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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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Advances in our understanding and ability to predict changes in our environment will require more comprehensive and coordinated measurements, data delivery systems, and modeling tools.
A computer-controlled, tracking ground terminal will be assembled at the NASA Glenn Research Center at Lewis Field to receive signals transmitted by the Glenn's Direct Data Distribution (D3) payload planned for a shuttle flight in low Earth orbit. The terminal will enable direct data reception of up to two 622-megabits-per-second (Mbps) beams from the space-based, K-band (19.05-GHz) transmitting array at an end-user bit error rate of up to 10(exp -12). The ground terminal will include a 0.9-m-diameter receive-only Cassegrain reflector antenna with a corrugated feed horn incorporating a dual circularly polarized, K-band feed assembly mounted on a multiaxis, gimbaled tracking pedestal as well as electronics to receive the downlink signals. The tracking system will acquire and automatically track the shuttle through the sky for all elevations greater than 20 above the horizon. The receiving electronics for the ground terminal consist of a six-pole microstrip bandpass filter, a three-stage monolithic microwave integrated circuit (MMIC) amplifier, and a Stirling cycle cryocooler (1 W at 80 K). The Sterling cycle cryocooler cools the front end of the receiver, also known as the low-noise amplifier (LNA), to about 77 K. Cryocooling the LNA significantly increases receiver performance, which is necessary so that it can use the antenna, which has an aperture of only 0.9 m. The following drawing illustrates the cryoterminal.
Exascale HPC systems are being designed with accelerators, such as GPUs, to accelerate parts of applications. In machine learning workloads as well as large-scale simulations that use GPUs as accelerators, the CPU (or host) memory is currently used as a buffer for data transfers between GPU (or device) memory and the file system. If the CPU does not need to operate on the data, then this is sub-optimal because it wastes host memory by reserving space for duplicated data. Furthermore, this “bounce buffer” approach wastes CPU cycles spent on transferring data. A new technique, NVIDIA GPUDirect Storage (GDS), can eliminate the need to use the host memory as a bounce buffer. Thereby, it becomes possible to transfer data directly between the device memory and the file system. This direct data path shortens latency by omitting the extra copy and enables higher-bandwidth. To take full advantage of GDS in existing applications, it is necessary to provide support with existing I/O libraries, such as HDF5 and MPI-IO, which are heavily used in applications. In this paper, we describe our effort of integrating GDS with HDF5, the top I/O library at NERSC and at DOE leadership computing facilities. We design and implement this integration using a HDF5 Virtual File Driver (VFD). The GDS VFD provides a file system abstraction to the application that allows HDF5 applications to perform I/O without the need to move data between CPUs and GPUs explicitly. We compare performance of the HDF5 GDS VFD with explicit data movement approaches and demonstrate superior performance with the GDS method.
Concentrations of 75 chemical constituents in the airborne particulate matter were measured in Cleveland, Ohio during 1971 and 1972. Daily values, maxima, geometric means and their standard deviations covering a 1-year period (45 to 50 sampling days) at each of 16 sites are presented on microfiche for 60 elements, and for a lesser number of days for 10 polycyclic aromatic hydrocarbon compounds (PAH), the aliphatic hydrocarbon compounds (AH) as a group and carbon. In addition, concentration roses showing directional properties are presented for 39 elements, 10 PAH and the AH as a group. The elements (except carbon) are shown both in terms of concentration and percentage of the suspended particulate matter.
