Search NASA⌕ Search

SEARCH · Search NASA

Results for “IBM”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Solar energy system economic evaluation: IBM System 2, Togus, Maine

The economic analysis of the solar energy system, is developed for Torgus and four other sites typical of a wide range of environmental and economic conditions in the continental United States. This analysis is accomplished based on the technical and economic models in the f-chart design procedure with inputs taken on the characteristics of the installed system and local conditions. The results are expressed in terms of the economic parameters of present worth of system cost over a projected twenty year life, life cycle savings, year of positive savings and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables is also investigated. Results demonstrate that the solar energy system is economically viable at all of the five sites for which the analysis was conducted.

Source record↗
NASA NTRS1980

Solar energy system performance evaluation: Seasonal report for IBM System 1B, Carlsbad, New Mexico

A hot solar heating and hot water system's operational performance from April 1979 through March 1980 is evaluated. The space heating and hot water loads were near expected values for the year. Solar energy provided 43 percent of the space heating and 53 percent of the hot water energy. The system did not meet the total system solar fraction design value of 69 percent because of a combination of higher estimated space heating load than was actually encountered and the apportioning of solar energy between the space heating and the domestic hot water loads. System losses and high building temperatures also contributed to this deviation. Total net savings were 23.072 million BTUs. Most of the energy savings came during the winter months, but hot water savings were sufficient to justify running the system during the summer months.

Source record↗
NASA NTRS1980

Solar energy system economic evaluation: IBM System 4, Clinton, Mississippi

An economic analysis of the solar energy system was developed for five sites, typical of a wide range of environmental and economic conditions in the continental United States. The analysis was based on the technical and economic models in the F-chart design procedure, with inputs based on the characteristic of the installed system and local conditions. The results are of the economic parameters of present worth of system cost over a 20 year time span: life cycle savings, year of positive savings and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables is also investigated.

Source record↗
NASA NTRS1980

Solar energy system economic evaluation for IBM System 3, Glendo, Wyoming

This analysis was based on the technical and economic models in f-chart design procedures with inputs based on the characteristics of the parameters of present worth of system cost over a projected twenty year life: life cycle savings, year of positive savings, and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainties in constituent system and economic variables was also investigated.

Source record↗
NASA NTRS1984

Transferring data oscilloscope to an IBM using an Apple II+

A set of PASCAL programs permitting the use of a laboratory microcomputer to facilitate and control the transfer of data from a digital oscilloscope (used with photomultipliers in experiments on soot formation in hydrocarbon combustion) to a mainframe computer and the subsequent mainframe processing of these data is presented. Advantages of this approach include the possibility of on-line computations, transmission flexibility, automatic transfer and selection, increased capacity and analysis options (such as smoothing, averaging, Fourier transformation, and high-quality plotting), and more rapid availability of results. The hardware and software are briefly characterized, the programs are discussed, and printouts of the listings are provided.

Miller, D. L.↗
NASA NTRS1986

An IBM PC-based math model for space station solar array simulation

This report discusses and documents the design, development, and verification of a microcomputer-based solar cell math model for simulating the Space Station's solar array Initial Operational Capability (IOC) reference configuration. The array model is developed utilizing a linear solar cell dc math model requiring only five input parameters: short circuit current, open circuit voltage, maximum power voltage, maximum power current, and orbit inclination. The accuracy of this model is investigated using actual solar array on orbit electrical data derived from the Solar Array Flight Experiment/Dynamic Augmentation Experiment (SAFE/DAE), conducted during the STS-41D mission. This simulator provides real-time simulated performance data during the steady state portion of the Space Station orbit (i.e., array fully exposed to sunlight). Eclipse to sunlight transients and shadowing effects are not included in the analysis, but are discussed briefly. Integrating the Solar Array Simulator (SAS) into the Power Management and Distribution (PMAD) subsystem is also discussed.

Emanuel, E. M.↗
NASA NTRS1985

Image processing on the IBM personal computer

An experimental, personal computer image processing system has been developed which provides a variety of processing functions in an environment that connects programs by means of a 'menu' for both casual and experienced users. The system is implemented by a compiled BASIC program that is coupled to assembly language subroutines. Image processing functions encompass subimage extraction, image coloring, area classification, histogramming, contrast enhancement, filtering, and pixel extraction.

