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At least 1,045 records · Page 58

Sliced-Inverse-Regression--Aided Rotated Compressive Sensing Method for Uncertainty Quantification

Compressive-sensing-based uncertainty quantification methods have become a pow- erful tool for problems with limited data. In this paper, we use the sliced inverse regression (SIR) method to provide an initial guess for the alternating direction method, which is used to enhance sparsity of the Hermite polynomial expansion of stochastic state variables. The sparsity improvement increases both the efficiency and accuracy of the compressive-sensing-based uncertainty quantification method. We demonstrate that the initial guess from SIR is more suitable for the cases when the available data is very limited (Algorithm 4). We also propose another algorithm (Algorithm 5) that performs dimension reduction first with sliced inverse regression, then constructs a Hermite polynomial expansion of the reduced model. This method allows us to approximate the statistics accurately with even less available data. Both methods are non-intrusive and require no a priori information of the sparsity of the system. We demonstrate the effectiveness of these two methods (Algorithms 4 and 5) using problems with up to 500 random dimensions.

Yang, Xiu↗

RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data

In modern science, big data plays an increasingly important role. Many scientific applications, such as running simulations on supercomputers or conducting experiments on advanced instruments, produce huge amount of data at unprecedented speed. Analyzing and understanding such big data is the key for scientists to make scientific breakthroughs. However, data might become unavailable for scientists to access when outages or maintenance of the storage system occur, which severely hinders scientific discovery. To improve the data availability, data duplication and erasure coding (EC) are often used. But as the scientific data gets larger, using these two methods can cause considerable storage and network overhead.In this paper, we propose RAPIDS, a hybrid approach that combines the multigrid-based error-bounded lossy compression with erasure coding, to significantly reduce the storage and network overhead required for maintaining high data availability. Our experiments show that RAPIDS reduces the storage overhead by up to 7.5x and network overhead by up to 3x to achieve the same level of availability compared to the regular EC method. We improve RAPIDS by building two models to optimize the fault tolerance configurations and data gathering strategy. We demonstrate that RAPIDS significantly improves performance when running on many CPU cores in parallel or on GPUs.

Wan, Lipeng↗

Real Time implementation of Artificial Intelligence compression algorithm for High-Speed Streaming Readout signals

The new generation of high-energy physics experiments plans to acquire data in streaming mode. With this approach, it is possible to access the information of the whole detector (organized in time slices) for optimal and lossless triggering of data acquisitions. With this approach, data rates, especially in large detectors, are often very high, and the network is likely to be the bottleneck for the entire Streaming Read Out system. The aim of this work is to study the implementation of a lossy compression algorithm based on Artificial Intelligence: an Autoencoder. With Machine Learning it is possible to achieve a high compression ratio and fast inference time with only a small degradation of the signals, almost negligible for the specific application. This work explores different configurations of the Autoencoder and the implementation on different hardware. Different Autoencoder configurations are explored to find the best trade-off between compression ratio and reconstruction loss, both for signals and energy spectrum. Different hardware implementations are also explored to find the best platform to achieve real-time performance for the specific application.

Rossi, Fabio (ORCID:0009000385713885)↗

Structural and electronic properties of GaAs and GaP semiconductors

The Structural and Electronic properties of Zinc Blende phase of GaAs and GaP compounds are studied using self consistent SIESTA-code, pseudopotentials and Density Functional Theory (DFT) in Local Density Approximation (LDA). The Lattice Constant, Equillibrium Volume, Cohesive Energy per pair, Compressibility and Band Gap are calculated. The band gaps calcultated with DFT using LDA is smaller than the experimental values. The P-V data fitted to third order Birch Murnaghan equation of state provide the Bulk Modulus and its pressure derivatives. Our Structural and Electronic properties estimations are in agreement with available experimental and theoretical data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-fidelity micro-scale modeling of the thermo-visco-plastic behavior of carbon fiber polymer matrix composites

An experimentally validated micro-scale analysis of the visco-thermo-mechanical behavior of polymer matrix composites under different loads is proposed. A new constitutive law for the matrix material is developed taking into account the pressure dependence of the material as well as strain-rate and temperature dependence. Capturing the matrix behavior under multi-axial stress states is concluded to be essential to accurately predict the composite material behavior, even when considering simple load cases such as transverse compression and/or shear. Without any calibration procedure at the composite level, good agreement with the experimental data is observed for different loading conditions, including strain-rate dependency. Using this validated micro-scale model, a three-dimensional simulation of the formation of a kink band under longitudinal compression of the composite is conducted. A new evidence at micro-scale is found supporting the hypothesis that shear stresses transferred between fibers and matrix are particularly important in the formation of the kink band.

