Particle Simulation Research Articles

Proposing an intelligent technique based on radial basis function neural network to forecast the energy spectrum of diagnostic X-ray imaging systems

In digital subtraction angiography (digital subtraction total cerebral angiography), cardiac and macrovascular cardiography, anorectal radiology, fluoroscopy, and computed tomography (CT), a prior knowledge to X-ray energy spectrum is crucial for assessing the image quality and also calculating patient X-ray dosage. The present investigation's main objective is to propose an intelligent technique for faster calculating X-ray energy spectrum of medical imaging systems with different exposure settings of tube voltage, filter material, and thickness based on limited specific spectra. In this study, Monte Carlo N Particle (MCNP) simulation code was initially used to generate some limited X-ray spectra for tube voltages of 20, 30, 40, 50, 80, 100, 130, and 150 kV for two different filters of beryllium and aluminum with thicknesses of 0. 4, 0.8, 1.2, 1.6 and 2 mm. Tube voltage, type, and thickness of filter were used as the 3 inputs of 150 Radial Basis Function Neural Network (RBFNN) to forecast point by point of the X-ray spectrum. After training, the RBFNNs could forecast most of the X-ray spectra for tube voltages in the range of 20–150 kV and two various filters of aluminum and beryllium with thicknesses in the range of 0–2 mm.

Computational studies of impurity migration during induction stirring of molten uranium

Understanding and controlling impurity behavior in actinide metal casting processes are foundational for efficient part production yet remain major challenges for researchers and industry. To help provide insight regarding impurity distribution during actinide metal casting, we have developed computational fluid dynamics (CFD) models for a laboratory-scale system using commercial and open-source codes. This article describes multiple experiment-informed models designed to simulate a specific laboratory system in which uranium melt, containing a known starting concentration of carbon impurity, is electromagnetically stirred in an induction furnace. The goal of the simulations is to predict the motion of impurity particles in the form of uranium monocarbide in the velocity field of the melt. Prior to simulating the uranium–carbon system, numerical models were validated using a previously published nonradioactive experimental system. Effects of the size and shape of impurity particles in the models were investigated and agree with experimental findings. Simulation of smaller particles (less than 50 μm) shows more homogenous distribution throughout the stirred melt. With increased particle size (100 μm), the body forces, which include the buoyancy force, dominate over the drag force, causing larger particles to move toward the crucible walls and upward in the system.

Microchemistry evolution during industrial DC casting and subsequent homogenization of aluminum alloy AlMn0.5Mg0.5 (AA 3105)

The properties of non-heat treatable Al wrought alloys are influenced by the materials microchemistry in terms of the portion of alloying elements either in solid solution or in precipitated form. In the present study we analyze the phase selection during solidification as well as the changes in solute level and particle state during subsequent homogenization of the Al-Mn alloy AA 3105 (ISO AlMn0.5Mg0.5). Characterization of the microchemistry reactions is performed by a combination of optical and scanning electron microscopy with differential scanning calorimetry and measurements of thermoelectric power as well as specific electrical resistivity. The results are underpinned by CALPHAD simulations of the second-phase particles in the as-cast state, while the changes in solute level as well as volume, size and type of second-phase particles during homogenization are tracked with a statistical microchemistry simulation tool named ClaNG. Owing to the high Si content of the present alloy the as-cast state is dominated by α-Al(Fe,Mn)Si phase constituent particles together with a few Al6(Mn,Fe) and Mg2Si phases. Homogenization is characterized by the formation and redissolution of Mg2Si and, at higher temperatures, dispersoids of the α-Al(Fe,Mn)Si phase.

Increased flexibility and efficiency of a double-scattering FLASH proton beamline configuration for in vivo SOBP radiotherapy treatments

Objective. To commission a proton, double-scattering FLASH beamline by maximizing efficiency and field size, enabling higher-linear energy transfer FLASH radiotherapy to cells and small animals using a spread-out Bragg peak (SOBP) treatment configuration. We further aim to provide a configuration guide for the design of future FLASH proton double-scattering (DS) beamlines. Approach. Beam spot size and spread were measured with film and implemented into TOol for PArticle Simulation (TOPAS). Monte Carlo simulations were optimized to verify the ideal positioning, dimensions, and material of scattering foils, secondary scatterers, ridge filters, range compensators, and apertures. A ridge filter with three discrete heights was used to create a spread-out Bragg peak (SOBP) and was experimentally verified using our in-house experimental FLASH beamline. The increase in dose rate was compared to nominal shoot-through techniques. Results. The configuration and scatterer distance producing the largest field size of acceptable flatness, without drastically compromising dose rate was determined to be an elliptical field of 2 cm × 1.5 cm (25% larger than a previous configuration). SOBP testing yielded three distinct but connected spikes in dose with flatness under 5%. Reducing the thickness of the (first) scattering foil by a factor of two was found to increase efficiency by 50%. The new settings increased the field size, provided a Bragg peak treatment option, and increased the maximum available dose rate by 85%, as compared to the previous, shoot through method. Significance. Beam line updates established FLASH dose rates of over 135 Gy s−1 (potentially higher) at our double-scattering beamline, increased the efficiency and field size, and enabled SOBP treatments by incorporating an optimized ridge filter. Based on our simulations we provide parametric suggestions when commissioning a new proton DS beamline. This enhanced FLASH beamline for SOBP irradiations with higher dose rates and larger field sizes will enable a wider variety of experimentation in future studies.

