3D Monte Carlo Simulations Research Articles

The Potential of Detecting Radio-flaring Ultracool Dwarfs at L band in the FAST Drift-scan Survey

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) completed its commissioning and began the Commensal Radio Astronomy FasT Survey (CRAFTS), a multi-year survey to cover 60% of the sky, in 2020. We present predictions for the number of radio-flaring ultracool dwarfs (UCDs) that are likely to be detected by CRAFTS. Based on the observed flaring UCDs from a number of unbiased, targeted radio surveys in the literature, we derive a detection rate of ≥3%. Assuming a flat radio spectrum ν L ν ∝ ν β+1 with β = −1.0 for UCD flares, we construct a flare luminosity function (here L = ν L ν ). CRAFTS is found to be sensitive enough for flares from UCDs up to ∼180 pc. Considering the Galactic thin disk, we carry out a 3D Monte Carlo simulation of the UCD population, which is then fed to mock CRAFTS observations. We estimate that ∼170 flaring UCDs would be detected through transient searches in circular polarization. Though only marginally sensitive to the scale height of UCDs, the results are very sensitive to the assumed spectral index β. For β from 0 to −2.5, the number of expected detections increases dramatically from ∼20 to ∼3460. We also contemplate the strategies for following up candidates of flaring UCDs, and discuss the implications of survey results for improving our knowledge of UCD behavior at L band and dynamos.

Transient Monte Carlo simulations for the optimisation and characterisation of monolithic silicon sensors

An ever-increasing demand for high-performance silicon sensors requires complex sensor designs that are challenging to simulate and model. The combination of electrostatic finite element simulations with a transient Monte Carlo approach provides simultaneous access to precise sensor modelling and high statistics. The high simulation statistics enable the inclusion of Landau fluctuations and production of secondary particles, which offers a realistic simulation scenario. The transient simulation approach is an important tool to achieve an accurate time-resolved description of the sensor, which is crucial in the face of novel detector prototypes with increasingly precise timing capabilities. The simulated time resolution as a function of operating parameters as well as the full transient pulse can be monitored and assessed, which offers a new perspective for the optimisation and characterisation of silicon sensors.In this paper, a combination of electrostatic finite-element simulations using 3D TCAD and transient Monte Carlo simulations with the Allpix2 framework are presented for a monolithic CMOS pixel sensor with a small collection electrode, that is characterised by a highly inhomogeneous, complex electric field. The results are compared to transient 3D TCAD simulations that offer a precise simulation of the transient behaviour but long computation times. Additionally, the simulations are benchmarked against test-beam data and good agreement is found for the performance parameters over a wide range of different operation conditions.

Comparison of photon transport efficiency in simple scintillation electron detector configurations for scanning electron microscope.

The purpose of this paper is to find some general rules for the design of robust scintillation electron detectors for a scanning electron microscope (SEM) that possesses an efficient light-guiding (LG) system. The paper offers some general instructions on how to avoid the improper design of highly inefficient LG configurations of the detectors. Attention was paid to the relevant optical properties of the scintillator, light guide, and other components used in the LG part of the scintillation detector. Utilizing the optical properties of the detector components, 3D Monte Carlo (MC) simulations of photon transport efficiency in the simple scintillation detector configurations were performed using the computer application called SCIUNI to assess shapes and dimensions of the LG part of the detector. The results of the simulation of both base-guided signal (BGS) configurations for SE detection and edge-guided signal (EGS) configurations for BSE detection are presented. It is demonstrated that the BGS configuration with a matted disc scintillator exit side connected to the cylindrical light guide without optical cement is almost always a sufficiently efficient system with a mean LG efficiency of about 20%. It is simulated that poorly designed EGS strip configurations have an extremely low mean LG efficiency of only 0.01%, which can significantly reduce detector performance. On the other hand, no simple nonoptimized EGS configuration with a light guide widening to a circular or square profile, with a polished cemented scintillator and with an indispensable hole in it has a mean LG efficiency lower than 6.5%.

