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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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Collects space systems cost and related data (flight rate, payload, etc.) over time. Gathers only public data. Non-recurring and recurring. Minimal data processing. Graph, visualize, add context. Focus on US space systems competitiveness. Keep fresh update as data arises, launches occur, etc. Keep fresh focus on recent data, indicative of the future.
Collects space systems cost and related data (flight rate, payload, etc.) over time. Gathers only public data. Non-recurring and recurring. Minimal data processing. Graph, visualize, add context. Focus on US space systems competitiveness. Keep fresh update as data arises, launches occur, etc. Keep fresh focus on recent data, indicative of the future.
Excel data file for the U.S. Solar Photovoltaic System Cost Benchmark Q1 2017 Report
Despite the maturation of the broader solar PV industry, the operations and maintenance (O&M) market segment is still relatively under developed. The lack of industry coherence jeopardizes the long-term performance of multiple gigawatts of installed capacity, and thus, the legitimacy of solar PV as a dependable source of electricity generation in the U.S. To address these challenges, the project team formed a new company, the Amicus Operations and Maintenance (O&M) Cooperative, whose mission is to ensure that solar PV fulfills its promise as a responsible and reliable energy source, for generations to come. Amicus O&M Cooperative created solutions to the market gaps by establishing a consistent level of O&M service offerings; standardizing scopes of work and legal agreements; training and certifying technicians; minimizing transaction costs for asset owners; and mitigating risk by creating redundancy in the companies who are able to perform work to these standards. We attracted double the number of member-companies originally forecast (goal: 10, actual: 20), broadening the reach of the service area, minimizing travel costs, and reducing response times for O&M services. We built a professional website and a software platform for managing work orders. Lastly, we have established multiple channels for communication among members, including monthly calls for sales topics and for technical/operational topics, an intranet for announcements/ questions/articles, and regular in-person meetings in association with the meetings of our sister cooperative, Amicus Solar. Throughout the project, participants sought feedback, input, and insights from stakeholders in the O&M market segment, including current and potential member-companies and potential clients. The problem statement above was confirmed many times over, with additional insight on the need for more workforce development, driving efficiency and lowering cost through better data analysis and remote diagnostics, and finding ways to reduce the cost of secondary and ancillary services as well (including items such as vegetation management and module cleaning). For solar to maintain its status as a reliable energy source – and for it to continue attracting investment – it must perform to expectation. This is where solar PV O&M technicians come into play. The cooperative helps them perform their work more cost effectively by streamlining “soft costs” including legal costs and work management, as well as reducing travel time and expenses. The new cooperative has demonstrated significant price reductions for O&M services relative to reported industry averages, which benefits clients directly and the public indirectly through cleaner air, economic development, and job growth.
This CRADA between LLNS and Longview Fusion Energy Systems utilized a modernized LLNL Integrated Process Model (IPM) to assess technoeconomic viability and power plant configurations for Inertial Fusion Energy (IFE). During the collaboration period, a streamlined IPM model was produced by LLNL, which consolidated a combination of 3 models under one file. Additionally, obsolete parameters were removed and parameters available for trade space analysis were organized in a user-friendly fashion on the front interface. Gain scaling curves were discussed and analyzed in the framework of the IPM. Additional updates were made to account for cost scaling to today's dollars using an average inflation rate. Heat transfer material costing was updated using a ground up approach with public vendor data. Further levelized cost of electricity (LCOE) methods and models were discussed and reviewed for applicability to the IPM. Prior published literature on optical scaling was also discussed. Moreover, as part of this CRADA, the Participant developed a fusion technology development roadmap and point designs.
This CRADA between LLNS and Longview Fusion Energy Systems utilized a modernized LLNL Integrated Process Model (IPM) to assess technoeconomic viability and power plant configurations for Inertial Fusion Energy (IFE). During the collaboration period, a streamlined IPM model was produced by LLNL, which consolidated a combination of 3 models under one file. Additionally, obsolete parameters were removed and parameters available for trade space analysis were organized in a user-friendly fashion on the front interface. Gain scaling curves were discussed and analyzed in the framework of the IPM. Additional updates were made to account for cost scaling to today's dollars using an average inflation rate. Heat transfer material costing was updated using a ground up approach with public vendor data. Further levelized cost of electricity (LCOE) methods and models were discussed and reviewed for applicability to the IPM. Prior published literature on optical scaling was also discussed. Moreover, as part of this CRADA, the Participant developed a fusion technology development roadmap and point designs.
The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.
The establishment of propfan technology readiness was determined and candidate drive systems for propfan application were identified. Candidate testbed aircraft were investigated for testbed aircraft suitability and four aircraft selected as possible propfan testbed vehicles. An evaluation of the four candidates was performed and the Boeing KC-135A and the Gulfstream American Gulfstream II recommended as the most suitable aircraft for test application. Conceptual designs of the two recommended aircraft were performed and cost and schedule data for the entire testbed program were generated. The program total cost was estimated and a wind tunnel program cost and schedule is generated in support of the testbed program.
