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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 37 records · Page 2

Energy-modelled climb and climb-dash - The Kaiser technique

F. Kaiser's germinal 1944 report on his 'resultant-height' concept, now known as energy modelling, is reviewed. The data base for the Me. 262 jet fighter is recreated via spline-lattice representation of specific excess power. Minimum-time and 'distance'-climb trajectories are generated in an attempt to check Kaiser's results. Agreement is good for the minimum-time calculations but only qualitative agreement is obtained for the mysterious 'distance climbs' whose documentation is fragmentary. The character of optimal climb-dash trajectories in energy approximation is examined and illustrated.

Merritt, S. R.

Validation and Calibration of Energy Models with Real Vehicle Data from Chassis Dynamometer Experiments

Accurate estimation of vehicle fuel consumption typically requires detailed modeling of complex internal powertrain dynamics, often resulting in computationally intensive simulations. However, many transportation applications-such as traffic flow modeling, optimization, and control-require simplified models that are fast, interpretable, and easy to implement, while still maintaining fidelity to physical energy behavior. This work builds upon a recently developed model reduction pipeline that derives physics-like energy models from high-fidelity Autonomie vehicle simulations. These reduced models preserve essential vehicle dynamics, enabling realistic fuel consumption estimation with minimal computational overhead. While the reduced models have demonstrated strong agreement with their Autonomie counterparts, previous validation efforts have been confined to simulation environments. This study extends the validation by comparing the reduced energy model's outputs against real-world vehicle data. Focusing on the MidSUV category, we tune the baseline Autonomie model to closely replicate the characteristics of a Toyota RAV4. We then assess the accuracy of the resulting reduced model in estimating fuel consumption under actual drive conditions. Our findings suggest that, when the reference Autonomie model is properly calibrated, the simplified model produced by the reduction pipeline can provide reliable, semi-principled fuel rate estimates suitable for large-scale transportation applications.

42 ENGINEERING

Health and air pollutant emission impacts of net zero CO2 by 2050 scenarios from the energy modeling forum 37 study

Carbon dioxide and non-greenhouse gas air pollutants are emitted from many of the same sources. Decarbonization actions thus typically yield air pollutant emission reductions, resulting in significant air quality benefits. Although several studies have highlighted this connection, including in the context of net zero carbon emission targets, substantial uncertainty remains regarding how alternative technological pathways to this goal will affect the spatial distribution and magnitude of air pollutants. Comprehensive multi-model and multi-scenario analyzes are needed to explore the relative impacts of alternative pathways. Here, our study begins to address this gap by leveraging the results from the recent Energy Modeling Forum 37 inter-model comparison exercise on U.S. decarbonization pathways. Comparing the results of the six teams who submitted air pollutant emissions suggests that strategies that target net zero U.S. carbon emissions would yield significant reductions in many air pollutants, and that this finding is generally robust across pathways. However, some energy sources, such as biomass and fossil fuels with carbon capture, will emit air pollutants and can potentially influence the magnitude, spatial distribution, and even sign of localized air pollutant emission changes. In the second part of this analysis, a simplified air quality and health impacts screening model is used to evaluate the air quality impacts in 2035 of sectoral emission changes from the three models that provided sectoral detail. Relative to a reference scenario, a net zero pathway is estimated to reduce fine particulate matter concentrations across the contiguous U.S., with health benefits from reduced mortality ranging from $\$$65 billion to $\$$250 billion in 2035 alone (2023$\$$s). These benefits would be expected to grow over time as the net zero trajectory becomes more stringent. Both the magnitude of potential benefits and the substantial variation of the projections across models underscore the need for an EMF-like inter-model comparison exercise focused on air quality.

