Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cost and performance data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

"PoliMOR: A Policy Engine \"Made-to-Order\" for Automated and Scalable Data Management in Lustre"

Modern supercomputing systems are increasingly reliant on hierarchical, multi-tiered file and storage system architectures due to cost-performance-capacity trade-offs. Within such multi-tiered systems, data management services are required to maintain healthy utilization, performance, and capacity levels. We present PoliMOR, a pragmatic and reliable policy-driven data management framework. PoliMOR is composed of modular, single-purpose agents that gather file system metadata and enforce policies on storage systems. PoliMOR facilitates automated and scalable data management with customizable agents tailored to HPC facility-specific storage systems and policies. Our evaluations demonstrate the scalability and performance of PoliMOR both by its individual agents and as a collective entity. We believe PoliMOR is widely applicable across HPC facilities with large-scale data management challenges and will garner interest from the HPC community, given its flexible and open-source nature.

George, Anjus↗
NASA NTRS1975

A random search algorithm for laboratory computers

The small laboratory computer is ideal for experimental control and data acquisition. Postexperimental data processing is often performed on large computers because of the availability of sophisticated programs, but costs and data compatibility are negative factors. Parameter optimization can be accomplished on the small computer, offering ease of programming, data compatibility, and low cost. A previously proposed random-search algorithm ('random creep') was found to be very slow in convergence. A method is proposed (the 'random leap' algorithm) which starts in a global search mode and automatically adjusts step size to speed convergence. A FORTRAN executive program for the random-leap algorithm is presented which calls a user-supplied function subroutine. An example of a function subroutine is given which calculates maximum-likelihood estimates of receiver operating-characteristic parameters from binary response data. Other applications in parameter estimation, generalized least squares, and matrix inversion are discussed.

Curry, R. E.↗
DOE OSTI2021

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Space shuttle/payload interface analysis (study 2.4). Volume 2: Space shuttle traffic analysis

The transfer is reported of the capability to perform capture/cost analyses to MSFC. Space shuttle performance and direct costs, tug characteristics, reliability, and cost data were provided by NASA. The launch vehicle, mission models, payloads, and computer programs are discussed along with capture/cost analysis, and cost estimates. For Vol. 1, see N74-12493.

Plough, J. A.↗
NASA NTRS1986

Evaluation of carbon-carbon for space engine nozzle

An investigation is underway to determine the suitability of carbon-carbon composite materials for lightweight nozzle extensions on the Orbit Transfer Vehicle (OTV). The best combinations of fiber precursor, matrix material, and oxidation protection coatings are being evaluated in a series of hot-fire tests in an O sub 2/H sub 2 rocket nozzle environment. Evaluation criteria include life expectancy (recession), strength to weight, producibility, maturity, and cost. A data base of carbon-carbon performance in the OTV nozzle environment will be established which may be used in designing a full-scale OTV nozzle extension.

Suhoza, J. P.↗
NASA NTRS2000

Applying Technology Ranking and Systems Engineering in Advanced Life Support

According to the Advanced Life Support (ALS) Program Plan, the Systems Modeling and Analysis Project (SMAP) has two important tasks: 1) prioritizing investments in ALS Research and Technology Development (R&TD), and 2) guiding the evolution of ALS systems. Investments could be prioritized simply by independently ranking different technologies, but we should also consider a technology's impact on system design. Guiding future ALS systems will require SMAP to consider many aspects of systems engineering. R&TD investments can be prioritized using familiar methods for ranking technology. The first step is gathering data on technology performance, safety, readiness level, and cost. Then the technologies are ranked using metrics or by decision analysis using net present economic value. The R&TD portfolio can be optimized to provide the maximum expected payoff in the face of uncertain future events. But more is needed. The optimum ALS system can not be designed simply by selecting the best technology for each predefined subsystem. Incorporating a new technology, such as food plants, can change the specifications of other subsystems, such as air regeneration. Systems must be designed top-down starting from system objectives, not bottom-up from selected technologies. The familiar top-down systems engineering process includes defining mission objectives, mission design, system specification, technology analysis, preliminary design, and detail design. Technology selection is only one part of systems analysis and engineering, and it is strongly related to the subsystem definitions. ALS systems should be designed using top-down systems engineering. R&TD technology selection should consider how the technology affects ALS system design. Technology ranking is useful but it is only a small part of systems engineering.

Jones, Harry↗
NASA NTRS2009

"Fly-by-Wireless" and Wireless Sensors Update

This slide presentation reviews the uses of wires in the Aerospace industry. The vision is to minimize cables and connectors and increase functionality across the aerospace industry by providing reliable lower cost modular and higher performance alternatives to wired data connectivity to benefit the entire vehicle and program

Studor, George F.↗
NASA NTRS2010

Fly-by-Wireless Update

The presentation reviews what is meant by the term 'fly-by-wireless', common problems and motivation, provides recent examples, and examines NASA's future and basis for collaboration. The vision is to minimize cables and connectors and increase functionality across the aerospace industry by providing reliable, lower cost, modular, and higher performance alternatives to wired data connectivity to benefit the entire vehicle/program life-cycle. Focus areas are system engineering and integration methods to reduce cables and connectors, vehicle provisions for modularity and accessibility, and a 'tool box' of alternatives to wired connectivity.

