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At least 1,459 records · Page 81

Measurements of K-edge and L-edge extended x-ray absorption fine structure at the national ignition facility (invited)

High-energy-density laser facilities and advances in dynamic compression techniques have expanded access to material states in the Terapascal regime relevant to inertial confinement fusion, planetary science, and geophysics. However, experimentally determining the material temperature in these extreme conditions has remained a difficult challenge. Extended X-ray Absorption Fine Structure (EXAFS), referring to the modulations in x-ray absorption above an absorption edge from photoelectrons’ interactions with neighboring atoms, has proven to be a versatile and robust technique for probing material temperature and density for mid-to-high Z elements under dynamic compression. The current platform at the National Ignition Facility has developed six configurations for EXAFS measurements between 7 and 18 keV for different absorption edges (Fe K, Co K, Cu K, Ta L3, Pb L3, and Zr K) using a curved-crystal spectrometer and a bright, continuum foil x-ray source. Here, in this work, we describe the platform geometry, x-ray source performance, spectrometer resolution and throughput, design considerations, and data in ambient and dynamic-compression conditions.

36 MATERIALS SCIENCE↗

Flow rate/pressure drop data gathered from testing a sample of the Space Shuttle Strain Isolation Pad (SIP): Effects of ambient pressure combined with tension and compression conditions

Tests were conducted on a sample of strain isolation pad (SIP) typical of that used in the shuttle orbiter thermal protection system to determine the characteristics of SIP internal flow. Data obtained were pressure drop as a function of flow rate for a range of ambient pressures representing various points along the Shuttle trajectory and for stretched and compressed conditions of the SIP. Flow was in the direction of the weave parallel to most of the fibers. The data are plotted in several standard engineering formats in order to be of maximum utility to the user. In addition to providing support to the Space Shuttle Program, these data are a source of experimental information on flow through fiberous (rather than the more usual sand bed type) porous media.

Springfield, R. D.↗

Simultaneous Observations of Traveling Convection Vortices: Ionosphere-Thermosphere Coupling

We present simultaneous observations of magnetosphere-ionosphere-thermosphere coupling over Svalbard during a traveling convection vortex (TCV) event. Various spaceborne and ground-based instruments made coordinated measurements, including magnetometers, particle detectors, an all-sky camera, European Incoherent Scatter (EISCAT) Svalbard Radar, Super Dual Auroral Radar Network (SuperDARN), and SCANning Doppler Imager (SCANDI). The instruments recorded TCVs associated with a sudden change in solar wind dynamic pressure. The data display typical features of TCVs including vortical ionospheric convection patterns seen by the ground magnetometers and SuperDARN radars and auroral precipitation near the cusp observed by the all-sky camera. Simultaneously, electron and ion temperature enhancements with corresponding density increase from soft precipitation are also observed by the EISCAT Svalbard Radar. The ground magnetometers also detected electromagnetic ion cyclotron waves at the approximate time of the TCV arrival. This implies that they were generated by a temperature anisotropy resulting from a compression on the dayside magnetosphere. SCANDI data show a divergence in thermospheric winds during the TCVs, presumably due to thermospheric heating associated with the current closure linked to a field-aligned current system generated by the TCVs. We conclude that solar wind pressure impulse-related transient phenomena can affect even the upper atmospheric dynamics via current systems established by a magnetosphere-ionosphere-thermosphere coupling process.

Kim, Hyomin↗

Data volume reduction for single-look polarimetric imaging radar data

An 8-b quantization scheme to reduce the data volume for single-look complex scattering matrix data measured by polarimetric imaging radar systems is described. The scattering matrices are not symmetrized before compression, thereby retaining information about background noise and system effects. The data volume is reduced by a factor of 3.2. It is shown, with measured data, that the signal to quantization noise ratio for the compression scheme is more than 35 dB for the cross-polarized channels, and more than 45 dB for the copolarized channels.

Van Zyl, Jakob J.↗

Investigation of the dilatational dissipation in compressible homogeneous shear flow

The dilatational dissipation rate within compressible homogeneous turbulent shear flow is studied using data from direct numerical simulations. It is found that the dilatational dissipation rate is mainly associated with large scale acoustic waves. Eddy shocklets are observed; however, they have little contribution to the average dissipation rate. A mechanism for the generation of eddy shocklets is shown to be the focusing of acoustic waves. Turbulence models for the dilatational dissipation rate are compared with data from the simulations. It is found that the formulation of Zeman used by Viegas & Rubesin to calculate a compressible mixing layer agrees well with the numerical simulation results for turbulent Mach numbers less than 0.3. However, it is also found that, for the Mach number range occurring in mixing layers, the model does not accurately represent the theory upon which it is based.

