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At least 289 records · Page 16

Numerical simulations of wave propagation in long bars with application to Kolsky bar testing

Material testing using the Kolsky bar, or split Hopkinson bar, technique has proven instrumental to conduct measurements of material behavior at strain rates in the order of 10 3 s -1 . Test design and data reduction, however, remain empirical endeavors based on the experimentalist's experience. Issues such as wave propagation across discontinuities, the effect of the deformation of the bar surfaces in contact with the specimen, the effect of geometric features in tensile specimens (dog-bone shape), wave dispersion in the bars and other particulars are generally treated using simplified models. The work presented here was conducted in Q3 and Q4 of FY14. The objective was to demonstrate the feasibility of numerical simulations of Kolsky bar tests, which was done successfully.

36 MATERIALS SCIENCE↗

Direct Numerical Simulation of Autoignition in a Jet in a Cross-Flow Configuration: ALCF-2 Early Science Program (Technical Report)

Autoignition in turbulent flows is a challenging fundamental problem due to the intricate coupling of different physical and chemical processes extending over multiple flow and chemistry scales. At the same time, the improved understanding and ability to predict autoignition in flows characterized by considerable fluctuations of velocity, composition, and temperature is essential for the development of novel low-emission concepts for power generation. The aim of this project is to study the fundamental aspects of autoignition in a fuel-air mixing device directly applicable to mixing ducts in gas turbines. The NEK5000-based code for low Mach number reactive flows is used to perform very large scale direct numerical simulations of autoignition of a diluted hydrogen jet ejected in a cross-flowing stream of hot turbulent air in a laboratory-scale configuration. We report on our experience running NEK5000 on the new BGQ system at ALCF mira during the early science period (ESP). First of all, the most efficient problem size per MPI-rank is obtained through core-level efficiency metric measured from the target simulation. Furthermore, the most efficient number of ranks is found through strong scaling experiments. Finally, low-level insight into the observed parallel efficiency is enabled through IBM’s HPC Toolkit libraries.

Abdilghanie, A.↗

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗

Confidence in Numerical Simulations

This PowerPoint presentation offers a high-level discussion of uncertainty, confidence and credibility in scientific Modeling and Simulation (M&S). It begins by briefly evoking M&S trends in computational physics and engineering. The first thrust of the discussion is to emphasize that the role of M&S in decision-making is either to support reasoning by similarity or to “forecast,” that is, make predictions about the future or extrapolate to settings or environments that cannot be tested experimentally. The second thrust is to explain that M&S-aided decision-making is an exercise in uncertainty management. The three broad classes of uncertainty in computational physics and engineering are variability and randomness, numerical uncertainty and model-form uncertainty. The last part of the discussion addresses how scientists “think.” This thought process parallels the scientific method where by a hypothesis is formulated, often accompanied by simplifying assumptions, then, physical experiments and numerical simulations are performed to confirm or reject the hypothesis. “Confidence” derives, not just from the levels of training and experience of analysts, but also from the rigor with which these assessments are performed, documented and peer-reviewed.

97 MATHEMATICS AND COMPUTING↗

MODELING STATISTICAL PROPERTIES OF SOLAR ACTIVE REGIONS THROUGH DIRECT NUMERICAL SIMULATIONS OF 3D-MHD TURBULENCE

Statistical properties of the Sun's photospheric turbulent magnetic field, especially those of the active regions (ARs), have been studied using the line-of-sight data from magnetograms taken by the Solar and Heliospheric Observatory and several other instruments. This includes structure functions and their exponents, flatness curves, and correlation functions. In these works, the dependence of structure function exponents ({zeta}{sub p}) of the order of the structure functions (p) was modeled using a non-intermittent K41 model. It is now well known that the ARs are highly turbulent and are associated with strong intermittent events. In this paper, we compare some of the observations from Abramenko et al. with the log-Poisson model used for modeling intermittent MHD turbulent flows. Next, we analyze the structure function data obtained from the direct numerical simulations (DNS) of homogeneous, incompressible 3D-MHD turbulence in three cases: sustained by forcing, freely decaying, and a flow initially driven and later allowed to decay (case 3). The respective DNS replicate the properties seen in the plots of {zeta}{sub p} against p of ARs. We also reproduce the trends and changes observed in intermittency in flatness and correlation functions of ARs. It is suggested from this analysis that an AR in the onset phase of a flare can be treated as a forced 3D-MHD turbulent system in its simplest form and that the flaring stage is representative of decaying 3D-MHD turbulence. It is also inferred that significant changes in intermittency from the initial onset phase of a flare to its final peak flaring phase are related to the time taken by the system to reach the initial onset phase.

