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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nexus of electrification and energy efficiency retrofit of commercial buildings at the district scale

Rapid electrification of buildings at the district scale is needed for cities to achieve climate change mitigation goals. However, most electrification studies focus on either the single building level or the city/region building stock level, and depend on the slow and uncertain process of requesting personally identifiable customer energy usage data from utilities. To answer a key question facing local policymakers: “Where can electrification proceed at scale without first upgrading the grid?” this study aims to quantify and inform building electrification impacts at the district scale using detailed building energy modeling and based on public records datasets. We explore how energy efficiency retrofits can help mitigate increased peak electric demand, and quantify impacts to energy use and carbon emissions. Building energy models of a baseline, and scenarios of simple electrification, energy retrofits, and electrification in combination with retrofits were created and simulated for 54 commercial buildings in two contiguous districts of San Francisco. A simple electrification scenario increased annual electricity consumption but reduced annual site energy usage by 15% to 17%, mainly due to replacing inefficient gas furnaces and boilers with more efficient heat pumps. Peak demand increased 7.4% for Fisherman's Wharf (e.g. within the capacity of the existing power grid), while the Design District showed a marginal decrease. Annual carbon emissions were reduced by 46% and 37%. Combining electrification with efficiency upgrades reduced peak demand by 26% and 40%, and annual carbon emissions by 63% and 64% for the two districts. Furthermore, these results indicate that impacts of electrification depend on the mix of building uses within a district, and coupling electrification with energy efficiency upgrades is an effective strategy to decarbonize buildings while maintaining or reducing the peak electric demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Standardization of the Distributed Ledger Technology cybersecurity stack for power and energy applications

The global trend towards the integration of distributed energy resources is opening the doors to advanced, complex, and distributedmarketplaces. Such advanced ecosystems, where utility-owned and non utility-owned assets can contribute towards grid operations,generally require distributed communication and grid architectures, which can be supported by Distributed Ledger Technologies(DLTs). However, the potential of DLTs for long-term scalable solutions in operational technology applications has not been fullyutilized, partly due to the lack of standardization across and between different DLTs, as well as other supporting building blocks(e.g., communication protocols). This paper attempts to address this gap by proposing a DLT cybersecurity stack specificallydesigned for researchers, DLT technology developers, and end users (such as utilities). The DLT cybersecurity stack has beennotionally mapped to related cybersecurity components, namely: the Open Systems Interconnection (OSI) model, the TransmissionControl Protocol/Internet Protocol (TCP/IP) suite, and existing Smart Grid architecture frameworks. In addition, the paper discussesseveral cybersecurity implications, and demonstrates the potential uses of the DLT stack through multiple power and energy usecases. It is important to note that the stack can be also applied to the DLT use cases that are outside the power and energy domain.This work has been performed by the Cybersecurity Task Force under the IEEE P2418.5 Blockchain for Energy Standard workinggroup that is stationed under the IEEE Power and Energy Society’s Smart Buildings, Loads, and Customer Systems (SBLC)technical committee.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamic signal recovery in distribution grids using compressive lossy measurements

Distribution system state estimation requires reliable aggregation of the measured data. However, the large volume of the measured data imposes a significant stress on the underlying communication infrastructure. With the challenges associated with measurement availability, current distribution systems are typically unobservable. To cope with the unobservability issue, compressive sensing theory allows us to recover system state information from a small number of measurements provided the states of the distribution system exhibit sparsity. In this paper, we evaluate the robustness of an updated Kalman filtered modified compressive sensing (KF-ModCS) technique that dynamically estimates the grid states using a small fraction of measured data. In practice, measurements used for sparsity based state estimation may also be intermittent due to communication network induced losses. Further, to understand the effect of packet losses on KF-ModCS, we provide an upper bound for the expected variances of the state estimation error for a given rate of information loss. This upper bound is further improved if the support set of the sparse signal that characterizes the state dynamics does not change over time and/or the reduced model is observable. Simulations based on two practical data sets collected from actual customers in a distribution grid validate the theoretical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

System benefits of industrial battery storage: A comparison of grid and facility control and dispatch

