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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Using Machine Learning and Data Analysis to Improve Customer Acquisition and Marketing in Residential Solar

High customer acquisition costs remain a persistent challenge in the U.S. residential solar industry. Effective customer acquisition in the residential solar market is increasingly achieved with the help of data analysis and machine learning, whether that means more targeted advertising, understanding customer motivations, or responding to competitors. New research by the National Renewable Energy Laboratory, Sandia National Laboratories, Vanderbilt University, University of Pennsylvania, and the California Center for Sustainable Energy and funded through the U.S. Department of Energy's Solar Energy Evolution and Diffusion (SEEDS) program demonstrates novel computational methods that can help drive down costs in the residential solar industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook – Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. NDE techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delamination, voids, AFP defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency (speed & cost), and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members to the NDE community is discussed.

Patricia A Howell↗
NASA NTRS1975

Remote sensor digital image data analysis using the General Electric Image 100 analysis system (a study of analysis speed, cost, and performance)

The author has identified the following significant results. It was found that the high speed man machine interaction capability is a distinct advantage of the image 100; however, the small size of the digital computer in the system is a definite limitation. The system can be highly useful in an analysis mode in which it complements a large general purpose computer. The image 100 was found to be extremely valuable in the analysis of aircraft MSS data where the spatial resolution begins to approach photographic quality and the analyst can exercise interpretation judgements and readily interact with the machine.

Mcmurtry, G. J.↗
NASA NTRS1985

Economics of liquid hydrogen from water electrolysis

An economical model for preliminary analysis of LH2 cost from water electrolysis is presented. The model is based on data from vendors and open literature, and is suitable for computer analysis of different scenarios for 'directional' purposes. Cost data associated with a production rate of 10,886 kg/day are presented. With minimum modification, the model can also be used to predict LH2 cost from any electrolyzer once the electrolyzer's cost data are available.

Lin, F. N.↗
DOE OSTI2020

Exploring Renewable Energy Opportunities in Select Southeast Asian Countries: A Geospatial Analysis of the Levelized Cost of Energy of Utility-Scale Wind and Solar Photovoltaics

The costs of renewable energy-based electricity generation have fallen precipitously in recent years to levels that are increasingly competitive with traditional generation such as fossil fuel-based generation. As these costs become increasingly competitive, private developers, policymakers, and energy system planners are searching for opportunities to harness high-quality renewable energy resources. Developing economies are setting ambitious targets and exploring how cost-effective, grid-connected renewable energy options can help power economic growth and meet growing electricity demands. This includes the member states of the Association of Southeast Asian Nations (ASEAN) that are determined to reach a target of 23% of renewable energy in the region's total primary energy supply by 2025. A critical gap to identifying opportunities and scaling up renewable energy is the lack of quality data and analyses to support decisions on the investment and deployment of renewables - including wind and solar photovoltaics (PV). This work supports decision making by providing high-quality data and spatial analysis of the cost of utility-scale wind and solar PV generation in select countries of Southeast Asia - specifically, the ASEAN member states. Generation costs are expressed as the levelized cost of energy (LCOE) - a commonly used metric that represents the net present value of the unit cost of electricity during the lifetime of a particular electricity generation technology. This is the first spatial estimate of LCOE for these technologies within the ASEAN member states - providing insights into the roles that renewable energy resource quality and other factors may play in generation costs.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification↗
NASA NTRS1999

