE OSTI2026

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI↗
DOE OSTI2024

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗
DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Divertor Plasma Detachment Control Neural Network

DivControlNN is a state-of-the-art software tool that leverages advanced machine learning techniques to predict and control divertor plasma behavior in fusion reactors. Plasma, a highly energetic and electrically charged gas, requires meticulous management to protect reactor components and maintain optimal energy production. Conventional simulation methods, although extremely detailed, typically demand extensive computational time-making them unsuitable for real-time control scenarios. DivControlNN addresses this challenge by learning from tens of thousands of high-fidelity simulations, thereby creating a rapid surrogate model that can deliver near-instantaneous predictions. At the core of its functionality is a sophisticated technique known as latent space mapping, which condenses complex, high-dimensional plasma data into a compact, lower-dimensional representation. This streamlined representation enables the system to quickly forecast essential plasma properties and determine the precise conditions required for effective detachment. Detachment is a crucial process in which the plasma is cooled before reaching the divertor plates, thereby reducing heat loads and mitigating material erosion. In recent experiments conducted on the KSTAR tokamak in South Korea, DivControlNN successfully guided the detachment process without any fine-tuning-even when applied to a new tungsten divertor configuration. By achieving a computational speed-up of over one hundred million times compared to traditional simulation methods while maintaining low prediction errors, DivControlNN stands to significantly enhance real-time control and diagnostic capabilities in future fusion reactors. This breakthrough paves the way for safer, more reliable reactor operation and represents a major advancement toward realizing fusion energy as a practical, sustainable, and clean power source.

Xu, Xueqiao [Lawrence Livermore National Laborator↗
DOE OSTI2023

Advanced Materials and Additive Manufacturing for Phase Change Thermal Energy Storage and Management: A Review

Abstract Phase change materials (PCMs) can enhance the performance of energy systems by time shifting or reducing peak thermal loads. The effectiveness of a PCM is defined by its energy and power density—the total available storage capacity (kWh m −3 ) and how fast it can be accessed (kW m −3 ). These are influenced by both material properties as well as geometry of the energy systems; however, prior efforts have primarily focused on improving material properties, namely, maximizing latent heat of fusion and increasing thermal conductivity. The latter is often at the expense of the former. Advanced manufacturing techniques hold tremendous potential to enable co‐optimization of material properties and device geometry, while potentially reducing material waste and manufacturing time. There is an emerging body of research focused on additive manufacturing of PCM composites and devices for thermal energy storage (TES) and thermal management. In this article, the fundamentals and applications of PCMs are reviewed and recent additive manufacturing advances in latent heat TES for both the PCM composite and associated heat exchanger are discussed. A forward‐looking perspective on the future and potential of PCM additive manufacturing for TES and thermal management is provided.

25 ENERGY STORAGE↗
DOE OSTI2026

Dynamic modeling of heat pipe integrated thermal battery latent heat storage system experiment validation

A heat pipe integrated thermal battery system has been constructed to investigate a high-temperature latent heat thermal energy storage technology that takes advantage of near isothermal operation of latent heat storage and heat pipes to potentially enable high-energy isothermal heat storage. A dynamic model constructed in Modelica has been validated, showing errors between 2.5 °C–39.7 °C across 10-h to 47-h simulations against experiment results, showing good prediction capability of experiment output, especially against phase change time. Model calibrations showing vessel heat-up capability of 3 kW and heat pipes combining to provide 600 W each during experiment operation validate experiment circumstances including reduced material loading and reduced power capability. The experiment configuration uses an Al-Mg-Zn eutectic metal as the storage material, heated via heat tape wrapped around the vessel and guide tubes to bring the system to operation range (>400 °C) and to simulate charging heat exchange, respectively, with heat rejection occurring through the surfaces of the material and facilitated via guide tubes with less insulation wrapping. The model is available in the open-source repository HYBRID on Github.

25 - ENERGY STORAGE↗
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Abnormal grain growth of 68Cu–16Al–16Zn alloys for elastocaloric cooling via cyclical heat treatments

Abstract Cu-based superelastic shape memory alloys are promising for low-stress elastocaloric cooling. We have synthesized bulk alloys of 68Cu–16Al–16Zn under different conditions in order to promote its grain growth and enhance its elastocaloric properties. High-temperature x-ray diffraction of untreated 68Cu–16Al–16Zn alloy showed that the phase boundary between the α + β mixed phases and the high temperature phase ( β phase) was between 973 K and 1023 K. Based on this result, the 68Cu–16Al–16Zn alloy was heated and cooled in a furnace repeatedly between 773 K and 1173 K. The maximum grain size after heat treatment of the ingot rolled to 67% reached 11.1 mm. The latent heat of the martensitic transformation after grain growth was 6.3 J g −1 , which is higher than the previously reported value for the compound. The stress–strain curve of 68Cu–16Al–16Zn rolled to 67% rolling with cyclical heat treatments showed a maximum stress of 106 MPa at 4.5% strain, with adiabatic temperature change of 5.9 K in heating during stress loading and 5.6 K in cooling in stress removal. Furthermore, no fatigue in the stress–strain behavior was observed up to at least 60 000 mechanical cycles at 2% strain.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A phase-field model for non-isothermal phase transformation and plasticity in polycrystalline yttria-stabilized tetragonal zirconia

