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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Polyimides formulated from a partially fluorinated diamine for aerospace tribological applications

Preliminary tribological studies on polyimides formulated from the diamine 2,2-bis 4-(4-aminophenoxy)phenyl hexafluorapane (4-BDAF) indicate that polyimides formulated from this diamine have excellent potential for high temperature tribological applications. The dianhydrides used to make the polyimides were pyromellitic (PMDA) and benzophenonetetracarboxylic acid (BTDA). Friction and wear studies at 25 and 200 C indicate that polyimides formulated using 50 mole percent of the PMDA dianhydride and 50 mole percent of the BTDA dianhydride perform better than polyimides formulated solely with the BTDA dianhydride. Graphite fiber reinforced polyimide composites were formulated with the polyimide made from the BTDA dianhydride, both graphitic and non-graphitic fibers were evaluated. Graphitic fibers produced better tribological results, since thin, flowing, "layer-like' transfer films were produced which did not build-up with long sliding durations. Non-graphitic fibers did not produce this type of transfer.

Fusaro, R. L.↗
DOE OSTI2023

Deployment Readiness Framework for Marine Energy

As electricity prices continue to rise and extreme weather events related to climate change become more frequent, many island and remote coastal communities are prioritizing their energy future. Isolated locations and coastal environments pose challenges for energy costs and grid resilience, but the ocean can be a key solution. Marine energy could provide these communities with clean, affordable, and reliable power. The U.S. Department of Energy's (DOE) National Renewable Energy Laboratory and Pacific Northwest National Laboratory are developing the Deployment Readiness Framework (DRF) to support remote, coastal, and island community-driven energy transitions. This framework can be used to better understand the readiness of communities for marine energy technology demonstration projects and their operation. The DRF builds on the Energy Transitions Initiative Partnership Project (ETIPP) supported in part by DOE's Water Power Technologies Office.

community readiness↗
DOE OSTI2023

Microstructure development in a cold worked SRF Nb sheet undergoing 700°C-900°C/3h heat treatments.

Bulk Nb for TESLA shaped SRF cavities is a mature technology, with high gradient (>35 MV/m) and high Q cavities (>1010, ~2K) routinely fabricated. Significant advances are in order to push Q?s to 1011 (~2K), and involve modifications to the sub-surface Nb layers by impurity doping (N, O). In order to achieve the lowest surface resistance any trapped flux needs to be expelled for cavities to reach high Q?s. There is clear evidence that cavities fabricated from polycrystalline sheets meeting current specifications require higher temperatures beyond 800oC leads to better flux expulsion, and hence improves Q. Recently, cavities fabricated with a non-traditional Nb sheet with initial cold work due to cold rolling expelled flux better after 800°C/3h heat treatment than cavities fabricated using fine-grain polycrystalline Nb sheets. Here, we analyze the microstructure development in Nb from the vendor supplied cold work non-annealed sheet that was fabricated into an SRF cavity as a function of heat treatment building upon the methodology development to analyze microstructure being developed by the FSU-MSU-UT-Austin- JLAB collaboration. The results indicate correlation between full recrystallization and better flux expulsion.