The Transport of Solar Ions Through the Earth's Magnetosphere

This report covers the initial phase of an investigation that was originally selected by NASA Headquarters for funding by a grant but was later transferred to NASA GSFC for continued funding under a new and separate contract. The principal objective of the investigation, led by Dr. O.W. Lennartsson, is to extract information about the solar origin plasma in Earth's magnetosphere, specifically about the entry and transport of this plasma, using energetic (10 eV/e to 18 keV/e) ion composition data from the Lockheed Plasma Composition Experiment on the NASA/ESA International Sun-Earth Explorer One (ISEE 1) satellite. These data were acquired many years ago, from November 1977 through March of 1982, but, because of subsequent failures of similar experiments on several other spacecraft, they are still the only substantial ion composition data available from Earth's magnetotail, beyond 10 R(sub E), in the critically important sub-kev to keV energy range. All of the Lockheed data now exist in a compacted scientific format, suitable for large-scale statistical investigations, which has been archived both at Lockheed Martin in Palo Alto and at the National Space Science Data Center (NSSDC) in Greenbelt. The completion of the archiving, by processing the remaining half of the data, was made possible by separate funding through a temporary NASA program for data restoration and was given priority over the data analysis by a no-cost extension of the subject grant. By chance, the period of performance coincided with an international study of source and loss processes of magnetospheric plasma, sponsored by the International Space Science Institute (ISSI) in Bern, Switzerland, for which Dr. Lennartsson was invited to serve as one of 12 co-chairs. This study meshed well with the continued analysis of the NASA/Lockheed ISEE ion composition data and provided a natural forum for a broader discussion of the results from this unique experiment. What follows is arranged, for the most part, in the context of the ISSI project.

Lennartsson, O. W.↗
NASA NTRS2013

Parts Quality Management: Direct Part Marking of Data Matrix Symbol for Mission Assurance

A United States Government Accountability Office (GAO) review of twelve NASA programs found widespread parts quality problems contributing to significant cost overruns, schedule delays, and reduced system reliability. Direct part marking with Data Matrix symbols could significantly improve the quality of inventory control and parts lifecycle management. This paper examines the feasibility of using direct part marking technologies for use in future NASA programs. A structural analysis is based on marked material type, operational environment (e.g., ground, suborbital, Low Earth Orbit), durability of marks, ease of operation, reliability, and affordability. A cost-benefits analysis considers marking technology (label printing, data plates, and direct part marking) and marking types (two-dimensional machine-readable, human-readable). Previous NASA parts marking efforts and historical cost data are accounted for, including inhouse vs. outsourced marking. Some marking methods are still under development. While this paper focuses on NASA programs, results may be applicable to a variety of industrial environments.

Moss, Chantrice↗
DOE OSTI2017

Case Study for the ARRA-funded Ground Source Heat Pump (GSHP) Demonstration at Wilders Grove Solid Waste Service Center in Raleigh, NC

High initial costs and lack of public awareness of ground-source heat pump (GSHP) technology are the two major barriers preventing rapid deployment of this energy-saving technology in the United States. Under the American Recovery and Reinvestment Act (ARRA), 26 GSHP projects have been competitively selected and carried out to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. This paper highlights the findings of a case study of one of the ARRA-funded GSHP demonstration projects, a distributed GSHP system for providing all the space conditioning, outdoor air ventilation, and 100% domestic hot water to the Wilders Grove Solid Waste Service Center of City of Raleigh, North Carolina. This case study is based on the analysis of measured performance data, construction costs, and simulations of the energy consumption of conventional central heating, ventilation, and air-conditioning (HVAC) systems providing the same level of space conditioning and outdoor air ventilation as the demonstrated GSHP system. The evaluated performance metrics include the energy efficiency of the heat pump equipment and the overall GSHP system, pumping performance, energy savings, carbon emission reductions, and cost-effectiveness of the GSHP system compared with conventional HVAC systems. This case study also identified opportunities for reducing uncertainties in the performance evaluation and improving the operational efficiency of the demonstrated GSHP system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1993

Toward lowering the cost of mission operations

The mission operations system is one of the more significant drivers of the cost of the mission operations and data analysis segment of missions. In large or long-lived projects, the MOS can also be a driver in total mission cost. Larger numbers of missions, together with an increasingly cost-conscious environment, dictate that future missions must more strictly control costs as they perform to their requirements. It is therefore prudent to examine the conduct of past missions for ways to conserve resources. In this paper we review inputs made to past projects' 'lessons-learned' activities, in which personnel from past projects (among other things) identified major cost drivers of MOS's and considered how economies were or might have been realized in both design and performance of their MOS. Common themes among four such reviews are summarized in an attempt to provide suggestions for cost reduction in future missions.