79 ASTRONOMY AND ASTROPHYSICS↗

Analytical modeling and numerical simulation of the short-wave infrared electron-injection detectors

This paper describes comprehensive analytical and simulation models for the design and optimization of the electron-injection based detectors. The electron-injection detectors evaluated here operate in the short-wave infrared range and utilize a type-II band alignment in InP/GaAsSb/InGaAs material system. The unique geometry of detectors along with an inherent negative-feedback mechanism in the device allows for achieving high internal avalanche-free amplifications without any excess noise. Physics-based closed-form analytical models are derived for the detector rise time and dark current. Our optical gain model takes into account the drop in the optical gain at high optical power levels. Furthermore, numerical simulation studies of the electrical characteristics of the device show good agreement with our analytical models as well experimental data. Performance comparison between devices with different injector sizes shows that enhancement in the gain and speed is anticipated by reducing the injector size. Sensitivity analysis for the key detector parameters shows the relative importance of each parameter. The results of this study may provide useful information and guidelines for development of future electron-injection based detectors as well as other heterojunction photodetectors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Direct numerical simulation of turbulent dispersion of evaporative aerosol clouds produced by an intense expiratory event

Airborne particles are a major route for transmission of COVID-19 and many other infectious diseases. When a person talks, sings, coughs, or sneezes, nasal and throat secretions are spewed into the air. After a short initial fragmentation stage, the expelled material is mostly composed of spherical particles of different sizes. While the dynamics of the largest droplets are dominated by gravitational effects, the smaller aerosol particles, mostly transported by means of hydrodynamic drag, form clouds that can remain afloat for long times. In subsaturated air environments, the dependence of pathogen-laden particle dispersion on their size is complicated due to evaporation of the aqueous fraction. Particle dynamics can significantly change when ambient conditions favor rapid evaporation rates that result in a transition from buoyancyto-drag dominated dispersion regimes. To investigate the effect of particle size and evaporation on pathogen-laden cloud evolution, a direct numerical simulation of a mild cough was coupled with an evaporative Lagrangian particle advection model. The results suggest that while the dispersion of cough particles in the tails of the size distribution are unlikely to be disrupted by evaporative effects, preferential aerosol diameters (30-40 μm) may exhibit significant increases in the residence time and horizontal range under typical ambient conditions. Using estimations of the viral concentration in the spewed fluid and the number of ejected particles in a typical respiratory event, we obtained a map of viral load per volume of air at the end of the cough and the number of virus copies per inhalation in the emitter vicinity.

60 APPLIED LIFE SCIENCES↗

Application of the Mixed-Mode Model for Numerical Simulation of Pearlitic Transformation

The multiscale model of pearlitic transformation, including the finite element solution of the second Fick’s equation with moving boundary in the microscale and Fourier equation in the macroscale, is presented in this paper. According to the mixed-mode approach, both the volume diffusion and the interface mobility were considered. Model describes sidewise and frontal growth of cementite and ferrite plates in a single grain of the austenite. Assessment of the possibility of the developed model application to determine the key parameters in terms of strength properties of pearlitic steel, i.e., pearlite grain size and colony size as well as interlamellar spacing for various cooling conditions, was the main aim of this work. The model was validated and verified on the basis of experimental tests performed for two eutectoid steels. In practice, developed model can support design process for a technology of high-strength rods and long products manufacturing. Rails were selected as a case study in this work, and therefore, numerical simulations of accelerated cooling of the rail head were performed and the relationship between the parameters of heat treatment, parameters of the structure and properties of the finished product was determined on the basis of obtained results.

