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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
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Light Bender Concept for Power Distribution on a Lunar Base

Power generation and distribution is a challenge for a future lunar base. A promising concept for lunar power distribution is the light bender—a system that utilizes autonomously deployed mirrors to reflect sunlight to shaded regions on the lunar surface. The light bender system consists of two components: tandem reflector mirrors (TRM) which reflect sunlight to a permanently shaded region and the Cassegrain Fresnel distribution optics (CFDO) which collects the reflected light from the TRM and redirects light to local consumer nodes. This paper describes the light bender system concepts and the associated system analysis and technology development performed as part of a 2021 NASA Innovative Advanced Concepts (NIAC) phase I award.

Bradford Robertson↗
NASA NTRSDate not supplied

The Light Bender Concept for Power Distribution on a Lunar Base

Power generation and distribution is a challenge for a future lunar base. A promising concept for lunar power distribution is the light bender—a system that utilizes autonomously deployed mirrors to reflect sunlight to shaded regions on the lunar surface. The light bender system consists of two components: tandem reflector mirrors (TRM) which reflect sunlight to a permanently shaded region and the Cassegrain Fresnel distribution optics (CFDO) which collects the reflected light from the TRM and redirects light to local consumer nodes. This paper describes the light bender system concepts and the associated system analysis and technology development performed as part of a 2021 NASA Innovative Advanced Concepts (NIAC) phase I award.

Bradford Robertson↗
NASA NTRS2024

Exploration Extravehicular Mobility Unit (xEMU) Helmet and Extravehicular Visor Assembly (EVVA) Chamber B Thermal Vacuum Testing Results

NASA’s Exploration Extravehicular Mobility Unit (xEMU) is the government reference next-generation spacesuit design and is engineered to protect astronauts from extreme lunar environmental temperatures. To evaluate the xEMU hardware thermal requirements, the xEMU Testing Team invented, designed, and executed a dual-suit, uncrewed thermal vacuum (TVAC) test at Johnson Space Center’s (JSC) Chamber B. This paper details the test methodology, hardware setup, and results from the xEMU helmet and extravehicular visor assembly (EVVA). Two helmets/EVVAs were tested simultaneously in Chamber B, with different thermal environments and EVVA configurations. For the helmet/EVVA on the Short xEMU (SxEMU) test article, five thermal profiles were tested during five simulated EVAs, with four different visor and shade configurations. For the helmet/EVVA on the second xEMU, eleven unique thermal profiles were tested including both cold and hot environmental cases over the course of five continuous days of testing, with a single visor and shade configuration. The radiative thermal environment was controlled through exposure to liquid-nitrogen shrouds on the chamber walls and through two separate heater cages surrounding each respective test article. The thermal effects of the Exploration Informatics (xINFO) lights and camera on the helmet/EVVA was also tested. Twenty-two temperature sensors were used to collect data in critical locations in the xEMU helmet/EVVA assembly. This paper will document the testing results and compare the test data against the xEMU helmet/EVVA and system-level thermal models for model validation.

xEMU↗
DOE OSTI2018

Thin-Film Module Reverse-Bias Breakdown Sites Identified by Thermal Imaging: Preprint

Thin-film module sections are stressed under reverse bias to simulate partial shading conditions. Such stresses can cause permanent damage in the form of 'wormlike' defects due to thermal runaway. When large reverse biases with limited current are applied to the cells, dark lock-in thermography (DLIT) can detect where spatially-localized breakdown initiates before thermal runaway leads to permanent damage. Predicted breakdown defect sites have been identified in both CIGS and CdTe modules using DLIT. These defects include small pinholes, craters, or voids in the absorber layer of the film that lead to built-in areas of weakness where high current densities may cause thermal damage in a partial-shading event.

14 SOLAR ENERGY↗
DOE OSTI2018

Thin-Film Module Reverse-Bias Breakdown Sites Identified by Thermal Imaging

Thin-film module sections are stressed under reverse bias to simulate partial shading conditions. Such stresses can cause permanent damage in the form of 'wormlike' defects due to thermal runaway. When large reverse biases with limited current are applied to the cells, dark lock-in thermography (DLIT) can detect where spatially-localized breakdown initiates before thermal runaway leads to permanent damage. Predicted breakdown defect sites have been identified in both CIGS and CdTe modules using DLIT. These defects include small pinholes, craters, or voids in the absorber layer of the film that lead to built-in areas of weakness where high current densities may cause thermal damage in a partial-shading event.