Balachandran, S.↗
DOE OSTI2025

Construction Methodology Transformation for the Benefit of Workforce Development

Construction is a key economic engine driving both national and global economies. While manual, onsite construction methods dominate the U.S. construction industry, a major shift towards offsite methods has been underway due to its efficiency, speed, and potential cost savings. The workforce necessary for offsite construction growth does not exist in its current form because of the focus on onsite methodologies and the lack of exposure to offsite building methods at all levels of a student’s learning journey. The growth of the U.S. construction industry and competitiveness in an increasingly global construction market over the coming decades can only be supported by a dramatic increase in the use of offsite methods, which requires ramping up workforce training for certain skillsets. The goal of Construction Methodology Transformation for the Benefit of Workforce Development was to understand the opportunities and barriers in both education and industry and to identify best practices for offering curriculum and training to educators, industry, and students that would support skills needed for careers in offsite construction. Our team proposed combining three offsite construction workforce development needs: content development, exposure and training, and job placement - under a single Platform model that would increase experience and career opportunities for students and help match them with potential industry members. Through our proposed solution we expected to see: developed offsite curriculum being utilized by educators and students; an increase in the identification of construction technology and offsite construction methods; an average increase in knowledge gain of at least 25% after participation in pilots; better equipped candidates who are prepared for jobs in offsite construction; and a beta workforce development platform that helps build more pathways for students looking for careers in offsite construction. The two pilots included almost 250 students and resulted in an average knowledge gain of 37 percent. Our research has identified areas of opportunity, for both education and industry to make collaborative training programs more efficient and successful. The chosen techniques for this program are extremely effective when both the school and factory have solid processes and cultures in place to accept students into training programs. This project serves as an important stepping stone to industrywide collaboration to move workforce development for offsite construction forward across the country. With continued collaboration programs like this can provide much needed early exposure and training in offsite construction and we can begin to fill important positions for the future of construction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Energy Impact of Radiative Cooling Paints in Warehouses Under Various United States Climates

Although radiative cooling research is widely found in the literature, no comprehensive study has yet been conducted on the impact of novel radiant cooling (>0.91 reflectance) on the energy efficiency of warehouses. Here, in this work, we develop three building models based on a Department of Energy prototype warehouse model using trnsys, representing a typical warehouse with a black roof, a typical warehouse with a white roof, and a warehouse with novel radiative cooling (RC) paint on its roof. These models are run for 15 different cities, each representative of a different ASHRAE climate zone, to better understand the impact of RC in many different climates. It was found that an RC-coated roof in a warehouse could reduce the building's annual heating, ventilation, and air conditioning (HVAC) loads by up to 14.11 kWh/m 2 of the roof area compared to a black roof, resulting in a maximum reduction in energy costs of 0.55 $\$$/m 2 or $\$$2646/year for a large 4835 m 2 warehouse. Similarly, replacing the typical white roof coating with an RC coating could reduce the warehouse's energy consumption by up to 8.17 kWh/ m 2 of roof area, thus reducing energy costs by as much as 0.29 $\$$/m 2 or $\$$1386/year for a 4835 m 2 warehouse. In addition, applying RC paint to an unconditioned warehouse could reduce the building's ASHRAE Standard 55 indoor temperature exceedance by up to 1330 h/year compared to a black roof and up to 532 h/year compared to a white roof.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Soft Matter Thermal and Mechnical Devices

The participant company, Treau, makes homes and buildings more comfortable with quiet, energy efficient, and easy to install heating and cooling systems. They entered the Cyclotron Road program with an idea for a heat exchanger and compressor and a general idea that the building heating and cooling sector was the best first target market. While at Cyclotron Road, they used the Cyclotron Road program staff and Berkeley Lab expertise to better understand the needs of the heating and cooling equipment market. This was critical to understand who the end customer was, and what features were needed in this market. They were then able to conduct product development with this target market/customer in mind. The Cyclotron Road program was also critical in building a manufacturing and scale-up plan that allowed the participant to build a credible growth and fundraising strategy. By the end of the program, the participant had a working prototype testing at Berkeley Lab’s HVAC testing facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Comparing the economic performance of ice storage and batteries for buildings with on-site PV through model predictive control and optimal sizing

Integrating renewable energy and energy storage systems provides a way of operating the electrical grid system more energy efficiently and stably. Thermal storage and batteries are the most common devices for integration. However, it is not clear which integrated storage system performs better in terms of overall economics. Ice storage has low initial and maintenance costs, but there is an efficiency penalty for charging of storage and it can only shift electrical loads associated with building cooling requirements. A battery's round-trip efficiency, on the contrary, is quite consistent and batteries can be used to shift both HVAC and non-HVAC loads. However, batteries have greater initial costs and a shorter life. Finally, this research presents a tool, using model predictive control and optimal sizing, and provides a case study for comparing life-cycle economics of battery and ice storage systems for commercial buildings that have chillers for cooling and an on-site photovoltaic system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Fusion Energy Sciences Network Requirements Review. Final Report, April - October 2021

