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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 721 records · Page 40

Physics-guided Machine Learning: from Supervised Deep Networks to Unsupervised Lightweight Models [Slides]

Machine learning yields great potentials in improving imaging performance (i.e., accuracy and efficiency). The incorporation of governing equation will improve generalization and alleviate label scarcity. Employ physical properties can reduce model complexity and significantly save training cost without compromising accuracy. Combining SciML imaging and edge computing would allow broader applications in energy, medicine, and other domains.

97 MATHEMATICS AND COMPUTING↗

Scalable, Dual-Mode Occupancy Sensing for Commercial Venues

The ability to establish accurate occupancy is a key enabler for improved energy efficiency in human-occupied indoor spaces. The accurate counts can be used to adjust, in real-time, air exchange, heating, and cooling, to closely match the environmental needs of the occupants rather than to use a single setting based on maximum room occupancy. This project focuses on the use of overhead fisheye cameras and artificial intelligence (AI) algorithms as the technology to realize accurate people counting in large commercial spaces. We developed Computational Occupancy Sensing SYstem ("COSSY''), which supports large-scale deployment (thousands of square feet) and straightforward installation (using conventional power over ethernet), while providing high accuracy and low cost. COSSY has been validated at Boston University and by a third party, demonstrating people-counting accuracy of at least 89.5% in large spaces (2,000 sqft). A cost/benefit analysis performed for Boston commercial market indicates that a full payback of COSSY deployment costs due to energy savings would occur within 3-6 months from installation. Applications of COSSY reach far beyond saving energy. The precise people counting in real time could also be useful for emergency response (e.g., fire), in spatial analytics (e.g., office space management) and in some health applications (e.g., social distance assessment during pandemics).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 Lighting R&D Opportunities

BTO’s Lighting R&D Opportunities is updated annually and covers foundational R&D needs for lighting technology and lighting application understanding that will result in maximum energy savings while also optimizing for building occupant well-being and productivity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗

International Cybersecurity: Capabilities and Overview [Slides]

Innovations in clean energy technology are beginning to transform electric grids around the world. It is more important than ever to understand and improve the resiliency and security of the grid against natural and human disruptions as our energy systems become more distributed, intelligent, and interconnected. Through its advanced cybersecurity technical assistance portfolio, experts at the National Renewable Energy Laboratory (NREL) work with international governments to support secure and resilient deployment of renewable energy assets and address grid interconnection challenges. Cybersecurity technical assistance is tailored to the needs of our international partners.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ResStock Measure Documentation: Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER) With Light Envelope Improvements

This report is part of series describing a variety of different ResStock™ measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Residential Variable-Speed Geothermal Heat Pump (4.4 COP, 30.9 EER) with Light Envelope Improvements" measure upgrade methodology and briefly discusses key results. All results can be accessed on the ResStock Open Energy Data Initiative "End-Use Load Profiles for the U.S. Building Stock" data lake and on the data viewer at resstock.nlr.gov.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Accelerating Combustion and Surface Chemistry Simulations

Design of modern combustion systems relies on computer models to predict how changes in design will affect performance. These models have largely displaced previous methods that rely on the designer’s intuition or costly and time-consuming physical testing. By using improved models, design cycles can be shortened, and cleaner and more efficient combustion devices can be created. This project aims to improve computer simulations of transportation fuels with the goal of making these simulations faster and more accurate for predicting combustion in vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗

Modeling Capabilities to Quantify the Benefits of DERMS (Cooperative Research and Development Final Report)

The funds-in under the CRADA will fund a team of National Renewable Energy Laboratory (NREL) researchers to participate in Energy I-Corps (formerly known as Lab-Corps). Energy I-Corps pairs teams of researchers with industry mentors for an intensive two-month training where the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. FedIMPACT, LLC and its affiliate IP Group, Inc., will evaluate the work completed at Energy I-Corps to determine whether it would like to pursue further commercialization and development of related technologies and background intellectual property.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Levelized Cost of Exergy Framework

Exergy is the amount of energy within a substance or within a transfer of energy that can be used to produce work or some other useful output when interacting with some reference environment. Two different energy systems that produce the same output with the same exergetic efficiency must necessarily have the same amount of exergy input, even if the amount of energy input to the two systems is vastly different. For example, a low-grade heat-driven desalination would require far more energy input than a reverse osmosis (RO) plant producing the same amount of water, but if their exergetic efficiencies were the same, they would require the same amount of exergy input. Thus, comparisons between different energy sources on the basis of energy is not always appropriate. Instead, a comparison on a per unit exergy basis provides more insight on the cost-effectiveness of different energy sources and systems. In this presentation, we describe a framework for analyzing the levelized cost of exergy (LCOEx) for both inputs and outputs of various energy systems. Our framework illustrates how the cost per unit exergy of a system's energy source, as well as the exergetic efficiency of the system, greatly affect the cost of the system output. We use the levelized cost of electricity as a benchmark value for LCOEx, due to electricity's ubiquity as an energy source, and because it is relatively inexpensive on a per unit exergy basis. The LCOEx of various heat sources are then compared to the LCOEx of electricity. Medium- and high-grade industrial heat (> 150 degrees C) produced by natural gas tends to have an LCOEx on par with electricity. This is due to the low cost of natural gas, as well as the high exergy content of heat at higher temperatures. Meanwhile, low-grade heat tends to be an expensive exergy source, owing to the low exergy content of the low-grade heat. We first apply our framework to desalination, where RO has come to dominate, due to the low LCOEx of the energy source (electricity) and relatively high exergetic efficiency of RO compared to thermal desalination systems. We then use this framework to highlight an opportunity for dehumidification systems to experience a similar cost improvement as desalination has. If an electrically-driven, high exergetic efficiency dehumidification system were developed (such as the membrane-based dehumidification systems proposed in literature), it would use a low cost exergy source with a high exergetic efficiency and could potentially lower the cost of dehumidification in the way that RO has done for desalination. Finally, we apply our framework to various fuels (natural gas, hydrogen, gasoline, etc.) and energy systems across different sectors (desalination, dehumidification, vehicles, etc.) to understand the variation in the cost of exergy input and exergetic efficiency of different systems and technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

