Search NASA⌕ Search

SEARCH · Search NASA

Results for “Energy Simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MCCCS-MN

The MCCCS‒MN (Monte Carlo for Complex Chemical Systems‒Minnesota) software is developed by the Siepmann research group at the University of Minnesota. MCCCS‒MN allows for the simulation of multi-component molecular systems in the canonical, isobaric-isothermal (including constant stress for solids), grand-canonical, semi-grand, and Gibbs (NVT, NPT, and more than two simulation boxes) ensembles. It uses the configurational-bias Monte Carlo method to efficiently sample phase space for linear, branched and cyclic chain molecules, the adiabatic nuclear and electronic sampling Monte Carlo method to treat many-body polarization effects, and the aggregation-volume-bias Monte Carlo algorithm to efficiently sample the spatial distribution of associating molecules. MCCCS-MN employs a molecular representation of the system where force fields contain bonded and non-bonded terms. Funding for the development of MCCCS-MN through grants from the National Science Foundation (simulation of fluid phase equilibria and chromatography) and the Department of Energy (simulation of adsorption equilibria) is gratefully acknowledged.

Siepmann, J.Ilja [University of Minnesota - Twin C↗
DOE OSTI2015

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

This study was intended to validate actual performance of three ZERHs in the Northeast to energy models created in REM/Rate v14.5 (one of the certified software programs used to generate a HERS Index) and the National Renewable Energy Laboratory’s Building Energy Optimization (BEopt™) v2.3 E+ (a more sophisticated hourly energy simulation software). This report details the validation methods used to analyze energy consumption at each home.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Model Energy Codes End-Use Opportunity Analysis

Model energy codes (ASHRAE Standard 90.1 and IECC) has significantly impacted programs and policies aimed at improving energy efficiency both in United States and across the globe. Standard 90.1, first published in 1975 (originally referred to as Standard 90) provides minimum energy efficiency guidelines for designing, constructing, operating, and maintaining new construction and renovated buildings. It is updated continuously, with new editions published every 3 years. Pacific Northwest National Laboratory (PNNL) conducts simulated energy and cost savings analysis of model energy codes to determine their expected impact and to track progress toward net-zero goals and efficiency targets. Additionally, the simulation outputs are examined to assess how energy is used across primary systems within prominent U.S. commercial building types to understand how energy is used in each building type at the end-use level and to identify areas for improvements in future code cycles. This end-use opportunity analysis of model energy codes provides ASHRAE technical committees and other interested parties a better understanding of how the Standard affects various building systems and end uses, specifically, those in the Standard that most prominently influence energy efficiency. Additionally, findings provide industry stakeholders guidance in identifying building types and end-uses with the most potential for energy efficiency improvements through energy codes and those that may require beyond code measures to meet energy use reduction targets. This paper summarizes features and functionalities of a webtool created by PNNL to explore and visualize the End-Use opportunity analysis.

ASHRAE 90.1, Energy Codes, Tableau↗
DOE OSTI2022

Achieving 50% Energy Savings in Chicago Homes: A Case Study for Advancing Equity and Climate Goals