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. Throughout 2021, ESnet and the Office of Fusion Energy Sciences (FES) of the DOE SC organized an ESnet requirements review of FES-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about their relationship to the FES program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Super-Large-Scale Hierarchically Porous Films Based on Self-Assembled Eye-Like Air Pores for High-Performance Daytime Radiative Cooling

Metal-free polymer daytime radiative cooling coatings with hierarchical eye-like air pores are proposed and fabricated with a super-large-scale film-stretching method. The hierarchically porous film (HPF) can be further coated with polymethyl methacrylate (PMMA) micro-hemispheres, forming coated HPF (cHPF), which do not dramatically change the optical or thermal properties. The cHPF is slightly better with a lower solar absorptivity (2.4%) and a higher thermal emissivity over the atmospheric transparency window (90.1%). The low solar absorptivity is due to the strong scattering of the hierarchical eye-like air pores, while the molecular vibrations and the focusing effect of the PMMA micro-hemispheres contribute to the high emissivity. Further, an average mid-day temperature reduction of 7.92 °C is achieved relative to the air temperature, and the average cooling power reaches 116.0 W m -2 , which are much better than the cooling performances of the commercial cooling cushion. During the day, the cHPF-covered simulated building is up to 6.47 and 4.84 °C cooler than the ambient and the white painted counterpart, respectively. The film is durable and resistant to chemical etching, and very promising to use globally, especially in warm and tropical regions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Open-Source Architecture for Multi-Party Update Verification for Data Acquisition Devices

Power grids are integral parts of modern daily life and are increasingly under cyberattack. Common software update processes for grid control devices rely on only one organization to provide verification. This paper roposes a multi-signature software update process to help better secure data acquisition devices from malicious actions by using standard cryptosystems such as TLS. A prototype system build on Linux and off-the-shelf hardware has shown successful update and attack prevention with our customized multi-party update software.

Newberg, Benjamin↗
DOE OSTI2020

How Do Visual Explanations Foster End Users' Appropriate Trust in Machine Learning?

We investigated the effects of different visual explanations on users' trust in machine learning classification. We proposed three forms of visual explanations of a classification based on identifying relevant training instances. We conducted a user study to evaluate these visual explanations as well as a no explanation condition. We measured users' trust of a classifier, quantified the effects of these three forms of explanations, and assessed the changes in users' trust. We found that participants trust a classifier appropriately when an explanation is available. The combination of human, classification algorithm and understandable explanation makes better decisions than the classifier and human alone.This work advances the state-of-the-art closer to building trust-able machine learning models and informs the design and appropriate use of automated systems.

Yang, Fumeng↗
DOE OSTI2020

Developing an Active Learning algorithm for learning Bayesian classifiers under the Multiple Instance Learning scenario

In the Multiple Instance Learning scenario, the training data consists of instances grouped into bags, and each bag is labelled with whether it is positive, i.e. contains at least one positive instance. First, Active Learning, in which additional labels can be iteratively requested, has the potential to allow more accurate classifiers to be learned with less labels. Active Learning has been applied to the Multiple Instance Learning under two settings: when bag labels of unlabelled bags can be requested, and when instance labels within bags known to be positive can be requested. Second, Bayesian Active learning methods have the potential to learn accurate classifiers with few labels, because they explicitly track the classifier uncertainty and can thus address its knowledge gaps. Yet, there does not exist any Bayesian Active Learning method for the Multiple Instance Learning Scenario. In this work, we develop the first such method. We develop a Bayesian classifier for the Multiple Instance Learning scenario, show how it can be efficiently used for Bayesian Active Learning, and perform experiments assessing its performance. While its performance exceeds that when no Active Learning is used, it is sometimes better, sometimes worse than the naive baseline of uncertainty sampling, depending on the situation. This suggests future work: building more customizable Bayesian Active Learning methods for the Multiple Instance Scenario, customizable to whether bag or instance label accuracy is targeted, and the labeling budget.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Safer Foundation Solar Demands Skill Collaborative