Blaisdell, G. A.↗

Lost Circulation Materials in Geothermal Drilling: Thermal Degradation, Viscosity, Compression, and Flow Loop Tests

This dataset provides a set of experimental data on the performance of lost circulation materials (LCMs) used in geothermal drilling operations. It includes results from four distinct tests: thermal degradation, viscosity measurements, compression tests, and high-temperature flow loop experiments. The materials tested, such as cedar fiber, cotton seed hulls, magma fiber, microcellulose, and sawdust, were analyzed under a range of conditions to assess their effectiveness in mitigating fluid losses in geothermal wells. Data on thermal degradation explores mass loss, water loss, and gas release for each material when subjected to temperatures between 90C and 250C. Viscosity measurements capture the behavior of LCM mixtures under different temperatures, while compression tests investigate the structural integrity of both undegraded and thermally degraded materials. The high-temperature flow loop experiments simulate geothermal well conditions, analyzing how different materials and mixtures affect fluid flow and sealing performance in a fractured reservoir environment. In addition to the experimental data, the dataset includes photos documenting the materials, schematics of test setups, and several published manuscripts that provide detailed insights into the experimental methods and findings.

15 GEOTHERMAL ENERGY↗

Torque Limit for Bolted Joint for Composites: TTTC Properties of Laminated Composites - Part A

The existing design code for torque limit of bolted joints for composites at Marshall Space Flight Center is MSFC-STD-486B, which was originally developed in 1960s for metallic materials. The theoretical basis for this code was a simplified mechanics analysis, which takes into account only the bolt, nut and washers, but not the structural members to be connected. The assumption was that metallic materials would not fail due to the bearing stress at the contact area between washer and the mechanical member. This is true for metallic materials; but for composite materials the results could be completely different. Unlike most metallic materials, laminated composite materials have superior mechanical properties (such as modulus and strength) in the in-plane direction, but not in the out-of-plane, or through-the-thickness (TTT) direction. During the torquing, TTT properties (particularly compressive modulus and compressive strength) play a dominant role in composite failure. Because of this concern, structural design engineers at Marshall are currently using a compromised empirical approach: using 50% of the torque value for composite members. Companies like Boeing is using a similar approach. An initial study was conducted last summer on this topic to develop theoretical model(s) that takes into consideration of composite members. Two simplified models were developed based on stress failure criterion and strain failure criterion, respective. However, these models could not be used to predict the torque limit because of the unavailability of material data, specifically, through-the-thickness compression (TTTC) modulus and strength. Therefore, the task for this summer is to experimentally determine the TTTC properties. Due to the time limitation, only one material has been tested: IM7/8552 with [0 degrees,plus or minus 45 degrees, 90 degree ] configuration. This report focuses the test results and their significance, while the experimentation will be described in a separate report by Mr. Kris Kostreva.

Zhao, Yi↗

A recursive technique for adaptive vector quantization

Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Lindsay, Robert A.↗

Energy balance and Alfvén Mach numbers in compressible magnetohydrodynamic turbulence with a large-scale magnetic field

Energy equipartition is a powerful theoretical tool for understanding astrophysical plasmas. It is invoked, for example, to measure magnetic fields in the interstellar medium (ISM), as evidence for small-scale turbulent dynamo action, and, in general, to estimate the energy budget of star-forming molecular clouds. Here, in this study, we motivate and explore the role of the volume-averaged root-mean-squared (rms) magnetic coupling term between the turbulent, δB , and large-scale, B 0 , fields, $\langle$(δB·B 0 ) 2 $\rangle$$_{V}^{1/2}$. By considering the second moments of the energy balance equations we show that the rms coupling term is in energy equipartition with the volume-averaged turbulent kinetic energy for turbulence with a sub-Alfvénic large-scale field. Under the assumption of exact energy equipartition between these terms, we derive relations for the magnetic and coupling term fluctuations, which provide excellent, parameter-free agreement with time-averaged data from 280 numerical simulations of compressible magnetohydrodynamic (MHD) turbulence. Furthermore, we explore the relation between the turbulent mean field and total Alfvén Mach numbers, and demonstrate that sub-Alfvénic turbulence can only be developed through a strong, large-scale magnetic field, which supports an extremely super-Alfvénic turbulent magnetic field. This means that the magnetic field fluctuations are significantly subdominant to the velocity fluctuations in the sub-Alfvénic large-scale field regime. Throughout our study, we broadly discuss the implications for observations of magnetic fields and understanding the dynamics in the magnetized ISM.

79 ASTRONOMY AND ASTROPHYSICS↗

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗

Reynolds number effects on the turbulence field in compressible boundary layers

Detailed experiments were conducted in a zero pressure gradient, supersonic turbulent boundary layer, including measurements of the three components of velocity fluctuations and the turbulent shear stress, for Reynolds numbers ranging from 11.7 million to 105 million at a freestream Mach number of 2.3. The mean flow measurements established the fully developed and equilibrium nature of the boundary layer. Measurements of the turbulence field show that the vertical and transverse fluctuations are essentially equal throughout the boundary layer at all Reynolds numbers, a feature that is different from observations in incompressible flows. The data show that the boundary layer exhibits similarity in the turbulence profiles for the entire Reynolds number range and agrees with previous compressible and incompressible data using Morkovin's scaling to account for compressibility effects.

