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At least 163 records · Page 9

Packaging HEP Heterogeneous Mini-apps for Portable Benchmarking and Facility Evaluation on Modern HPCs

High Energy Physics (HEP) experiments are making increasing use of GPUs and GPU dominated High Performance Computer facilities. Both the software and hardware of these systems are rapidly evolving, creating challenges for experiments to make informed decisions as to where they wish to devote resources. In its first phase, the High Energy Physics Center for Computational Excellence (HEP-CCE) produced portable versions of a number of heterogeneous HEP mini-apps, such as \ptor, FastCaloSim, Patatrack and the WireCell Toolkit, that exercise a broad range of GPU characteristics, enabling cross platform and facility benchmarking and evaluation. However, these mini-apps still require a significant amount of manual intervention to deploy on a new facility. We present our work in developing turn-key deployments of these mini-apps, where by means of containerization and automated configuration and build techniques such as Spack, we are able to quickly test new hardware, software, environments and entire facilities with minimal user intervention, and then track performance metrics over time.

Atif, Mohammad [Brookhaven] (ORCID:000000026889770↗

Controlling TV-Camera f-Stop Remotely

Lens opening of television camera controlled manually from remote location by simple and inexpensive data link without modifications to camera lens system. Allows closeup views of wide-brightness-range events otherwise hazardous for human operator.

Talley, G. L., Jr.↗

Boundary Representation Tolerance Impacts on Mesh Generation and Adaptation

The control of discretization error is critical to obtaining reliable simulation results. Re-cent progress has matured anisotropic mesh adaptation, which automates discretization error control for complex geometries. However, the meshing process can fail when geometric model Boundary REPresentation (BREP) tolerances are larger than boundary layer surface nor-mal and tangential spacing requirements. Geometry sources are often created in Mechanical Computer-Aided Design (MCAD) systems, which are designed to produce models for manufacturing and not the stricter requirements of viscous flow analysis. BREP tolerances are strained by three factors: the inherent complexity of the model (e.g., large range of scales and complex topology), the numerical difficulties arising from surface/surface intersections, and the omission of crucial data during export and translation. Manual preparation of geometry is commonly employed to enable expert-guided mesh generation, which severely inhibits work-flow automation. Accommodation of loose BREP tolerances is required for automated mesh processes, because barrier issues may not be detected until well into the solution process. To raise awareness of this class of geometry issues and their impact on simulation, a survey of these barrier issues is presented with example mitigation techniques. This awareness may also impact geometry creation workflows to prevent the introduction of these artifacts.

CAD↗

Temporal Wind Pairs for Space Launch Vehicle Capability Assessment and Risk Mitigation

Space launch vehicles incorporate upper-level wind assessments to determine wind effects on the vehicle and for a commit to launch decision. These assessments make use of wind profiles measured hours prior to launch and may not represent the actual wind the vehicle will fly through. Uncertainty in the winds over the time period between the assessment and launch introduces uncertainty in assessment of vehicle controllability and structural integrity that must be accounted for to ensure launch safety. Temporal wind pairs are used in engineering development of allowances to mitigate uncertainty. Five sets of temporal wind pairs at various times (0.75, 1.5, 2, 3 and 4-hrs) at the United States Air Force Eastern Range and Western Range, as well as the National Aeronautics and Space Administration's Wallops Flight Facility are developed for use in upper-level wind assessments on vehicle performance. Historical databases are compiled from balloon-based and vertically pointing Doppler radar wind profiler systems. Various automated and manual quality control procedures are used to remove unacceptable profiles. Statistical analyses on the resultant wind pairs from each site are performed to determine if the observed extreme wind changes in the sample pairs are representative of extreme temporal wind change. Wind change samples in the Eastern Range and Western Range databases characterize extreme wind change. However, the small sample sizes in the Wallops Flight Facility databases yield low confidence that the sample population characterizes extreme wind change that could occur.

