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At least 1,423 records · Page 79

MO-D-PinS Room/Hall E-02: Multiparametric Fuctional Imaging in Radiation Therapy

MRI, with its excellent soft tissue contrast and its ability to provide physiological as well as anatomical information, is becoming increasingly used in radiation therapy for treatment planning, image-guided radiation therapy, and treatment evaluation. This session will explore solutions to integrating MRI into the simulation process. Obstacles for using MRI for simulation include distortions and artifacts, image acquisition speed, complexity of imaging techniques, and lack of electron density information. Partners in Solutions presents vendor representatives who will present their approaches to meeting these challenges and others. An increased awareness of how MRI simulation works will allow physicists to better understand and use this powerful technique. The speakers are all employees who are presenting information about their company’s products.

60 APPLIED LIFE SCIENCES↗

Quantum Algorithm for High Energy Physics Simulations

Simulating quantum field theories is a flagship application of quantum computing. However, calculating experimentally relevant high energy scattering amplitudes entirely on a quantum computer is prohibitively difficult. It is well known that such high energy scattering processes can be factored into pieces that can be computed using well established perturbative techniques, and pieces which currently have to be simulated using classical Markov chain algorithms. These classical Markov chain simulation approaches work well to capture many of the salient features, but cannot capture all quantum effects. To exploit quantum resources in the most efficient way, we introduce a new paradigm for quantum algorithms in field theories. This approach uses quantum computers only for those parts of the problem which are not computable using existing techniques. In particular, we develop a polynomial time quantum final state shower that accurately models the effects of intermediate spin states similar to those present in high energy electroweak showers with a global evolution variable. The algorithm is explicitly demonstrated for a simplified quantum field theory on a quantum computer.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Structure and dynamics of ethane confined in silica nanopores in the presence of CO 2

Fundamental understanding of the subcritical/supercritical behavior of key hydrocarbon species inside nano-porous matrices at elevated pressure and temperature is less developed compared to bulk fluids, but this knowledge is of great importance for chemical and energy engineering industries. This study explores in detail the structure and dynamics of ethane (C 2 H 6 ) fluid confined in silica nanopores, with a focus on the effects of pressure and different ratios of C 2 H 6 and CO 2 at non-ambient temperature. Quasi-elastic neutron scattering (QENS) experiments were carried out for the pure C 2 H 6 , C 2 H 6 :CO 2 = 3:1, and 1:3 mixed fluids confined in 4-nm cylindrical silica pores at three different pressures (30 bars, 65 bars, and 100 bars) at 323 K. Two Lorentzian functions were required to fit the spectra, corresponding to fast and slow translational motions. No localized motions (rotations and vibrations) were detected. Higher pressures resulted in hindrances of the diffusivity of C 2 H 6 molecules in all systems investigated. Pore size was found to be an important factor, i.e., the dynamics of confined C 2 H 6 is more restricted in smaller pores compared to the larger pores used in previous studies. Molecular dynamics simulations were performed to complement the QENS experiment at 65 bars, providing supportive structure information and comparable dynamic information. The simulations indicate that CO 2 molecules are more strongly attracted to the pore surface compared to C 2 H 6 . The C 2 H 6 molecules interacting with or near the pore surface form a dense first layer (L1) close to the pore surface and a second less dense layer (L2) extending into the pore center. Both the experiments and simulations revealed the role that CO 2 molecules play in enhancing C 2 H 6 diffusion (“molecular lubrication”) at high CO 2 :C 2 H 6 ratios. The energy scales of the two dynamic components, fast and slow, quantified by both techniques, are in very good agreement. Herein, the simulations identified the fast component as the main contributor to the dynamics. Molecule motions in the L2 region are mostly responsible for the dynamics (fast and slow) that can be detected by the instrument.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FIELD IMPLEMENTATION PLAN FOR A WILLISTON BASIN BRINE EXTRACTION AND STORAGE TEST