The milestones and accomplishments achieved in Safer’s Solar Demands Skill Training program required a collective effort of stakeholders. The ability to achieve the desired results and impact lives of the population we serve works best when collaborating with community stakeholders such as community-based organizations, faith-based organizations, community activists, local law enforcement, community residents, employers, and elected and appointed officials. We are working harder than ever to place clients in-demand careers and high-growth industry sectors. Our employer engagement with high growth sectors continues to increase, we have been able to deepen our relationships in this space by providing in demand stackable credential training. Launched our initiative in the green job space by partnering with organizations like ComEd, the Department of Energy, community-based organizations, faith-based organizations, and manufacturers that helped to train clients in the green jobs and renewable energy space. By the end of the year, we will have completed our tenth cohort of photovoltaic solar installation training. The training has been used as a foundation for solar panel installers to acquire new skills in in the green jobs career pathways, such as sales and customer service. It has also served as a pipeline to union-level trade positions through the skills participants obtained through partnership engagement. Safer Foundation's policy and advocacy team plays a major role in expanding opportunities for people with records to over one hundred occupations, including the trades. This reform has allowed many to secure living wage employment, reducing the high recidivism rate within Illinois. Safer continues to build our social enterprise with Reconstructive Technology Partners (RTP). RTP is introducing people with records to the construction trades such as solar, carpentry and electrical through residential remodeling of homes on smaller construction projects. Understanding the need to have a greater community presence, outreach was extended to a boots on the ground model, including, but not limited to door-to-door engagement, DE-EE0008571 Safer Foundation Page 4 of 29 local radio broadcasting and print ads in local newspapers. We continue to seek innovative ways to increase Safer Foundations' presence in the renewable energy space. Outreach efforts gave us an opportunity to share critical reentry information and opportunities about our PV installer program. Giving us reach with local and national audiences alike. We launched a systematic approach to improving client data and client tracking through an evidence-based practices initiative. That implemented an agency wide cross-functional data management system. The system supported our goal of reviewing, evaluating, and making recommendations to improve operational processes, program delivery, information sharing, and more. Played a significant part in the success of the solar program. Finally, economists around the nation agree that there is a significant labor shortage. The shortage directly threatens our ability to sustain our economic growth; if employers do not have access to the workers they need, it can lead to a shutdown in the economic recovery. The demand for Safer Foundation services is more important and impactful than ever. We will continue to build upon our 50 years of experience to address the challenges ahead and serve more people in a better way. We are confident we will accomplish beautiful things that benefit everyone involved because together, we are powerful.

14 SOLAR ENERGY↗
NASA NTRS1995

A versatile system for processing geostationary satellite data with run-time visualization capability

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow can be interactively assessed and altered as needed. In this environment, the intermediate data processing 'images' can be viewed, enabling the investigator to easily monitor the various data processing steps as they progress. Additionally, this environment allows the rapid testing of new processing modules and allows their effects to be visually compared with previous results.

Landsfeld, M.↗
NASA NTRS1997

Quiet Flow Characteristics of the NASA-Ames Laminar Flow Supersonic Wind Tunnel for Mach 1.6 Transition Studies

Low-disturbance or 'quiet' wind tunnels are an essential part of any meaningful boundary layer transition research. In particular, the receptivity of supersonic boundary layers to wind tunnel disturbances can significantly alter the transition phenomena under investigation on a test model. Consequently, considerable study has gone into the design of a new wind tunnel to provide quiet (low-disturbance) flow, encompassing both theoretical and experimental efforts. Our pilot (eighth-scale) supersonic wind tunnel was reported in 1992. NASA-Ames Fluid Mechanics Laboratory (FML) commissioned a quiet wind tunnel in 1994 to support Supersonic Laminar Flow Control (SLFC) research. Known as the Laminar Flow Supersonic Wind Tunnel (LFSWT), this tunnel is designed to operate at potential cruise Mach numbers and unit Reynolds numbers (Re) of the High Speed Civil Transport (HSCT). The need to better understand the transition phenomena on the leading edge region of swept (HSCT) wings provided the impetus for building the LFSWT. Additional information is contained in the original extended abstract.