Decker, Ryan K.↗

Temporal Wind Pairs for Space Launch Vehicle Capability Assessment and Risk Mitigation

Space launch vehicles incorporate upper-level wind assessments to determine wind effects on the vehicle and for a commit to launch decision. These assessments make use of wind profiles measured hours prior to launch and may not represent the actual wind the vehicle will fly through. Uncertainty in the winds over the time period between the assessment and launch introduces uncertainty in assessment of vehicle controllability and structural integrity that must be accounted for to ensure launch safety. Temporal wind pairs are used in engineering development of allowances to mitigate uncertainty. Five sets of temporal wind pairs at various times (0.75, 1.5, 2, 3 and 4-hrs) at the United States Air Force Eastern Range and Western Range, as well as the National Aeronautics and Space Administration's Wallops Flight Facility are developed for use in upper-level wind assessments on vehicle performance. Historical databases are compiled from balloon-based and vertically pointing Doppler radar wind profiler systems. Various automated and manual quality control procedures are used to remove unacceptable profiles. Statistical analyses on the resultant wind pairs from each site are performed to determine if the observed extreme wind changes in the sample pairs are representative of extreme temporal wind change. Wind change samples in the Eastern Range and Western Range databases characterize extreme wind change. However, the small sample sizes in the Wallops Flight Facility databases yield low confidence that the sample population characterizes extreme wind change that could occur.

Decker, Ryan K.↗

Operating manual: Fast response solar array simulator

The fast response solar array simulator (FRSAS) is a universal solar array simulator which features an AC response identical to that of a real array over a large range of DC operating points. In addition, short circuit current (I sub sc) and open circuit voltage (V sub oc) are digitally programmable over a wide range for use not only in simulating a wide range of array sizes, but also to simulate (I sub sc) and (V sub oc) variations with illumination and temperature. A means for simulation of current variations due to spinning is available. Provisions for remote control and monitoring, automatic failure sensing and warning, and a load simulator are also included.

Vonhatten, R.↗

The ERTS-1 investigation (ER-600). Volume 4: ERTS-1 range analysis

The Range Analysis Team conducted an investigation to determine the utility of using LANDSAT 1 data for mapping vegetation-type information on range and related grazing lands. Two study areas within the Houston Area Test Site (HATS) were mapped to the highest classification level possible using manual image interpretation and computer aided classification techniques. Rangeland was distinguished from nonrangeland (water, urban area, and cropland) and was further classified as woodland versus nonwoodland. Finer classification of coastal features was attempted with some success in differentiating the lowland zone from the drier upland zone. Computer aided temporal analysis techniques enhanced discrimination among nearly all the vegetation types found in this investigation.

Erb, R. B.↗

Lightweight Right-Angle Valve For Cryogenics

Lightweight right-angle valve isolates pressurized liquid or gas stream from vacuum over wide range of temperatures from ambient down to cryogenic. Sized to fit tubes of types ordinarily used in cryogenic equipment. Maintains isolation, without need for manual adjustment of packing gland as pressure and temperature vary. Mass of valve less than 60 grams. Made of off-the-shelf parts and few simple custom-machined parts.

Calhoun, Richard B.↗

Development of Turbulence-Measuring Equipment

Hot wire turbulence-measuring equipment has been developed to meet the more stringent requirements involved in the measurement of fluctuations in flow parameters at supersonic velocities. The higher mean speed necessitates the resolution of higher frequency components than at low speed, and the relatively low turbulence level present at supersonic speed makes necessary an improved noise level for the equipment. The equipment covers the frequency range from 2 to about 70,000 cycles per second. Constant-current operation is employed. Compensation for hot-wire lag is adjusted manually using square-wave testing to indicate proper setting. These and other features make the equipment adaptable to all-purpose turbulence work with improved utility and accuracy over that of older types of equipment. Sample measurements are given to demonstrate the performance.

