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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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Impact Energy Analysis in Kolsky Bar Experiments for Shock Mitigation Applications.
Abstract not provided.
Performance Scaling Variability and Energy Analysis for a Resilient ULFM-based PDE Solver.
Abstract not provided.
A Beam Energy Analysis and Monitoring System for Linear Accelerators
Explore the source record for details and available documents.
Scaling and Energy Analysis for a Resilient ULFM-Based PDE Solver.
Abstract not provided.
Systems and Energy Analysis: Post-combustion Analysis Update
Presented by NETL at 2017 NETL Carbon Capture Project Review Meeting, 08/17
Informing energy consumption uncertainty: an analysis of energy data revisions
Quality energy consumption data are important for many types of analysis, and global data sets estimate trends of county level energy consumption, derived from country reported data and regional reports. We present a novel basis for informing uncertainty in energy data by quantifying the changes in reported energy consumption as countries update their previously reported data. We use 17 editions of the British Petroleum World Energy Statistics (2001-2017) to evaluate how reported energy consumption is revised over time in aggregate coal, oil, and natural gas consumption data. We find that 70% of non-zero data points are adjusted by an average of 1.3% of a country’s total fossil fuel use in the year after their first publication. Earlier data points are revised less often, but almost half of historical trends contain some revisions in later years. The size and rate of data revisions vary over countries and fuels: coal data points have larger, less frequent revisions while oil data points have smaller more frequent revisions, with natural gas in between. A K-means cluster analysis was performed to group together countries with similar revision patterns. These groups span income, economy classification, OECD membership, and regions. Standard country groupings, therefore, do not predict the extent to which a country's energy data has undergone revisions in the past.
Energy-Systems Economic Analysis
Energy Systems Economic Analysis (ESEA) program is flexible analytical tool for rank ordering of alternative energy systems. Basic ESEA approach derives an estimate of those costs incurred as result of purchasing, installing and operating an energy system. These costs, suitably aggregated into yearly costs over lifetime of system, are divided by expected yearly energy output to determine busbar energy costs. ESEA, developed in 1979, is written in FORTRAN IV for batch execution.
Energy Storage and Decarbonization Analysis for Energy Regulators: Technical Analysis for the Illinois Commerce Commission
Jurisdictions around the world are enacting and enforcing an increasing number of policies to fight climate change, leading to higher penetration of variable renewable energy (VRE) and energy storage systems (ESSs) in the power grid. One of the biggest challenges associated with this process is the evaluation of the appropriate amount of ESS required to mitigate the variability of the VREs and achieve decarbonization goals of a particular jurisdiction. This report presents methodologies developed and results obtained for determining the minimum amount of ESS required to adequately serve load in a system where fossil fueled generators are being replaced by VREs over the next two decades. This technical analysis is performed by Sandia National Laboratories for the DOE Office of Electricity Energy Storage Program in collaboration with the Illinois Commerce Commission (ICC). The Illinois MISO Zone 4 is used as a case study. Several boundary conditions are investigated in this analysis including capacity adequacy and energy adequacy to determine the quantity of ESS required for MISO Zone 4. Multiple scenarios are designed and evaluated to incorporate the impact of varying capacity values of VREs and on the resource adequacy of the system. Several retirement scenarios involving fossil-fueled assets are also considered. Based on the current plans of new additions and retirements of generating assets, the results of the technical analysis indicate that Illinois MISO Zone 4 will require a significant quantity of ESS to satisfy their electricity demand over the next two decades.
MetaHeuristic Feature Selection for Energy Group Optimization and Analysis
Energy discretization is a crucial component of deterministic neutron transport simulations. Metaheuristic (MH) optimizers are effective algorithms to determine group structures that maximize both solution accuracy and computational efficiency. This project establishes a framework for optimizing group structures for PARTISN simulations using the Python library MEALPY. Group structure optimization is formulated as a binary feature selection problem, and results are investigated with permutation and material importance techniques to determine physically relevant energy bounds. We conclude that MH optimizers find group structures that drastically improve flux calculations while preserving k-effective accuracy. Further, we find that individual energy bounds are not necessarily physically relevant, but rather specific energy ranges are.
Modified Energy Span Analysis Reveals Heterogeneous Catalytic Kinetics
Mechanistic modeling is a cornerstone of catalyst development generally conducted with microkinetic models or density functional theory-based energy profiles. We extend the energy span model of homogeneous catalysis to heterogeneous systems by introducing the modified energy span analysis (MESA) model by implementing collision theory and gas-phase concentration effects. We determine analytically turnover frequencies, coverages, rate-determining steps, apparent activation energies, and reaction orders in agreement with microkinetic and kinetic Monte Carlo simulations. The model applies to discrete catalyst state systems, including single-atom catalysts, homogeneous systems, and microporous materials. A generalizable rate expression is derived for reactor modeling or mechanistic insights from solely experimentally measured reaction orders. Here, we illustrate MESA on three published mechanisms and reveal unexpected phenomena absent in traditional energy span profiles.