14 SOLAR ENERGY↗
DOE OSTI2018

New Rating Opening Windows to a World of Comfort, Opportunity, and Cost-Effective Savings

Window attachments offer a huge, cost-effective energy-saving opportunity that remains largely untapped. The newly launched window attachment energy rating and certification program, through the Attachments Energy Rating Council (AERC), is altering the way people think about residential and commercial window attachments by providing reliable, easy-to-understand energy performance information to consumers. Window attachments, such as blinds, shades, shutters, awnings, and low-emissivity (low-e) storm windows, represent an enormous existing market. With 64% of U.S. homes having single- or double-pane clear (non-low-e) less-efficient windows, the savings opportunity is significant. Studies of model homes show energy savings of 10% or more after installing more efficient storm window and cellular shades technologies (AERC 2016).In a study conducted by Efficiency Vermont, 68% of respondents had concerns with their existing windows and could benefit from an upgrade (Efficiency Vermont 2016).Through AERC, window attachment products are rated based on their Energy Performance (EP). The EP metric is an easy-to-understand comparative metric created for consumers. This rating not only allows consumers to make more informed decisions when buying attachments products, but also creates a new energy savings measure for utilities and efficiency programs to incentivize energy efficient window attachment products. This paper will outline the savings potential of window attachments, introduce the AERC rating program, detail the methodology behind the Energy Performance ratings, and explain the AERCalc tool that generates the ratings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Window Attachments: Possibilities for Utility Collaboration

Window attachments represent a new and exciting energy-efficient envelope measure for utilities. Collectively, windows in residential and commercial buildings are estimated to generate 32% of all HVAC heating and cooling loads. Very few programs offer incentives for installation of energy-efficient windows because the combined product and installation costs generally exceed the associated energy savings. However, preliminary data indicates that energy-efficient window attachments, including low-emissivity storm windows, cellular shades, and roller shades, can deliver cost-effective energy savings. DOE has committed more than $1.6 million to fund a new window attachment energy performance rating and certification organization – the Attachments Energy Rating Council – to enable consumers to make comparisons among window attachments. This paper is meant to help programs get up to speed on this new energy savings measure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

New Rating Opening Windows to a World of Comfort, Opportunity, and Cost-Effective Savings

Window attachments offer a huge, cost-effective energy-saving opportunity that remains largely untapped. The newly launched window attachment energy rating and certification program, through the Attachments Energy Rating Council (AERC), is altering the way people think about residential and commercial window attachments by providing reliable, easy-to-understand energy performance information to consumers. Window attachments, such as blinds, shades, shutters, awnings, and low-emissivity (low-e) storm windows, represent an enormous existing market. With 64% of U.S. homes having single- or double-pane clear (non-low-e) less-efficient windows, the savings opportunity is significant. Studies of model homes show energy savings of 10% or more after installing more efficient storm window and cellular shades technologies (AERC 2016). In a study conducted by Efficiency Vermont, 68% of respondents had concerns with their existing windows and could benefit from an upgrade (Efficiency Vermont 2016). Through AERC, window attachment products are rated based on their Energy Performance (EP). The EP metric is an easy-to-understand comparative metric created for consumers. This rating not only allows consumers to make more informed decisions when buying attachments products, but also creates a new energy savings measure for utilities and efficiency programs to incentivize energy efficient window attachment products. Here, this paper will outline the savings potential of window attachments, introduce the AERC rating program, detail the methodology behind the Energy Performance ratings, and explain the AERCalc tool that generates the ratings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗
DOE OSTI2019