36 MATERIALS SCIENCE↗

DME-Propane Ignition Delay Time Measurements at Mixing Controlled Compression Ignition Engine-Relevant Conditions

The blend of dimethyl ether (DME, CH 3 OCH 3 ) and propane (C 3 H 8 ) is a potentially renewable fuel mixture that has the potential to replace diesel in compression ignition engines. The combination can potentially reduce particulate and greenhouse gas emissions compared to a conventional diesel engine operating under similar conditions. However, detailed conceptual and simulation studies must be conducted before adopting a new fuel on a compression ignition engine. For these simulations, accurate chemical kinetic models are necessary. However, the validity of chemical kinetic mechanisms in the literature is unknown for mixing controlled compression ignition (MCCI) engine operating conditions. Hence, in this work, we studied the ignition of dimethyl ether (DME) and propane blends in a shock tube at MCCI engine conditions. Ignition delay time (IDT) data was collected behind the reflected shock for DME-propane mixtures for heavy-duty compression ignition (CI) engine parameters. Undiluted experiments spanning temperatures of 700 to 1100 K and pressures of 55 to 84 bar for various blends (100% CH 3 OCH 3 / 0% C 3 H 8, 100% C 3 H 8 / 0% CH 3 OCH 3 , 60% CH 3 OCH 3 / 40% C 3 H 8 ) of DME and propane were combusted in synthetic air (21% O 2 / 79% N 2 ). Some experiments were conducted at higher pressures (90-120 bar) to understand model performance at these conditions. Comparisons of IDT were made with the predictions of recent chemical kinetic mechanisms for DME-propane mixture, including the Aramco3.0, NUIG, and Dames et al. mechanisms. All mechanisms overpredicted IDT compared to experimental values. Sensitivity analysis was conducted with Dames et al. model, and critical reactions sensitive to IDT of DME-propane mixture near 100 bar are outlined.

Mohammed, Zuhayr Pasha↗

A GENERAL FRAMEWORK FOR ENHANCING SPARSITY OF GENERALIZED POLYNOMIAL CHAOS EXPANSIONS

Compressive sensing has become a powerful addition to uncertainty quantification when only limited data are available. In this paper, we provide a general framework to enhance the sparsity of the representation of uncertainty in the form of generalized polynomial chaos expansion. We use an alternating direction method to identify new sets of random variables through iterative rotations so the new representation of the uncertainty is sparser. Consequently, we increase both the efficiency and accuracy of the compressive-sensing-based uncertainty quantification method. We demonstrate that the previously developed iterative method to enhance the sparsity of Hermite polynomial expansion is a special case of this general framework. Moreover, we use Legendre and Chebyshev polynomial expansions to demonstrate the effectiveness of this method with applications in solving stochastic partial differential equations and high-dimensional (O(100)) problems.

Yang, Xiu↗

Dilatant hardening of fluid‐saturated sandstone

Abstract The presence of pore fluid in rock affects both the elastic and inelastic deformation processes, yet laboratory testing is typically performed on dry material even though in situ the rock is often saturated. Techniques were developed for testing fluid‐saturated porous rock under the limiting conditions of drained, undrained, and unjacketed response. Confined compression experiments, both conventional triaxial and plane strain, were performed on water‐saturated Berea sandstone to investigate poroelastic and inelastic behavior. Measured drained response was used to calibrate an elasto‐plastic constitutive model that predicts undrained inelastic deformation. The experimental data show good agreement with the model: dilatant hardening in undrained triaxial and plane strain compression tests under constant mean stress was predicted and observed.