EVI-Rental: A Scalable Model to Quantify the Impact of Rental Car Electrification

This fact sheet describes the Electric Vehicle Infrastructure - Rental Car (EVI-Rental) tool, a flexible and comprehensive simulation tool that addresses key questions about the charging demand, infrastructure needs, and business impacts of adding growing numbers of electric vehicles (EVs) to rental fleets. To validate the EVI-Rental model, the Athena research team conducted a case study at Dallas-Fort Worth International Airport (DFW) to understand the impact of state-of-charge requirements, different charger types and charging schedules, solar power generation, and behind-the-meter storage on a fully electrified rental car fleet.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Uncertainty Visualization for Renewable Energy Potential

In this paper, we present the reV (Renewable Energy Potential) Dashboard, an interactive browser-based tool for uncertainty visualization and data exploration built using customized plotly dash components. With continuing development and utilization of computational models to study the power sector there is an increasing need for data-driven visualization tools which allow scientists, researchers, and engineers to interact with their data in real-time. Our principle motivation for developing this interactive uncertainty visualization was to provide domain scientists and modelers a platform which allows them to better understand and communicate scientific findings stemming from intricate information encoded in their data that is otherwise difficult to capture by conventional analysis. The development of customized dashboard components using the React programming paradigm, combined with fully pre-processed data, allows for users to select a variety of data options to update and manipulate the visualization in a straightforward computationally efficient manner.

dashboard↗

Lack of robustness and accuracy of many numerical schemes for phase-field simulations

In this paper, we study the stability, accuracy and convergence behavior of various numerical schemes for phase-field modeling through a simple ODE model. Both theoretical analysis and numerical experiments are carried out on this ODE model to demonstrate the limitation of most numerical schemes that have been used in practice. One main conclusion is that the first-order fully implicit scheme is the only robust algorithm for phase-field simulations while all other schemes (that have been analyzed) may have convergence issue if the time step size is not exceedingly small. More specifically, by rigorous analysis in most cases, we have the following conclusions: (i) The first-order fully implicit scheme converges to the correct steady state solution for all time step sizes. In the case of multiple solutions, one of the solution branches always converges to the correct steady state solution. (ii) The first-order convex splitting scheme, which is equivalent to the first-order fully implicit scheme with a different time scaling, always converges to the correct steady state solution but may seriously lack numerical accuracy for transient solutions. (iii) For the second-order fully implicit and convex splitting schemes, for any time step size $δt > 0$, there exists an initial condition $u_0$ , with $|u_0| > 1$, such that the numerical solution converges to the wrong steady state solution. (iv) For $|u_0|$ ≤ 1, all second-order schemes studied in this paper converge to the correct steady state solution although severe numerical oscillations occur for most of them if the time step size is not sufficiently small. (v) An unconditionally energy-stable scheme (such as the modified Crank–Nicolson scheme) is not necessarily better than a conditionally energy-stable scheme (such as the Crank–Nicolson scheme). Finally, most, if not all, of the above conclusions are expected to be true for more general Allen–Cahn and other phase-field models.

97 MATHEMATICS AND COMPUTING↗

Autonomous Discovery in Science and Engineering

The Center for Advanced Mathematics for Energy Research Applications (CAMERA) is an integrated, cross-disciplinary center aimed at inventing, developing, and delivering the fundamental new mathematics required to capitalize on experimental investigations at scientific facilities. Jointly funded by the Office of Advanced Scientific Computing Research (ASCR) and the Office of Basic Energy Sciences (BES) within the US Department of Energy’s Office of Science, CAMERA identifies areas in experimental science that can be aided by new mathematical insights, develops the needed algorithmic tools, and delivers them as user-friendly software to the experimental community.

97 MATHEMATICS AND COMPUTING↗

The effects of introducing elasticity using different interpolation schemes to the grand potential phase field model

Introducing elastic energy in the phase field method has been shown to influence interfacial energy, depending on the elastic interpolation scheme. This study investigates the impact of the elastic energy when using a grand potential-based phase field method, comparing the result of Khachaturyan’s strain interpolation scheme (KHS) and Voight-Taylor’s elastic energy interpolation scheme (VTS). The KHS model leads to a decrease in the interfacial energy, while the VTS model leads to an increase. The change in interfacial energy is greater with the VTS model than the KHS model, which suggests that the KHS model is more appropriate to limit the artificial impact of the elastic energy on the interfacial energy. When the contribution at the interface is not negligible, it is shown that both the microstructure evolution kinetics and the equilibrium microstructure can be influenced by the choice of the elastic scheme being used. In addition, this paper shows that the grand potential model might not be appropriate when the system requires the introduction of a composition-dependent term in the elastic energy contribution. This limitation is due to the need for an explicit and invertible relation between the total potential and the composition.

36 MATERIALS SCIENCE↗