Here we propose an elastoplastic phase-field (PF) model to investigate the mechanics of tetragonal-to-monoclinic phase transformation (TMPT) and elastoplastic deformation of polycrystalline yttria-stabilized tetragonal zirconia (YSTZ). A Landau polynomial with non-vanishing chemical energy at the equilibrium temperature is introduced to account for the actual formation energies of the phases. The effects of different grain orientations, latent heat, and temperature on TMPT and deformation mechanisms are considered. The suppressive transformation effects of the grain boundaries (GBs) is modeled using an inhomogeneous kinetic coefficient in the bulk and GBs. The simulation results for single crystals demonstrate the capability of the model to reproduce the orientation-dependent compressive deformation of YSTZ similar to atomistic simulations and micropillar experiments. The single crystal with [100] crystallographic orientation along the loading direction (SC[100]) displays both TMPT and plasticity, SC[101] experiences only phase transformation, while SC[001] undergoes only plastic yielding. The TMPT induced by compressive loading exhibits shape memory effect (SME) below the equilibrium transformation temperature and pseudoelasticity above it, while the critical transformation stress increases with increasing loading temperature. The irrecoverable plastic strain is found to trap a part of the monoclinic phase, which prevents a complete reverse transformation. The polycrystalline cases also display SME and PE at low and high temperatures, respectively. Due to the orientation differences between grains and the stress concentrations at geometric nonlinearities, plastic deformation occurs in polycrystalline YSTZ for an applied load less than the yield stress. The results suggest a possible limitation of plasticity and an improvement of the shape recovery of YSTZ if one can control the orientation of the grains and/or increase the density of stacking faults at the GBs during material processing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamic Thermal Performance Analysis of PCM Products Used for Energy Efficiency and Internal Climate Control in Buildings

PCMs are attractive for the future generation of buildings, where energy efficiency targets and thermal comfort expectations are increasingly prioritized. Experimental analysis of local thermal processes in these dynamic components and whole-building energy consumption predictions are essential for the proper implementation of PCMs in buildings. This paper discusses the experimental analysis of the thermophysical characteristics of both a latent heat storage material (PCM) and a product containing this PCM. The prototype product under investigation is a panelized PCM technology containing inorganic, salt-hydrate-based PCM. The thermal analysis includes studies of melting and freezing temperatures, enthalpy changes during phase change processes, nucleation intensity, sub-cooling effects, and PCM stability. The PCM’s stability is also investigated, as is the ability of PCM products to control local temperatures and peak load transmission times. Two inorganic PCM formulations based on calcium chloride hexahydrate (CaCl 2 .6H 2 O) were prepared and tested in laboratory conditions. Material-scale testing results were compared with outcomes from the system-scale analysis, using both laboratory test methods as well as field exposure in test huts. This work demonstrates that PCM technologies used in buildings can effectively control both the magnitude of thermal storage capacity as well as the time of the peak thermal load. It was found that commonly used material-scale testing methods may not always be beneficial in assessing the dynamic thermal performance characteristics of building technologies containing PCMs.

42 ENGINEERING↗
DOE OSTI2023

End-Use Savings Shapes Measure Documentation: Variable Refrigerant Flow with Heat Recovery and Dedicated Outdoor Air System

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy's ResStock™ and ComStock™ models over the past 3 years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ComStock is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The baseline model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology and results of the baseline model are discussed in the final technical report of the End-Use Load Profiles project. This documentation focuses on a single heating, ventilation, and air-conditioning (HVAC) end-use savings shape measure - a variable refrigerant flow with heat recovery (VRF HR) heating and cooling system coupled with a dedicated outdoor air system (DOAS) for ventilation. This measure replaces existing multi-zone variable air volume (VAV) systems or single-zone rooftop units (RTU) with a VRF HR system coupled with a DOAS that includes an energy/heat recovery ventilator (E/HRV). The measure covers 53% of exisiting building stock's floor area and is not applicable to HVAC system types using district heating or cooling or buildings/spaces that include high-ventilation spaces such as kitchens where the amount of exhaust air is large. A DOAS with E/HRV is used to provide required outdoor ventilation air to spaces since ventilation air is generally not supplied by a VRF HR system. An exhaust air energy recovery ventilator (ERV ) with sensible and latent heat exchange is added to humid climate zones while a heat recovery ventilator (HRV ) with sensible only exchange is added to drier climate zones. The ERV is modeled as a fixed membrane plate counterflow heat exchanger, while the HRV is modeled as a sensible-only fixed aluminum plate counterflow heat exchanger. Both systems include a bypass (for temperature control and economizer lockout) and minimum exhaust temperature control for frost prevention.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Informed Multi‐Scale Approach Applied to the British Columbia Fires of Late Summer 2017