Customer-owned, distributed battery installations are being incentivized by utilities to increase installed battery capacity. In many of these incentive agreements, the battery owner relinquishes battery control to the utility in exchange for incentive money. The industrial sector has lagged in storage installation when compared to the residential and commercial sectors. This study compares the economic advantages to utilities and industrial facilities in different dispatch control situations. The study presents a novel framework for the optimization of multiple systems using load profiles from the industrial, residential, and commercial sectors. Case studies are presented to illustrate different dispatch scenarios. Further, the simulations showed more fiscal benefit for the industrial facilities to dispatch the battery for electrical demand reduction than utility dispatch. In the case studies, facility dispatch control resulted in an increase of facility savings by a factor of about 8.7 when compared to utility dispatch. Battery size plays a significant factor on the impact of the grid’s generating costs, showing that larger batteries can provide significant benefit even if dispatched by the facility. Future policies concerning industrial battery installations should consider overall economic benefits to utility and facility in the form of rate structures and incentive participation based on battery size.

25 ENERGY STORAGE↗
DOE OSTI2023

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Aggregate residential demand flexibility behavior: A novel assessment framework

Residential demand flexibility (DF) could save the U.S. electric grid up to 10 GW of peak demand while supporting increased amounts of renewable generation. However, less than 40% of the estimated DF peak reduction capacity is currently realized, and less than 8% of American households are enrolled. These low participation rates are combined with high rates of "overriding" a DF event and eventual opt-outs among enrolled customers. There is still not a comprehensive understanding of the drivers of DF participation and occupant interaction with DF program signals. We, therefore, present a novel survey processing framework to assess occupant DF-relevant behavior from the American Time Use Survey (ATUS). Using the framework, we summarize both the extensive and intensive behavior of more than 200,000 ATUS respondents (2003-2018 data) and provide insights on the DF-relevant behavior of residential occupants, which is generally overlooked in the literature. Here we use the framework to identify the activity priorities of residential occupants in the United States during different DF-relevant periods (critical peak, peak, and off-peak). These preferred activities capture overlooked routine behaviors that could be barriers to DF participation, if ignored, and might explain the high levels of overrides often exhibited by participants of demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Stretchable and wearable polymeric heaters and strain sensors fabricated using liquid metals

Wearable electronic devices (WEDs) are receiving significant attention because of the increasing interest in soft robotics, electronic skin, and wearable sensors. Liquid metals (LMs) are compelling for WEDs owing to their metallic conductivity, fluidic nature, and low toxicity. For this study, we fabricated stretchable and soft WEDs using LM (eutectic gallium-indium alloy) wires (LMWs) patterned via force wetting through custom-made stencils on an elastic substrate. LMWs can generate thermal energy via Joule heating upon current application and deliver it to the substrate, resulting in wearable polymeric heaters. The LM mixed with carbonyl iron particles (CIPs) can also be patterned while preserving fluidic behavior. The degree of thermal energy generated through the LMWs can be manipulated as a function of the CIP concentration in the LM and geometrical factors of the electrode patterns, i.e., width and length. An elastic film patterned with LMWs attached to the human body exhibits changes in the effective electrical resistance depending on applied strain, demonstrating potential as a wearable strain sensor. This LM utilized WED that can generate thermal energy upon current application through the LMWs and detect the bodily motion has significant potential for application in wearable thermotherapy, electronic skin, and soft sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

MPLBM-UT: Multiphase LBM library for permeable media analysis

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The MOOSE electromagnetics module

The Multiphysics Object-Oriented Simulation Environment (MOOSE) electromagnetics module has been developed to increase MOOSE physics module capabilities, enabling standalone and coupled computational electromagnetics within the MOOSE multiphysics ecosystem. The module is actively being utilized in the areas of plasma physics and advanced manufacturing, and it currently provides initial demonstrated capability in multi-dimensional, complex-valued electromagnetic wave propagation, electrostatic contact, reflection and transmission, and electromagnetic eigenvalue problems. Two-dimensional wave propagation and one-dimensional wave reflection and transmission are showcased as examples in this work. The modularity, parallelism, and plug-in infrastructure for custom future development is inherited from MOOSE itself, and the module can be used with both MOOSE-based and external codes, giving great flexibility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

NEML2: An efficient and modular multiphysics constitutive modeling library for hybrid computing environments

This paper presents NEML2, an open-source, high-performance library developed for constitutive material modeling, designed to support the flexible and modular development of models for complex material behavior. Building on the foundational structure of its predecessor, NEML, the NEML2 library introduces significant improvements, including enhanced vectorization, automatic differentiation, and seamless integration with PyTorch, facilitating the application of machine learning techniques in material simulations. NEML2 provides a C++ backend with Python bindings, enabling users to create custom material models that can be executed efficiently on both CPU and GPU platforms. The library also supports coupling with Multiphysics simulation frameworks like MOOSE, making it suitable for realistic simulations involving coupled physical processes. Rigorous quality assurance through unit and regression testing ensures the reliability of results, while the extensible, user-friendly design encourages collaboration and reproducibility across the scientific community. This paper provides an overview of NEML2’s architecture, core features, and applications, highlighting its impact on accelerating material qualification and advancing computational methods in materials science.