36 MATERIALS SCIENCE↗

High-order two-fluid plasma solver for direct numerical simulations of plasma flows with full transport phenomena

The two-fluid plasma equations for a single ion species, with full transport terms, including temperature and magnetic field dependent ion and electron viscous stresses and heat fluxes, frictional drag force, and ohmic heating terms, have been implemented in the CFDNS code and solved by using sixth-order non-dissipative compact finite differences for plasma flows in several different regimes. In order to be able to fully resolve all the dynamically relevant time and length scales, while maintaining computational feasibility, the assumptions of infinite speed of light and negligible electron inertia have been made. Non-dimensional analysis of the two-fluid plasma equations shows that, by varying the characteristic/background number density, length scale, temperature, and magnetic strength, the corresponding Hall, resistive, and ideal magnetohydrodynamic equations can be recovered as limiting cases. The accuracy and robustness of this two-fluid plasma solver in handling plasma flows in different regimes have been validated against four canonical problems: Alfven and whistler dispersion relations, electromagnetic plasma shock, and magnetic reconnection. For all test cases, by using physical dissipation and diffusion, with negligible numerical dissipation/diffusion, fully converged Direct Numerical Simulation (DNS)-like solutions are obtained when the ion Reynolds number based on the grid size is smaller than a threshold value which is about 2.3. For the magnetic reconnection problem, the results show that the magnetic flux saturation time and value converge when the ion and magnetic Reynolds numbers are large enough. Thus, the DNS-like results become relevant to practical problems with much larger Reynolds numbers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Simulations of Gas Production from Gas Hydrate Reservoirs at the Prudhoe Bay Unit 7-11-12 Pad on Alaska North Slope

In December 2018, a partnership between the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), the Japan Oil, Gas and Metals National Corporation (JOGMEC), and the U.S. Geological Survey (USGS) successfully drilled and logged the Hydrate-01 Stratigraphic Test Well (STW) in the greater Prudhoe Bay oil field on Alaska North Slope. The logging-while-drilling (LWD) data confirmed the presence of gas hydrate-bearing reservoirs within two sand reservoirs (Unit B and Unit D) that are suitable targets for future testing. The interpreted log data and core sample measurements were used to create reservoir models for the Prudhoe Bay Unit (PBU) Kuparuk 7-11-12 Site. The models combine both gas hydrate-bearing sections in Unit B and Unit D together with the intermediate Unit C and over- and underburden sands and shales. The vertical heterogeneity in porosity, gas hydrate saturation, and permeability distributions for reservoir and non-reservoir units was implemented using fine mesh discretization. The depressurization method was applied to Unit B to induce gas hydrate destabilization at constant bottom hole pressure (BHP) values. The results of the numerical simulations support the development of production scenarios, well design, surface facilities, and field test procedures with the main goal to perform efficient and safe scientific production testing. Project results contribute to the knowledge base of permafrost-associated gas hydrate accumulations as a future energy source.

Myshakin, Evgeniy↗

Supercritical CO 2 Water Displacements and CO 2 Capillary Trapping: Micromodel Experiment and Numerical Simulation

