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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 OSTI2026

A bioinspired approach for adaptive solid-solid phase change material coatings with optimized surface features for passive thermal regulation

The necessity to reduce global energy consumption calls for innovative strategies in building thermal management. Passive thermal regulation, particularly through bio-inspired designs, offers a promising avenue by mimicking nature's efficient control of optical properties. This research introduces a novel, climate-responsive coating that integrates optimized bio-inspired surface features with a solid-solid phase change material (SS-PCM) to dynamically manage solar absorptivity without adding additional thickness, enabling both heating and cooling as needed. Drawing on the photonic architectures of the Saharan silver ant and Morpho Didius butterfly, we employed a modeling and multi-objective optimization framework to tailor these surface features. Simulations reveal that surface texture, rather than the intrinsic phase transition of the SS PCM, dominates optical control. Relative to a flat SS PCM coating, optimized isotropic random roughness and broader range features yielded the highest passive heating power increase of about 144 % and 319 % respectively suitable for cold climates. Saharan ant-inspired features enhanced passive cooling for hot climates, achieving a 21.8 % improvement. For moderate climates, Butterfly-wing-inspired surface features provided a balanced enhancement of 19 % for heating and 7 % for cooling. Across all cases, the optimized surface features reduced combined heating and cooling energy demand more effectively than the baseline coating, while preserving material thickness. These findings demonstrate that climate-adaptive, optimized bio-inspired surface features can unlock the full potential of SS PCM coatings, providing a versatile pathway to significant energy savings in buildings and other applications. The methodology establishes a framework for designing next-generation adaptive envelopes that leverage natural photonic principles for high-impact, low-cost thermal regulation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort

The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2024

Wildland Urban Interface (WUI) Emissions: Laboratory Measurement of Aerosol and Trace Gas from Combustion of Manufactured Building Materials

Wildfires are increasing in intensity and more often threatening the wildland urban interface (WUI) where buildings and homes coexist with the natural environment. WUI emissions have not been as well-studied as emissions from vegetation. Thus, there is a need to quantify the emissions of building materials used in home construction under flaming and smoldering conditions to study their impacts to human health, visibility, air quality, and climate. Here, in a controlled laboratory setting, we quantify emissions of aerosols and trace gases including formaldehyde, particulate matter, and black carbon. We focus on the combustion of traditional single-source wood-based construction fuels. Our results indicate that, similar to natural fuels, the aerosol optical properties were more related to combustion conditions than the fuel type. Overall, we observed significant variability in the gas and particle emissions. Consistent trends include high formaldehyde (HCHO) and carbon monoxide (CO) emissions for smoldering conditions and higher carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and black carbon for flaming conditions. Finally, these observations highlight the need to better characterize emissions for materials in the built environment to assess large-scale climate and human health impacts of fires at the WUI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate and air pollution implications of potential energy infrastructure and policy measures in India

India is a rapidly developing economy with interrelated air quality, sustainable development, and climate change mitigation goals. There are unique challenges to achieving each of these goals as well as potential tradeoffs among them. This study examines the implications of possible future energy, climate, and air pollution control policies and measures in India through 2050. We take a scenario approach using the GCAM global energy-climate-land model combined with the Hector simple climate model and the TM5-FASST air quality source-receptor model to examine energy, climate and air quality outcomes. Reducing use of traditional biomass in buildings can reduce primary carbonaceous particulate emissions well below 2015 levels. However, policies that are more ambitious than current plans would likely be required to reduce SO 2 and NO x emissions well below 2015 levels. Among single policy cases considered, pricing of greenhouse gas (GHG) emissions and expansion of natural gas infrastructure have the largest impacts on overall energy system changes relative to the reference scenario. Ambitious air pollution control and GHG policies lead to the largest reductions in air pollution concentrations and radiative forcing, respectively. However, ambitious air pollution control and GHG policies differ in the extent to which they support or impede other policy objectives. Forcing increases due to reduced aerosols from ambitious air pollution policies can be mitigated, at least in part, by applying air pollution control and GHG policies together.

