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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 397 records · Page 22

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Chandler, William S.↗

Design and Construction Documents Associated with N232, Sustainability Base

This request comprehensively covers documents associated with the design and construction of Sustainability Base, N232. The intent of this project specifically envisioned broad dissemination of these materials to others undertaking the design and construction of high-performing energy- and resource-efficient buildings in comparable climate zones.

architectural↗

Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

mixture model↗

Developing a Customized Composite Drought Index for Pakistan

Pakistan experiences frequent and intense agricultural drought, varying spatially and temporally. Prolonged dry conditions often result in failed crop production. Using multiple variables, different components of drought can be captured across a multitude of climatic zones and throughout different seasons. Developing a composite drought index (CDI), specific for each district, will provide a more complete view of agricultural drought and enhance early warning systems.

Schwartz, Caily↗

TPSAS-NF1676L-27534-DND

This presentation describes the preparation, validation and provision of MERRA-2 data products to the building industry for use in energy efficient designs, building codes and monitoring energy efficiency. It highlights efforts to use MERRA-2 surface meteorological data products for the derivation of quantities relevant to the energy and building industry such as heating and cooling degree days and building climate zones on a global basis for the past 30 years. A difference of the zones from the first 15 years and last 30 years shows that warming zones are creeping northward. The talk also presents work provide similar parameters for building energy performance assessment requiring data products closer to real time.

Paul W Stackhouse, Jr↗

Experiment Design and Visualization Techniques for an X-59 Low-boom Variability Study

This presentation outlines the design of experiments approach and data visualization techniques for a simulation study of sonic booms from NASA’s X-59 supersonic aircraft. The X-59 will soon be flown over communities across the contiguous USA as it produces a low-loudness sonic boom, or low-boom. Survey data on human perception of low-booms will be collected to support development of potential future commercial supersonic aircraft noise regulatory standards. The macroscopic atmosphere plays a critical role in the loudness of sonic booms. The extensive sonic boom simulation study presented herein was completed to assess climatological, geographical, and seasonal effects on the variability of the X-59’s low-boom loudness and noise exposure region size in order to inform X-59 community test planning. The loudness and extent of the noise exposure region make up the “sonic boom carpet.” Two spatial and temporal resolutions of atmospheric input data to the simulation were investigated. A Fast Flexible Space-Filling Design was used to select the locations across the USA for the two spatial resolutions. Analysis of simulated X-59 low-boom loudness data within a regional subset of the northeast USA was completed using a bootstrap forest to determine the final spatial and temporal resolution of the countrywide simulation study. Atmospheric profiles from NOAA’s Climate Forecast System Version 2 database were used to generate over one million simulated X-59 carpets at the final selected 138 locations across the USA. Effects of aircraft heading, season, geography, and climate zone on low-boom levels and noise exposure region size were analyzed. Models were developed to estimate loudness metrics throughout the USA for X-59 supersonic cruise overflight, and results were visualized on maps to show geographical and seasonal trends. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗

Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites

Remote sensing-based evapotranspiration (ET) products have been evaluated primarily using data from northern middle latitudes; therefore, little is known about their performance at low latitudes. To address this bias, an evaluation dataset was compiled using eddy covariance data from 40 sites between latitudes 30° S and 30° N. The flux data were obtained from the emerging network in Mexico (MexFlux) and from openly available databases of FLUXNET, AsiaFlux, and OzFlux. This unique reference dataset was then used to evaluate remote sensing-based ET products in environments that have been underrepresented in earlier studies. The evaluated products were: MODIS ET (MOD16, both the discontinued collection 5 (C5) and the latest collection (C6)), Global Land Evaporation Amsterdam Model (GLEAM) ET, and Atmosphere-Land Exchange Inverse (ALEXI) ET. Products were compared with unadjusted fluxes (ETorig) and with fluxes corrected for the lack of energy balance closure (ETebc). Three common statistical metrics were used: coefficient of determination (R2), root mean square error (RMSE), and percent bias (PBIAS). The effect of a vegetation mismatch between pixel and site on product evaluation results was investigated by examining the relationship between the statistical metrics and product-specific vegetation match indexes. Evaluation results of this study and those published in the literature were used to examine the performance of the products across latitudes. Differences between the MOD16 collection 5 and 6 datasets were generally smaller than differences with the other products. Performance and ranking of the evaluated products depended on whether ETorig or ETebc was used. When using ETorig, GLEAM generally had the highest R2, smallest PBIAS, and best RMSE values across the studied land cover types and climate zones. Neither MOD16 nor ALEXI performed consistently better than the other. When using ETebc, none of the products stood out in terms of both low bias and strong correlations. The use of ETebc instead of ETorig affected the biases more than the correlations. The product evaluation results showed no significant relationship with the degree of match between the vegetation at the pixel and site scale. The latitudinal comparison showed tendencies of lower R2 (all products) but better PBIAS and normalized RMSE values (MOD16 and GLEAM) for forests at low latitudes than for forests at northern middle latitudes. For non-forest vegetation, the products showed no clear latitudinal differences in performance.