Kovasznay, Leslie S G↗

Acousto-ultrasonics to Assess Material and Structural Properties

This report was created to serve as a manual for applying the Acousto-Ultrasonic NDE method, as practiced at NASA Glenn, to the study of materials and structures for a wide range of applications. Three state of the art acousto-ultrasonic (A-U) analysis parameters, ultrasonic decay (UD) rate, mean time (or skewing factor, "s"), and the centroid of the power spectrum, "f(sub c)," have been studied and applied at GRC for NDE interrogation of various materials and structures of aerospace interest. In addition to this, a unique application of Lamb wave analysis is shown. An appendix gives a brief overview of Lamb Wave analysis. This paper presents the analysis employed to calculate these parameters and the development and reasoning behind their use. It also discusses the planning of A-U measurements for materials and structures to be studied. Types of transducer coupling are discussed including contact and non-contact via laser and air. Experimental planning includes matching transducer frequency range to material and geometry of the specimen to be studied. The effect on results of initially zeroing the DC component of the ultrasonic waveform is compared with not doing so. A wide range of interrogation problems are addressed via the application of these analysis parameters to real specimens is shown for five cases: Case 1: Differences in density in [0] SiC/RBSN ceramic matrix composite. Case 2: Effect of tensile fatigue cycling in [+/-45] SiC/SiC ceramic matrix composite. Case 3: Detecting creep life, and failure, in Udimet 520 Nickel-Based Super Alloy. Case 4: Detecting Surface Layer Formation in T-650-35/PMR-15 Polymer Matrix Composites Panels due to Thermal Aging. Case 5: Detecting Spin Test Degradation in PMC Flywheels. Among these cases a wide range of materials and geometries are studied.

Kautz, Harold E.↗

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Tan, Bin↗

Results of the Aerosol Sampling Experiment on the International Space Station

The indoor air quality of the International Space Station (ISS), in terms of particulate matter, has been assessed through a sampling experiment that collected airborne debris for return to Earth. The Aerosol Sampling Experiment took place on ISS in December 2016 and January 2017, with sample return in February 2017. For redundancy, two different aerosol samplers collected particles in two size ranges spanning from 10 nm to hundreds of micrometers. Multiple analysis techniques have been used to characterize the particles, such as reflective light microscopy, manual scanning electron microscopy (SEM) analysis (secondary and backscattered imaging) with energy dispersive spectroscopy (EDS) x-ray analysis, computer controlled scanning electron microscopy (CCSEM) and Raman spectroscopy. Sampling took place in five locations on ISS, with the greatest deposition of particles in Node 3, followed by Node 1, the US Lab and Node 2. The PMM had very few airborne particles, as expected, owing to the lack of human presence. A large proportion of the sampled material consisted of fibers from clothing. Many particles had complex morphologies or contained multiple metals in a carbonaceous matrix. Metal particles were analyzed for each sampling location in terms of both weight and number percent, with 27 heavy metals detected. Fiberglass and TiO2 particles were present in every location. Quantitative analysis results are presented, and where possible, particle emission sources are identified with the intention to fuel discussions on mitigation.

Meyer, Marit E.↗

Prediction of Turbulence-Generated Noise in Unheated Jets: JeNo Users' Manual (Version 1.0) - Part 2

JeNo (Version 1.0) is a Fortran90 computer code that calculates the far-field sound spectral density produced by axisymmetric, unheated jets at a user specified observer location and frequency range. The user must provide a structured computational grid and a mean flow solution from a Reynolds-Averaged Navier Stokes (RANS) code as input. Turbulence kinetic energy and its dissipation rate from a k-epsilon or k-omega turbulence model must also be provided. JeNo is a research code, and as such, its development is ongoing. The goal is to create a code that is able to accurately compute far-field sound pressure levels for jets at all observer angles and all operating conditions. In order to achieve this goal, current theories must be combined with the best practices in numerical modeling, all of which must be validated by experiment. Since the acoustic predictions from JeNo are based on the mean flow solutions from a RANS code, quality predictions depend on accurate aerodynamic input.This is why acoustic source modeling, turbulence modeling, together with the development of advanced measurement systems are the leading areas of research in jet noise research at NASA Glenn Research Center.