India↗
DOE OSTI2022

Impact of Mass Wood Walls on Building Energy Use, Peak Demand, and Thermal Comfort

Thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours. Cross-Laminated Timber (CLT) and other mass wood products provide thermal mass to the building envelope in a lighter and more environmentally friendly form than concrete. However, the influence of CLTs on heating and cooling energy, peak energy demand, and the indoor climate is not well-known. This project was formed to find the energy efficiency benefits of mass timber structures. The objectives were to (1) test the thermal performance of insulated mass wall structures in controlled laboratory conditions, (2) validate simulation models to expand performance to natural climatic conditions, (3) isolate the impact of the thermal properties of wood (thermal mass, thermal conductivity, moisture storage) on heating and cooling energy use and peak energy demand, and to optimize the performance. Currently, the designs used for CLT buildings have focused on structural and fire issues, and they do not consider the thermal mass benefits. Therefore, the thermal performance is not necessarily optimized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Evaluation of the Energy, Hygrothermal, and Thermal Capacity Performance of Cross-Laminated Timber

Cross-laminated timber (CLT) construction is gaining momentum in the US because it offers multiple advantages over traditional construction methods. Benefits that have received the most attention focus on constructability, the environment, and protection (e.g., blast resistance), although CLT construction is likely to offer other benefits, as well. Still, these have not been studied at length because such evaluations are costly, requiring long-term assessments in an actual building and specialized technical knowledge. Among the possible benefits, CLT construction likely provides a higher-performing building envelope. Using CLT panels to enclose a building means fewer joints in the opaque envelope than what is required in traditional stick-framed construction. Fewer joints mean fewer locations where the air- and water-resistive barrier (WRB) could be compromised; thus, a CLT building enclosure may require less maintenance and have a longer lifespan than a traditionally built structure because of fewer air and water leaks. In addition, CLT’s thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours, reducing operational energy consumption throughout the lifetime of the CLT building (Salonvaara et al., 2022). Furthermore, more stable indoor temperatures can increase occupant comfort. The CLT’s thermal mass can also reduce energy costs by adjusting to utility time-of-use pricing without affecting occupant comfort. The ability of CLT buildings to bridge periods without HVAC operation prepares them for future grid interaction and provides a certain level of resilience against power outages. Researchers have attempted to quantify these benefits; however, their work is based on simplified simulations with numerous assumptions. To correctly understand the benefits, an actual building must be monitored. Therefore, information needs to be gathered on indoor and outdoor temperatures, HVAC energy consumption, thermostat setpoints, temperatures, and thermal transport in CLT components to comprehend how these parameters are affected by the CLT’s thermal mass. These data are needed to reduce the number of assumptions and calibrate simulation models to optimize HVAC controls to minimize overall energy consumption, reduce energy use and higher fees during peak demand, and maintain occupant comfort. Additionally, the calibrated simulation model allows the optimization exercise to be repeated in various US climates. Potential benefits can be tailored to buildings in various locations, and decisions can be made on where CLT construction could be most advantageous. Furthermore, monitoring and simulation results are needed to evaluate the durability of the CLT structures in different climates. This project’s researchers gathered information to help understand and quantify the benefits of CLT buildings concerning operational energy, moderated indoor temperatures, and comfort; the dynamic operation to provide grid services; and resilience in times of power outage. Through the corroboration of simulation models with real-world measurements, this study paves the way for extrapolating findings to other climatic zones and building typologies, thereby broadening the understanding of CLT’s multifaceted benefits and reinforcing its position as a material of choice in sustainable construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗
DOE OSTI2021

Exploring thermal state in mixed immersive virtual environments

Combining immersive virtual environment (IVE) with a controlled environment is a potential solution for analyzing human thermal experience during building design. Existing studies in this field have not adequately analyzed scenarios involving stabilized comfortable and uncomfortable temperature conditions using both thermal state votes and physiological responses, or the influence of the seasons. By combining IVE with a climate chamber, called mixed IVE (MIVE) in this study, experiments were conducted to test the hypothesis that participants' virtual experience did not significantly alter their thermal experience compared to their in-situ experience. Response variables were the control temperature distribution, the thermal state vote (at temperature steps 18.3 °C, 23.8 °C, and 29.4 °C), and physiological responses (heart rate and skin temperature). The results show that the first two response variables were not significantly different between the MIVE and in-situ settings (except for one case). Due to the heat development of the head mounted display device, the mean forehead skin temperature in the MIVE experiments was significantly higher than that in the in-situ experiments in most cases. Furthermore, such difference in skin temperature did not seem to affect general thermal state votes. In addition, significant skin temperature differences at some locations were also observed between the MIVE and in-situ settings.