The potential to accelerate the processing of low- and high-level tank waste by applying real-time monitoring (RTM) of chemical and physical properties has prompted research into the suitability of multiple analytical methods for that purpose. The broad variety of waste stream properties and the large number of analytes of interest (as evidenced by Waste Acceptance Criteria (WAC) and Process Control Limit (PCL) lists) lead to an overwhelming set of possible analytical scenarios. This report describes the use of Best Basis Inventory (BBI) data to find the most relevant analytical targets for the specific case of monitoring the blending of High Level Waste from multiple tanks prior to introduction into a vitrification facility. Campaigns for blending this waste to minimize the risk of exceeding WACs and PCLs have been proposed. However, the predicted compositions of the blended materials do not incorporate any uncertainties that may be associated with the representativeness of the waste layer samples or the laboratory analyses that generated the BBI data. Also, they do not include any uncertainty associated with the precision of collecting highly specific fractions of the layers during a blending campaign or any inhomogeneities that may exist in those layers. Monte Carlo methods are used to apply uncertainties to the compositions of the individual layers specified in the campaign recipes. The resulting variations in the compositions of the blended materials allow estimation of the risks of exceeding WACs and PCLs for each campaign. A critical subset of WACs/PCLs – NOx, NaK, AlFeZr, and S – are especially at risk of being exceeded in multiple campaigns. These analytes should be the focus of instrument development. We also have extracted the expected solid/supernate distribution for these analytes, which establishes important performance criteria for individual analytical methods. The BBI data also permits an understanding of the different chemical forms in which the analytes appear. Thus, the need to establish instrumental sensitivity to these forms can be gainfully addressed. Although concentrating on one specific application – the blending of tank waste - this approach should be generalizable for the analysis of other possible RTM applications for waste processing.
The proposed Direct Feed High Level Waste (DFHLW) approach for processing high-level tank waste at Hanford is intended to reduce processing time by bypassing the Pretreatment Facility and transferring waste directly from the tank farm to the WTP HLW vitrification facility. This processing strategy could reduce or eliminate the washing and leaching steps that would have occurred in the Pretreatment facility. Operation of the vitrification facility is subject to chemical and radiological limits protecting safety (e.g. Waste Acceptance Criteria, or WACs) and process quality (e.g. Process Control Limits, or PCLs). Without washing and leaching, there is a greater risk of exceeding the WACs and PCLs. Hanford process engineers have devised blending strategies based on known chemical and radiological composition, volumes, and solids loadings of individual layers within each waste tank. These blending campaigns succeed in predicting a processing strategy that does not exceed the WACs and PCLs. However, the calculations do not ascribe uncertainties to the tank analysis data, quantities of material taken from the tanks to make the blend, or potential for mixing of layers within tanks. In order to confirm that a process strategy is working, it would be advantageous to have inline or at-line analytical instrumentation installed in the processing facilities that deliver measurement results in real time.
A 3 in. x 3 in. NaI(Tl) gamma ray (0.3 to 10 MeV) spectrometer with a CsI(Na) charged particle and anti-Compton shield has been developed for the Orbiting Solar Observatory (OSO-7) which was launched September 30, 1971. The instrument, designed for a rotating wheel compartment, utilizes a 377 channel quadratic PHA with accumulation times of 3, 1, or 0.5 minutes. Quick look and calibration data obtained via a direct data link to a minicomputer allows near real time monitoring and control of the experiment. Various commands changing the operating mode can be executed. The functions which can be commanded include: rotation of the quadrants in which data is collected by 90 deg; gain adjustment of the central detector over a 6:1 range; manual or automatic sequencing of calibrations; variations of accumulation times by telemetering selected channels; and selection of reference directions. A small X-ray detector covering the range 7.5 to 120 keV is also included.
Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifidelity methods for multiple-input multiple-output linear regression targeting data-limited applications with high-dimensional outputs. Multifidelity methods integrate many inexpensive low-fidelity model evaluations with limited, costly high-fidelity evaluations. We introduce two projection-based multifidelity linear regression approaches with linear and nonlinear features that leverage principal component basis vectors for dimensionality reduction and combine multifidelity data through: (i) a direct data augmentation using low-fidelity data, and (ii) a data augmentation incorporating explicit linear corrections between low-fidelity and high-fidelity data. The data augmentation approaches combine high-fidelity and low-fidelity data into a unified training set and train the linear regression model through weighted least squares with fidelity-specific weights. We introduce a proximity-based weighting scheme with automatic weight selection strategy through cross-validation. Here, the proposed multifidelity linear regression methods are demonstrated on approximating the surface pressure field of a hypersonic vehicle in flight and the temperature field on an aircraft disc braking system. In an ultra low-data regime of no more than twelve high-fidelity samples, multifidelity linear regression achieves approximately 2% – 12% improvement in median accuracy and a higher R 2 score relative to single-fidelity methods at comparable computational cost.