Since 2019, the National Renewable Energy Laboratory (NREL) and Elevate have collaborated to identify pathways to deep energy retrofits in Chicago's housing stock, document equity implications and co-benefits of this transition, and validate the findings by implementing retrofits in real Chicago homes. This document summarizes our analysis process to model advanced retrofit packages that lead to greater than 50% energy savings in Chicago homes. Based on these findings, we have also developed a roadmap with the City to guide implementation, and are deploying the recommended retrofit packages in real Chicago homes to realize these energy savings. This work was developed in collaboration with two key stakeholders - the City of Chicago and Commonwealth Edison (ComEd) - and funded by the U.S. Department of Energy (DOE). NREL's Residential Buildings team maintains the best-in-class ResStock™ energy model of the U.S. residential building stock. For this work, we calibrated ResStock to Chicago's unique local housing stock to accurately simulate energy use in Chicago homes both for current conditions and with various retrofit scenarios. We simulated a wide range of potential building retrofits covering all aspects of residential energy use and then grouped these into packages based on energy and utility bill savings. ResStock can model diverse building types and housing characteristics, so we're able to observe the range of outcomes that might occur when these upgrades are deployed across the entire housing stock. We can then estimate potential energy savings from an advanced retrofit program on Chicago's housing stock by comparing the modeled energy use before versus after a retrofit. This novel version of ResStock, calibrated to Chicago with data from Elevate, can help City officials, ComEd, and other partners plan for community-scale decarbonization via residential retrofits. Specifically, this work contributes the following project goals: Develop a building retrofit prioritization strategy for Chicago single-family and 2- to 4-unit buildings; Identify neighborhoods and home types that have the highest potential for savings from electrification; and Assess the impact of advanced building retrofits on energy use, utility bills, and CO2 emissions at the city and building level. Although this study is specific to Chicago, its methods and learnings are applicable across the United States. These findings are especially notable for heat pumps and electrification retrofits in cold climates.

building energy modeling↗
DOE OSTI2022

Photovoltaic windows cut energy use and CO 2 emissions by 40% in highly glazed buildings

Buildings account for 30% of global energy use. The architectural trend across building sectors is toward more glass despite higher energy use and carbon emissions than opaque cladding alternatives. Numerous window technologies - low-emissivity coatings, triple glazing, dynamic tinting, and the more recently developed photovoltaic glass - have emerged in the last two decades as approaches to reduce building energy. However, a comprehensive understanding of where and how these window technologies can be installed to enable optimal energy savings under different climate conditions remains limited. Here we test window technologies using thousands of macroscale building-energy simulations for different climate zones and building designs to evaluate the associated net energy use and carbon-emissions reduction potential. Novel window technologies, especially photovoltaic windows with high thermal performance, offer energy savings in all climates, ranging from 10,000-40,000 GJ per year over substandard windows for a typical office building, resulting in up to 2,000 tons of annual CO 2 emissions reduction. Highly glazed, net-zero buildings are achievable via photovoltaic windows when combined with careful geometric considerations.

14 SOLAR ENERGY↗
DOE OSTI2016

WE-FG-207B-10: Dual-Energy CT Monochromatic Image Consistency Across Vendors and Platforms

Purpose: Although dual-energy CT provides improved sensitivity of HU for certain tissue types at lower simulated energy levels, if these values vary by scanner type they may impact clinical patient management decisions. Each manufacturer has selected a specific dual-energy CT approach (or in one case, three different approaches); understanding HU variability among low monochromatic images may be required when more than one dual-energy CT scanner type is available for use. Methods: A large elliptical dualenergy quality control phantom (Gammex Inc.; Middleton, WI) containing several standard tissue type materials was scanned at least three times on each of the following systems: GE HD750, prototype GE Revolution CT with GSI, Siemens Flash, Siemens Edge, Siemens AS 128, and Philips IQon. Images were generated at 50, 70, and 140 keV. Soft tissue and Iodine HU were measured on a single central 5mm-thick image; NIST constants were used to calculate the ideal HU for each material. Scan acquisitions were approximately dose-matched (∼25mGy CTDIvol) and image parameters were held as consistent as possible (thickness, kernel, no noise reduction). Results: Measured soft tissue (29 HU at 120 kVp) varied from 28 HU to 44 HU at 50 keV (excluding one outlier), from 21 HU to 31 HU at 70 keV, and from 19 HU to 32 HU at 140 keV. Measured iodine (5mg/ml, 106 HU at 120 kVp) varied from 246 HU to 280 HU at 50 keV, from 123 HU to 129 HU at 70 keV, and from 22 HU to 32 HU at 140 keV. Conclusion: Measured HU in standard rods across 3 dual-energy CT manufacturers and 6 scanner models varied directly with monochromatic level, with the most variability was observed at 50 keV and least variability at 70keV. Future work will include additional scanner platforms and how measurement variability impacts radiologists. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Energy and IAQ Implications of Alternative Minimum Ventilation Rates in California Retail and School Buildings