42 ENGINEERING↗
DOE OSTI2026

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗
DOE OSTI2022

On-policy learning-based deep reinforcement learning assessment for building control efficiency and stability

Artificial intelligence technologies have emerged as a game changer not only in specific applications such as image recognition and machine translation but also in many scientific domains. In particular, as deep reinforcement learning (DRL) has shown great success in complex control problems, DRL-based control has been considered as a potential solution to efficiently control and manage building systems. However, broad assessment of DRL-based building control is still required to characterize their pros and cons in comparison with conventional building control methods (e.g., rule-based feedback controls). In this paper, we assessed DRL-based controls with on-policy learning-based algorithms and continuous control actions for cooling control of large office buildings in the summer season to minimize whole-building energy use and occupant discomfort. We compared DRL-based control methods with two baseline control methods: (1) a pre-determined schedule with supply temperature and static pressure setpoints, and (2) advanced reset method that adjusts setpoints based on heuristic rules, i.e., ASHRAE Guideline 36. We also tested the DRL algorithms to evaluate their performances in multiple climate locations. We found that DRL-based control methods outperformed the baseline control methods in terms of energy savings while maintaining a thermal comfort. DRL reduced energy use between ~4%–22% on average compared to the baseline methods, depending on climate location. We also evaluated DRL-based control in terms of control stability and showed that DRL-based methods should address the span of hardware lifetimes in practical operations.

control stability↗
DOE OSTI2026

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO 2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and emissions reductions of 3–100 %, with strategic energy management achieving 3–5 % and renewable electricity paired with electrified heating achieving up to 100 %. Text mining revealed that energy, hardware, and process technologies account for 91 % of literature coverage. Water, building envelope, and CO 2 utilization remain underexplored, indicating priorities for future research. This integrative approach to technology assessment supports growers, developers, and policymakers in aligning CEA system design with local conditions, improving resource efficiency and addressing gaps in cross-domain technology coverage.

Controlled environment agriculture↗
DOE OSTI2026

Good practices for documenting AI-based studies on energy and buildings

Artificial intelligence has transformed building science research over the past decade, with applications spanning energy modeling, energy prediction, HVAC optimization and controls, fault detection, and occupancy modeling. However, many studies lack adequate documentation of datasets, algorithms, training procedures, and validation methods. Building science research faces additional challenges including inconsistent evaluation metrics, limited generalizability across building types, climates, and significant gaps between experimental studies and deployed systems. This communication provides practical guidance for good practices in documenting and publishing AI-based research following established standards from the computer science and machine learning communities. By adopting frameworks such as Datasheets for Datasets, Model Cards, and standardized reproducibility checklists, researchers can ensure their work meets the rigorous documentation standards necessary for reproducible, comparable, and impactful building science research.

Hong, Tianzhen [Lawrence Berkeley National Laborat↗
DOE OSTI2020

Smart Ventilation for Advanced California Homes

This project investigated smart ventilation approaches to minimize energy use for providing indoor air quality (IAQ) in high performance new California homes. Evaluation criteria included annual ventilation-related energy, peak energy and time-of-use savings, and the indoor air quality relative to a minimally code-compliant ventilation system. The simulations used CONTAM’s air flow and contaminant transport model, combined with the EnergyPlus building loads model. House types representing the default California Energy Code compliance homes were investigated for four California climate zones, covering a wide range of climate types. Both single and multi-zone smart ventilation controls were investigated. Contaminant sources included contaminants emitted continuously and varying with time, temperature and relative humidity, episodic emissions from occupant activities and outdoor particles. Single-zone ventilation controls that varied ventilation depending on outdoor temperatures were able to consistently save half of ventilation-related energy without compromising long-term IAQ. Ventilation strategies that tracked occupancy were less successful, because this work included generic contaminants with constant background emission rates. Energy performance for occupancy controls improved with a one-hour pre-occupancy flush out strategy. The addition of zoning ventilation controls did not offer significant IAQ to energy improvements compared to non-zonal versions of the same ventilation system type. The best controls had HVAC energy savings of 10-20%, with individual cases reaching up to 40% savings. However, these savings cannot be achieved without worsening personal exposures for at least one contaminant. A metric is needed to assess the competing changes in exposure to different contaminants in order to determine the net-health impacts of a control strategy. Controls that directly sensed contaminants and controlled them to acceptable levels showed that the California OEHHA limit for formaldehyde completely dominates system performance, with homes not able to meet the limit even with continuous operation of a fan sized to twice the current code minimum.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Wall Upgrades for Energy Retrofits: A Techno-Economic Study