Wolf, Stephen W. D.↗
NASA NTRS2011

Sustainably Sourced, Thermally Resistant, Radiation Hard Biopolymer

This material represents a breakthrough in the production, manufacturing, and application of thermal protection system (TPS) materials and radiation shielding, as this represents the first effort to develop a non-metallic, non-ceramic, biomaterial-based, sustainable TPS with the capability to also act as radiation shielding. Until now, the standing philosophy for radiation shielding involved carrying the shielding at liftoff or utilizing onboard water sources. This shielding material could be grown onboard and applied as needed prior to different radiation landscapes (commonly seen during missions involving gravitational assists). The material is a bioplastic material. Bioplastics are any combination of a biopolymer and a plasticizer. In this case, the biopolymer is a starch-based material and a commonly accessible plasticizer. Starch molecules are composed of two major polymers: amylase and amylopectin. The biopolymer phenolic compounds are common to the ablative thermal protection system family of materials. With similar constituents come similar chemical ablation processes, with the potential to have comparable, if not better, ablation characteristics. It can also be used as a flame-resistant barrier for commercial applications in buildings, homes, cars, and heater firewall material. The biopolymer is observed to undergo chemical transformations (oxidative and structural degradation) at radiation doses that are 1,000 times the maximum dose of an unmanned mission (10-25 Mrad), indicating that it would be a viable candidate for robust radiation shielding. As a comparison, the total integrated radiation dose for a three-year manned mission to Mars is 0.1 krad, far below the radiation limit at which starch molecules degrade. For electron radiation, the biopolymer starches show minimal deterioration when exposed to energies greater than 180 keV. This flame-resistant, thermal-insulating material is non-hazardous and may be sustainably sourced. It poses no hazardous waste threats during its lifecycle. The material composition is radiation-tolerant up to megarad doses, indicating its use as a radiation shielding material. It is lightweight, non-metallic, and able to be mechanically densified, permitting a tunable gradient of thermal and radiation protection as needed. The dual-use (thermal and radiation shielding), sustainable nature of this material makes it suitable for both industrial applications as a sustainable/green building material, and for space applications as thermal protection material and radiation shield.

Pugel, Diane↗
NASA NTRS2022

Ten Years of VIIRS On-Orbit Geolocation Calibration and Performance

The first innovative Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been in operation for 10 years since its launch on 28 October 2011. The second VIIRS sensor aboard the first Join Polar Satellite System (JPSS-1) satellite has been in operation for 4 years since its launch on 18 November 2017, which became NOAA-20. Well-geolocated and radiometrically calibrated Level-1 sensor data records (SDRs) from VIIRS are crucial to numerical weather prediction (NWP) and Level-2+ environmental data record (EDR) algorithms and products. The high quality of Level-2+ EDRs is a requirement for the continuity of NASA Earth science data records (ESDRs) and climate data records (CDRs), one of the two objectives of the SNPP mission and one of the three elements in the JPSS mission objective. The other objective of the SNPP mission is risk reduction for the follow-on JPSS missions. This paper summarizes the on-orbit geolocation calibration and validation (Cal/Val) activities for both VIIRS sensors onboard SNPP and NOAA-20 in the past 10 years. These activities include nominal geolocation Cal/Val activities, risk reduction activities, and improvements for the on-orbit VIIRS sensor operations. After these activities, sub-pixel geolocation accuracy is achieved. Nadir equivalent geolocation uncertainty is generally within 75 m (1-σ), or 20% imagery band pixels, in either the along-scan or along-track direction for both SNPP and NOAA-20 VIIRS sensors. The worst 16-day measured geolocation errors (radial, 3-σ) are 280 m and 267 m, respectively, in the latest SNPP and NOAA-20 VIIRS data collections, which are better than the required accuracy of 375 m (radial, 3-σ). The risk reduction activities also improved VIIRS builds for JPSS-3 and JPSS-4 satellites, and provide lessons learned for other VIIRS-like sensor builds.

VIIRS↗