GPU↗
DOE OSTI2025

UQpy Version 4.2: Uncertainty quantification with Python

We introduce a new module for the UQpy software package which extends its capabilities into the field of Scientific Machine Learning. This module builds on PyTorch to create a flexible and robust platform for uncertainty quantification in machine learning. The scientific machine learning module of UQpy introduces custom layers, neural networks, and neural network trainers that are compatible with torch version 2.2.2 and allow for “plug and play” integration into existing torch code.

Neural networks↗
DOE OSTI2025

SNAPRed: Reduction of multidimensional neutron time-of-flight diffraction data

SNAP is a neutron time-of-flight diffractometer at the Spallation Neutron Source operated by Oak Ridge National Laboratory. It generates large arrays of neutron detection events that encode the crystalline atomic structure of materials under study. SNAPRed is an application that makes these datasets accessible to end users by orchestrating the process of data reduction while automatically managing the variable neutron instrumentation configuration. It supports arbitrary grouping and masking of individual detector pixels and includes custom-developed data compression approaches to accommodate the large volumes of data generated by the SNAP instrument.

Diffraction↗
DOE OSTI2020

Stabilization of light-induced effects in Si modules for IEC 61215 design qualification

Standardized testing of commercial photovoltaic modules is widely used around the world and decreases risks of module failures. Such testing also reduces financial risks for module manufacturers and customers. This work examines the expected impact of certain defects in silicon (Si) modules during standardized accelerated testing. Specifically, the behavior of boron-oxygen (BO) light-induced degradation (LID) and light- and elevated temperature-induced degradation (LeTID) are simulated during some of the stress tests in IEC 61215. LID and LeTID reaction rates at qualification temperatures are estimated from earlier published data. It is demonstrated the BO-related LID may cause some false positives and false negatives when IEC 61215 tests are performed as prescribed in the 2016 published version. Possible stabilization steps to avoid these false results are suggested. State changes for the defects causing LeTID occur much more slowly than those causing BO LID, and therefore LeTID is predicted to have a lesser impact on the IEC 61215 stress tests results.

14 SOLAR ENERGY↗
DOE OSTI2020

Hand me the franchise agreement: municipalities add another policy tool to their clean energy toolbox

A growing list of the more than 20,000 municipalities in the United States are considering pathways to achieve renewable energy goals. One emerging trend is for municipalities to incorporate energy objectives into their franchise agreements with an electric service provider. Franchise agreements are contracts between municipalities and utilities that grant the utility authority to serve customers in the municipality. In some cases, municipalities have negotiated renewable energy objectives into these agreements. It is still unclear how many municipalities have exercised this authority and to what effect. From a national dataset of 3500 franchise agreements, we selected five cities that adopted renewable energy or energy efficiency objectives into or alongside their franchise agreements for deeper analysis: Chicago, Illinois; Denver, Colorado; Sarasota, Florida; Minneapolis, Minnesota; and Salt Lake City, Utah. We generated seven key takeaways for other cities considering this pathway to achieve their energy objectives. In summary, municipalities can leverage franchise negotiations to pursue both modest and ambitious clean energy goals (i.e. 100% renewable electricity). This study provides municipalities with critical insight on how they can use this potentially formidable tool to achieve their own energy objectives.

14 SOLAR ENERGY↗
DOE OSTI2023

Characterization of high-temperature figure of merit for solar-thermal absorbers

The figure of merit (FOM) is a widely used metric to characterize the solar-thermal conversion performance of solar absorber layers. Many of previous works have reported FOMs estimated from the radiative properties measured at room temperature. However, advanced concentrated solar power (CSP) plants operate at very high temperatures (~750°C), which can strongly affect the absorber’s radiative properties. Here, the present work proposes using a 1-D conduction-based reference bar technique to directly measure the converted thermal energy to determine the FOM at high absorber temperatures (≳ 750°C) while operating under a large solar concentration (~ 1200 x suns). Using the finite difference method, we carefully analyze several key parameters influencing the design of the experimental setup, such as temperature distribution, material properties, heat loss, and sensor accuracy. In addition, a rigorous uncertainty analysis is incorporated into the FOM to ascertain the confidence level of the result. We validate this new technique on a custom-built tungsten reference bar with an oxidized Inconel 625 solar-thermal absorber. A good agreement between the model and the experiment shows the reliability of the FOM measurement with a well-defined uncertainty. The same method can be implemented to measure the high-temperature FOM of most surface or volumetric solar absorbers for CSP.

