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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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Antitheft container is used to prevent theft of calculators, portable computers, and other small instruments. Container design is simple and flexible enough to allow easy access to display or input systems of instruments, while not interfering with power input to device.
Abstract Training machine learning models on classical computers is usually a time and compute intensive process. With Moore’s law nearing its inevitable end and an ever-increasing demand for large-scale data analysis using machine learning, we must leverage non-conventional computing paradigms like quantum computing to train machine learning models efficiently. Adiabatic quantum computers can approximately solve NP-hard problems, such as the quadratic unconstrained binary optimization (QUBO), faster than classical computers. Since many machine learning problems are also NP-hard, we believe adiabatic quantum computers might be instrumental in training machine learning models efficiently in the post Moore’s law era. In order to solve problems on adiabatic quantum computers, they must be formulated as QUBO problems, which is very challenging. In this paper, we formulate the training problems of three machine learning models—linear regression, support vector machine (SVM) and balanced k-means clustering—as QUBO problems, making them conducive to be trained on adiabatic quantum computers. We also analyze the computational complexities of our formulations and compare them to corresponding state-of-the-art classical approaches. We show that the time and space complexities of our formulations are better (in case of SVM and balanced k-means clustering) or equivalent (in case of linear regression) to their classical counterparts.
The Wind computational fluid dynamics code was used to perform a series of simulations on two offset stream nozzle concepts for jet noise reduction. The first concept used an S-duct to direct the secondary stream to the lower side of the nozzle. The second concept used vanes to turn the secondary flow downward. The analyses were completed in preparation of tests conducted in the NASA Glenn Research Center Aeroacoustic Propulsion Laboratory. The offset stream nozzles demonstrated good performance and reduced the amount of turbulence on the lower side of the jet plume. The computer analyses proved instrumental in guiding the development of the final test configurations and giving insight into the flow mechanics of offset stream nozzles. The computational predictions were compared with flowfield results from the jet rig testing and showed excellent agreement.
The N 2 O/CO analyzer uses LGR’s patented Off-axis ICOS technology, which employs a high-finesse optical cavity as the measurement cell. LGR’s technology has many proven advantages over conventional first-generation cavity ringdown spectroscopy (CRDS) techniques. In brief, since the laser beam does not have to be resonantly coupled to the measurement cell, precise beam alignment is not critical. Mentors can disassemble the cell for cleaning (CAREFULLY) the front surface mirrors. Analyzers are relatively inexpensive and inherently robust thermally and mechanically. In addition, since LGR’s technology can record reliable absorption spectra over a far wider range of optical depths (absorbance values) than CRDS, LGR analyzers provide measurements over a much wider range of mixing ratios (gas concentrations). The N 2 O/CO analyzer includes an internal computer that sends real-time data to the local instrument computer through its digital (RS-232) output.
The Earth Observing System (EOS) Microwave Limb Sounder (MLS) is a complex instrument with a front end computer and 32 subsystem computers. MLS is one of four instruments on NASA's EOS Aura spacecraft With almost 8 years in orbit, MLS has a few lessons learned which can be applied during the design phase of future instruments to effect better longevity, more robust operations and a significant cost benefit during operations phase.
The growing number of cores provided by today’s high-end computing systems present substantial challenges to application developers in their pursuit of parallel efficiency. To find the most effective optimization strategy, application developers need insight into the runtime behavior of their code. The University of Oregon (UO) and the Juelich Supercomputing Centre of Forschungszentrum Juelich (FZJ) develop the performance analysis tools TAU and Scalasca, respectively, which allow high-performance computing (HPC) users to collect and analyze relevant performance data – even at very large scales. TAU and Scalasca are considered among the most advanced parallel performance systems available, and are used extensively across HPC centers in the U.S., Germany, and around the world. The TAU and Scalasca groups share a heritage of parallel performance tool research and partnership throughout the past fifteen years. Indeed, the close interactions of the two groups resulted in a cross-fertilization of tool ideas and technologies that pushed TAU and Scalasca to what they are today. It also produced two performance systems with an increasing degree of functional overlap. While each tool has its specific analysis focus, the tools were implementing measurement infrastructures that were substantially similar. Because each tool provides complementary performance analysis, sharing of measurement results is valuable to provide the user with more facets to understand performance behavior. However, each measurement system was producing performance data in different formats, requiring data interoperability tools to be created. A common measurement and instrumentation system was needed to more closely integrate TAU and Scalasca and to avoid the duplication of development and maintenance effort. The PRIMA (Performance Refactoring of Instrumentation, Measurement, and Analysis) project was proposed over three years ago as a joint international effort between UO and FZJ to accomplish these objectives: (1) refactor TAU and Scalasca performance system components for core code sharing and (2) integrate TAU and Scalasca functionality through data interfaces, formats, and utilities. As presented in this report, the project has completed these goals. In addition to shared technical advances, the groups have worked to engage with users through application performance engineering and tools training. In this regard, the project benefits from the close interactions the teams have with national laboratories in the United States and Germany. We have also sought to enhance our interactions through joint tutorials and outreach. UO has become a member of the Virtual Institute of High-Productivity Supercomputing (VI-HPS) established by the Helmholtz Association of German Research Centres as a center of excellence, focusing on HPC tools for diagnosing programming errors and optimizing performance. UO and FZJ have conducted several VI-HPS training activities together within the past three years.