The author has identified the following significant results. The multiplicative scale factor needed to calibrate the recorded intensity is obtained by fitting the measured curve against a brightness model. The model was converted to the multispectral band scanner signal. Inversion of this measured signature is shown as the profile of attenuation coefficients versus altitude. Because of Gaussian noise, data were not measured directly. Data were fit with two exponential curves, one covering the lower altitude and the other covering the higher altitude. A twenty point curve was derived by selecting a data point and plotting its value from each of twenty adjacent scans. Noise from the lower altitudes was found to be erratic.
A radiative transfer model is used to investigate how the error of spectral hemispherical reflectance data obtained from nadir reflectance values varies with wavelength, solar zenith angle, leaf area index, and leaf orientation distribution. Several techniques employing multiple off-nadir view angles taken in azimuth planes are found to accurately infer spectral hemispherical reflectances, and to be well suited to sensor systems that scan in a known azimuth plane or view fore and aft in a known azimuth plane. The effects of errors in hemispherical reflectance on terrestrial energy budget and productivity calculations is also considered.
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Integration of a supersonic inlet simulation with a computer aided design (CAD) system is demonstrated. The integration is performed using the Project Integration Architecture (PIA). PIA provides a common environment for wrapping many types of applications. Accessing geometry data from CAD files is accomplished by incorporating appropriate function calls from the Computational Analysis Programming Interface (CAPRI). CAPRI is a CAD vendor neutral programming interface that aids in acquiring geometry data directly from CAD files. The benefits of wrapping a supersonic inlet simulation into PIA using CAPRI are; direct access of geometry data, accurate capture of geometry data, automatic conversion of data units, CAD vendor neutral operation, and on-line interactive history capture. This paper describes the PIA and the CAPRI wrapper and details the supersonic inlet simulation demonstration.
In this paper we demonstrate direct data streaming from instruments and detectors at a large-scale experimental facility to a supercomputer for real-time data processing and feedback. Streaming data to supercomputers introduces the potential for novel scientific applications and workflow models, including the ability to provide real-time feedback from very large datasets during an experiment and the integration of real-time ML training and inference at scale. We discuss a successful demonstration for real-time processing of data from the Advanced Photon Source (APS) on the Polaris supercomputer using an EPICS-based streaming framework. We describe the capabilities of the streaming framework itself, and outline the architecture that allows us to process experimentally derived data on a supercomputer without file-based data transfers. We present throughput measurements that are indicative of system performance capable of sustaining the expected data production rates of the facility, as well as discuss some outstanding challenges and our future directions.
Direct numerical simulations (DNS) of turbulent flows provide a complete data base to develop and to test turbulence models. In this article, the progress made in developing models for the dissipation rate equation is reviewed. New scaling arguments for the various terms in the dissipation rate equation were tested using data from DNS of homogeneous shear flows. Modifications to the epsilon-equation model that take into account near-wall effects were developed using DNS of turbulent channel flows. Testing of new models for flows under mean compression was carried out using data from DNS of isotropically compressed turbulence. In all of these studies the data from the simulations was essential in guiding the model development. The next generation of DNS will be at higher Reynolds numbers, and will undoubtedly lead to improved models for computations of flows of practical interest.
Scientific data visualization has finally come of age as an important and accepted discipline. While scientists have been using computer graphics to visualize experimental data and computational results for at least 30 years, recent improvements in cost/performance of graphics workstations, more readily available software, and a new-found identity based on the report "Visualization in Scientific Computing" (McCormick, DeFanti, and Brown, 1987) have solidified the discipline. The thesis here is that scientists are forced to work too hard to create these visualizations, but that the evolving set of visualization tools can greatly reduce the requisite effort. The architecture of a new class of software can lead to a more widespread availability of interactive visualization tools, which can make the process of creating a visualization as simple as doing interactive chart and graph layout.