The goals of this project are to: Develop an early lifecycle software cost estimation tool leveraging existing data and capabilities Collect additional software data from: a) Jet Propulsion Laboratory; b) Goddard Space Flight Center; and c) Marshall Space Flight Center. Analyze, normalize, evaluate, stratify, and validate data. Create a calibrated, validated, and documented tool initially using available data and subsequently using newly collected data.
The Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates for vehicle technologies as well as conventional and alternative fuels, and it details the assumptions used to calculate those costs, such as gas and electricity prices, discount rates, and vehicle miles traveled. The 2022 update added more classes of light-duty vehicles, medium and heavy-duty vehicles, an aviation page, and it aligned diesel pathways with aviation pathways.
Purpose: To assess the cost-effectiveness of intensity modulated radiation therapy (IMRT) versus 3-dimensional conformal radiation therapy (3D-CRT) in the treatment of head-and neck-cancer (HNC). Methods and Materials: We used a Markov model to simulate radiation therapy-induced xerostomia and dysphagia in a hypothetical cohort of 65-year-old HNC patients. Model input parameters were derived from PARSPORT (CRUK/03/005) patient-level trial data and quality-of-life and Medicare cost data from published literature. We calculated average incremental cost-effectiveness ratios (ICERs) from the US health care perspective as cost per quality-adjusted life-year (QALY) gained and compared our ICERs with current cost-effectiveness standards whereby treatment comparators less than $50,000 per QALY gained are considered cost-effective. Results: In the first 2 years after initial treatment, IMRT is not cost-effective compared with 3D-CRT, given an average ICER of $101,100 per QALY gained. However, over 15 years (remaining lifetime on the basis of average life expectancy of a 65-year-old), IMRT is more cost-effective at $34,523 per QALY gained. Conclusion: Although HNC patients receiving IMRT will likely experience reduced xerostomia and dysphagia symptoms, the small quality-of-life benefit associated with IMRT is not cost-effective in the short term but may be cost-effective over a patient's lifetime, assuming benefits persist over time and patients are healthy and likely to live for a sustained period. Additional data quantifying the long-term benefits of IMRT, however, are needed.
The Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates for vehicle technologies as well as fuels, and it details the assumptions used to calculate those costs, such as gas and electricity prices, discount rates, and vehicle miles traveled. The 2024 update added more biofuels pathways to align with pathways used in the Biomass Scenario Model.
A low-cost transportable earth resources ground station was built in Canada and installed to operational status at Shoe Cove, Newfoundland. The system concepts developed for this station provide timely availability of data in both photographic and digital form. The system was designed with several objectives in mind: (1) to provide a system which could receive, store and process line-scan image data from a wide variety of satellites, most especially the LANDSAT and NOAA (VHRR) series, as well as aircraft scanner data, and data from future remote sensing and meteorological satellites; (2) the system has been designed to be operated by a small staff and to produce black and white images and computer-compatible tapes (CCT's) of all relevant data; (3) the system is compact in its physical design so that it is possible to configure it as a self-contained ground station, housed in a 3 x 12 meter trailer; (4) the system is designed to process all data at real-time rates or better and is designed in a modular fashion so that it can be easily upgraded to do further processing of the data, and/or to handle new satellites and sensors.
A data management system study is presented that defines, in functional terms, the most cost effective ground data management system to support Advanced Technology Laboratory (ATL) flights of the space shuttle. Results from each subtask performed and the recommended system configuration for reformatting the experiment instrumentation tapes to computer compatible tape are examined. Included are cost factors for development of a mini control center for real-time support of the ATL flights.
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The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics data analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.
As the disparity between compute and I/O on high-performance computing systems has continued to widen, it has become increasingly difficult to perform post-hoc data analytics on full-resolution scientific simulation data due to the high I/O cost. Error-bounded data decomposition and progressive data retrieval framework has recently been developed to address such a challenge by performing data decomposition before storage and reading only part of the decomposed data when necessary. However, the performance of the progressive retrieval framework has been suffering from the over-pessimistic error control theory, such that the achieved maximum error of recomposed data is significantly lower than the required error. Therefore, more data than required is fetched for recomposition, incurring additional I/O overhead. In order to tackle this issue, we propose a DNN-based progressive retrieval framework that can better identify the minimum amount of data to be retrieved. Our contributions are as follows: 1) We provide an in-depth investigation of the recently developed progressive retrieval framework; 2) We propose two designs of prediction models (named D-MGARD and E-MGARD) to estimate the amount of retrieved data size based on error bounds. 3) We evaluate our proposed solutions using scientific datasets generated by real-world simulations from two domains. Evaluation results demonstrate the effectiveness of our solution in accurately predicting the amount of retrieval data size, as well as the advantages of our solution over the traditional approach to reducing the I/O overhead. Based on our evaluation, our solution is shown to read significantly less data (5% - 40% with D-MGARD, 20% - 80% with E-MGARD).