For a stand-alone retail building, a primary school, and a secondary school in each of the 16 California climate zones, the EnergyPlus building energy simulation model was used to estimate how minimum mechanical ventilation rates (VRs) affect energy use and indoor air concentrations of an indoor-generated contaminant. The modeling indicates large changes in heating energy use, but only moderate changes in total building energy use, as minimum VRs in the retail building are changed. For example, predicted state-wide heating energy consumption in the retail building decreases by more than 50% and total building energy consumption decreases by approximately 10% as the minimum VR decreases from the Title 24 requirement to no mechanical ventilation. The primary and secondary schools have notably higher internal heat gains than in the retail building models, resulting in significantly reduced demand for heating. The school heating energy use was correspondingly less sensitive to changes in the minimum VR. The modeling indicates that minimum VRs influence HVAC energy and total energy use in schools by only a few percent. For both the retail building and the school buildings, minimum VRs substantially affected the predicted annual-average indoor concentrations of an indoor generated contaminant, with larger effects in schools. The shape of the curves relating contaminant concentrations with VRs illustrate the importance of avoiding particularly low VRs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

SU-E-T-46: A Monte Carlo Investigation of Radiation Interactions with Gold Nanoparticles in Water for 6 MV, 85 KeV and 40 KeV Photon Beams

Purpose: To determine the effect of gold-nanoparticles (AuNPs) on energy deposition in water for different irradiation conditions. Methods: TOPAS version B12 Monte Carlo code was used to simulate energy deposition in water from monoenergetic 40 keV and 85 keV photon beams and a 6 MV Varian Clinac photon beam (IAEA phase space file, 10x10 cm{sup 2}, SSD 100 cm). For the 40 and 85 keV beams, monoenergetic 2x2 mm{sup 2} parallel beams were used to irradiate a 30x30x10 µm {sup 3} water mini-phantom located at 1.5 cm depth in a 30x30x50 cm{sup 3} water phantom. 5000 AuNPs of 50 nm diameter were randomly distributed inside the mini-phantom. Energy deposition was scored in the mini-phantom with the AuNPs’ material set to gold and then water. For the 6 MV beam, we created another phase space (PHSP) file on the surface of a 2 mm diameter sphere located at 1.5 cm depth in the water phantom. The PHSP file consisted of all particles entering the sphere including backscattered particles. Simulations were then performed using the new PHSP as the source with the mini-phantom centered in a 2 mm diameter water sphere in vacuum. The g4em-livermore reference list was used with “EMRangeMin/EMRangeMax = 100 eV/7 MeV” and “SetProductionCutLowerEdge = 990 eV” to create the new PHSP, and “SetProductionCutLowerEdge = 100 eV” for the mini-phantom simulations. All other parameters were set as defaults (“finalRange = 100 µm”). Results: The addition of AuNPs resulted in an increase in the mini-phantom energy deposition of (7.5 ± 8.7)%, (1.6 ± 8.2)%, and (−0.6 ± 1.1)% for 40 keV, 85 keV and 6 MV beams respectively. Conclusion: Enhanced energy deposition was seen at low photon energies, but decreased with increasing energy. No enhancement was observed for the 6 MV beam. Future work is required to decrease the statistical uncertainties in the simulations. This research is partially supported from institutional funds from the Center for Radiation Oncology Research, The University of Texas MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.

Rosenberg, L. S.↗
NASA NTRS1981

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

A computer simulation code was employed to evaluate several generic types of solar power systems (up to 10 MWe). Details of the simulation methodology, and the solar plant concepts are given along with cost and performance results. The Solar Energy Simulation computer code (SESII) was used, which optimizes the size of the collector field and energy storage subsystem for given engine-generator and energy-transport characteristics. Nine plant types were examined which employed combinations of different technology options, such as: distributed or central receivers with one- or two-axis tracking or no tracking; point- or line-focusing concentrator; central or distributed power conversion; Rankin, Brayton, or Stirling thermodynamic cycles; and thermal or electrical storage. Optimal cost curves were plotted as a function of levelized busbar energy cost and annualized plant capacity. Point-focusing distributed receiver systems were found to be most efficient (17-26 percent).