Air pollutants

Holistic Transportation and Energy Modeling

This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Optimal aeroassisted coplanar orbital transfer using an energy model

The atmospheric portion of the trajectories for the aeroassisted coplanar orbit transfer was investigated. The equations of motion for the problem are expressed using reduced order model and total vehicle energy, kinetic plus potential, as the independent variable rather than time. The order reduction is achieved analytically without an approximation of the vehicle dynamics. In this model, the problem of coplanar orbit transfer is seen as one in which a given amount of energy must be transferred from the vehicle to the atmosphere during the trajectory without overheating the vehicle. An optimal control problem is posed where a linear combination of the integrated square of the heating rate and the vehicle drag is the cost function to be minimized. The necessary conditions for optimality are obtained. These result in a 4th order two-point-boundary-value problem. A parametric study of the optimal guidance trajectory in which the proportion of the heating rate term versus the drag varies is made. Simulations of the guidance trajectories are presented.

Halyo, Nesim

Energy Models for One-Carrier Transport in Semiconductor Devices

Moment models of carrier transport, derived from the Boltzmann equation, made possible the simulation of certain key effects through such realistic assumptions as energy dependent mobility functions. This type of global dependence permits the observation of velocity overshoot in the vicinity of device junctions, not discerned via classical drift-diffusion models, which are primarily local in nature. It was found that a critical role is played in the hydrodynamic model by the heat conduction term. When ignored, the overshoot is inappropriately damped. When the standard choice of the Wiedemann-Franz law is made for the conductivity, spurious overshoot is observed. Agreement with Monte-Carlo simulation in this regime required empirical modification of this law, or nonstandard choices. Simulations of the hydrodynamic model in one and two dimensions, as well as simulations of a newly developed energy model, the RT model, are presented. The RT model, intermediate between the hydrodynamic and drift-diffusion model, was developed to eliminate the parabolic energy band and Maxwellian distribution assumptions, and to reduce the spurious overshoot with physically consistent assumptions. The algorithms employed for both models are the essentially non-oscillatory shock capturing algorithms. Some mathematical results are presented and contrasted with the highly developed state of the drift-diffusion model.

Jerome, Joseph W.

Integration of Electric Vehicle Charging Loads in Residential Building Stock Energy Modeling

The rapid adoption of electric vehicles (EVs) has resulted in significant new household electric loads that have the potential to change how energy costs are incurred by homeowners and the landscape of utility operations and energy infrastructure. Whereas adoption patterns and magnitudes of residential building and EV charging loads are influenced by distinct factors, the loads themselves are tightly coupled with the behavior of the individual occupants and EV owners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Modeling energy flow and nutrient cycling in natural semiarid grassland ecosystems with the aid of thematic mapper data

Energy flow and nutrient cycling were modeled as affected by herbivory on selected intensive sites along gradients of precipitation and soils, validating the model output by monitoring selected parameters with data derived from the Thematic Mapper (TM). Herbivore production was modeled along the gradient of soils and herbivory, and validated with data derived from TM in a spatial data base.

Lewis, James K.

Informing electrification strategies of residential neighborhoods with urban building energy modeling

Electrifying end uses is a key strategy to reducing GHG emissions in buildings. However, it may increase peak electricity demand that triggers the need to upgrade the existing power distribution system, leading to delays in electrification and needs of significant investment. There is also concern that building electrification may cause an increase of energy costs, leading to further energy burden for low-income communities. This study uses the urban scale building modeling tool CityBES to assess the electrification impacts of more than 43,000 residential buildings in a neighborhood of Portland, Oregon, USA. Energy efficiency upgrades were investigated on their potential to mitigate the increase of peak electricity demand and energy burden. Simulation results from the calibrated EnergyPlus models show that electrification with heat pumps for space heating and cooling as well as for domestic water heating can reduce CO2e emissions by 38%, but increase peak electricity demand by about 9% from the baseline building stock. Combining electrification measures and energy efficiency upgrades can reduce CO2e emissions by 48% while reducing peak electricity demand by 6% and saving the median household energy costs by 28%. City and utility decision makers should consider integrating energy efficiency upgrades with electrification measures as an effective residential building electrification strategy, which significantly reduces carbon emissions, caps or even decreases peak demand while reducing energy burden of residents.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

A comparison of observed and model energy balance for an extratropical cyclone system

Eddy kinetic energy budgets are presented for both moist and dry 48 h forecasts and corresponding observations of a developing winter extratropical cyclone. A diagnosis of observational data energetics is presented and compared with model results for an intense, occluding winter cyclone associated with a strong, well-developed jet stream. The nature of the eddy kinetic energy sources and sinks associated with the strong baroclinic development occurring in this cyclonic system is examined, and the extent to which to observed energy sources and sinks are present in the numerical predictions is addressed. The possibility of explaining differences between the observed and predicted cyclone systems by analyzing these kinetic energy properties is considered.