Quantum computing is emerging as a remarkable technology that offers the possibility of achieving major scientific breakthroughs in many areas. Here, by leveraging the unique features of quantum mechanics, quantum computers may be instrumental in advancing many areas, including science, energy, defense, medicine, and finance. This includes solving complex problems whose solution lies well beyond the capacity of contemporary and even future supercomputers that are based on conventional computing technologies. As a foundation for future generations of computing and information processing, quantum computing represents an exciting area for developing new ideas in computer science and computational engineering.
Quantum computing is emerging as a remarkable technology that offers the possibility of achieving major scientific breakthroughs in many areas. By leveraging the unique features of quantum mechanics, quantum computers may be instrumental in advancing many areas, including science, energy, defense, medicine, and finance. This includes solving complex problems whose solution lies well beyond the capacity of contemporary and even future supercomputers that are based on conventional computing technologies. As a foundation for future generations of computing and information processing, quantum computing represents an exciting area for developing new ideas in computer science and computational engineering.
Solid state digital computer, its high speed data handling system, and computer programs for laboratory instrumentation
Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.
The microparticle flow sensor (MFS) is a system for identifying and counting microscopic particles entrained in a flowing liquid. The MFS includes a transparent, optoelectronically instrumented laminar-flow chamber (see figure) and a computer for processing instrument-readout data. The MFS could be used to count microparticles (including micro-organisms) in diverse applications -- for example, production of microcapsules, treatment of wastewater, pumping of industrial chemicals, and identification of ownership of liquid products.
The Mars 2020 Perseverance rover is currently collecting drill cores of ancient igneous and sedimentary rock in and around Jezero crater for potential transport to Earth. These samples from the martian surface will enable detailed mineralogical, geochemical, and petrological measurements to characterize ancient depositional and diagenetic environments, quantitatively age-date the samples, and identify the building blocks for life or evidence for life itself. Furthermore, these drill cores are especially precious because they may represent the most pristine samples from the martian surface and our best chance at identifying martian life, as future sample return missions may be conducted by humans that can introduce biological contaminants to the samples. Because of the importance of these samples, we must take great care in their handling, curation, and preliminary analyses so that they are preserved for scientific measurements for decades to come. In-situ measurements by Perseverance have identified minerals that further warrant special treatment of the returned samples. Hydrated sulfate carbonate, swelling clay minerals, and oxychlorine salts are extremely sensitive to changes in temperature and relative humidity. The structures of hydrated sulfates and oxychlorine minerals, in particular, readily change when exposed to different conditions, meaning the mineral assemblage of the as-returned samples may be lost if the samples aren’t handled properly. Characterizing the as-returned mineral assemblage, particularly of the salts, is essential for reconstructing past aqueous conditions and habitability. To characterize the as-returned mineral assemblage, the samples must be analyzed rapidly before phase changes occur and/or under controlled conditions (e.g., within a glove box). Significant recent advances in X-ray instrumentation for robotic exploration of the solar system have resulted in high-resolution miniaturized instruments that would provide mineralogical, geochemical, and petrological information on the returned martian samples without degradation of the mineral assemblage. Here, we describe a combined X-ray diffractometer/X-ray fluorescence spectrometer (XRD/XRF), an X-ray computed tomographic (XCT) instrument, and a scanned beam XRF mapping instrument that could be used in a glove box so that the martian samples remain under controlled conditions.