Wall, S. D.↗
NASA NTRS2007

DSN Antenna Array Architectures Based on Future NASA Mission Needs

A flexible method of parametric, full life-cycle cost analysis has been combined with data on NASA's future communication needs to estimate the required number and operational dates of new antennas for the Deep Space Network (DSN). The requirements were derived from a subset of missions in the Integrated Mission Set database of NASA's Space Communications Architecture Working Group. Assuming that no new antennas are 'constructed', the simulation shows that the DSN is unlikely to meet more than 20% of mission requirements by 2030. Minimum full life-cycle costs result when antennas in the diameter range, 18m-34m, are constructed. Architectures using a mixture of antenna diameters produce a slightly lower full life-cycle cost.

array↗
NASA NTRS1971

Integrated operations/payloads/fleet analysis. Volume 1: Summary, study overview

The preparation of payload input data for analysis, and the capture and cost analyses are described for the current fleet, a low cost expendable fleet, and the space shuttle/space tug fleet. The data preparation consisted of formatting, extending, and correcting the input data which were broken down in terms of satellite gross weight. The results of the analyses indicate a significant reduction in the required total number of new payload units for the space shuttle/space tug fleet. Another result is that 26% of the payloads for the new low cost expendable fleet and 26% for the space shuttle/space tug fleet are of low cost payload designs.

Source record↗
NASA NTRS1972

Cost analysis of water recovery systems

Cost and performance data from Gemini, Skylab, and other aerospace and biotechnology programs were analyzed to identify major cost elements required to establish cost estimating relationships for advanced life support subsystems for long range planning in support of earth orbital programs. Cost analysis are presented for five leading water reclamation systems; (1) RITE waste management-water system;(2) reverse osmosis system;(3) multifiltration system;(4) vapor compression system; and(5) closed air evaporation system with electrolytic pretreatment.

Yakut, M. M.↗
DOE OSTI2025

Updating Nuclear Energy Cost Estimates for Net Zero World Initiative

Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

A comparison of remote sensing techniques for Minnesota wetlands classification

A wetland classification study in a typically complex 650 sq km test site in east central Minnesota compared the time, cost and accuracy of manually interpreted 1:24,000 scale color infrared aerial photographs with digital analysis of Landsat data. The comparison was between the same general wetland and non-wetland classes; accuracy of both systems was evaluated with intensive ground verification. For the same general classes, the overall mapping accuracy was 96 percent for the aerial photo interpretation and 71 percent for Landsat double-date classification. Results with maximum likelihood and SECHO classifiers were the same, 71 percent, while mapping accuracy with a layered classifier was only 66 percent. Compared to a general geometric correction and a single-date data set, geographic position and classification accuracy improved when a precision geometric correction and a double-date data set were used. Landsat digital analysis was faster, 24 vs. 90 days, but photointerpretation was more economical at $0.15/hectare (including all costs of procurement, processing and analysis), compared with Landsat costs of $0.35/hectare (not including costs of data procurement, processing prior to delivery to user and related overhead).

Werth, L. F.↗
DOE OSTI2021

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Electric Power Research Institute (EPRI) [Abstract]

Carbon dioxide (CO 2 ) capture from flue gas generated by fossil fuel-fired power plants has been proposed as an efficient approach to limit CO 2 emissions to the atmosphere. Due to the high cyclic CO 2 sorption capacity, well-tuned adsorption chemistry and non-volatility, solid sorbents are widely studied for CO 2 capture processes such as pressure swing adsorption (PSA) and temperature swing adsorption (TSA). Realistic applications of traditional solid sorbent systems face many challenges since moisture and heat management are problematic and solid-solid heat exchange is inefficient. Recently, a novel solid sorbent system, the sorbent polymer composite (SPC), has been developed to overcome those challenges in an energy-saving CO 2 capture process using TSA membrane contactors. A SPC material is comprised of a powdered solid sorbent embedded into a hydrophobic and porous polymer matrix. It allows gases to permeate through and achieve full contact with the sorbents while rejecting water moisture in the CO 2 capture process. In this collaborative research, NETL will conduct performance testing of a novel SPC material and EPRI will conduct a cost analysis based on that performance data.

20 FOSSIL-FUELED POWER PLANTS↗