Diego Salazar-Martínez↗

Simulation and Regression Modeling of Nasa'S X-59 Low-Boom Carpets Across America

NASA’s X-59 aircraft is predicted to produce a significantly quieter cruise sonic boom than traditional N-wave-producing aircraft. A propagation simulation study was undertaken to quantify loudness levels, exposure size, and variability of the X-59’s low-boom carpet using realistic atmospheric profiles across the contiguous United States of America (CONUS). Near-field pressure data of the X-59 in supersonic cruise from NASA’s fully unstructured Navier–Stokes three-dimensional (known as FUN3D) computational fluid dynamics code were propagated using NASA’s PCBoom code, which solves an enhanced Burgers equation along acoustic rays. Atmospheric profiles from the National Oceanic and Atmospheric Administration’s Climate Forecast System Version 2 database were used for propagation at 138 locations across the CONUS. Carpets at each location were generated for aircraft headings in the four cardinal directions. Over one million X-59 carpets were generated in total. The effects of the heading, season, geography, and climate zone on boom levels and exposure size are presented. Multiple linear regression models were developed to estimate carpet width and loudness metrics across the CONUS. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗

Simulation and Regression Modeling of X-59 Low-Boom Carpets Across America

The NASA X-59 aircraft is predicted to produce a significantly quieter cruise sonic boom than traditional N-wave-producing aircraft. A propagation simulation study was undertaken to quantify loudness levels, exposure size, and variability of the X-59 low-boom carpet using realistic atmospheric profiles across the contiguous United States of America (CONUS). Near-field pressure data of the X-59 in supersonic cruise from NASA’s fully unstructured Navier–Stokes three-dimensional (known as FUN3D) computational fluid dynamics code were propagated using NASA’s PCBoom code, which solves an enhanced Burgers equation along acoustic rays. Atmospheric profiles from the National Oceanic and Atmospheric Administration’s Climate Forecast System Version 2 database were used for propagation at 138 locations across the CONUS. Carpets at each location were generated for aircraft headings in the four cardinal directions. Over one million X-59 carpets were generated in total. The effects of the heading, season, geography, and climate zone on boom levels and exposure size are presented. Multiple linear regression models were developed to estimate carpet width and loudness metrics across the CONUS. These results inform regulators and mission planners on expected variations in boom levels and carpet extent from atmospheric variations. Understanding potential carpet variability is important when planning community noise surveys using the X-59.

X-59↗

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗

Influence of Atmospheric Variability on Predicted Sonic Boom Metrics

As part of the Quesst mission, NASA will fly the X-59 aircraft over selected communities to survey community responses to low sonic booms. Previously, we developed a Kalman filter method to estimate the loudness metrics experienced by each survey participant during each flight. The Kalman filter fuses acoustic measurements with predictions from PCBoom, a sonic boom propagation model. PCBoom requires vertical profiles of the temperature, humidity, and wind to propagate sonic booms through the atmosphere and predict the loudness metrics at the ground. Prior to each X-59 flight, NASA will launch weather balloons to measure the vertical atmospheric profile. However, the atmosphere changes continually with geographic location and time. The purpose of this work is to determine where and when to launch these weather balloons to minimize the uncertainty in the predicted loudness metrics caused by atmospheric variability. We analyzed the effect of atmospheric variability on the predicted Perceived Level in three communities in different climate zones in the United States. To achieve acceptable uncertainty in the Perceived Level, weather balloons should be launched from at least two different sites within the survey area within one hour of each X-59 flight.

sonic boom↗

Flexible, Multipurpose Laboratory Advances Building and Thermal Energy Systems: Expanding Evaluation and Development of Grid-Interactive Buildings

Robust hardware and controls are necessary to ensure results match their intent before they can be used broadly. However, this often requires multiple field experiments in a variety of climate zones. In the field, it is more difficult to obtain information on other important factors, such as thermal, grid, and occupant interaction. Gaps also exist in understanding the performance degradation and life cycle of thermal energy systems as they relate to buildings. There is a lack of robust, high-quality performance data for projects at scale; this data can be expensive to produce and often remain proprietary.