Latest Fusion energy experiments envision a quasi-continuous operation regime. In consequence, the largest experimental devices, currently in development, specify high-availability (HA) requirements for the whole plant infrastructure. HA features enable the whole facility to perform seamlessly in the case of failure of any of its components, coping with the increasing duration of plasma discharges (steady-state) and assuring safety of equipment, people, environment and investment. IPFN developed a control and data acquisition system, aiming for fast control of advanced Fusion devices, which is thus required to provide such HA features. The system is based on in-house developed Advanced Telecommunication Computing Architecture (ATCA) instrumentation modules - IO blades and data switch blades, establishing a PCIe network on the ATCA shelf's back-plane. The data switch communicates to an external host computer through a PCIe data network. At the hardware management level, the system architecture takes advantage of ATCA native redundancy and hot swap specifications to implement fail-over substitution of IO or data switch blades. A redundant host scheme is also supported by the ATCA/PCIe platform. At the software level, PCIe provides implementation of hot plug services, which translate the hardware changes to the corresponding software/operating system devices. The paper presents how the ATCA and PCIe based system can be setup to perform with the desired degree of HA, thus being suitable for advanced Fusion control and data acquisition systems. (authors)
The growing number of cores provided by today’s high-end computing systems present substantial challenges to application developers in their pursuit of parallel efficiency. To find the most effective optimization strategy, application developers need insight into the runtime behavior of their code. The University of Oregon (UO) and the Julich Supercomputing Centre of Forschungszentrum Julich (FZJ) developed the performance analysis tools TAU and Scalasca, respectively, which allow high-performance computing (HPC) users to collect and analyze relevant performance data – even at very large scales. TAU and Scalasca are considered among the most advanced parallel performance systems available, and are used extensively across HPC centers in the U.S., Germany, and around the world.
A 36 GHz computer controlled airborne Surface Contour Radar (SCR) is described, which was developed by the Naval Research Laboratory and NASA. The system uses pulse-compression techniques and dual frequency carriers spaced far enough apart to be decorrelated on the sea surface. The continuous wave transmitter is biphase modulated, the return signal is autocorrelated, and the code length and clock rate are variable, providing selectable range resolutions of 0.15, 0.30, 0.61 and 1.52 m. The SCR generates a false-color coded elevation map of the sea surface below the aircraft in real time, and can routinely produce ocean directional wave spectra with off-line data processing.
Computer algorithms and statistical techniques were used to identify, measure, and quantify the properties of solar granulation derived from movies collected by the Solar Optical Universal Polarimeter on Spacelab 2. The results show that there is neither a typical solar granule nor a typical granule evolution. A granule's evolution is dependent on local magnetic flux density, its position with respect to the active region plage, its position in the mesogranulation pattern, and the evolution of granules in its immediate neighborhood.
The Microvax 2 computer, the basic software in VMS, and the Mitsubishi High Speed Disk were received and installed. The digital scanning tunneling microscope is fully installed and operational. A new technique was developed for pseudocolor analysis of the line plot images of a scanning tunneling microscope. Computer studies and mathematical modeling of the empirical data associated with many of the film calibration studies were presented. A gas can follow-up experiment which will be launched in September, on the Space Shuttle STS-50, was prepared and loaded. Papers were presented on the structure of the human hair strand using scanning electron microscopy and x ray analysis and updated research on the annual rings produced by the surf clam of the ocean estuaries of Maryland. Scanning electron microscopic work was conducted by the research team for the study of the Mossbauer and Magnetic Susceptibility Studies on NmNi(4.25)Fe(.85) and its Hydride.
The standard practice in calibration laboratories across the country, including the Measurement Standards and Calibration Laboratory (MSCL) at the Johnson Space Center, is to use accuracy ratios to determine if instruments are in-tolerance rather than computing the actual uncertainty associated with the instruments. In the past, the accepted practice was to use an accuracy ratio of 10:1, but then state of the art advanced to the point where the 10:1 ratio could no longer be maintained, and the ratio was arbitrarily lowered to 4:1. It is now becoming increasingly difficult to maintain the 4:1 accuracy ratio, and in some cases 1:1 is the best that can be achieved. However, the effect of using these small accuracy ratios on the number of mistakes made in classifying instruments as in or out of tolerance is completely unknown. In order to assess the effect of using accuracy ratios in calibration, a simulation program was written to compute the proportion of instruments determined to be out of tolerance which were actually in, denoted by alpha, and the proportion of instruments determined to be in-tolerance which were actually out, denoted by beta. This was done for accuracy ratios of 1:1 and 10:1, for one to five progressive calibrations, under varying standard and instrument conditions. Selected results are presented and explained.