The Energy & Environmental Research Center (EERC) successfully completed all technical work of Phase I, including development of a field implementation plan (FIP) for a brine extraction and storage test (BEST) in the North Dakota portion of the Williston Basin. This implementation plan was commissioned by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) as a proxy for managing formation pressure plumes and measuring/monitoring the movement of differential pressure and CO2 plumes in the subsurface for future saline CO2 storage projects. BEST comprises the demonstration and validation of active reservoir management (ARM) strategies and extracted brine treatment technologies. Two prospective commercial brine injection sites were evaluated for BEST to satisfy DOE’s goals. Ultimately, an active saltwater disposal (SWD) site, Johnsons Corner, was selected because it possesses an ideal combination of key factors making it uniquely suited to host BEST. This site is located in western North Dakota and operated by Nuverra Environmental Solutions (Nuverra), a national leader in brine handling, treatment, and injection. An integrated management approach was used to incorporate local and regional geologic characterization activities with geologic and simulation models, inform a monitoring, verification, and accounting (MVA) plan, and to conduct a risk assessment. This approach was used to design a FIP for an ARM schema and an extracted brine treatment technology test bed facility. The FIP leverages an existing pressure plume generated by two commercial SWD wells. These wells, in conjunction with a new brine extraction well, will be used to conduct the ARM schema. Results of these tests will be quantified based on their impact on the performance of the existing SWD wells and the surrounding reservoir system. Extracted brine will be injected into an underlying deep saline formation through a new injection well. The locations of proposed extraction and injection wells were selected during the Phase I efforts. These wells will be permitted as North Dakota Administrative Code Underground Injection Control Class II wells and will yield additional characterization data which will further refine the FIP in Phase II. An array of surface and downhole monitoring techniques will validate ARM performance against predictive simulation results. Infrastructure will be constructed to manage extracted fluids at the surface and provide brine to a treatment test bed facility. Treatment of extracted brine can provide a means of reducing extracted brine disposal volumes, an alternate source of water, and/or salable products for beneficial use. A test bed facility will be constructed to provide a means of demonstrating these technologies on a wide range of brine concentrations. Screening criteria based on a techno-economic and life cycle assessment were developed to select high-salinity brine treatment technologies for extended duration treatment (30–60 days) in Phase II. A detailed cost assessment determined total implementation costs for BEST of $19,901,065 million (DOE share $15,680,505). These costs are inclusive of all necessary equipment, infrastructure construction, operations and project closeout costs required to implement BEST. An ideal combination of key factors makes the Johnsons Corner site uniquely suited to be the BEST demonstration.

10 SYNTHETIC FUELS↗

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations

Characterizing the phase space distribution of particle beams in accelerators is a central part of accelerator understanding and performance optimization. However, conventional reconstruction-based techniques either use simplifying assumptions or require specialized diagnostics to infer high-dimensional (> $2D$) beam properties. In this Letter, we introduce a general-purpose algorithm that combines neural networks with differentiable particle tracking to efficiently reconstruct high-dimensional phase space distributions without using specialized beam diagnostics or beam manipulations. Furthermore, we demonstrate that our algorithm accurately reconstructs detailed 4D phase space distributions with corresponding confidence intervals in both simulation and experiment using a single focusing quadrupole and diagnostic screen. This technique allows for the measurement of multiple correlated phase spaces simultaneously, which will enable simplified 6D phase space distribution reconstructions in the future.

47 OTHER INSTRUMENTATION↗

Reducing Southern Ocean Shortwave Radiation Errors in the ERA5 Reanalysis with Machine Learning and 25 Years of Surface Observations

Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SW down exhibited large errors (mean bias = 54 W m -2 , mean absolute error = 82 W m -2 , root-mean-square error = 132 W m -2 , and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SW down with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SW down using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.

54 ENVIRONMENTAL SCIENCES↗

Relativistic Modeling Capabilities in Perseus Extended MHD Simulation Code for HED Plasmas