Dare, P. M.

Modeling energy and mass fluxes from prairie canopies

The main emphasis of this research project is on partitioning of mass and energy fluxes between vegetation and soil at the FIFE site, preparation of data from the FIFE Information System for an international thermal data set comparison, and studying the relation between surface temperatures observed from satellites and in situ measurements of surface temperature.

Norman, John M.

The seasonal CO2 cycle on Mars - An application of an energy balance climate model

Energy balance climate models of the Budyko-Sellers variety are applied to the carbon-dioxide cycle on Mars. Recent data available from the Viking mission, in particular the seasonal pressure variations measured by Viking landers, are used to constrain the models. No set of parameters was found for which a one-dimensional model parameterized in terms of ground temperature gave an adequate fit to the observed pressure variations. A modified, two-dimensional model including the effects of dust storms and the polar hood reasonably reproduces the pressure curve, however. The implications of these results for Martian climate changes are discussed.

James, P. B.

Coupling Noah-Multiparameterization land-surface Model with Energy Research and Forecasting Model

The Energy Research and Forecasting (ERF) model is a high-performance atmospheric model built on the AMReX adaptive mesh refinement (AMR) framework, enabling efficient simulations on heterogeneous computing platforms that combine multicore processors with hardware accelerators. To support land–atmosphere interactions within ERF’s AMR-based environment, a land-surface model must be capable of operating directly on hierarchically refined meshes. In this work, we present a methodology for coupling the Fortran-based Noah-Multiparameterization (Noah-MP) land-surface model with ERF’s C++ codebase. Rather than rewriting Noah-MP, we construct a Fortran–C interoperability layer using CodeScribe, a tool that leverages large language models (LLMs) to automate the generation of interface code. CodeScribe applies structured prompting techniques to generate bindings that support efficient data exchange and function calls between ERF and Noah-MP. The coupling framework also incorporates AMR-aware data handling strategies, allowing NoahMP to operate seamlessly within ERF’s hierarchical mesh structure. This work provides a structured approach for integrating legacy Fortran models into modern C++-based modeling systems using LLM-assisted code generation.

54 ENVIRONMENTAL SCIENCES

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

Comparative Study of Enhanced Geothermal System Supply Curves Across CONUS from Two Temperature Models Using the Renewable Energy Potential Model (reV)

Enhanced geothermal systems (EGS) have had recent breakthroughs within the geothermal sector. These breakthroughs are reflected in the National Renewable Energy Laboratory (NREL) 2024 Annual Technology Baseline and will result in updated EGS supply curves (i.e., the available resource capacity relative to cost). Our research uses NREL's Renewable Energy Potential (reV) model to compare EGS supply curves across the conterminous United States (CONUS) for two different temperature models: the Stanford temperature model (STM) and the Southern Methodist University temperature model (SMU). The reV model provides the levelized cost of energy (LCOE) at a consistent resolution across CONUS, taking into consideration transmission costs and constraints as well as technical exclusions pertaining to sensitive cultural, ecological, or infrastructure locations. In addition to a countrywide analysis of both models, we also conducted a regional analysis of Texas. We observed the STM had, on average, lower temperatures across different depths, resulting in slightly higher mean and median LCOEs as compared to the SMU temperature model at the same depths. In the regional analysis for Texas, however, when we compared only the common points between the two temperature models, the STM had lower median and mean LCOEs compared to SMU due to higher temperatures at depths greater than 5 km.

enhanced geothermal systems

An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.

Ma, Ke

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY