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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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Pre-flight scheduling and pre-flight requirements of the space transportation system are discussed. Payload safety requirements, shuttle flight manifests, and interface specifications are studied in detail.
The trade-offs between different desirable plan properties –e. g. PDDL temporal plan preferences – are often difficult to understand. Recent work proposes to address this by iterative planning with explanations elucidating the dependencies between such plan properties. Users can ask questions of the form “Why does the plan you suggest not satisfy property p?”, which are answered by “Because then we would have to forego q” where ¬q is entailed by p in plan space. It has been shown that such plan-property dependencies can be computed reasonably efficiently. But is this form of explanation actually useful for users? We contribute a user study evaluating that question. We design use cases from three domains and run a large user study (N= 40 for each domain, ca. 40 minutes work time per user and domain) on the internet platform Prolific. Comparing users with vs. without access to the explanations, we find that the explanations tend to enable users to identify better trade-offs between the plan properties, indicating an improved understanding of the task.
The space transportation system (STS) and ancillary equipment user studies are presented. Space shuttle data and planning requirements needed by the STS user are discussed along with the potential for common usage of multi-mission support equipment by the military and other aerospace personnel.
The HPDF User Experience (UX) team conducted eight semi-structured interviews with twelve individuals leading data and computing infrastructure work at DOE Office of Science (SC) user facilities or projects. This report presents key takeaways synthesizing community perspectives and needs, along with recommendations for the project. These insights should be considered as conceptual design work continues, early partnerships begin, workflow readiness activities evaluate and enhance key scientific tools, and early access systems are made available to the Office of Science (SC) community. Vigilance in meeting community requirements and ensuring workflow readiness will be needed to ensure HPDF’s success.
The Storage Sizing and Placement Simulation (SSIM) application allows a user to define the possible sizes and locations of energy storage elements on an existing grid model defined in OpenDSS. Given these possibilities, the software will automatically search through them and attempt to determine which configurations result in the best overall grid performance. This quick-start guide will go through, in detail, the creation of an SSIM model based on a modified version of the IEEE 34 bus test feeder system. There are two primary parts of this document. The first is a complete list of instructions with little-to-no explanation of the meanings of the actions requested. The second is a detailed description of each input and action stating the intent and effect of each. There are links between the two sections.
Data formats and functional flow charts for interplanetary trajectory computation program
The multi-mission support equipment (MMSE) applicable to six payloads is studied. Tables indicate individual satellite projects to which each MMSE is applicable, and which equipments are applicable to multiple payload configurations when more than one project's payload would be flown on the STS. An estimate of the first date on which interface definition information needed by a payload project are also shown.
A record of what is currently known about STS ancillary equipment is presented in this user-oriented design so that a potential user may evaluate whether he could use the described ancillary equipment or if he would need to design and fabricate a payload-unique item. References that the user can use to obtain additional details and requirements to aid in his evaluation and decision are included.
Alternative candidate STS flight charge approaches which will provide a basis for NASA's determination of an STS flight charge policy were analyzed. The analysis used STS transportation costs furnished by NASA. The STS User Charge Analysis was accomplished by (1) generating criteria for evaluation of alternative flight charge approaches, (2) defining alternative flight charge approaches, (3) computing flight charges for selected missions, (4) evaluating results using the criteria generated under (1), and (5) recommending flight charge approaches to be used as a basis for the formulation of a STS user flight charge policy.
With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.
User experience and visual design are greatly improved when usability testing is performed on a periodic basis. Design decisions should be tested by real users so that application owners can understand the effectiveness of each decision and identify areas for improvement. It is important that applications be tested not just once, but as a part of a continuing process that looks to build upon previous tests. NASA's Earthdata Search Client has undergone a usability study to ensure its users' needs are being met and that users understand how to use the tool efficiently and effectively. This poster will highlight the process followed for usability study, the results of the study, and what has been implemented in light of the results to improve the application's interface.
Users of the Orbiter/Spacelab combination will require both higher electrical power and longer duration than is available with the current baseline system. Present Orbiter/Spacelab mission capability is primarily constrained by the hydrogen and oxygen available to generate power in the Orbiter fuel cells. It is also necessary to assure that considerable attitude or point flexibility is retained to assure efficient operation of the Orbiter radiator cooling system. Beyond these early limitations, it is foreseen that orbital operations will eventually need even greater quantities of the basic space utilities: electrical power; heat rejection; and attitude control. Such operations, forecasted for the mid to late 1980's, will be best accommodated by a module stored in orbit that can furnish these to a docked Orbiter/Spacelab or other vehicles. The Orbital Service Module concept to provide for these services is presented.
The purpose of the BRAVO User's Manual is to describe the BRAVO methodology in terms of step-by-step procedures. The BRAVO methodology then becomes a tool which a team of analysts can utilize to perform cost effectiveness analyses on potential future space applications with a relatively general set of input information and a relatively small expenditure of resources. An overview of the BRAVO procedure is given by describing the complete procedure in a general form.
The effect of the changes incorporated in the LANDSAT D system on the ability of a local user terminal to receive, record and process data in real time was studied. Alternate solutions to the problems raised by these changes were evaluated. A loading analysis was performed in order to determine the quantities of data that a local user terminal (LUT) would be interested in receiving and processing. The number of bits in an MSS and a TM scene were calculated along with the number of scenes per day that an LUT might require for processing. These then combined to a total number of processed bits/day for an LUT as a function of sensor and coverage circle radius.
A users's manual for the computer programs involved in a study of the space tug docking simulation is presented. The following subjects are considered: (1) subroutine narratives, (2) program elements, (3) system subroutines, and (4) Univac 1108 cross reference listing. The functional and operational requirements for the computer programming are explained.
The following tasks related to the FY 74 Shuttle Users Analysis were completed: (1) STS user charge analysis, (2) business risk and value of operations in space (BRAVO) analysis, and (3) standardized subsystem module analysis. The first task was required to initiate the process of furnishing transportation charge estimates for STS payloads to STS users.
Pooled ridesharing offers on-demand, one-way, cost-effective transportation for passengers traveling in similar directions via a shared vehicle ride with others they do not know. Despite its potential benefits, the adoption of pooled rideshare remains low in the United States. This exploratory study aims to evaluate potential service improvements and features that may increase users’ willingness to adopt the service. The study analyzed transportation behaviors, rideshare preferences, and willingness to adopt pooled rideshare services among 8296 U.S. participants in 2025, building on findings from a 2021 nationwide survey of 5385 U.S. participants. The study incorporated 77 actionable items developed from the results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. Participants rated features such as driver verification (94%), vehicle information (93%), peak time reliability (93%), and saving time and money (92–93%) as most important for improving rideshare services. A pre-to-post analysis of willingness to use pooled rideshare utilizing the actionable items as per respondents’ preferences showed improvement: “definitely will” increased from 15.9% to 20.1% and “probably will” rose from 35.6% to 47.7%. These results suggest that well-targeted service improvements may meaningfully enhance pooled rideshare acceptance. This study offers practical guidance for Transportation Network Companies (TNCs) and policymakers aiming to improve pooled rideshare as well as potential future research opportunities.
Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.