Makhnenko, Roman Y.↗

Modeling and Simulation of Compression Molding Process for Sheet Molding Compound (SMC) of Chopped Carbon Fiber Composites

Compression molded SMC composed of chopped carbon fiber and resin polymer which balances the mechanical performance and manufacturing cost presents a promising solution for vehicle lightweight strategy. However, the performance of the SMC molded parts highly depends on the compression molding process and local microstructure, which greatly increases the cost for the part level performance testing and elongates the design cycle. ICME (Integrated Computational Material Engineering) approaches are thus necessary tools to reduce the number of experiments required during part design and speed up the deployment of the SMC materials. As the fundamental stage of the ICME workflow, commercial software packages for SMC compression molding exist yet remain not fully validated especially for chopped fiber systems. In this study, SMC plaques are prepared through compression molding process. The corresponding simulation models are built in Autodesk Moldflow with the same part geometry and processing conditions as in the molding tests. The output variables of the compression molding simulations, including press force history and fiber orientation of the part, are compared with experimental data. Influence of the processing conditions to the fiber orientation of the SMC plaque is also discussed. It is found that generally Autodesk Moldflow can achieve a good simulation of the compression molding process for chopped carbon fiber SMC, yet quantitative discrepancies still remain between predicted variables and experimental results.

36 MATERIALS SCIENCE↗

Application of Al-Cu-W-Ta graded density impactors in dynamic ramp compression experiments

Graded density impactors (GDIs) are utilized to dynamically compress materials to extreme conditions. Two modifications to a previously developed Mg-Cu-W GDI are made in this work before using it in a dynamic compression experiment: Mg is replaced with Al and a Ta disk is glued to the back. The Mg phase is replaced by Al because FCC Al remains solid to higher pressure along its Hugoniot compared to Mg. The addition of the Ta disk creates a constant particle velocity regime and facilitates a definition of peak pressure states. Microstructure analysis, profilometry, and ultrasonic C-scans of the Al-Cu-W GDI all confirm excellent uniformity. We evaluated signal variation in the radial direction of a dynamically compressed Al-LiF bilayer target to evaluate the contribution of spatial nonuniformity to errors. Velocity traces from five photon Doppler velocimetry (PDV) probes located at different radial distances from the center of the target varied at most by 1.1% with a root mean square of 0.3% during the compression ramp, demonstrating low PDV measurement error over a relatively large experimental area. The experimental PDV data additionally agrees well with 1D simulations that use inputs from predictive characterization models developed for the material properties resulting from tape casting, laminating, and powder consolidation processes. Low measurement error during quasi-isentropic compression, leading to better precision, promises a robust platform to reach extreme compression and low-temperature recovery states and facilitates discovery via synthesis, quenching, and preservation of new high-pressure phases.

36 MATERIALS SCIENCE↗

Numerical assessment of the role of slip and twinning in magnesium alloy AZ31B during loading path reversal

Magnesium alloy AZ31B plastically deforms via twinning and slip. Corresponding to the unidirectional nature of twinning, the activity of twinning/detwinning is directly related to loading history and materials texture. Using the elastic viscoplastic self-consistent model implementing with the twinning and detwinning model (EVPSC–TDT), we revisited experimental data of AZ31B sheets under four different strain paths: (1) tension–compression–tension along rolling direction, (2) tension–compression–tension along transverse direction, (3) compression–tension–compression along rolling direction, and (4) compression–tension–compression along transverse direction, and identified the dominant deformation mechanisms with respect to the strain path. We captured plastic deformation behaviors observed in experiments and quantitatively interpreted experimental observations in terms of the activities of different deformation mechanisms and the evolution of texture. It is found that the in-plane pre-tension has slight effect on the subsequent deformation, and the pre-compression and the reverse tension after compression have significant effect on the subsequent deformation. The inelastic behavior under compressive unloading is found to be insignificant at a small strain level but pronounced at a large strain level. Lastly, such significant effect is mainly ascribed to the activity of twinning and detwinning.

36 MATERIALS SCIENCE↗

High pressure melting curves of silver, gold and copper

In this work, based on the Lindemann's formula of melting and the pressure-dependent Grüneisen parameter, we have investigated the pressure effect on melting temperature of silver, gold and copper metals. The analytical expression of melting temperature as a function of volume compression has been derived. Our results are compared with available experimental data as well as with previous theoretical studies and the good and reasonable agreements are found. We also proposed the potential of this approach on predicting melting of copper at very high pressure.