Transport Energy Impact Analysis; NREL (National Renewable Energy Laboratory)
Presented at the Sustainable Transportation Energy Pathways Spring 2015 Symposium on May 13, 2015, this presentation by Jeff Gonder of the National Renewable Energy Laboratory (NREL) provides information about NREL's transportation energy impact analysis of connected and automated vehicles.
Material and Energy Efficiency: A Framework for Broader Analysis of Energy Use in the U.S. Economy
Energy efficiency analysis has focused predominantly on reducing energy at its point of use by individual components, processes, or products. Efforts to address the energy embodied in materials through strategies and technologies that reduce raw material production - while maintaining the function and use of materials - offer a complementary and expansive approach to traditional energy efficiency analysis. The U.S. Department of Energy (DOE) energy analysis community currently lacks analytical tools that are appropriate for 1) estimating on a product and economy-wide basis energy efficiency potential achieved through material efficiency strategies and 2) evaluating how these new strategies may complement existing energy efficiency efforts. The goal of this report is to describe a standardized analysis framework that would enable calculation of embodied and direct energy and the estimation of energy reduction potential achieved through changes in material use. The proposed framework meets this functionality by spanning the entire U.S. economy, including international trade flows; capturing material and energy use in products and services from raw material extraction to retirement; maintaining material and energy balances; and adjusting dynamically to absolute and relative changes in materials and energy use. The framework is composed of two main elements: a dynamic hybrid input-output (IO) model and a material energy identity. The hybrid IO model defines recipes for material and energy flows in physical (e.g., British thermal units [Btus] and tons) and monetary units, and allows for dynamic adjustments to the amount of materials and energy used. The second element of the analytical framework, the material energy identity, acts as a way of identifying and organizing energy and material efficiency strategies, which are then implemented and analyzed in the hybrid IO model. The report also provides a simple example application of the proposed framework, which illustrates the concept of reducing energy use through changes to material efficiency.
Dynamical Downscaling of Earth System Model Data for Energy System Analysis
Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.
National Renewable Energy Laboratory Data and Analysis on Energy in Cities
This is a broad overview of the data and analysis developed through the Cities-LEAP project that will be presented at the Colorado College Economics and Business Department seminar series on September 3, 2018.
Assessing National Employment Impacts of Investment in Residential and Commercial Sector Energy Efficiency: Review and Example Analysis
Energy efficiency is a key solution to concerns regarding future energy supply, energy security, and the harmful long-term effects of climate change. In addition to addressing these issues, actions motivated by governmental policies and programs, along with efforts by utilities and third parties, result in greater energy efficiency and also save consumers money. A continuing question is the degree to which energy efficiency measures spur economic growth and higher levels of employment. Research interest in this topic has recently risen in response to trends reflecting increased market adoption of energy efficiency measures, increased reliance on energy efficiency as a resource to offset new electricity generation, and the utilization of energy efficiency portfolio standards by states to spur wider adoption of energy efficiency and reduce future electricity demand.
Energy Savings Analysis of the Proposed NYStretch-Energy Code 2018
This study was conducted by the Pacific Northwest National Laboratory (PNNL) in support of the stretch energy code development led by the New York State Energy Research and Development Authority (NYSERDA). In 2017 NYSERDA developed its 2016 Stretch Code Supplement to the 2016 New York State Energy Conservation Construction Code (hereinafter referred to as “NYStretch-Energy”). NYStretch-Energy is intended as a model energy code for statewide voluntary adoption that anticipates other code advancements culminating in the goal of a statewide Net Zero Energy Code by 2028. Since then, NYSERDA continues to develop the NYStretch-Energy Code 2018 edition. To support the effort, PNNL conducted energy simulation analysis to quantify the energy savings of proposed commercial provisions of the NYStretch-Energy Code (2018) in New York. The focus of this project is the 20% improvement over existing commercial model energy codes. A key requirement of the proposed stretch code is that it be ‘adoptable’ as an energy code, meaning that it must align with current code scope and limitations, and primarily impact building components that are currently regulated by local building departments. It is largely limited to prescriptive measures, which are what most building departments and design projects are most familiar with. This report describes a set of energy-efficiency measures (EEMs) that demonstrate 20% energy savings over ANSI/ASHRAE/IES Standard 90.1-2013 (ASHRAE 2013) across a broad range of commercial building types and all three climate zones in New York. In collaboration with New Building Institute, the EEMs were developed from national model codes and standards, high-performance building codes and standards, regional energy codes, and measures being proposed as part of the on-going code development process. PNNL analyzed these measures using whole building energy models for selected prototype commercial buildings and multifamily buildings representing buildings in New York. Section 2 of this report describes the analysis methodology, including the building types and construction area weights update for this analysis, the baseline, and the method to conduct the energy saving analysis. Section 3 provides detailed specifications of the EEMs and bundles. Section 4 summarizes the results of individual EEMs and EEM bundles by building type, energy end-use and climate zone. Appendix A documents detailed descriptions of the selected prototype buildings. Appendix B provides energy end-use breakdown results by building type for both the baseline code and stretch code in all climate zones.