This project is submitted in response to DE-FOA-0001153, and will be carried out by Dr. Charles Seyler and Dr. Nathaniel Hamlin as post doc under the direction of Professor Seyler. The objectives are to enable PERSEUS to self-consistently model relativistic high-energy-density (HED) laboratory and astrophysical phenomena. Electrons and ions in a plasma are generally modeled either as fluids using a two-fluid code, like PERSEUS, or as particles using a Particle-In- Cell (PIC) code. Nonrelativistic PERSEUS solves the two-fluid equations, formulated in terms of a generalized Ohm’s law (GOL), so as to model about nine orders of magnitude in density variation using a local semi-implicit method. Relativistic PERSEUS preserves this structure and therefore retains these advantageous properties, enabling it to model a broader range of relativistic HED phenomena than previous codes. We have also overcome a major technical challenge associated with solving a relativistic system of equations relating conserved quantities (momentum, energy, etc.) to primitive variables (density, velocity, and pressure). We have thus far developed a relativistic version of PERSEUS and demonstrated that it recovers expected nonrelativistic results. We are currently using relativistic PERSEUS to model two HED phenomena, namely laser-plasma interactions and X-pinches, both of which show spectroscopic evidence of relativistic electrons. In an X-pinch, a section of wire carrying sufficiently large current forms a plasma column that pinches down to a point-like source, generating X-rays for use in radiographic imaging. Laser-plasma interactions have been simulated using PIC codes, and we use their results as a benchmark for comparison. However, neither PIC codes nor existing two-fluid schemes can simulate X-pinches, due to the broad range of densities which have thus far made such a simulation computationally prohibitive. In both laser-plasma interaction and Xpinch simulations, we have observed relativistic phenomena that PERSEUS could not previously model. This includes relativistic channeling of a laser into an over-dense deuterium gas (i.e. induced transparency), consistent with PIC simulation results, along with energetic electrons and ions following an X-pinch and likely accompanied by strong X-ray emission, consistent with experimental observations of energetic X-rays. This proposal includes our latest simulation results. We will improve computational efficiency with techniques that allow the use of a less refined numerical grid. This will enable extensions to three-dimensional geometries. We will improve modeling of laser-plasma interactions and X-pinches, including radiative transport processes, in order to improve comparisons with PIC simulations and experimental diagnostics. We will also model power loss through electrode surface plasmas in magnetically insulated transmission lines (MITLs). We will model relativistic astrophysical phenomena in both astrophysical and HED regimes, which could shed light on the validity of laboratory astrophysics for certain problems. These phenomena are currently modeled using PIC codes and existing relativistic two-fluid codes, neither of which can model the range of length scales of which relativistic PERSEUS is capable. There is strong potential for this project to have a broad impact on both the astrophysical and laboratory plasma communities. In the laboratory community, our work is applicable to those concerned with laser-plasma interactions such as laser-driven fusion, and those in the dense Z pinch community concerned with X-pinches and electrode surface plasmas. An improved understanding of the mechanisms of hard (i.e. high-energy) X-ray generation will likely make important contributions toward the use of X-pinches for radiography through the harnessing or mitigation of hard X-rays, depending on the application. The modeling of electrode surface plasmas, including vacuum electron flow, will improve our understanding of power loss to various loads.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Arrow of Time in the Collapse of Collisionless Self-gravitating Systems: Non-validity of the Vlasov–Poisson Equation during Violent Relaxation

The collapse of a collisionless self-gravitating system, with the fast achievement of a quasi-stationary state, is driven by violent relaxation, with a typical particle interacting with the time-changing collective potential. It is traditionally assumed that this evolution is governed by the Vlasov–Poisson equation, in which case entropy must be conserved. We run N-body simulations of isolated self-gravitating systems, using three simulation codes, NBODY-6 (direct summation without softening), NBODY-2 (direct summation with softening), and GADGET-2 (tree code with softening), for different numbers of particles and initial conditions. At each snapshot, we estimate the Shannon entropy of the distribution function with three different techniques: Kernel, Nearest Neighbor, and EnBiD. For all simulation codes and estimators, the entropy evolution converges to the same limit as N increases. During violent relaxation, the entropy has a fast increase followed by damping oscillations, indicating that violent relaxation must be described by a kinetic equation other than the Vlasov–Poisson equation, even for N as large as that of astronomical structures. This indicates that violent relaxation cannot be described by a time-reversible equation, shedding some light on the so-called “fundamental paradox of stellar dynamics.” The long-term evolution is well-described by the orbit-averaged Fokker–Planck model, with Coulomb logarithm values in the expected range 10--12. By means of NBODY-2, we also study the dependence of the two-body relaxation timescale on the softening length. The approach presented in the current work can potentially provide a general method for testing any kinetic equation intended to describe the macroscopic evolution of N-body systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Atomic-Scale Structure and Stress Release Mechanism in Core–Shell Nanoparticles

