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DOE OSTI2024

Energy burden aware and thermal resilience informed thermal energy storage system planning for disadvantaged communities

Disadvantaged communities often face a disproportionate energy burden because they need to allocate a higher percentage of their income to energy costs. More importantly, climate change-induced extreme weather events, such as heat waves and severe cold snaps, exacerbate these communities’ energy burdens. As a result, low- and medium-income communities are more likely to experience energy supply disruptions, increased health risks, and elevated energy bills because of inadequate thermal insulation and airtightness in their houses. Thermal energy storage (TES) systems, such as large-scale (community-level) geothermal energy storage and small-scale (building-level) phase change material (PCM)–based storage, have a great potential to improve building energy efficiency and to enhance thermal comfort, load shifting, and integration with renewable energy. The objective of this study is to optimally allocate building level PCM-based TES systems at the community level by considering energy equity and extreme weather effects. To this end, we developed an energy burden and thermal resilience–informed TES system planning framework, which includes three modules: (1) a community-level energy burden and thermal resilience assessment module, (2) building-level a TES system integration and assessment module, and (3) a community-level optimal planning module. Case studies were conducted on four disadvantaged communities in Montgomery and Shelby Counties in Tennessee with energy burdens >10% and with high percentages of people of color. The results indicate that this comprehensive planning framework can assist disadvantaged communities in reducing their energy burden and in bolstering their resilience against the adverse effects of climate change.

Shen, Zhenglai↗

DOE OSTI2024

Performance Assessment of a Dual-purpose HP-TES for a Typical Year Comparing Different Climate Zones

Complete electrification of heating and cooling systems in the United States would overload the existing electrical grid. To this end, recent research efforts have focused on energy storage as one way to reduce ever-increasing peak electricity demands. One such technology is heat pump integrated thermal-energy storage (HP-TES) systems, which can enable load-shifting and reduce demand during peak hours. In this work, a Modelica model of a 4-Ton, dual-mode (heating and cooling) HP-TES system using a room-temperature phase-change material (PCM) integrated through a secondary hydronic loop was developed and simulated for a typical meteorological year in Riverside, CA (ASHRAE Climate Zone 2B), and Chicago, IL (ASHRAE Climate Zone 5A), for a DOE small office prototype building. The COP improvement and demand reduction were analyzed during the time-of-use peak hours along with the required recharge cycle energy demand. A typical summer in Riverside, CA resulted in model-predicted peak COP increases of 50 – 100% compared to the baseline heat pump, especially at higher outdoor temperatures, coupled with maximum peak energy reductions of 22%. During shoulder and winter season simulations, heating energy savings were higher as outdoor temperatures dropped below the PCM phase change temperature. For Chicago, IL, backup heating was necessary to meet the required system capacity for very cold ambient conditions, resulting in winter peak energy savings between 16 – 60% when accounting for backup heating requirements. The recharge energy was found to be mostly below the baseline HP energy during the peak. With improved component selections and controls, the recharge energy may be reduced. The outcomes from the simulations can provide first-order estimates for potential peak energy savings, challenges, and required controls in any location before conducting any field testing.

25 ENERGY STORAGE↗

DOE OSTI2024

Pushing the Envelope-Moving Dynamic Building Envelope Thermal Energy Storage Systems Mainstream: Preprint

Buildings contribute to nearly 40% of the U.S. national energy consumption and a significant portion of CO2 emissions. More importantly, disadvantaged communities are disproportionately affected by energy burden and thermal discomfort in their homes. This paper will discuss two novel DOE's BTO supported thermal energy storage (TES) integrated dynamic building envelope technologies, their ability to harvest ambient energy, and improve energy efficiency by reducing HVAC loads and peak electricity demand while enhancing energy and thermal resilience in buildings. The paper will also discuss the recent advancements that have made these systems more affordable and easier to integrate into new and existing buildings. The first solution is a thermally anisotropic building envelope (TABE) system that can redirect ambient thermal energy (heat or coolness) from diurnal outdoor conditions, solar irradiance, and night sky radiation from the envelope to a hydronic loop. The redirected thermal energy can be stored in a TABE-integrated thermal energy storage system and use the stored energy to offset HVAC energy use and peak demand. The second solution is an innovative plug-and-play thermal switch in the form of insertable plugs integrated with a phase change material (PCM). The plug can vary its thermal resistance based on the indoor and outdoor conditions, thus allowing preferential directional heat flow, and enhancing utilization of free ambient cooling and heating to charge/discharge the PCM, much like a solid-state economizer. While the fist solution can be actively controlled, the second solution is passive, requiring no external power, and work solely based on the ambient temperature.