Khavaran, Abbas↗

Consist v0.1.0

A Python library for provenance tracking, intelligent caching, and data virtualization in scientific simulation workflows. It automatically records code, configuration, and input data to skip redundant computations and enables querying results across many runs without manual bookkeeping. Designed to support multi-model simulation workflows like the BEAM CORE toolset at LBL, but designed to be extensible to a wide range of research workflows. Combines lineage tracking features as provided by OpenLineage with deterministic hashing like SnakeMake, and adds powerful analysis tools on model outputs.

Needell, Zachary [Lawrence Berkeley National Labor↗

Land classification of south-central Iowa from computer enhanced images

The author has identified the following significant results. Enhanced LANDSAT imagery was most useful for land classification purposes, because these images could be photographically printed at large scales such as 1:63,360. The ability to see individual picture elements was no hindrance as long as general image patterns could be discerned. Low cost photographic processing systems for color printings have proved to be effective in the utilization of computer enhanced LANDSAT products for land classification purposes. The initial investment for this type of system was very low, ranging from $100 to $200 beyond a black and white photo lab. The technical expertise can be acquired from reading a color printing and processing manual.

Lucas, J. R.↗

Tool Support for Parametric Analysis of Large Software Simulation Systems

The analysis of large and complex parameterized software systems, e.g., systems simulation in aerospace, is very complicated and time-consuming due to the large parameter space, and the complex, highly coupled nonlinear nature of the different system components. Thus, such systems are generally validated only in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. We have addressed the factors deterring such an analysis with a tool to support envelope assessment: we utilize a combination of advanced Monte Carlo generation with n-factor combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. Additional test-cases, automatically generated from models (e.g., UML, Simulink, Stateflow) improve the coverage. The distributed test runs of the software system produce vast amounts of data, making manual analysis impossible. Our tool automatically analyzes the generated data through a combination of unsupervised Bayesian clustering techniques (AutoBayes) and supervised learning of critical parameter ranges using the treatment learner TAR3. The tool has been developed around the Trick simulation environment, which is widely used within NASA. We will present this tool with a GN&C (Guidance, Navigation and Control) simulation of a small satellite system.

Schumann, Johann↗

Propagation predictions for the HF-range by the Research Institute of the Deutsche Bundespost

Long term and short term HF propagation prediction service is described. The long term prediction method is computer based. The short term prediction method is still a manual method which relies mainly on a number of continuous field strength recordings and on the forecaster's ability to interpret the recordings and to combine this information with all available solar-geophysical data. Examples of the predictions are given and are compared with actually observed HF propagation conditions.

Damboldt, T.↗

Digital holography for real-time non-invasive monitoring of larval fish at power plant intakes

Effective evaluation of technological and operational approaches to reduce entrainment of marine organisms at cooling water intake structures (CWIS) requires accurate organism-sensing systems. Current detection methods lead to large temporal data gaps, require tedious manual analysis, and are fatal to organisms. In this report we describe integrating deep learning with a non-lethal, non-intrusive imaging method—digital holography—to rapidly detect fish larvae. Laboratory experiments demonstrated that the instrument could successfully image fish larvae at flow rates exceeding ranges seen in CWIS. Holograms of two fish larvae species, in the presence of bubbles and detritus, were collected to build a large database for training a lightweight convolutional neural network. The model achieves 97% extraction accuracy in quantifying larvae, and distinguishing them from other particles, including detritus and bubbles, when applied to a dataset of manually classified images, exceeding previous metrics for non-lethal, accurate, and real-time detection. These results demonstrate the potential of in situ holographic imaging for monitoring endangered larval fish species at power plant intake structures, and for high-fidelity, real-time applications in monitoring aquatic ichthyoplankton.

endangered species↗