Studor, George↗
DOE OSTI2021

Measured and satellite-derived albedo data for estimating bifacial photovoltaic system performance

The albedo of the ground surface is an important factor in the cost-effectiveness of a bifacial photovoltaic (PV) system. To improve the availability of reliable albedo data, datasets of ground albedo and associated meteorological data were developed by using existing measurement network data and data measured by the PV industry. The measured datasets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Satellite-derived values of albedo are available from the National Solar Radiation Data Base (NSRDB). The NSRDB albedos were compared to the measured albedos for Surface Radiation budget (SURFRAD) network locations for the period 2001–2017, and the mean bias difference results were from -0.044 to +0.056. Overall, these differences are greater than the albedo measurement uncertainty of ±0.02; consequently, the NSRDB albedos should be used with caution for estimating the performance of bifacial PV systems. Differences between SURFRAD and NSRDB albedos are attributed to the NSRDB method for determining albedo and to the ground surfaces within the NSRDB 4 km spatial resolution pixel consisting of a mixture of surface types rather than just the single surface types viewed by the albedometers at the SURFRAD stations.

14 SOLAR ENERGY↗
DOE OSTI2021

Optics Enabled Networks and Architectures for Data Center Cost and Power Efficiency

Bandwidth demand for datacenter networks continues as performance increases and is further fueled by the exploding demand for AI and new HPC workloads. Managing power and costs will require a range of solutions including new networking and workload specialized architectures, composable systems and optical circuit switching. In this study we focus primarily on two topics, examining the benefits of flatter networks (enabled mainly by means of co-packaged-optics-enabled switches) and the utilization improvement potential for composable (disaggregated) systems, while discussing specialized hardware and networks, and optical circuit switching more briefly.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1976

Silicon materials task of the low cost solar array project, part 2

Purity requirements for solar cell grade silicon material was developed and defined by evaluating the effects of specific impurities and impurity levels on the performance of silicon solar cells. Also, data was generated forming the basis for cost-tradeoff analyses of silicon solar cell material. Growth, evaluation, solar cell fabrication and testing was completed for the baseline boron-doped Czochralski material. Measurements indicate Cn and Mn seriously degrade cell performance, while neither Ni nor Cu produce any serious reduction in cell efficiency.

Hopkins, R. H.↗
NASA NTRS1981

Electrochemical energy storage subsystems study, volume 1

The effects on life cycle costs (LCC) of major design and performance technology parameters for multi kW LEO and GEO energy storage subsystems using NiCd and NiH2 batteries and fuel cell/electrolysis cell devices were examined. Design, performance and LCC dynamic models are developed based on mission and system/subsystem requirements and existing or derived physical and cost data relationships. The models define baseline designs and costs. The major design and performance parameters are each varied to determine their influence on LCC around the baseline values.

Miller, F. Q.↗
NASA NTRS1975

SEPS guidance and navigation autonomy selection via mission analysis

A systematic rationale for selecting a cost-effective guidance and navigation (G & N) autonomy level for the solar electric propulsion stage (SEPS) vehicle is developed. After a definition of autonomy levels, a mission analysis is performed for representative SEPS missions using realistic G & N sensor hardware. Cost data for fabricating, integrating and refurbishing onboard avionics hardware and the ground costs corresponding to each autonomy level are generated. Results are presented that indicate performance of various G & N sensor hardware sets and the dominating factors which influence G & N autonomy level selection.

Causey, W.↗
NASA NTRS1975

Methods of extending signatures and training without ground information

Methods of performing signature extension, using LANDSAT-1 data, are explored. The emphasis is on improving the performance and cost-effectiveness of large area wheat surveys. Two methods were developed: ASC, and MASC. Two methods, Ratio, and RADIFF, previously used with aircraft data were adapted to and tested on LANDSAT-1 data. An investigation into the sources and nature of between scene data variations was included. Initial investigations into the selection of training fields without in situ ground truth were undertaken.

Henderson, R. G.↗
NASA NTRS2014

Enabling Future Low-Cost Small Mission Concepts

A SmallSat using a small Radioisotope Power System for deep space destinations could potentially fit into a Discovery class mission cost cap and perform significant science with a timely return of data. Only applicable when the Discovery 12 guidelines were applied. Commonality of hardware and science instruments among identical spacecraft enabled to meet the Discovery Class mission cost cap. Multiple spacecraft shared the costs of the Launch Approval Engineering Process. Assumed a secondary science instrument was contributed. Small RPS could provide small spacecraft with a relatively high power (approx. 60 We) option for missions to deep space destinations (> 10 AU) with multiple science instruments. Study of Centaur mission demonstrated the ability to achieve New Frontiers level science. Multiple spacecraft possible with small RPS, allowing for multiple targets, science from multiple platforms, and/or redundancy.

Lee, Young↗
NASA NTRS2017

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗
NASA NTRS1978

Economic evaluation of DSS 13 unattended operations demonstration

The goals and data collection requirements to be used for the economic and performance evaluation indexes and life cycle cost parameters for the upcoming operations demonstration of an automated Deep Space Station (DSS) run unattended and controlled remotely from JPL are presented. These evaluation indexes compare the remote operation of telemetry at DSS 13 with the cost and performance of a comparable manned operation at DSS 11. A description is presented of the data that needs to be collected, how the data will be analyzed, and what can and cannot be learned from this operations demonstration.

Remer, D. S.↗