30 DIRECT ENERGY CONVERSION↗

Moving Zero Energy Office Buildings to the Mainstream: Establishing Design Guidelines and Energy Targets: Preprint

Office buildings represent a significant portion of the commercial sector and are ideal candidates to lead the market towards achieving zero energy or zero energy ready buildings. The variety of sizes and uses for office buildings make them challenging to determine set design guidance that can be deployed across the market. A project committee for ASHRAE’s Zero Energy - Advanced Energy Design Guide (ZE-AEDG) for small and medium office buildings , comprised of members from five major national associations with market-pull in commercial buildings, created design guidance for achieving zero energy office buildings for new construction and major retrofit. This design guidance focuses on the process, providing a pathway for both office owners and design teams to achieve zero energy status. Energy use intensity targets range from 16 kBtu/ft²·yr to 36 kBtu/ft²·yr for the different climate zones were established such that office buildings can be “zero-ready,” that is, having low energy consumption that can easily be offset with renewables, preferably on-site. The design guidance was rooted in extensive energy modeling, as well as case studies of actual office buildings that have achieved high levels of energy performance and met zero energy or zero energy ready status. A unique aspect of the zero-energy guide is that it is not compared against a baseline but focuses on achieving an absolute target. The paper presents process of creating the targets, the selection of strategies to achieve the targets, and sample case studies that show how the cost-sensitive solutions are achievable for the design community. It also presents outreach strategies to deploy market achievable zero energy measures.

buildings↗

Evaluation of the PV Resource Dataset in Central and North America: Preprint

A recent effort from the National Renewable Energy Laboratory (NREL) has led to a new radiative transfer model, Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), to efficiently compute plane-of-array (POA) irradiance. This model has been implemented by the National Solar Radiation Data Base (NSRDB) to provide photovoltaic (PV) resource over Central and North America in both narrow- and broad wavelength bands. This study conducts a comprehensive evaluation of the PV resource dataset using surface-based observations in various climate zones. The results demonstrate the PV resource has an excellent agreement with the cloudy-sky observations from thermopiles and reference cells.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Where and When Does Solar Plus Storage Make Sense for Commercial Buildings?

As the capital cost of battery energy storage systems (BESS) declines, opportunities for commercial buildings to achieve net savings through peak demand management and energy arbitrage are emerging. National Renewable Energy Laboratory researchers modeled energy storage project economics - with and without accompanying solar photovoltaic systems - using local utility rates, ASHRAE climate zones, and solar intensity data to identify regions where these systems deliver life cycle savings now and in future cost scenarios.

battery energy storage systems↗

The Cost of Comfort in Your Home: Peak-Time Energy and Cost Savings from Setpoint Adjustment of Space Heating and Cooling

This poster presents the tradeoff between energy costs and thermal comfort in homes. Residential heating and cooling systems use a thermostat control to maintain a comfortable temperature range, but tighter temperature control leads to higher annual energy costs. We estimate the impact of temperature setpoint adjustment on annual energy costs using a residential building model developed at NREL. We show that increasing the allowable temperature range reduces energy costs in all five of the climate zones in the U.S. Annual costs reduced by about $100, with larger savings in areas with more heating and/or cooling loads.

30 DIRECT ENERGY CONVERSION↗

Peak Power Reduction for HVAC Operations in Multi-unit Commercial Buildings

The load profiles of most commercial consumers are characterized by brief periods of very high power consumption followed by intervals of relatively lower demand. In order to flatten commercial load profiles, several power utilities in addition to billing energy consumption, levy a demand charge (DC) on the monthly peak demand. In this work, we consider the problem of joint optimization of energy costs (EC) and DC incurred by a multi-unit building which follows a demand response (DR) program. Despite the non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using linear programming. We evaluate the performance of the proposed power control scheme for various climate zones in the US. We show that depending on the ambient conditions and the prescribed tariff structure, our strategy can result in savings of up to nearly 19% compared to the baseline.

Raza Naqvi, Syed A.↗

Commercial Energy Code Compliance – Just the Facts, Ma’am

What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. This paper builds on the methodology presented at the 2016 Summer Study and provides a first glimpse of the results as seen in the field. The field study team has implemented the pilot methodology, compiling a data set of over 200 office and retail buildings in climate zones 2A and 5A. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This paper will review the findings of that analysis, discuss critical aspects of the methodology, such as sampling and recruitment strategies, and identify areas where the greatest return—bang for the buck—exists in improving compliance with codes in commercial buildings. In addition, the team will make specific recommendations for jurisdictions looking to use the methodology to maximize energy code savings achieved in the field.

Cheslak, Kimberly↗