Myers, H. J.↗
NASA NTRS1989

A user-friendly, menu-driven, language-free laser characteristics curves graphing program for desk-top IBM PC compatible computers

A facility was established that uses collected data and feeds it into mathematical models that generate improved data arrays by correcting for various losses, base line drift, and conversion to unity scaling. These developed data arrays have headers and other identifying information affixed and are subsequently stored in a Laser Materials and Characteristics data base which is accessible to various users. The two part data base: absorption - emission spectra and tabulated data, is developed around twelve laser models. The tabulated section of the data base is divided into several parts: crystalline, optical, mechanical, and thermal properties; aborption and emission spectra information; chemical name and formulas; and miscellaneous. A menu-driven, language-free graphing program will reduce and/or remove the requirement that users become competent FORTRAN programmers and the concomitant requirement that they also spend several days to a few weeks becoming conversant with the GEOGRAF library and sequence of calls and the continual refreshers of both. The work included becoming thoroughly conversant with or at least very familiar with GEOGRAF by GEOCOMP Corp. The development of the graphing program involved trial runs of the various callable library routines on dummy data in order to become familiar with actual implementation and sequencing. This was followed by trial runs with actual data base files and some additional data from current research that was not in the data base but currently needed graphs. After successful runs, with dummy and real data, using actual FORTRAN instructions steps were undertaken to develop the menu-driven language-free implementation of a program which would require the user only know how to use microcomputers. The user would simply be responding to items displayed on the video screen. To assist the user in arriving at the optimum values needed for a specific graph, a paper, and pencil check list was made available to use on the trial runs.

Klutz, Glenn↗
NASA NTRS1991

Time variant analysis of large scale constrained rotorcraft systems dynamics - An exploitation of IBM-3090 vector-processor's pipe-lining feature

A generalized algorithmic procedure is presented for handling the constraints in transmissions, which are treated as a multibody system of interconnected rigid/flexible bodies. The type of constraints are classified based on the interconnection of the bodies, assuming one or more points of contact to exist between them. The method is explained through flow charts and configuration/interaction tables. A significant increase in speed of execution is achieved by vectorizing the developed code in computationally intensive areas. The study of an example consisting of two meshing disks rotating at high angular velocity is carried out. The dynamic behavior of the constraint forces associated with the generalized coordinates of the system are plotted by selecting various modes. Applications are intended for the study of dynamic and subsequent prediction of constraint forces at the gear teeth contacting points in helicopter transmissions with the aim of improving performance dependability.

Amirouche, F. M. L.↗
NASA NTRS1992

George M. Low Trophy: NASA's quality and excellence award. 1992 recipients: Honeywell Clearwater, IBM Houston

The George M. Low Trophy is awarded to current NASA contractors, subcontractors, and suppliers in the aerospace industry who have demonstrated sustained excellence and outstanding achievements in quality and productivity for three or more years. The objectives of the award are to increase public awareness of the importance of quality and productivity to the Nation's aerospace program and industry in general; encourage domestic business to continue efforts to enhance quality, increase productivity, and thereby strengthen competitiveness; and provide the means for sharing the successful methods and techniques used by the applicants with other American enterprises. Information is given on candidate eligibility for large businesses, the selection process, the nomination letter, and the application report. The 1992 highlights and recipients are included.

Source record↗
NASA NTRS1995

Supersonic Transport Analysis on the IBM Parallel System SP2

Several studies of supersonic transport (SST) configurations have been undertaken by members of the High Speed Aerodynamics branch at NASA Ames. These computational investigations involved the analysis of shapes to study the sonic boom signatures, aerodynamic performance characteristics, as well as studies of nacelle/airframe integration. A variety of different computer codes were employed including both structured and unstructured codes. The AIRPLANE code has been used extensively in these investigations. This computer code solves the Euler equations for inviscid flow by exploiting an explicit finite volume method on a mesh of tetrahedral cells. AIRPLANE is capable of handling complete aircraft configurations including nacelles and diverters. An example of a generic SST configuration is shown and a comparison of computed and experimental force coefficients is presented. Most of the computations in support of the SST investigations have been run on the YMP and C-90 computers currently installed at NASA Ames. Additional information is contained in the original extended abstract.

Jameson, Antony↗
NASA NTRS2019

Simulation of Non-Markovian Dynamics on IBM QX

Currently available quantum computers allow us to run proof of principle algorithms that are unitary in their nature. Therefore, this architecture is unoptimized for simulation of an open quantum system. Here we present a method that helps us to overcome unitarity. We show how to run a non-Markovian evolution of a qubit system. We discuss all the discrepancies from theoretical predictions.

Wudarski, Filip A.↗
NASA NTRS2011

Accelerating Climate and Weather Simulations through Hybrid Computing

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

hybrid computing↗
DOE OSTI2022

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