According to the article, core–shell nanoparticles find applications in catalysts, sensors, and theranostics. The full internal 3D atomic structure, however, cannot be resolved by current imaging and diffraction techniques. We analyzed the atomic positions and stress-release mechanism in a cubic Au–Pd core–shell nanoparticle in approximately 1000 times higher resolution than current experimental techniques using large-scale molecular dynamics simulation to overcome these limitations. The core–shell nanocube of 73 nm size was modeled similarly to solution synthesis by random epitaxial deposition of a 4 nm thick shell of Pd atoms onto a Au core of 65 nm side length using reliable interatomic potentials. The internal structure reveals specific deformations and stress relaxation mechanisms that are caused by the +4.8% lattice mismatch of gold relative to palladium and differential confinement of extended particle facets, edges, and corners by one, two, or three Au–Pd interfaces, respectively. The three-dimensional lattice strain causes long-range, arc-like bending of atomic rows along the faces and edges of the particle, especially near the Au–Pd interface, a bulging deformation of the Pd shell, and stacking faults in the Pd shell at the corners of the particle. The strain pattern and mechanism of stress release were further characterized by profiles of the atomic layer spacing in the principal crystallographic directions. Accordingly, strain in the Pd shell is several times larger in the extended facets than near the edges and corners of the nanoparticle, which likely affects adsorption, optical, and electrochemical properties. The findings are consistent with available experimental data, including 3D reconstructions of the same cubic nanoparticle by coherent diffractive imaging (CDI) and may be verified by more powerful experimental techniques in the future. The stress release mechanisms are representative for cubic core–shell nanoparticles with fcc structure and can be explored for different shapes by the same methods.

Chemistry↗

SU-D-18C-01: A Novel 4D-MRI Technology Based On K-Space Retrospective Sorting

Purpose: Current 4D-MRI techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of an entirely new framework of 4D-MRI based on k-space retrospective sorting. Methods: An important challenge of the proposed technique is to determine the number of repeated scans(NR) required to obtain sufficient k-space data for 4D-MRI. To do that, simulations using 29 cancer patients' respiratory profiles were performed to derive the relationship between data acquisition completeness(Cp) and NR, also relationship between NR(Cp=95%) and the following factors: total slice(NS), respiratory phase bin length(Lb), frame rate(fr), resolution(R) and image acquisition starting-phase(P0). To evaluate our technique, a computer simulation study on a 4D digital human phantom (XCAT) were conducted with regular breathing (fr=0.5Hz; R=256×256). A 2D echo planer imaging(EPI) MRI sequence were assumed to acquire raw k-space data, with respiratory signal and acquisition time for each k-space data line recorded simultaneously. K-space data was re-sorted based on respiratory phases. To evaluate 4D-MRI image quality, tumor trajectories were measured and compared with the input signal. Mean relative amplitude difference(D) and cross-correlation coefficient(CC) are calculated. Finally, phase-sharing sliding window technique was applied to investigate the feasibility of generating ultra-fast 4D-MRI. Result: Cp increased with NR(Cp=100*[1-exp(-0.19*NR)], when NS=30, Lb=100%/6). NR(Cp=95%) was inversely-proportional to Lb (r=0.97), but independent of other factors. 4D-MRI on XCAT demonstrated highly accurate motion information (D=0.67%, CC=0.996) with much less artifacts than those on image-based sorting 4D-MRI. Ultra-fast 4D-MRI with an apparent temporal resolution of 10 frames/second was reconstructed using the phase-sharing sliding window technique. Conclusions: A novel 4D-MRI technology based on k-space sorting has been successfully developed and evaluated on the digital phantom. Framework established can be applied to a variety of MR sequences, showing great promises to develop the optimal 4D-MRI technique for many radiation therapy applications. NIH (1R21CA165384-01A1)

60 APPLIED LIFE SCIENCES↗

SU-F-J-201: Validation Study of Proton Radiography Against CT Data for Quantitative Imaging of Anatomical Changes in Head and Neck Patients