Abstract Pyrocumulonimbus (PyroCb) clouds have a complex origin dependent on fire dynamics and meteorological conditions. When a pyrocumulonimbus cloud develops and is maintained over a period of time, it can inject significant aerosol into the troposphere and lower stratosphere, resulting in a longer‐term (months to years) occurrence of aerosol in the stratosphere. In this work, we investigate the British Columbia wildfires on 12–13 August 2017 using a multi‐scale simulation framework. We use the output of a physics‐based wildfire model (FIRETEC) with parameterized energy, particle, and gas emissions to drive the upper atmospheric aerosol mass injection within a regional cloud resolving model (HIGRAD). We demonstrate that vertical motions produced by latent heat release of the condensation of ice and cloud particles within the PyroCbs induce another 5 km of lifting of the simulated aerosol plume. Primary black carbon and organic aerosols (OAs) alone may not be enough to explain the observed aerosol burden, thus we show that secondary OA produced via condensation of gases by the fires, ash, and possibly dust can enhance lofted aerosol mass. A simulation with all emission mechanisms active, driven by the observed fuel load and environmental conditions, reasonably reproduces an aerosol profile inferred from observational data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mechanistic basis of post-treatment control of SIV after anti-α4β7 antibody therapy

Treating macaques with an anti-α4β7 antibody under the umbrella of combination antiretroviral therapy (cART) during early SIV infection can lead to viral remission, with viral loads maintained at < 50 SIV RNA copies/ml after removal of all treatment in a subset of animals. Depletion of CD8+ lymphocytes in controllers resulted in transient recrudescence of viremia, suggesting that the combination of cART and anti-α4β7 antibody treatment led to a state where ongoing immune responses kept the virus undetectable in the absence of treatment. A previous mathematical model of HIV infection and cART incorporates immune effector cell responses and exhibits the property of two different viral load set-points. While the lower set-point could correspond to the attainment of long-term viral remission, attaining the higher set-point may be the result of viral rebound. Here we expand that model to include possible mechanisms of action of an anti-α4β7 antibody operating in these treated animals. We show that the model can fit the longitudinal viral load data from both IgG control and anti-α4β7 antibody treated macaques, suggesting explanations for the viral control associated with cART and an anti-α4β7 antibody treatment. This effective perturbation to the virus-host interaction can also explain observations in other nonhuman primate experiments in which cART and immunotherapy have led to post-treatment control or resetting of the viral load set-point. Interestingly, because the viral kinetics in the various treated animals differed—some animals exhibited large fluctuations in viral load after cART cessation—the model suggests that anti-α4β7 treatment could act by different primary mechanisms in different animals and still lead to post-treatment viral control. This outcome is nonetheless in accordance with a model with two stable viral load set-points, in which therapy can perturb the system from one set-point to a lower one through different biological mechanisms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Numerical modeling and parametric study of a dual purpose underground thermal battery

We report integrating thermal energy storage with building energy systems can enable flexible building electric demands at buildings to help mitigate the mismatch between electricity supply and demand. A novel building heating and cooling system that integrates a dual-source heat pump with hybrid thermal storage named dual-purpose underground thermal battery (DPUTB) has been developed for reshaping building electric demands. The proposed DPUTB integrated geothermal heat pump system is an original innovation that enables Grid-interactive Energy Efficient buildings. This paper focuses on the study of the novel DPUTB. The DPUTB works as both a thermal storage tank (an inner tank) and a ground heat exchanger (an outer tank separated from the inner tank by the insulation material). High fidelity and computationally effective models are needed to predict the performance of the novel DPUTB. This study has developed a simplified dynamic model for the DPUTB according to heat transfer and energy conservation principles and validated it by using experimental data obtained from testing a small-scale DPUTB apparatus. A parametric study was conducted to identify a design that can achieve the target thermal storage performance of load shift and energy efficiency. The parametric study results show that the inner tank shell thermal conductivity and the phase change material's melting point are the two most influencing factors on the performance of the DPUTB. One single full-size DPUTB with the identified design could provide 1-ton cooling (3.51 kW) with the supply temperature lower than 11 °C for 4 hours in summer after being fully charged in 8 hours. The inner tank filled with phase change material is for cooling thermal storage as a latent tank in the design. However, its capacity can be as high as 60 MJ as a sensible water tank for heating storage in winter. In the future study, the DPUTB model will be incorporated into the dual-source heat pump system for evaluating the overall system performance of demand side management in the long term.

25 ENERGY STORAGE↗