anisotropic envelope↗

DOE OSTI2024

Pushing the Envelope—Moving Dynamic Building Envelope Thermal Energy Storage Systems Mainstream

Shrestha, Som↗

DOE OSTI2026

Nuclear Data Libraries Sensitivity Studies for ORSA Using SCALE

Subcritical assemblies offer valuable training capabilities in nuclear criticality safety (NCS) for individuals handling fissile material. At Oak Ridge National Laboratory(ORNL), the Oak Ridge Subcritical Assembly (ORSA), a new experimental facility, is being established to provide hands-on training for the Nuclear Criticality Safety Program (NCSP).It is essential to accurately determine the neutron multiplication factor (keff) to ensure that ORSA remains subcritical and safe during operations. This study investigated the sensitivity of keff to variations across Evaluated Nuclear Data File (ENDF/B) libraries, consisting of ENDF/B-VII.1, ENDF/B-VIII.0, and ENDF/B-VIII.1. The analysis was conducted using the CSAS6 sequence in the SCALE-6.3 code system. Individual isotopes in the ORSA model were replaced one at a time with ENDF/B-VII.1 as the base library and changing to ENDF/B-VIII.0or ENDF/B-VIII.1. The results demonstrated that the changes in keffof the nuclides associated with the ORSA model were mostly within the uncertainty of the base model (~24 pcm), except for primary nuclides like Uranium-235and H-poly with few other nuclides. The relative delta keff values of Uranium-235 and H-poly, expressed in pcm, were +280 and -212 in ENDF/B-VIII.0 and +332 and -275 in ENDF/B-VIII.1, respectively, which were notable changes in reactivity. These results demonstrated that ORSA was largely insensitive to variations across these nuclear data libraries.

Hong, Evan [North Carolina State University]↗

DOE OSTI2021

Dynamic tunability of phase-change material transition temperatures using ions for thermal energy storage

Thermal energy storage (TES) based on phase-change materials (PCMs) has many current and potential applications, such as climate control in buildings, thermal management for batteries and electronics, thermal textiles, and transportation of pharmaceuticals. Despite its promise, the adoption of TES has been limited, in part due to limited tunability of the transition temperature, which hinders TES performance for varying use temperatures. Transition temperature tuning of a material using an external stimulus, such as pressure or an electric field, typically requires very large stimuli. To circumvent this problem, here, we report on the dynamic transition temperature tunability of a PCM using ions. We achieve a transition temperature tunability up to 6°C in polyethylene glycol (PEG) by using the salt lithium oxalatodifluoroborate at a low voltage of 2.5 V, which may enable simpler and safer devices/system designs. We also explain the thermal properties of the salt/PCM solution using the Flory-Huggins theory.

25 ENERGY STORAGE↗

DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗

DOE OSTI2024

Salt Hydrate Eutectic Thermal Energy Storage for Building Thermal Regulation (Final Technical Report)

Thermal energy storage is anticipated to play an important role in developing the power grid of the future - a power grid that meets increasing demands of users, is resistant to disruptions, but also allows for greater penetration of renewable resources. Specifically, thermal energy storage materials can be integrated into HVAC systems and building envelopes, where they can be used to shift power demands for building climate control from periods of peak demand to periods of low demand. Phase change materials (PCMs) are compelling as low-cost, high energy density thermal energy storage materials for building thermal management. However, there is a lack of high performance low-cost PCMs within the specific temperature ranges which would most effectively allow for power load shifting. Inorganic salt hydrates represent a promising class of PCMs, but their inherent limitations cause them to be currently unavailable for reliable building applications. The overarching goals of this research effort are to: 1) Discover low-cost, high volumetric density salt hydrate eutectic PCMs to store low-quality heat (10 to 40 °C); 2) Introduce a high thermal conductivity matrix to reduce the time constant for energy storage to ~0.1 to 1 hr, incorporate nucleation catalysts to decrease undercooling, and utilize microencapsulation and shape stabilization approaches, minimizing moisture loss/gain, mitigating phase separation, and maintaining stable melting behavior over the lifetime of the compounds; 3) Evaluate the impact these systems have on peak load shifting, and the potential for overall energy savings under different climatic scenarios and building configurations. These goals will be achieved by an integrated research program consisting of six cohesive research subtasks: 1) Materials discovery of eutectic salt hydrate PCMs by using computationally predicted thermodynamic equilibria, coupled with high-throughput experimental validation, 2) Rapid experimental screening of nucleation catalysts identified through robust computational databases, 3) Embedding salt hydrate PCM into a low cost and scalable high conductivity matrix, 4) Microencapsulation of salt hydrate microspheres using hybrid inorganic-polymer microencapsulation approach, 5) Shape stabilization by thermoreversible salt hydrate salogels, and 6) Analysis of end-use using thermal simulations, and characterization of mock-up energy storage finished components.