Rosenberg, L. S.↗
DOE OSTI2013

Improving Building Performance at Urban Scale with a Framework for Real-time Data Sharing

This paper describes work in progress toward an urban-scale system aiming to reduce energy use in neighboring buildings by providing three components: a database for accessing past and present weather data from high quality weather stations; a network for communicating energy-saving strategies between building owners; and a set of modeling tools for real-time building energy simulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models

We describe a new framework that allows users to explore and steer ensembles of energy systems simulations by coupling multiple energy models and interactive visualization through a dataflow API. Through the visual interface, users can interactively explore complex parameter spaces populated by hundreds, or thousands, of simulation runs and interactively spawn new simulations to 'fill in' regions of interest in the parameter space. The computational and visualization capabilities reside within a general-purpose dataflow architecture for connecting producers of multidimensional timeseries data, such as energy simulations, with consumers of that data, whether they be visualizations, statistical analyses, or datastores. Fast computation and agile dataflow can enhance the engagement with energy simulations, allowing users to populate the parameter space in real time. However, many energy simulations are far too slow to provide an interactive response. To support interactive feedback, we are creating reduced-form simulations developed through machine learning techniques, which provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost. These reduced-form simulations have response times on the order of seconds, suitable for real-time human-in-the-loop design and analysis. The approximation methods apply to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. Such reduced-form representations do not replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and exploration for large ensembles of simulations. The improved understanding, facilitated by the reduced-form models, dataflow API, and visualization tools, allows researchers to better allocate computational resources to capture informative relationships within the system as well as provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Rethinking Occupancy - Based Ventilation Controls

Traditionally, occupancy-based ventilation controls have only ventilated when occupants are present – usually based on measurements of CO2 and/or humidity. These indictors may be fine for pollutants released directly by occupants, such as bioeffluents, or by their activities, such as cooking and cleaning. However, they do not account for pollutants not associated with occupancy, such as formaldehyde from building materials and furnishings. In this study we examined how occupancy-based ventilation controls could account for these other pollutants using the relative exposure approach for variable ventilation. A real-time control was used for exhaust and balanced fans, three occupancy schedules and two different pollutant emission assumptions using the REGCAP ventilation and residential energy simulation program. The simulations were performed for a prototype high performance home compliant with U.S. Department of Energy Building America Zero Energy Ready program requirements in the 15 climate zones defined by the U.S. DOE. Median ventilation energy savings were between zero and 26% of ventilation-related energy use depending on the occupancy schedule, climate, fan type and emission assumptions. Occupancy-based control savings increased for balanced ventilation fans, reduced emissions during unoccupied periods, and longer unoccupied times. Accounting for pollutant emissions during unoccupied times significantly reduces the energy savings for occupancy-based controls.

Walker, Iain↗
DOE OSTI2015

Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling & Simulation (Phase I Final Report)

Today, the importance of nuclear power in the US is a geopolitical matter as much as it is an economic one. This is due to the notion that increasing the use of nuclear power reduces the US's reliance on imported oil and gas. In order to design future systems and continue operational improvements at existing US plants, advanced modeling and simulation of nuclear power reactors is crucial. A variety of challenges exist to using advanced modeling and simulation in practice, especially for the nuclear energy community and other organizations with fewer computational resources and limited expertise. There is an increasing need of access to highly capable compute, data, and software resources from network systems, which are becoming more administratively restricted from access through installation of traditional client-server applications. The nuclear energy community is not capable of maintaining exponential growth of computing capability and data storage coupled with the necessary end-to-end network bandwidth improvements. Applications that provide higher fidelity with increased physics and decreased assumptions, by their very nature, require more and more computational resources. We believe Web-based, Cloud-enabled, end-to-end simulation software for nuclear energy advanced modeling and simulation to be the solution to these challenges.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2015

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Energy↗