Purpose: In clinical pencil-beam-scanned (PBS) proton therapy, the advantage of the characteristic sharp dose fall-off after the Bragg Peak (BP) becomes a disadvantage if the BP positions of a plan’s constituent pencil beams are shifted, eg.due to anatomical changes. Thus, for fractionated PBS proton therapy, accurate knowledge of the water equivalent path length (WEPL) of the traversed anatomy is critical. In this work we investigate the feasibility of using 2D proton range maps (proton radiography, PR) with the active-scanning gantry at PSI. Methods: We simulated our approach using Monte Carlo methods (MC) to simulate proton beam interactions in patients using clinical imaging data. We selected six head and neck cases having significant anatomical changes detected in per-treatment CTs.PRs (two at 0°/90°) were generated from MC simulations of low-dose pencil beams at 230MeV. Each beam’s residual depth-dose was propagated through the patient geometry (from CT) and detected on exiting the patient anatomy in an ideal depth-resolved detector (eg. range telescope). Firstly, to validate the technique, proton radiographs were compared to the ground truth, which was the WEPL from ray-tracing in the patient CT at the pencil beam location. Secondly, WEPL difference maps (per-treatment – planning imaging timepoints) were then generated to locate the anatomical changes, both in the CT (ground truth) and in the PRs. Binomial classification was performed to evaluate the efficacy of the technique relative to CT. Results: Over the projections simulated over all six patients, 70%, 79% and 95% of the grid points agreed with the ground truth proton range to within ±0.5%, ±1%, and ±3% respectively. The sensitivity, specificity, precision and accuracy were high (mean±1σ, 83±8%, 87±13%, 95±10%, 83±7% respectively). Conclusion: We show that proton-based radiographic images can accurately monitor patient positioning and in vivo range verification, while providing equivalent WEPL information to a CT scan, with the advantage of a much lower imaging dose.

60 APPLIED LIFE SCIENCES↗

Evaluation of sky spectra and sky models in daylighting simulations

Sky models in daylight simulations represent the luminance variation across the sky-dome for different locations, dates, times and weather conditions, but skies are typically modelled as colourless. Recent studies explore techniques for incorporating the spectral content of daylighting in simulations. This paper provides an evaluation of the existing spectral sky models in lighting simulation software. The comparisons are made between the available mathematical sky models and naturally occurring skies that were recorded using high dynamic range photography and spectrophotometric measurements. The results show that recently developed sky models present progress compared to colourless sky models, but further research is needed to accurately simulate daylight spectra.

97 MATHEMATICS AND COMPUTING↗

Measuring the strong electrostatic and magnetic fields with proton radiography for ultra-high intensity laser channeling on fast ignition

In order to investigate the intense laser propagation and channel formation in dense plasma, we conducted an experiment with proton deflectometry on the OMEGA EP Laser facility. The proton image was analyzed by tracing the trajectory of mono-energetic protons, which provides understanding the electric and magnetic fields that were generated around the channel. The estimated field strengths (E ∼ 10{sup 11} V/m and B ∼ 10{sup 8} G) agree with the predictions from 2D-Particle-in-cell (PIC) simulations, indicating the feasibility of the proton deflectometry technique for over-critical density plasma.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Probabilistic Resource Adequacy Suite (PRAS)

The Probabilistic Resource Adequacy Suite (PRAS) provides an open-source, research-oriented collection of tools for analysing the resource adequacy of a bulk power system. The simulation methods offered support everything from classical convolution-based analytical techniques through to high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.

Stephen, Gord↗

Nuclear Power Plant Control Room Modernization - Simulation Based Design

As many plants age and equipment modifications are implemented, the industry has the opportunity to address the issue of control room obsolescence through technology application and enhanced engineering techniques using existing systems. This paper addresses the practice of Simulation Based Design (SBD) for control room modernization driven by plant modifications and upgrades.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Data-driven nonlocal model for fragmentation in the crushing of solids

A technique is proposed for reproducing particle size distributions in three-dimensional simulations of the crushing and comminution of solid materials. The method is designed to produce realistic distributions over a wide range of loading conditions, especially for small fragments. In contrast to most existing methods, the new model does not explicitly treat the small-scale process of fracture. Instead, it uses measured fragment distributions from laboratory tests as the basic material property that is incorporated into the algorithm, providing a data-driven approach. The algorithm is implemented within a nonlocal peridynamic solver, which simulates the underlying continuum mechanics and contact interactions between fragments after they are formed. Finally, the technique is illustrated in reproducing fragmentation data from drop weight testing on sandstone samples.

58 GEOSCIENCES↗