36 MATERIALS SCIENCE↗

Effect of Mach number on the efficiency of microwave energy deposition in supersonic flow

The article is devoted to experimental and numerical studies of the efficiency of microwave energy deposition into a supersonic flow around the blunt cylinder at different Mach numbers. Identical conditions for energy deposition have been kept in the experiments, thus allowing to evaluate the pure effect of varying Mach number on the pressure drop. Euler equations are solved numerically to model the corresponding unsteady flow compressed gas. The results of numerical simulations are compared to the data obtained from the physical experiments. It is shown that the momentum, which the body receives during interaction of the gas domain modified by microwave discharge with a shock layer before the body, increases almost linearly with rising of Mach number and the efficiency of energy deposition also rises.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Note: The performance of new density functionals for a recent blind test of non-covalent interactions

Benchmark datasets of non-covalent interactions are essential for assessing the performance of density functionals and other quantum chemistry approaches. In a recent blind test, Taylor et al. benchmarked 14 methods on a new dataset consisting of 10 dimer potential energy curves calculated using coupled cluster with singles, doubles, and perturbative triples (CCSD(T)) at the complete basis set (CBS) limit (80 data points in total). Finally, the dataset is particularly interesting because compressed, near-equilibrium, and stretched regions of the potential energy surface are extensively sampled.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

HP-TACO: A high-pressure triaxial compression apparatus for in situ x-ray measurements in geomaterials

Triaxial compression experiments are commonly used to characterize the elastic and inelastic behavior of geomaterials. In situ measurements of grain kinematics, particle breakage, stresses, and other microscopic phenomena have seldom been made during such experiments, particularly at high pressures relevant to many geologic and man-made processes, limiting our fundamental understanding. To address this issue, we developed a new triaxial compression device called HP-TACO (High-Pressure TriAxial COmpression Apparatus). HP-TACO is a miniaturized, conventional triaxial compression apparatus permitting confining pressures up to 50 MPa and deviatoric straining of materials, while also allowing in situ x-ray measurements of grain-scale kinematics and stresses. Here, in this study, we present the design of and first results from HP-TACO during its use in laboratory and synchrotron settings to study grain-scale kinematics and stresses in triaxially compressed sands subjected to 15 and 30 MPa confining pressures. The data highlight the unique capabilities of HP-TACO for studying the high-pressure mechanics of sands, providing new insight into micromechanical processes occurring during geologic and man-made processes.

47 OTHER INSTRUMENTATION↗

Phase diagram and edge states of the 𝜈 = 5/2 fractional quantum Hall state with Landau level mixing and finite well thickness

The 𝜈 = 5/2 fractional quantum Hall effect is a system of intense experimental and theoretical interest as its ground state may host non-Abelian excitations, but the exact nature of the ground state is still undetermined. We present the results of an exact diagonalization study of an electron system in the disk configuration, including the effects of Landau level (LL) mixing and the finite thickness of the quantum well confining the electrons. The degeneracy between the two leading candidates for the ground state, the Pfaffian and anti-Pfaffian, is broken by interactions with a neutralizing background, in addition to the inclusion of two- and three-body interactions via LL mixing. As a result of the neutralizing background in the disk configuration, there is a phase transition from the anti-Pfaffian to the Pfaffian as LL mixing is turned on, in stark contrast to what is observed in spherical geometry. This behavior is in agreement with existing experiments, showing the appearance of the Pfaffian state at strong LL mixing before the system enters a compressible phase. Furthermore, the inclusion of LL mixing leads to an increased charge 𝑒/4 quasihole size. LL mixing interactions are also shown to overcome the effects of edge reconstruction. Due to finite thickness effects, these properties are enhanced dramatically. We also find that only the Pfaffian and anti-Pfaffian states continue to possess energy gaps at finite width, while gaps for compressible stripe states close, which is in agreement with available experimental data.

Tylan-Tyler, Anthony↗

Elevated and Low Temperature Deformation of Cast Depleted Uranium

Goals: Understand crystal structure and micro-structure changes during high and low temperature deformation of uranium, in particular texture, and develop constitutive micro-structure based model for uranium deformation. Deliverables achieved: Completed texture measures for 11 pre- and post-dU compression samples, quantified texture pre- and post-deformation, and provided data to constrain deformation models.

Materials Science(36)↗

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