Introduction to the Monte Carlo dose engine COMPASS for BNCT.

The Monte Carlo method is the most commonly used dose calculation method in the field of boron neutron capture therapy (BNCT). General-purpose Monte Carlo (MC) code (e.g., MCNP) has been used in most treatment planning systems (TPS) to calculate dose distribution, which takes overmuch time in radiotherapy planning. Based on this, we developed COMPASS (COMpact PArticle Simulation System), an MC engine specifically for BNCT dose calculation. Several optimization algorithms are used in COMPASS to make it faster than general-purpose MC code. The parallel computation of COMPASS is performed by the message passing interface (MPI) library and OpenMP commands, which allows the user to increase computational speed by increasing the computer configurations. The physical dose of each voxel is calculated for developing a treatment plan. Comparison results show that the computed dose distribution of COMPASS is in good agreement with MCNP, and the computational efficiency is better than MCNP. These results validate that COMPASS has better performance than MCNP in BNCT dose calculation.

The modification of roughness to corner effect in plasma etching

Plasma etching, a quite vital technique for transferring the mask pattern onto the substrate, is subjected to charging phenomena. Compared to the round contact-hole which has been studied by a great deal of previous research on the charging issues, the rectangle mask hole presents a significant corner effect. The case study here thus focuses on several kinds of isolated rectangle mask holes with various edge roughnesses and ratios of length (L) and width (W d). The modification of the roughness to the corner effect has been investigated using classical particle simulations, including a string algorithm for the evolution of the hole opening. This work shows that the corner effect becomes unobvious with the increase of the dominant amplitude and with the decrease of the wavelength of the roughness. In addition, the simulated results indicate that a small ratio (L: W d) can reduce the corner effect. Mechanisms behind these observations were explained mainly based on the analysis of the spatial electric field distribution as well as the opening evolution. This study would be beneficial for controlling the rectangle mask pattern transfer.

Stellar halo striations from assumptions of axisymmetry

ABSTRACT Motivated by the Large Magellanic Cloud (LMC)’s impact on the integral of motion space of the stellar halo, we run an N-body merger simulation to produce a population of halo-like stars. We subsequently move to a test-particle simulation, in which the LMC perturbs this debris. When an axisymmetric potential is assumed for the final snapshot of the N-body merger remnant, a series of vertical striations in (Lz, E) space form as the LMC approaches its pericentre. These result from the formation of overdensities in angular momentum owing to a relationship between the precession rate of near radial orbits and the torquing of these orbits by the LMC. This effect is heavily dependent on the shape of the inner potential. If a quadrupole component of the potential is included, these striations become significantly less apparent due to the difference in precession rate between the two potentials. The absence of these features in data, and the dramatic change in orbital plane precession rate, discourages the use of an axisymmetric potential for highly eccentric orbits accreted from a massive Gaia Sausage/Enceladus-like merger. Given the link the between appearance of these striations and the shape of the potential, this effect may provide a new method of constraining the axisymmetry of the halo.

MATILDA.FT: A mesoscale simulation package for inhomogeneous soft matter.

In this paper, we announce the public release of a massively parallel, graphics processing unit (GPU)-accelerated software, which is the first to combine both coarse-grained particle simulations and field-theoretic simulations in one simulation package. MATILDA.FT (Mesoscale, Accelerated, Theoretically Informed, Langevin, Dissipative particle dynamics, and Field Theory) was designed from the ground-up to run on CUDA-enabled GPUs with Thrust library acceleration, enabling it to harness the possibility of massive parallelism to efficiently simulate systems on a mesoscopic scale. It has been used to model a variety of systems, from polymer solutions and nanoparticle-polymer interfaces to coarse-grained peptide models and liquid crystals. MATILDA.FT is written in CUDA/C++ and is object oriented, making its source-code easy to understand and extend. Here, we present an overview of the currently available features, and the logic of parallel algorithms and methods. We provide the necessary theoretical background and present examples of systems simulated using MATILDA.FT as the simulation engine. The source code, along with the documentation, additional tools, and examples, can be found on the GitHub MATILDA.FT repository.