14 SOLAR ENERGY↗
DOE OSTI2025

Flexible transparent conducting electrodes unexpectedly influence MAPbI 3 film morphology and perovskite solar cell performance

Fabricating perovskite solar cells (PSCs) on plastic substrates will enable cost-effective manufacturing of lightweight and portable energy systems. Here, we study the influence of flexible transparent conductive electrodes (TCEs) on the methylammonium lead iodide (MAPbI3) film morphology and PSC performance. Three types of TCEs on polyethylene terephthalate (PET) are compared: a custom-made AgNWs/indium zinc oxide hybrid TCE and two commercial substrates with indium tin oxide (ITO) or metal/insulator/metal (MIM) as the TCE. Using the same p-i-n architecture and hole transport layer (HTL), we find that PSCs fabricated on the hybrid TCE show better performance and stability compared to those made on commercial TCEs. The PSC performance enhancement is attributed to the superior structural and optical properties of MAPbI3 film deposited on the hybrid TCE, which is explained by the surface energy difference of the HTL. While it is anticipated that solar cell performance can be affected by TCEs’ transmittance and sheet resistance as they determine light absorption and carrier transport, respectively, our finding of TCE influencing the morphology and crystallinity of MAPbI3 film, and hence PSC performance, is unexpected.

14 SOLAR ENERGY↗
DOE OSTI2021

Pressurized in situ X-ray diffraction insights into super/subcritical carbonation reaction pathways of steelmaking slags and constituent silicate minerals

This study explores mineral carbonation of industrial stainless steelmaking slags and relevant synthetic constituent minerals via in situ pressurized X-ray diffraction, to clarify carbonation reaction pathways and efficiency for carbon storage and waste valorization. The primary mineral phases of Argon Oxygen Decarburization (AOD) and Continuous Casting (CC) slags, namely, åkermanite, bredigite, cuspidine, merwinite, and β- and γ-C 2 S, were reacted in a custom-built beryllium-capped XRD reactor filled with either water-saturated (wet) subcritical CO 2 (g), or wet supercritical CO 2(SC) , in a series of carbonation experiments. Formation of calcite and aragonite was observed for most Ca-bearing minerals, transient precipitation of metastable vaterite was observed, while carbonation of AOD and CC slags in CO 2(SC) resulted in hydrated crystalline calcium carbonates and indirect evidence of amorphous carbonate. Overall, results obtained suggest that low-pressure subcritical carbonation routes are attractive for standalone slag carbonation processes, while high-pressure supercritical carbonation routes are amiable to symbiotic integration with CO 2(SC) -generating green technologies.

42 ENGINEERING↗
DOE OSTI2022

Leveraging computational thermodynamics to guide SiC-ZrC chemical vapor deposition process development

Here using the CALPHAD approach to understand zirconium carbide deposition, a series of phase equilibria were calculated from a custom thermodynamic database based on a literature source, and the equilibria were used to explore the potential chemical vapor deposition (CVD) processing space in the ZrCl 4 -CH 3 SiCl 3 -CH 4 -H 2 system as a function of pressure, temperature, and gas composition. Several gas ratios were considered. At a given ZrCl 4 :CH 3 SiCl 3 ratio within the range studied, the most important factor was found to be the ratios of CH 4 :ZrCl 4 , wherein the nature of the composition – carbide vs. silicide – could be controlled. A pure binary composition of ZrC and SiC is expected to form by increasing the initial amount of methane and decreasing the amount of hydrogen from values predicted purely based on thermodynamic equilibrium. Rietveld analysis of the x-ray diffractograms from corresponding experimental depositions confirmed that increasing the CH 4 :ZrCl 4 ratio increased the fraction of carbon-containing species (SiC, ZrC) and decreased the fraction of non-carbides (ZrSi, ZrSi 2 , etc.), as predicted from the CALPHAD results.

36 MATERIALS SCIENCE↗