Acharya, M.↗

Cognition at the Point of Sensing

Over the last 15 years, compressive sensing techniques have been developed which have the potential to greatly reduce the amount of data collected by systems while preserving the amount of information obtained. A cost of this efficiency is that a computationally-intensive optimization routine must be used to put the sensed data into a form that a person can interpret. At the same time, machine learning techniques have experienced tremendous growth as well. Machines have demonstrated the ability learn how to effectively perform tasks such as detection and classification at speeds much faster than humanly possible. Our goal in this project was to study the feasibility of using compressive sensing systems "at the edge." That is, how can compressive sensing sensors be deployed such that information is created at the remote sensor rather than sending raw data to a central processing location? Studies were performed to analyze whether machine learning could be done on the compressively sensed data in its raw form. If a machine is performing the task, is it possible to do so without putting the data into a human interpretable form? We show that this is possible for some systems, in particular a compressive sensing snapshot imaging spectrometer. Machine learning tasks were demonstrated to be more effective and more robust to noise when the machine learning algorithm worked on data in its raw form. This system is shown to outperform a traditional spectrometer. Techniques for reducing the complexity of the reconstruction routine were also analyzed. Techniques for such as data regularization, deep neural networks, and matrix completion were studied and shown to have benefits over traditional reconstruction techniques. In this project we showed that compressive sensing sensors are indeed feasible at the edge. As always, sensors and algorithms must be carefully tuned to work in the constrained environment. In this project we developed tools and techniques to enable those analyses.

47 OTHER INSTRUMENTATION↗

Overset grids in compressible flow

Numerical experiments have been performed to investigate the importance of boundary data handling with overset grids in computational fluid dynamics. Experience in using embedded grid techniques in compressible flow has shown that shock waves which cross grid boundaries become ill defined and convergence is generally degraded. Numerical boundary schemes were studied to investigate the cause of these problems and a viable solution was generated using the method of characteristics to define a boundary scheme. The model test problem investigated consisted of a detached shock wave on a 2-dimensional Mach 2 blunt, cylindrical body.

Eberhardt, S.↗

A control-oriented combustion model framework for compression ignition engines operating on low-reactivity fuel

This work focuses on zero-dimensional modeling of the heat release rate in a compression ignition engine operating on gasoline-like fuels. Due to the properties of gasoline, such as high volatility and longer ignition delay than diesel, the injection strategies can vary significantly from the operation with conventional diesel fuel. Different injection strategies are commonly used to achieve varying degrees of in-cylinder stratification in order to shape the combustion event and maximize efficiency. The proposed zero-dimensional combustion model was developed to account for the different stages in combustion caused by the fuel stratification. As the ignition delay model is an integral part of the entire combustion process and significantly affects the prediction accuracy, special attention has been paid to local phenomena influencing ignition delay. A one-dimensional spray model by Musculus and Kattke was employed in conjunction with a Lagrangian tracking approach in order to estimate the local air–fuel ratio within the spray tip, as a proxy for reactivity. The local air–fuel ratio, in-cylinder temperature and pressure were used in an integral fashion to estimate the ignition delay. Heat release rates were modeled using first-order non-linear differential equations. The proposed combustion model was validated against experimental data of a heavy-duty compression ignition engine with up to three injection events at mostly 1038 r/min and 14 bar brake mean effective pressure. Further validation of the model was carried out at other engine loads and speeds. Model prediction errors in CA50 of less than 1 °CA across all conditions were found. Modeling results of other combustion metrics such as combustion duration and indicated mean effective pressure are also highly satisfactory. In addition, the model has been shown to be capable of estimating the ringing intensity for most conditions.

Pamminger, Michael↗

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗

Recent development in the design, testing and impact-damage tolerance of stiffened composite panels

Structural technology of laminated filamentary-composite stiffened-panel structures under combined inplane and lateral loadings is discussed. Attention is focused on: (1) methods for analyzing the behavior of these structures under load and for determining appropriate structural proportions for weight-efficient configurations; and (2) effects of impact damage and geometric imperfections on structural performance. Recent improvements in buckling analysis involving combined inplane compression and shear loadings and transverse shear deformations are presented. A computer code is described for proportioning or sizing laminate layers and cross-sectional dimensions, and the code is used to develop structural efficiency data for a variety of configurations, loading conditions, and constraint conditions. Experimental data on buckling of panels under inplane compression is presented. Mechanisms of impact damage initiation and propagation are described.

Williams, J. G.↗

Progressive Damage Analysis of Post-Buckled Stiffened Panels under Static Compressive Loading

The validation of progressive damage analysis methods requires experimental data that captures the initiation of damage, its evolution with continued loading, and the morphology of damage throughout its evolution. In support of the NASA Advanced Composites Project, several validation specimens of increasing complexity have been tested and characterized in order to provide the data required to assess the capabilities of several progressive damage analysis methods for fiber-reinforced composite materials. The analytical capabilities of interest for this validation program include networks of interacting matrix cracks and delaminations in post-buckled stiffened structures. A series of single stringer compression specimens was tested and characterized at NASA Langley Research Center. The experimental data from these tests are compared with progressive damage finite element analysis results. Test/analysis comparisons are made in terms of load/displacement histories, damage morphology, and damage size versus load metrics.

Frank A Leone↗