Breakage in quasi-static discrete element simulations of ice rubble

Breakage of particles plays a key role in force transmission in granular materials. Discrete element method (DEM) simulations are often used to model granular materials, but modeling particle breakage in them remains a challenge. Models for breakage of non-spherical particles are scarce and often the existing models are computationally heavy to be used in simulations with large numbers of particles. To address this, the present study develops a particle breakage model for quasi-static DEM simulations of non-spherical particles that fail due to shear. The model is novel, since it is based on experimental observations and high resolution modeling. Breakage models based on experimental evidence are rare as it is often virtually impossible to gain detailed data on the mechanisms related to breakage. The developed particle breakage model was integrated into a DEM code and direct shear box experiments on ice rubble, a granular material consisting of ice particles, were then simulated. Accounting for particle breakage in DEM simulations improved their accuracy: simulations were compared to experiments and the results were found to be in better agreement when particle breakage was taken into account. The effect of particle breakage on the shear strength of a granular material was found to be independent of particle size, decreasing fast with increasing particle strength. The combined effect of shear box length and breakage was also studied. The results showed that the strength of a granular material may be determined reasonably well with a shear box that has a box to particle length ratio greater than 60.

Evolution from the gradient drift instability to the formation of the spoke potential hump in a partially magnetized plasma

Rotating spokes commonly occur in partially magnetized plasma devices. This work explores the evolution from the gradient drift instability into an m = 1 rotating spoke mode in a magnetically enhanced hollow cathode discharge (with emissive cathode) by means of 2D radial-azimuthal particle-in-cell/Monte Carlo collision simulations. It is shown that the formation of the spoke potential hump region can be explained as a result of the local collapse of the anode sheath due to the gradient drift instability, which is triggered within the anode sheath. The sheath non-neutrality effect on the instability is considered and incorporated in the two-fluid linear theory of gradient drift instability. The unstable modes predicted by the theory are in good agreement with the fluctuation modes developed in the particle simulations.

Nonlinear Interaction of Low-frequency Alfvén Waves and Ions

The interaction between Alfvén waves and particles is a critical phenomenon in space and laboratory plasmas, and it has been observed that low-frequency Alfvén waves can accelerate and heat ions through subharmonic resonant interactions. In this study, we use test particle simulations to verify the nonlinear heating of parallelly propagating low-frequency Alfvén waves on ions and analyze the underlying process in terms of the Poincaré section. Our results demonstrate that low-frequency Alfvén waves can periodically pick up ions, leading to oscillations of average parallel velocity and temperature of the plasma by phase mixing, ultimately resulting in the stabilization of acceleration. Furthermore, we have developed an analysis that can estimate the time required for heating and accelerating. In the case of multiple waves, our findings indicate that the presence of more chaotic modes does not necessarily result in better wave heating. We have also discussed the effect of random phases on the heating process. Overall, this research sheds light on the crucial role played by the interaction between Alfvén waves and particles in astrophysics and provides new insights into the mechanisms underlying the heating and acceleration of ions through subharmonic resonant interactions with low-frequency Alfvén waves. These findings may have significant implications for the understanding of plasma dynamics in a range of astrophysical environments.

Unified stochastic particle simulation of polyatomic gas flows using SPARTACUS

Numerically simulating multiscale nonequilibrium gas flows that involve internal energy exchange is a challenging problem in engineering applications due to the complexity of the physical processes. The unified stochastic particle (USP) method, based on the Bhatnagar-Gross-Krook (BGK) model, is a promising approach for efficiently simulating multiscale flows. In this paper, we develop a USP method for polyatomic gases that can simulate hypersonic gas flows involving internal energy exchange across all flow regimes. This method is integrated into the open-source SPARTACUS solver, which was previously developed for monatomic gases. The newly developed USP method reassigns the velocity and internal energies of a subset of computational particles based on a precisely designed local target distribution function. A conservation algorithm is applied to ensure that the momentum and energy are conserved. To validate the accuracy and efficiency of the solver, we perform three benchmark cases, including flow past a two-dimensional cylinder, a three-dimensional 70° blunted cone, and an axisymmetric double cone configuration. The results demonstrate that SPARTACUS achieves excellent agreement with the reference results of DSMC and experimental data. Additionally, SPARTACUS provides significant computational efficiency advantages over the DSMC solver SPARTA, particularly in simulating three-dimensional gas flows.