25 ENERGY STORAGE↗

DOE OSTI2025

Thermal Energy Storage (TES) Modeling and Design (CRADA Final Report)

This project will assess the performance of an innovative high efficiency air conditioner integrated with a composite phase change material (PCM). The research will address critical electric grid challenges by evaluating the thermal efficiency and load-shifting capabilities in NREL’s HVAC characterization lab.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multipolymer Matrix

Additive manufacturing (AM) techniques to directly integrate phase change materials (PCMs) are of interest for efficient thermal energy storage (TES) architectures. Complex, high surface-to-volume ratio composites embedded with PCM can improve thermal management with reduced material waste for customizable device fabrication. Reducing feature sizes of TES-integrated heat exchangers using AM can increase heat transfer without thermal conductivity enhancement. Here, composite AM materials containing 60 wt% microencapsulated phase change materials (MEPCM) are fabricated using off-the-shelf printers at common speeds and resolutions. High MEPCM loading in filaments is achieved with powder extrusion using two polymers, thermoplastic-polyurethane (TPU) and polycaprolactone (PCL), that mediate flexibility and rigidity for effective extrusion and printing without filament fracture or buckling. Furthermore, with PCL and TPU at 20 wt% each and 60 wt% MEPCM (P 20 T 20 M 60 ), smooth, form-stable filaments are consistently printed. Powder-based extrusion displays negligible damaging effects on the MEPCM. Printed P 20 T 20 M 60 demonstrates 105 J/g of energy storage with no degradation through 250 thermal cycles, within 5% of the theoretical storage enthalpy. Combining PCL/TPU shows good interfacial adhesion between print layers and produces high surface area objects, like 15% gyroids, and dense, 100% infilled pucks. Prints are also scalable to a 900 cm 3 honeycomb heat exchanger with an estimated 9 Wh energy storage.

25 ENERGY STORAGE↗

DOE OSTI2023

Suppressing Structural Relaxation in Nanoscale Antimony to Enable Ultralow‐Drift Phase‐Change Memory Applications

Abstract Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10 −4 –10 −3 . This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO 2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Depletion capabilities in the OpenMC Monte Carlo particle transport code

A depletion solver has been implemented in OpenMC and is described herein. The depletion solver is implemented in Python and interfaces with OpenMC’s transport solver through a C++ application programming interface, which enables an in-memory transport-depletion coupling. Multiple integration methods for advancing in time have been implemented and exhibit tradeoffs in cost, accuracy, and memory use. For all time integration methods, evaluation of the matrix exponential is performed by using the incomplete partial fraction form of the Chebyshev rational approximation method. Simulations of a pressurized water reactor (PWR) pincell and a sodium-cooled fast reactor (SFR) assembly were carried out with OpenMC and Serpent. For both problems, the use of a high-fidelity depletion chain results in predictions of k eff that agree within 20–30 pcm between OpenMC and Serpent. Predicted actinide concentrations were found to agree to a fraction of a percent, and most fission product concentrations were found to agree within 1%. Here, the few cases where larger differences were observed can be attributed either to differences in how the energy dependence of fission product yields is handled or deficiencies in the nuclear data used. OpenMC simulations of the PWR and SFR problems using a simplified 228-nuclide depletion chain demonstrate that it achieves accuracy close to that of the full, high-fidelity depletion chain with respect to the studied responses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Improved MPACT energy deposition and explicit heat generation coupling with CTF

The CASL neutronics code MPACT assumes local energy deposition with equilibrium delayed energy for steady-state and transient calculations. These approximations limit the accurate representation of the heat generation in space and its variations over time, both of which are essential for power distribution and thermal–hydraulic coupling analyses. This paper presents an explicit energy deposition model considering the neutron and gamma heating of all regions and the time-dependent delayed energy. The MPACT/CTF interfaces are updated to transfer the explicit heat sources. The new model agrees well with MCNP for problems without thermal–hydraulic feedback. The MPACT/CTF coupled calculation for a hot-full-power quarter-core case using the new model exhibits a reduction of peak pin power by 2.3% and fuel centerline temperature by 17 K. The new model also shows a keff difference up to -100 pcm in depletion and a 30 K peak fuel temperature reduction in a reactivity-initiated-accident problem.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