Quantifying Rates of Erosion Using Historical Aerial Photos - 19478

Erosion can play an important role in the fate and transport of waste at sites where disposal of long-lived waste is anticipated. The statistical characterization of key processes related to erosion is essential to the understanding of site stability through time. In this work multi-temporal historical aerial images are analyzed in conjunction with orthophotography and Lidar data to develop probability distributions for variables representing important erosion processes. Scans of photographic negatives were obtained for multiple photographs and several negatives were scanned with a calibrated photogrammetric scanner by Geomni (formerly Blue Skies Consulting) in Belen, New Mexico. Other negatives were provided by USDA or scanned on a high-resolution, large format media scanner in the United States National Archives Cartographic Research Room, College Park, Maryland (1939). An additional set of aerial photographs was obtained from the USGS EROS Data Center web site. For other years, photographic prints were available for aerial photography. Several prints were scanned with a large-format media scanner at 1200 dpi. Ground control points for selected digital images used in the stereoscopic analyses were identified in ArcMap. Ground control points were collected by matching features which could be identified in the aerial photography as well as the orthophotography or shaded relief imagery from the Lidar dataset. Such features included fence line intersections, road intersections, railroad bridges, and structures, depending on the age of the photography. Many old fence lines and abandoned roads remained visible in the shaded relief imagery while they were completely obscured by tree canopy in modern photography. Ground control elevations were sampled from the Lidar-based DEM or directly from point clouds. The image coordinates and matching three-dimensional projected coordinates of the ground control points were exported to IDL where parameters for a three-dimensional direct linear transformation (DLT) were obtained. Built-in singular value decomposition routines were used to solve an overdetermined set of equations for the eleven parameters of the DLT for a particular historical photograph. A solution to the DLT parameters was obtained for each historical aerial photograph in which features of interest were identified using the stereoscope. Ultimately, this process resulted in the identification of locations for features like gully heads using both the Lidar dataset and projection of the estimated location from the historical aerial photo under consideration back to the Lidar dataset. The distance between the estimate of the location from the historical image and that of the Lidar dataset was the estimated distance the feature has moved. This distance was then divided by the number of years between the Lidar dataset and the year of the historical aerial image of interest to get a rate of movement through time. This was done for several dozen points on each historical aerial image. There was inevitable uncertainty associated with the estimation of points from the historical aerial imagery. This includes estimation of changes in locations of features like gully heads through time. In this work a method to estimate the uncertainty associated with measurements of locations of features using the stereoscopic analysis is developed and applied. For features with locations in space that do not change (e.g., road intersections, etc.) the difference in measurements of locations from the Lidar dataset and that of the estimate from the historical aerial image provides an observation of the measurement error. These points used to estimate the measurement error are referred to as control points. For each of the historical aerial images, a different measurement error distribution is estimated using control points. These measurement errors are combined with the estimated distances from the stereoscopic analyses to produce distributions of gully retreat rates and hillslope erosion rates used along with output from Erosion Working Group (EWG) Landscape Evolution Models (LEMs) to provide statistical probability distributions for input into the PPA Model. Specifically, gully head retreat rate and gully widening rate were characterized using statistical probability distributions. The central limit theorem was then applied to develop rates that represent long-term averages that are used to inform a PPA Model built in GoldSim. The importance of these rates with respect to characterization of future risk can then assessed using sensitivity analyses. This provides an approach to determine if subsequent reduction of the uncertainty associated with the probability distributions of erosion rates will correspond to meaningful reduction in the estimation of future risk from the site. Ultimately this is a general method that utilizes historical aerial imagery to estimate rates of erosion with uncertainty. This information can be used to inform PPA models to project future risks from a given site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Lessons Learned from Three Agrivoltaic Installations in New Jersey

Agrivoltaics is a new technology that has the potential to positively impact commercial farming by combining agricultural practices with the generation of solar energy. While some yield reduction is to be expected, resulting from less sunlight reaching the plant canopy and ground occupied by support structures, the generated electricity provides a low-risk supplemental income to farmers. In order to combine farming with electricity generation, agrivoltaic systems use a lower ground coverage ratio compared to normal solar farms and the PV panels are often mounted higher above the ground in order to facilitate the movement of agricultural equipment and to reduce the contrast between shaded and non-shaded areas. With funding provided from the state of New Jersey and the New Jersey Agricultural Experiment Station (NJAES), we designed and installed three unique agrivoltaic research systems at Rutgers/NJAES farms. These projects were recently completed and are generating electricity that is exported to the grid. This paper discusses the lessons we have learned along the way, including all the steps necessary to see an agrivoltaic project through to completion.

14 SOLAR ENERGY↗
DOE OSTI2024

Lessons Learned from Three Agrivoltaic Installations in New Jersey

Agrivoltaics is a new technology that has the potential to positively impact commercial farming by combining agricultural practices with the generation of solar energy. While some yield reduction is to be expected, resulting from less sunlight reaching the plant canopy and ground occupied by support structures, the generated electricity provides a low-risk supplemental income to farmers. In order to combine farming with electricity generation, agrivoltaic systems use a lower ground coverage ratio compared to normal solar farms and the PV panels are often mounted higher above the ground in order to facilitate the movement of agricultural equipment and to reduce the contrast between shaded and non-shaded areas. With funding provided from the state of New Jersey and the New Jersey Agricultural Experiment Station (NJAES), we designed and installed three unique agrivoltaic research systems at Rutgers/NJAES farms. These projects were recently completed and are generating electricity that is exported to the grid. This paper discusses the lessons we have learned along the way, including all the steps necessary to see an agrivoltaic project through to completion.