A computational study of the influence of evaporation and molecular transport on temporally-evolving droplet-laden plane jets

Numerical simulations of temporally-evolving droplet-laden plane jets are performed in conditions relevant to rocket main engines fed with liquid oxygen (LOx) and gaseous methane (CH4). The computations are performed using a direct numerical simulation (DNS) solver with the liquid phase represented within the discrete particle simulation (DPS) framework. Considering the multiplicity of the physical phenomena that are involved in such conditions – e.g., atomization, dispersion, evaporation – a progressive and phenomenological methodology is retained to proceed with a complexity-increasing set of computations. Thus, the development of a purely gaseous jet is first studied with the corresponding set of data providing a reference or baseline condition. Then, other conditions are considered to analyze the influence of (i) liquid droplet evaporation and (ii) molecular mixing processes as described by two distinct multicomponent transport models. The analysis of the obtained results shows that both evaporation and molecular transport representation play a crucial role in the plane jet development and may drastically alter its characteristics before ignition and subsequent combustion stabilization may take place. Finally, the obtained results also unambiguously put into evidence the influence of the Lewis number onto the vaporization rate.

A physically consistent Discrete Element Method for arbitrary shapes using Volume-interacting Level Sets

The properties of granular materials depend strongly on the shapes of their individual constituent particles or granules. Nonetheless, incorporating the effects of non-spherical or complex particle shapes into existing modelling frameworks, such as the discrete element method (DEM), has remained challenging. In this work, we propose the volume-interaction level set DEM (VLS-DEM) approach for carrying out physically accurate simulations of particles with arbitrary geometries. VLS-DEM builds upon level set DEM (LS-DEM), both of which implicitly define the geometry of a particle through a discrete signed distance function. However, instead of using surface nodes to compute the interparticle forces, VLS-DEM uses the overlap volume as computed by an Octree integration algorithm. This addresses some of the shortcomings of LS-DEM in terms of the accuracy and precision of the shape description and opens up the possibility for bottom-up parametrisation methods. A number of tests were performed to compare VLS-DEM with regular DEM, LS-DEM, and analytical models. VLS-DEM is shown to give physically accurate results, comparable to analytical theory, even for highly complex systems such as those with concave interlocked particles.

A force–displacement relation based on the JKR theory for DEM simulations of adhesive particles

Studying the collective behavior of adhesive particles with the discrete element method (DEM) requires well-founded force–displacement relations (force models). While the Johnson–Kendall–Roberts (JKR) theory reliably predicts the dependence of the contact radius a on the force F, it has remained a challenge in this framework to obtain a straightforward force–displacement relation F(δ) with physically meaningful parameters to calculate the force F from the displacement δ. We derive a novel force–displacement relation from the JKR theory as a composition of functions F(δ)=(F∘a∘λ)(δ), with the intermediate functions contact radius a(λ) and effective adhesive contact radius λ(δ). We also analyze contact geometry errors in the Hertz and JKR models, derive the exact contact centroid to accurately calculate contact torques and relative tangential velocities, and propose a smoothed JKR model to avoid discontinuities in force and energy. We find that incorrect torques and relative tangential velocities are obtained when the stiffness quotient is neglected because it affects the exact location of the contact centroid. We also find that contact geometry errors can become non-negligible for nanoparticles due to their large relative contact size. In addition, we show from bouncing ball simulations that the JKR models with a nominal coefficient of restitution derived for the Hertz model result in higher damping and thus reduced actual coefficients of restitution. Our analysis serves as a foundation for contact-mechanics-based force models for DEM simulations of adhesive particles to investigate their collective behavior in the future.

Quantum simulation of fundamental particles and forces

Quantum simulation of fundamental particles and forces

Monte Carlo Simulation Study on the Optimal Neutron Energy and Boron Concentration for SARS-COV-2 Inactivation through BNCT

Researchers have been exploring various radiation therapies to treat COVID-19 patients ranging from mild to severe. One technique that has shown promise is Boron Neutron Capture Therapy (BNCT). This therapy involves administering of 10B isotope to the targeted area, which is then exposed to chargeless neutrons. These neutrons can be absorbed by areas with high concentrations of 10B. When the neutrons react with the 10B (10B + n?7Li + 4He reaction), it results in the transfer of highly ionizing energy, causing confined lethality and destroying the targeted area. In this study, we used the Particle and Heavy Ion Transport Code System simulation to evaluate whether Boron Neutron Capture Therapy could be effective as an anti-viral therapy. The study involves creating a model of the SAR-COV-2 target phantom's geometry and defining its chemical composition to collect data. It was found out that when tested at different neutron energies and concentrations (30 ppm, 50 ppm, and 100 ppm), a sufficient amount of dose to cause biological damage to the Sars-CoV-2 enveloped protein could be achieved with 30 ppm boron concentration and a neutron energy of 1.0x10-10 MeV.