A multiphysics model of the versatile test reactor based on the MOOSE framework

The traditional modeling approach for sodium fast reactor cores relies on separate physics models, where the fuel performance, thermal–hydraulics, and neutronics calculations required to predict the core physics characteristics for nominal conditions are decoupled by relying on user-imposed boundary conditions. Here, this paper aims at evaluating the impact of multiphysics simulations for predicting the core characteristics of the Versatile Test Reactor, which is being designed as a 300-MWt sodium-cooled fast reactor. The purpose of the Versatile Test Reactor is to accelerate the testing of advanced nuclear materials in the United States. The proposed multiphysics model relies on the Griffin reactor physics code, the SAM thermal–hydraulic system code, the BISON fuel performance code, as well as generic Multiphysics Object-Oriented Simulation Environment capabilities implemented in the open-source tensor mechanics module. For k eff calculations, the introduction of a tight coupling between the neutronics, thermo-mechanical and thermal–hydraulics models induces a change of around 543 pcm in the eigenvalue, compared to the traditional standalone neutronics calculation where approximate temperature profiles are used. The multiphysics model is then employed for quantifying the impact of the thermal conductivity uncertainties on some of the key figures of merit, such as the fuel centerline temperature, assembly powers, and keff for nominal core conditions. As anticipated, uncertainties on fuel thermal conductivity mostly impact the fuel centerline temperature, and to a lesser extend the k eff .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Deployment of neural-network-based neutron microscopic cross sections in the Griffin reactor physics application

The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗

DOE OSTI2025

Thermomechanics coupling to Monte Carlo particle transport on unstructured mesh geometries using Cardinal

Geometry deformation due to thermal expansion influences neutron transport in many systems. Studying this phenomenon involves coupling models for neutronics, thermal hydraulics, and solid mechanics. To enable high fidelity modeling of these coupled physics, new capabilities were introduced in Cardinal, coupling OpenMC Monte Carlo particle transport models with MOOSE thermomechanical physics on unstructured moving-mesh geometries. In this work, we present a fully open-source capability leveraging on-the-fly mesh skinning to automatically regenerate OpenMC geometry, which allows multiphysics feedback from temperature, density, and geometry changes. The new capability is verified using an analytic benchmark slab problem, which couples S 2 neutron transport with thermal conduction, convective boundary conditions, Doppler-broadened cross sections, and nonlinear thermal expansion effects along the heated slab. Cardinal reproduces the analytic solutions for the neutron flux, heating, k eff , and temperature with demonstrated convergence in various error terms including mesh resolution and cross section temperature library spacing. For the nominal benchmark conditions and with a fine mesh, maximum relative errors for neutron flux, temperature, and heating are lower than 1%, while errors in integral quantities such as k eff and slab length are within 1 pcm and 48 µm, respectively. This work (i) presents a new numerical approach to thermomechanics coupling with OpenMC models, (ii) is the first (to our knowledge) to utilize a mechanical partial differential equation (PDE) solution to solve the (Griesheimer and Kooreman, 2022) analytic benchmark, and (iii) develops this verified capability within an open-source package.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Design and performance evaluation of a dual-circuit thermal energy storage module for air conditioners

We present experimental results and a validated numerical model of a dual-circuit phase-change thermal energy storage module for air conditioners. The module incorporates a phase-change material encapsulated in compressed expanded natural graphite foam. We used n-tetradecane as the PCM with a transition temperature (~4.5 °C) suitable for air-conditioning applications. Heat exchange to and from the module is accomplished through two fluid loops operating as a heat source and sink embedded inside multiple slabs of the composite material. This dual-circuit design enables easier integration with air-conditioning equipment and provides enhanced flexibility in system operation as compared to the state-of-the-art thermal storage systems. When integrated with an air-conditioner, this design will enable peak-load shaving and enhances operational efficiency. The thermal storage device was designed for a nominal storage capacity of ~ 3.5 kWh. We evaluated the heat transfer and energy storage performance of this device using standalone heat transfer experiments to estimate key thermal resistances and identify design improvements before integration with an air conditioner. The numerical model of the heat exchanger uses a combination of discretized and lumped parameter approaches to maintain a balance between accuracy and computational expense. Our analyses show that the geometric features and integration of fluid tubes are key contributors to the thermal contact resistance between the fluid and the thermal storage material, and consequently, to the overall performance of the thermal storage module. Our standalone experiments also identified important operating scenarios in which this thermal storage module can be used for air-conditioning in buildings.

25 ENERGY STORAGE↗