14 SOLAR ENERGY↗
DOE OSTI2021

Development of a kinetic model to describe six types of symbiotic interactions in a formate utilizing microalgae-bacteria cultivation system

This study investigated an algae/formate-utilizing-bacteria system that has been developed for carbon capture. This photomixotrophic consortium consumed formate to support bacterial growth so that the resulting respiration CO 2 could be simultaneously used by algae to avoid CO 2 gas-lipid mass transfer limitation. To understand biomass growth and population interactions in this unique system, a kinetic model has been developed to describe algae and bacteria multiplication, formate and nitrogen utilizations, CO 2 mass transfer, O 2 generation and consumption, lighting condition and shading effect. The simulation indicated that this ecosystem could form six types of interactions (mutualism, commensalism, parasitism, neutralism, amensalism, and competition) depending on the light intensity and nutrient availability. Furthermore, the simulation of both batch culture and chemostat, along with parameter sensitivity tests and experimental observations, offered insights into optimal applications of algae-bacteria consortium based photobiorefinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Simulating the Daylight Performance of Complex Fenestration Systems Using Bidirectional Scattering Distribution Functions within Radiance

We describe two methods which rely on bidirectional scattering distribution functions (BSDFs) to model the daylighting performance of complex fenestration systems (CFS), enabling greater flexibility and accuracy in evaluating arbitrary assemblies of glazing, shading, and other optically-complex coplanar window systems. Two tools within Radiance enable a) efficient annual performance evaluations of CFS, and b) accurate renderings of CFS despite the loss of spatial resolution associated with low-resolution BSDF datasets for inhomogeneous systems. Validation, accuracy, and limitations of the methods are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well as a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.

climate change↗
DOE OSTI2023

Reverse-Bias Resilience of Monolithic Perovskite/Silicon Tandem Solar Cells

Metal halide perovskites have rapidly enabled a range of high-performance photovoltaic technologies. However, catastrophic failure under reverse voltage bias poses a roadblock for their commercialization. In this work, we conduct a series of stress tests to compare the reverse-bias stability of perovskite single-junction, silicon single-junction, and monolithic perovskite/silicon tandem solar cells. We demonstrate that the tested perovskite/silicon tandem devices are considerably more resilient against reverse bias compared with perovskite single-junction devices. The origin of such improved stability stems from the low reverse-bias diode current of the silicon subcell. This translates to dropping most of the voltage over the silicon subcell, where such a favorable voltage distribution protects the perovskite subcell from reverse-bias-induced degradation. These results highlight that, compared with other perovskite technologies, monolithic perovskite/silicon tandems are at a higher technology readiness level in terms of tackling the reverse bias and partial shading challenges, which is a considerable advantage toward commercialization.

halide perovskite↗
DOE OSTI2016

Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests

Understanding the temporal patterns of leaf traits is critical in determining the seasonality and magnitude of terrestrial carbon, water, and energy fluxes. However, we lack robust and efficient ways to monitor the temporal dynamics of leaf traits. Here we assessed the potential of leaf spectroscopy to predict and monitor leaf traits across their entire life cycle at different forest sites and light environments (sunlit vs. shaded) using a weekly sampled dataset across the entire growing season at two temperate deciduous forests. In addition, the dataset includes field measured leaf-level directional-hemispherical reflectance/transmittance together with seven important leaf traits [total chlorophyll (chlorophyll a and b), carotenoids, mass-based nitrogen concentration (N mass ), mass-based carbon concentration (C mass ), and leaf mass per area (LMA)]. All leaf traits varied significantly throughout the growing season, and displayed trait-specific temporal patterns. We used a Partial Least Square Regression (PLSR) modeling approach to estimate leaf traits from spectra, and found that PLSR was able to capture the variability across time, sites, and light environments of all leaf traits investigated (R 2 = 0.6–0.8 for temporal variability; R 2 = 0.3–0.7 for cross-site variability; R 2 = 0.4–0.8 for variability from light environments). We also tested alternative field sampling designs and found that for most leaf traits, biweekly leaf sampling throughout the growing season enabled accurate characterization of the seasonal patterns. Compared with the estimation of foliar pigments, the performance of N mass , C mass and LMA PLSR models improved more significantly with sampling frequency. Our results demonstrate that leaf spectra-trait relationships vary with time, and thus tracking the seasonality of leaf traits requires statistical models calibrated with data sampled throughout the growing season. In conclusion, our results have broad implications for future research that use vegetation spectra to infer leaf traits at different growing stages.

54 ENVIRONMENTAL SCIENCES↗