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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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Topics: Computing: The View from NASA Headquarters; Earth Resources Laboratory Applications Software: Versatile Tool for Data Analysis; The Hypercube: Cost-Effective Supercomputing; Artificial Intelligence: Rendezvous with NASA; NASA's Ada Connection; COSMIC: NASA's Software Treasurehouse; Golden Oldies: Tried and True NASA Software; Computer Technical Briefs; NASA TU Services; Digital Fly-by-Wire.
The Astrophysics Implementation Plan calls for a minority role in L3, planned for launch in 2034. L3 The third large mission in ESAs Cosmic Visions 2015-2025 Programme NASA and ESA have been discussing a collaboration for 2 years Gravitational Observatory Advisory Team (GOAT) ESA study evaluating and recommend scientific performance tradeoffs, detection technologies, technology development activities, data analysis capabilities, schedule and cost US representatives: Guido Mueller, Mark Kasevich, Bill Klipstein, RTS Started in October 2014, concluding with a final report in late Marchor early April 2016. ESA solicited interest from ESA Member States in November 2015 NASA is continuing technology development support. ESA is restarting technology development activities.
The analysis and preliminary design of a 25 kW concentrator enhanced lightweight flexible solar array are presented. The study was organized into five major tasks: (1) assessment and specification of design requirements; (2) mechanical design; (3) electric design; (4) concentrator design; and (5) cost projection. The tasks were conducted in an iterative manner so as to best derive a baseline design selection. The objectives of the study are discussed and comparative configurations and mass data on the SEP (Solar Electric Propulsion) array design, concentrator design options and configuration/mass data on the selected concentrator enhanced solar array baseline design are presented. Design requirements supporting design analysis and detailed baseline design data are discussed. The results of the cost projection analysis and new technology are also discussed.
An automated system for conducting annual gypsy moth defoliation surveys using LANDSAT MSS data and digital processing techniques is described. A two-step preprocessing procedure was developed that uses multitemporal data sets representing forest canopy conditions before and after defoliation to create a digital image in which all nonforest cover types are eliminated or masked out of a LANDSAT image that exhibits insect defoliation. A temporal window for defoliation assessment was identified and a statewide data base was established. A data management system to interface image analysis software with the statewide data base was developed and a cost benefit analysis of this operational system was conducted.
Supporting Data can be downloaded at: https://gain.inl.gov/content/uploads/4/2024/06/INL-RPT-24-77048-R1.xlsx Nuclear energy is a critical cornerstone of the current United States clean energy supply and may play a larger role in the future in support of a transition to a net-zero economy. The current fleet of nuclear reactors predominantly consists of large light-water reactors (LWRs), while many of the reactor designs under consideration are smaller and/or different technologies. Because these new designs have not yet been built, there is a high degree of uncertainty associated with their cost. This complicates energy-planning efforts because cost projections are not always standardized, consistent, and centralized in an easily accessible location. To help support energy planning in the US, this report provides advanced nuclear cost ranges using a transparent methodology along with other relevant information that can be used to help support decision making and energy planning. The purpose of this work was to conduct a methodical process for cost evaluation using only public information that was vetted with the end-goal to provide reference cost projections for nuclear energy. To provide a solid basis for these values, the approach and assumptions are explicitly laid out throughout the report allowing any user of the data to challenge or reconsider them. Because future US nuclear-reactor costs are still unknown due to little recent observed data, the report opted to compile a comprehensive list of bottom-up estimates and evaluate averages/trends within the data to identify reference ranges. This was deemed preferable to opining on the robustness or validity of one cost estimation versus another. To that end, the work evaluated thousands of lines of cost subaccounts from several bottom-up cost estimates. A wide variety of different reactor types captured in the data are of various sizes and technologies. Some of these reactors will be representative of advanced reactors under development while others will not. Thus, the results here are dependent on the data that are available and the accuracy of the estimates that are used. Each bottom-up estimate was reviewed to determine whether it was complete. Incomplete data sets were corrected to ensure an adequate basis of cross-comparison. The report is not without limitations and should be interpreted as an initial step to develop cost ranges for nuclear technology. Ultimately, future work can build upon the methodology with refined cost estimates to reduce uncertainty. US-based overnight capital cost (OCC) estimates were compiled from extensive data sets into ranges for both large and small reactor sizes for 2030. To project the cost declines over time, learning rates were sampled from literature sources. No SMRs were previously built; hence, learning rates based on bottom-up approaches (e.g., by quantifying the impact stemming from fabrication of different components, modular work, site construction, commissioning) were prioritized. For larger reactors, actual learning rates from deployments were used to project future costs (adjusted to account for standardization or lack thereof between designs). Other costs included are fixed and variable operations and maintenance costs. The final variables were capacity factors and ramp rates to support energy planning.
After evaluating the total lifetime costs of various commercial systems, it was determined that an in-house development would be more cost-effective in the long run. Matlab was chosen as the development platform, since it is now being taught to most engineering students. The presentation will discuss the specifications of the system.
Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.
Cost and Performance System (CAPS) is an automated system used from the planning phase through implementation to analysis and documentation. Data is retrievable or available for analysis of cost versus performance anomalies. CAPS provides a uniform system across intra- and international elements. A common system is recommended throughout an entire cost or profit center. Data can be easily accumulated and aggregated into higher levels of tracking and reporting of cost and performance.The level and quality of performance or productivity is indicated in the CAPS model and its process. The CAPS model provides the necessary decision information and insight to the principal investigator/project engineer for a successful project management experience. CAPS provides all levels of management with the appropriate detailed level of data.
A representative set of payloads for both science and applications disciplines were selected that would ensure a realistic and statistically significant estimate of equipment utilization. The selected payloads were analyzed to determine the applicability of Nuclear Instrumentation Modular (NIM)/Computer Automated Measurement Control (CAMAC) equipment in satisfying their data acquisition and control requirements. The analyses results were combined with the comparable results from related studies to arrive at an overall assessment of the applicability and commonality of NIM/CAMAC equipment usage across the spectrum of payloads.
An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.
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.
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.
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.
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.
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.
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.
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.
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.