Site C1 UTD Sonic Anemometer / Processed Data
This dataset contains processed data from the Site C1 UTD Sonic Anemometer.
17 WIND ENERGY↗
SEARCH · Search NASA
Results for “Processed sonic”
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.
Tower - TTU (SWiFT) Tower, All levels - Processed Data
This dataset includes processed sonic anemometer measurements at the 200-m SWIFT tower near Lubbock, Texas on July 4, 2012. Observations are of a canonical convective atmospheric boundary layer. Subgrid stresses and fluxes are computed by subtracting 15-min running average from the signals measured at 1 Hz.
17 WIND ENERGY↗
Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves
Ultrasonic transmission is sensitive to the spatial variation in mechanical properties of materials due to the presence of cracks/fractures. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-informed unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing. Novelty of the work involves the assignment of both statistically consistent and physically consistent clusters to the measurements of shear waveforms acquired across the one axial and two frontal planes. Physically consistent/relevant information is incorporated by considering the travel time of the peak of spectral energy and transmission coefficient of the transmitted waveform. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. Finally, the proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.
42 ENGINEERING↗
Utah FORGE: Well 16B(78)-32 Logs from Schlumberger Technologies
This dataset is a collection of well logs provided by Schlumberger Technologies from the Utah FORGE well 16B(78)-32 drilling project. Information here includes critical borehole information collected by an ultrasonic borehole imager (UBI) and a fullbore formation microimager (FMI). Well 16B(78)-32 serves as the production well for reservoir creation, fluid circulation, and demonstration of heat extraction for the FORGE project. It has been drilled as a doublet approximately 300 feet parallel to and above the injection well 16A(78)-32. The total depth measured 10,947 feet and the vertical depth measured 8,357 feet.
11.5 inch intermediate casing logs↗
Lidar - UT-Dallas WindCube 200S Doppler Lidar - Processed Data
fixed scan against southeast sonic of 50m, 100m and 150m and supersite at 60m height
17 WIND ENERGY↗
Finite Element Simulation of the Acoustic Pressure Inside a Beverage Container for Non-Thermal, Ultrasound-based Pasteurization
The purpose of this effort is to investigate whether large acoustic pressure waves can be transmitted inside beverage containers to enable pasteurization. Acoustic waves are known to induce large nonlinear compressive forces and shock waves in fluids, suggesting that compression waves may be capable of damaging bacteria inside beverage containers without appreciably increasingly the temperature or altering the freshness and flavor of the beverage contents. Although a combined process such as thermosonication (e.g., sonication with heating) is likely more efficient, it is instructive to compute the acoustic pressure field distribution inside the beverage container. The COMSOL simulations used two and three-dimensional models of beverage containers placed in a water bath to compute the acoustic pressure field. A limitation of these COMSOL models is that they cannot determine the bacterial lysis efficiency, rather the models provide an indirect metric of bacterial lysis based on the magnitude of the pressure field and its distribution.
42 ENGINEERING↗
Deployment of inference as a service at the US CMS Tier-2 data centers
Coprocessors, especially GPUs, will be a vital ingredient of data production workflows at the HL-LHC. At CMS, the GPU-as-a-service approach for production workflows is implemented by the SONIC project (Services for Optimized Network Inference on Coprocessors). SONIC provides a mechanism for outsourcing computationally demanding algorithms, such as neural network inference, to remote servers, where requests from multiple clients are intelligently distributed across multiple GPUs by a load-balancing service. This talk highlights the recent progress in deploying SONIC at selected U.S. CMS Tier-2 data centers. Using realistic CMS Run3 data processing workflows, such as those containing transformer-based algorithms, we demonstrate how SONIC is integrated into the production-like environment to enable accelerated inference offloading. We will present developments from both the client and server sides, including production job and data center configurations for NVIDIA and AMD GPUs. We will also present performance scaling benchmarks and discuss the challenges of operating SONIC in CMS production, such as server discovery, GPU saturation, fallback server logic, etc.
Holzman, Burt↗
Structural insights into self-assembly of a slow-evolving and mechanically robust supramolecular gel via time-resolved small-angle neutron scattering
The current time-resolved SANS study captures different stages of self-assembly process commencing from nucleation as a function of sonication.
Mirzamani, Marzieh↗
UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 8 - Raw Data
Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.
17 WIND ENERGY↗
UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 9 - Raw Data
Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.
17 WIND ENERGY↗
Arctic Black Carbon Aerosol Deposition Study North Slope of Alaska 2020- Sonic Anemometer Measurements
Particles are removed from the atmosphere through both wet and dry deposition. These processes are poorly understood, though they constitute important uncertainties in climate and air quality models. This project aims to use observational constraints on particle fluxes to improve model representations of dry deposition. Within this data set, we measured wind properties using a sonic anemometer. Measurements were made at the meteorological tower between 9 Sept and 25 Oct 2021. This site is a coastal tundra location, and received snow during the project.
Gill Windmaster 3D Ultrasonic Anemometer↗
Utah FORGE Well 78B-32 Daily Drilling Reports and Logs
This data set includes the daily drilling reports and Pason data for well 78B-32 and Schlumberger logs acquired after drilling completion. This well was drilled between June 27th and July 31st of 2021. Also included is raw and processed data for a variety of well data metrics including temperature, porosity, density, and sonic data. This data was taken at the Utah FORGE site as part of the Utah FORGE project.