Emergence of Adaptation of Collective Behavior Based on Visual Perception

Unmanned swarms are widespread used in the IoT. The ability of unmanned swarms to achieve adaptive collective behavior in complicated mission scenarios is a prerequisite for meeting mission objectives. However, classical collective behavior models often use the velocity and position of neighbors as inputs to be constructed from a phenomenological perspective. This complicates the construction of unmanned swarms and is incompatible with biological perception. Therefore, this paper proposes an Observation-Orientation-Decision-Action (OODA) framework for the construction of adaptive collective behavior based on visual perception, inspired by biological collective behavior formations. The model contains no explicit alignment, and no information exchange occurs between individuals. Instead, individuals make decisions based purely on the sight distance corresponding to different relative orientations. Based on adaptability evaluation metrics defined at the collective level, experiments including coordinated collective motion, single disturbed individual, single external disturbance, narrow passage, and multiple external disturbances scenarios show that the group can respond adaptively to different scenarios with a stable crystal structure while avoiding collisions. In addition to particle simulations, different scenarios provide validation using the Webots robot simulator. As a result, this approach compensates for the inadequacies of existing models and provides technical support for the application of unmanned swarms in various IoT scenarios.

A hybrid 1D-2D Lagrangian solver with moving coupling to simulate dam-break flow

In dam-break problems, two-dimensional (2D) models on the vertical plane appropriately capture the non-hydrostatic pressure distribution but with a high computational cost. This study presents a hybrid Lagrangian solver of one-dimensional (1D) shallow water flow and a 2D large-eddy simulation with a sub-particle scale to simulate dam-break flows over frictional beds. The proposed 1D-2D hybrid scheme is a useful trade-off between the accuracy of the 2D models on the vertical plane and the computational efficiency of 1D shallow water equations models. The configuration of sub-domains is established so that the 1D solves the regions with dominantly hydrostatic pressure, while the 2D solver accounts for the non-hydrostaticity. A moving coupling method is introduced based on two-layer shallow water equations with a uniform velocity distribution that constructs two sub-domains, including inner and outer zones in the section coupling model (SCM), or upper and lower layers within the layer coupling model (LCM). Then, the region with high vertical accelerations is substituted by the 2D model in the SCM or mixed SCM-LCM in which the overlapping zone and boundary interface move with time, based on the 1D flow feature. Also, a new method is proposed to deal with irregular boundary interfaces in the LCM while satisfying the momentum transfer. The present hybrid model is advantageous as it meets mass conservation, and there is no need for typical inflow/outflow boundary conditions at the coupling interfaces for simulating dam-break waves. Moving particle simulation (MPS) is utilized to solve the Lagrangian equations, which is advantageous in dealing with free-surface problems with large deformation. The model validation reveals that the hybrid results of water depths are in very good agreement with observed data and those obtained from the 2D model for selected dam-break flows with the ratio of initial depths downstream to upstream up to 0.4. In this respect, the average root-mean-square-error (RMSE) is computed at 8.09 mm in the SCM, 8.16 mm in the mixed SCM-LCM, and 7.48 mm in the pure 2D model, while both hybrid models save the computational time by 55% compared to the 2D model. Moreover, the mixed SCM-LCM preserves the nonlinearity of the wavefront over long times, whereas the SCM converts the wavefront into a shockwave considering the same number of fluid particles.

Cosmic rays and random magnetic traps.

The spatial distribution of cosmic ray (CR) particles in the interstellar medium (ISM) is of major importance in radio astronomy, where its knowledge is essential for the interpretation of observations, and in theoretical astrophysics, where CRs contribute to the structure and dynamics of the ISM. Local inhomogeneities in interstellar magnetic field strength and structure can affect the local diffusivity and ensemble dynamics of the CR particles. Magnetic traps (regions between magnetic mirrors located on the same magnetic line) can lead to especially strong and persistent features in the CR spatial distribution. Using test particle simulations, we study the spatial distribution of an ensemble of CR particles (both protons and electrons) in various magnetic field configurations, from an idealized axisymmetric trap to those that emerge in intermittent (dynamo-generated) random magnetic fields. We demonstrate that both the inhomogeneity in the CR sources and the energy losses by the CR particles can lead to persistent local inhomogeneities in the CR distribution and that the protons and electrons have different spatial distributions. Our results can have profound implications for the interpretation of the synchrotron emission from astronomical objects, and in particular its random fluctuations.