Homes built before 1992, when the U.S. Department of Energy’s (DOE) Building Energy Codes Program was established, represent approximately 68% of the residential building stock in the country. Up to 43% of these homes have little to no insulation in the walls and have very high air leakage rates of 10 or more air changes per hour at 50 pascals of pressure (ACH50). These issues can represent a substantial portion of unnecessary money spent on utility bills for homeowners, especially in the colder climates. There is a significant need for cost-effective, reliable retrofit methods for these homes that include air, moisture, and vapor controls which are considered best practices for high-performance new home construction. Well-tested and documented wall retrofit systems can help to achieve substantial energy savings and also improve durability, comfort, health, and resilience. In 2018, DOE’s Building Technologies Office awarded Pacific Northwest National Laboratory, Oak Ridge National Laboratory, and the University of Minnesota funding to complete a 3-year project to compare a range of residential wall retrofit systems that prioritized affordability, durability and energy savings potential. In addition to these core criteria, the ease-of-construction and the wide-scale applicability of the solutions also were considered. In this project, the research team identified, constructed, tested, simulated, and analyzed the feasibility and economics of 16 wall retrofit assemblies (14 test configurations and two baseline configurations).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Integration of Thermoelectric Modules to Vapor Compression Systems

This paper describes the technology of a thermoelectric (TE) integrated heat pump. It uses a TE heat pump to subcool the refrigerant liquid before entering the evaporator to enlarge the evaporating capacity; and elevate the heat in the refrigerant flow to a supplemental heating coil and discharge the capacity to the indoor air flow. Using the DOE/ORNL Heat Pump Design Model, four system configurations were modelled on a baseline two-speed heat pump, the baseline heat pump with adding a supplemental coil, the TE integrated heat pump having one stage TE heating to control a 20R liquid refrigerant temperature drop; and having two stages TE heating to control up to 40R temperature drop. The system models were used to produce performance curves for EnergyPlus building energy simulations. We selected template residential buildings, poorly insulated: pre-1990 buildings, and well-insulated: IECC2021 buildings; in five cold climate zones: 5A, 5B, 6A, 6B, 7. The building energy simulations demonstrated energy saving potentials, utility cost reductions and estimated payback periods.

Shen, Bo↗
DOE OSTI2026

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗
DOE OSTI2025

Next generation retrofit wall panels with integrated vacuum insulation panels

Approximately two-thirds of residential buildings in the United States were constructed before the Department of Energy established energy conservation measures. These buildings present major opportunities for improving energy efficiency, though retrofitting them remains technically and economically challenging. This study presents the development and the durability evaluation of an innovative retrofit panel system that integrates vacuum insulation panels (VIP) with a nail-base panel (called a retrofit insulated panel) to enhance thermal performance with minimal disruption to occupants and without altering standard nail-based panel installation practices. Hygrothermal simulations were conducted to assess the moisture behavior of wall assemblies before and after retrofit installation under varying water vapor control strategies and climate conditions. Results indicate that, with appropriate moisture control strategy, the retrofit system effectively prevents moisture accumulation, keeping mold index values and relative humidity levels below critical thresholds. Additionally, Guarded Hot Box testing was performed to compute the effective R-value of the panel under different coverage areas that demonstrates its effectiveness in enhancing both thermal and moisture performance in existing residential buildings.

Iffa, Emishaw [ORNL]↗