We report that the CO 2 capillary trapping is an important scientific issue in geological carbon sequestration, but few researches focus on the trapping mechanism at pore scale under supercritical CO 2 condition. In this study, based on the high-pressure fluids-microscopy-micromodel experimental system, we performed drainage experiment, i.e. supercritical CO 2 displacing water, and imbibition experiment, i.e. water displacing CO 2 , under the conditions of 45°C and 8.5 MPa. The DSLR camera was used to capture pictures of CO 2 -water two-phase immiscible flow and the microscopy was used to capture the capillary trapping behavior for the supercritical CO 2 at the pore scale. The computational fluid dynamic method was adopted to simulate the two-phase fluid flow processes. The numerical results are generally in agree ment with the experimental observations, and further provide three-dimensional geometries on the interface during the drainage-imbibition processes and the trapped supercritical CO 2 droplet/cluster. Lastly, the capillary trapping curve, i.e. the relationship between the initial CO 2 saturation and the residual saturation, was obtained from the numerical results, and we made an assessment of the three capillary trapping models, i.e. Land's, Jurauld's and Spiteri's trapping models. A comparison of the models performance indicates that Jurauld's model behaves slightly better than Land's model, whereas Spiteri's model behaves poorly. However, given that Land's model only contains one parameter of clear physical meaning, it is recommended for practical use.

58 GEOSCIENCES↗

Numerical Simulation and Optimization of the Thermodynamic Process of the Molten Salt Furnace

In this paper, a numerical model of the molten salt furnace process was developed, by using computational fluid dynamics (CFD) technique and considering the gas flow, the combustion and the radiation heat transfer. The results demonstrate that the performances of the salt furnace could be improved by optimization using the numerical model. The temperatures along the circumference of the furnace coil and outside shell are quite even, and the deviant combustion phenomenon is not observed. A back-flow formed in the upper part of the furnace chamber enhances the circulation and the mixing of the gas and effectively stabilizes the combustion in the furnace. The behaviors of CO, CO 2 , NO x , and H 2 O are presented in terms of the gas flow, temperature distribution and volumetric concentration distribution. It is concluded that the furnace with the constant air flow rate of 15,500 Nm 3 /h and the guiding vane angle at 48–50 deg is optimized for the combustion effectiveness.

42 ENGINEERING↗

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗

A new model for two-dimensional numerical simulation of pseudo-2D gas-solids fluidized beds

Pseudo-two dimensional (pseudo-2D) fluidized beds, for which the thickness of the system is much smaller than the other two dimensions, is widely used to perform fundamental studies on bubble behavior, solids mixing, or clustering phenomenon in different gas-solids fluidization systems. The abundant data from such experimental systems are very useful for numerical model development and validation. However, it has been reported that two-dimensional (2D) computational fluid dynamic (CFD) simulations of pseudo-2D gas-solids fluidized beds usually predict poor quantitative agreement with the experimental data, especially for the solids velocity field. In this paper, a new model is proposed to improve the 2D numerical simulations of pseudo-2D gas-solids fluidized beds by properly accounting for the frictional effect of the front and back walls. Two previously reported pseudo-2D experimental systems were simulated with this model. Compared to the traditional 2D simulations, significant improvements in the numerical predictions have been observed and the predicted results are in better agreement with the available experimental data.

42 ENGINEERING↗

A numerical simulation of solar energetic particle dropouts during impulsive events

This paper investigates the conditions for producing rapid variations of solar energetic particle (SEP) intensity commonly known as 'dropouts'. In particular, we use numerical model simulations based on solving the focused transport equation in the three-dimensional Parker interplanetary magnetic field to put constraints on the properties of particle transport coefficients in both directions perpendicular and parallel to the magnetic field. Our calculations of the temporal intensity profile of 0.5 and 5 MeV protons at the Earth show that the perpendicular diffusion must be small while the parallel mean free path is long in order to reproduce the phenomenon of SEP dropouts. When the parallel mean free path is a fraction of 1 AU and the observer is located at 1 AU, the perpendicular to parallel diffusion ratio must be below 10{sup –5} if we want to see the particle flux dropping by at least several times within 3 hr. When the observer is located at a larger solar radial distance, the perpendicular to parallel diffusion ratio for reproducing the dropouts should be even lower than that in the case of 1 AU distance. A shorter parallel mean free path or a larger radial distance from the source to observer will cause the particles to arrive later, making the effects of perpendicular diffusion more prominent and SEP dropouts disappear. All of these effects require the magnetic turbulence that resonates with the particles to be low everywhere in the inner heliosphere.

79 ASTRONOMY AND ASTROPHYSICS↗