15 GEOTHERMAL ENERGY↗
In situ probing of structure and deagglomeration of SnO 2 colloids via small-angle X-ray scattering
Transforming dry nanopowders into stable colloidal dispersions remains challenging due to the cohesive forces between the nanoparticles (NPs) which promote agglomeration. Effective dispersion and deagglomeration of these agglomerates is a critical process in the formulation and preparation of nanoparticle-based functional materials via the colloidal route. Understanding the deagglomeration dynamics provides information to improve microstructural quality in various applications by enabling engineering of agglomerate size, structure and morphology. However, the deagglomeration process dynamics with respect to the evolution of the fractal agglomerate structures, particularly for very small NPs, is still poorly understood and requires further investigation. This study employs in situ small-angle X-ray scattering (SAXS) to investigate the sonication-induced deagglomeration of SnO 2 NPs. Electrostatically stabilized SnO 2 colloids with varying primary particle size (6–21 nm) are investigated in a specifically designed in situ cell using synchrotron-based SAXS to study the influence of sonication time and intensity on the nanoscaled agglomerates. Complete structural analysis via SAXS reveals a direct correlation between changes in agglomerate size and structure, size-dependent deagglomeration behavior and a dependence on the overall energy introduced during sonication into the dispersion regardless of the actual power as well as ultrasonic process parameters in case of SnO 2 NPs. The results suggest that control of the dispersion process during ultrasonic deagglomeration results in tailoring agglomerates with respect to size and structure.
Deagglomeration↗
GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments
Machine learning algorithms are becoming increasingly prevalent and performant in the reconstruction of events in accelerator-based neutrino experiments. These sophisticated algorithms can be computationally expensive. At the same time, the data volumes of such experiments are rapidly increasing. The demand to process billions of neutrino events with many machine learning algorithm inferences creates a computing challenge. We explore a computing model in which heterogeneous computing with GPU coprocessors is made available as a web service. The coprocessors can be efficiently and elastically deployed to provide the right amount of computing for a given processing task. With our approach, Services for Optimized Network Inference on Coprocessors (SONIC), we integrate GPU acceleration specifically for the ProtoDUNE-SP reconstruction chain without disrupting the native computing workflow. With our integrated framework, we accelerate the most time-consuming task, track and particle shower hit identification, by a factor of 17. This results in a factor of 2.7 reduction in the total processing time when compared with CPU-only production. For this particular task, only 1 GPU is required for every 68 CPU threads, providing a cost-effective solution.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Environmentally improved CdTe photovoltaic recycling through novel technologies and facility location strategies
Abstract Photovoltaic waste is projected to reach up to 78 million tons across globally dispersed locations through 2050. Current recycling infrastructure is inadequate to process these waste volumes responsibly. This necessitates commercializing novel, environmentally advantageous photovoltaic recycling technologies that improve upon incumbent industrial operations. CdTe photovoltaic recycling is a promising candidate for improvements as 25,000 tons of spent modules are recycled worldwide annually. This paper evaluates the operational performance and compares six novel technologies, the incumbent technology used in industry and one technology which extends the incumbent process across ten environmental impact categories. The tradeoff between incurring a transportation burden (ship or road) to recycle in a large‐scale centralized facility with a higher operational efficiency and avoiding transportation by recycling in a small‐scale decentralized facility with a lower operational efficiency is evaluated. Thermal delamination to eliminate the ethylene vinyl acetate and separate the photovoltaic glass panels is preferable to the incumbent mechanical process across nine environmental impact categories and decreases the climate‐change impact of CdTe photovoltaic recycling by 23%. Bath and probe sonication are ineffective for delamination, and the use of organic solvents is more environmentally burdensome than the incumbent mechanical process. Centralized recycling with shipping is environmentally preferable than with road‐based transportation. For every 100‐km increase in road transportation from the decentralized to the centralized facility, the inventory requirement in the centralized facility should be 6% lower than the decentralized facility for centralized recycling to have a lower climate‐change impact than decentralized recycling. The corresponding value for shipping is 0.4%.
Ravikumar, Dwarakanath↗
Novel Ionomers and electrode structures for improved PEMFC electrode performance at low PGM loadings (Final Report)
In this project, the objective is to develop new ORR electrocatalysts on optimized supports which can exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001412 directly relevant to the subtopic. This project’s approach is to develop novel, electrode-specific ionomers, and integrate them with state-of-the-art NSTF electrocatalyst powder to develop a cathode electrode achieving >= 044 A/mg PGM mass activity, <=30% mass activity loss during metal cycling, and <=0.125 g PGM /kW performance under DOE testing protocols. Ionomer O 2 permeability and proton conductivity will be increased by up to 1.5X over the baseline 3M800 perfluorosulfonate (PFSA) ionomer to enhance cathode electrode performance. Integration of cathode NSTF powder into an ionomer-containing electrode will increase the surface enhancement factor (SEF) to >=40 cm 2 PGM /cm 2 GEO allowing NSTF containing cathodes to exceed DOE MEA robustness targets. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of significant findings, conclusions, and developments over the entire project period from Oct. 1 st 2016 – Jan. 31 st 2020. This work has overcome key operation robustness issues with classic NSTF electrodes, identified pathways to improved dispersed and dispersed NSTF cathode performance, developed novel ionomers with high bulk conductivity and oxygen permeability, demonstrated exceptional support-independent electrode activity, and significantly increased metal and support stability through ionomer development. At this point, Tufts, MTU and all 5 FCPAD national labs have been involved, and contributed to, the improvements, learning and achievements of this work. Over the course of this project, more than 50 grams of dispersed NSTF powder in 15 different configurations have been generated, paving the way for scaleup within 3M. These whiskers have been processed in multiple ways, including acid leaching, powder-annealed, and sonicated by various means. For Task 2, 27 different types of ionomers were tested, 19 of which were made for the first time during the course of this project. 377 electrode inks with both NSTF and metal-on-carbon catalysts with I/C ratios from 0.2 to 1.2 were generated and mostly coated on a 3M pilot manufacturing line resulting in more than 700 different electrode types.
08 HYDROGEN↗
Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service
Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