3D Monte-Carlo simulation of Ganymede’s water exosphere

In this paper we present ab initio 3D Monte-Carlo simulations of Ganymede’s surface sputtered and sublimated H2O exosphere. As inputs, we include surface water content maps and temperature distribution maps based on Galileo and Very Large Telescope (VLT) observations. For plasma precipitation, we use hybrid model results for thermal H+ and O+, energetic H+, O++, S+++, and electrons, with unprecedented energy resolution. Our results show that up to a solar zenith angle of ∼60° and up to ∼600 km altitude, sublimated H2O dominates the atmosphere by up to four orders of magnitudes in number density, while sputtering dominates elsewhere. Sputtering is mainly induced by the impinging O+, O++, and S+++ ions, while protons (H+) and electrons only add about 1% of the total sputtered H2O molecules to the atmosphere. Electrons are thus not important for the generation of the atmosphere, but they are important for spectroscopic observability of the atmosphere since they are the main inducer of the Lyman-α and O I emission lines. The extended H2O atmosphere at altitudes ≳1 Ganymede radius is mainly the result of sputtering by thermal O+ ions, which is the only ion species with substantial fluxes in the low-energy range (10 eV–10 keV), i.e., is the only species that efficiently induces nuclear sputtering. Most released H2O molecules return to the surface where they immediately adsorb, not forming a thermalized atmosphere. The morphology of Ganymede’s magnetosphere, and the resulting dichotomies in the surface fluxes of the precipitating magnetospheric particles (polar fluxes > equatorial fluxes and leading equatorial fluxes > trailing equatorial fluxes), are thus well discernible in the sputtered atmosphere, persisting up to altitudes of a few thousand kilometers. In-situ measurements, as they are planned for the upcoming JUpiter ICy Moons Explorer (JUICE) mission, will mainly probe this sputtered atmosphere, except for encounters with the near-surface atmosphere on Ganymede’s day-side, where the sublimated atmosphere will be probed instead. Finally, we compare our model results to the first observational evidence for a sublimated H2O atmosphere on Ganymede, and find a very good agreement.

A simulation study investigating potential diffusion-based MRI signatures of microstrokes

Recent studies suggested that cerebrovascular micro-occlusions, i.e. microstokes, could lead to ischemic tissue infarctions and cognitive deficits. Due to their small size, identifying measurable biomarkers of these microvascular lesions remains a major challenge. This work aims to simulate potential MRI signatures combining arterial spin labeling (ASL) and multi-directional diffusion-weighted imaging (DWI). Driving our hypothesis are recent observations demonstrating a radial reorientation of microvasculature around the micro-infarction locus during recovery in mice. Synthetic capillary beds, randomly- and radially-oriented, and optical coherence tomography (OCT) angiograms, acquired in the barrel cortex of mice (n = 5) before and after inducing targeted photothrombosis, were analyzed. Computational vascular graphs combined with a 3D Monte-Carlo simulator were used to characterize the magnetic resonance (MR) response, encompassing the effects of magnetic field perturbations caused by deoxyhemoglobin, and the advection and diffusion of the nuclear spins. We quantified the minimal intravoxel signal loss ratio when applying multiple gradient directions, at varying sequence parameters with and without ASL. With ASL, our results demonstrate a significant difference (p < 0.05) between the signal-ratios computed at baseline and 3 weeks after photothrombosis. The statistical power further increased (p < 0.005) using angiograms measured at week 4. Without ASL, no reliable signal change was found. We found that higher ratios, and accordingly improved significance, were achieved at lower magnetic field strengths (e.g., B0 = 3T) and shorter echo time TE (< 16 ms). Our simulations suggest that microstrokes might be characterized through ASL-DWI sequence, providing necessary insights for posterior experimental validations, and ultimately, future translational trials.

The nonlinear synergistic enhancement electric conductive effect in polymer-matrix composites containing hybrid fillers of carbon nanotubes and graphene nanoplatelets

Polymer-matrix composites containing hybrid fillers can exhibit electric performance due to synergistic conductive effect. In this work, the nonlinear synergistic enhancement electric conductive effect (NSECE) in nanocomposites containing carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) is studied by the 3D Monte Carlo simulation. The 3D model with random distribution based on tunnel theory for nanocomposites filled with cylindrical CNTs and disc-shaped GNPs is developed. The morphology of CNTs and GNPs are researched for the NSECE in percolation threshold. The results show that the reason of NSECE is the different network construction ability of CNTs and GNPs with different morphology. When the monofiller nanocomposites of each of those exact fillers have similar percolation thresholds and the length of CNTs is smaller than the diameter of GNPs, hybrid nanocomposites filled with CNTs and GNPs is more likely to exhibit NSECE in their electrical performance.

Stochastic finite element model assessing length effect for unreinforced masonry walls subjected to one-way vertical bending under out-of-plane loading

The strength of unreinforced masonry (URM) walls subjected to one-way vertical bending under out-of-plane loading (no pre-compression) is known to be affected by the tensile bond strength. Factors such as batching, workmanship, and environmental exposure alter the strength of this bond, resulting in spatial variability for any URM assembly. In narrow wall panels a single weak joint may dictate the failure load of a masonry wall, whereas for longer walls there is higher potential for weak joints to occur and load redistribution. This paper focuses on a stochastic assessment of clay brick URM walls with spatially variable tensile bond strength subjected to uniformly distributed out-of-plane loads in one-way vertical bending and assessing the effect of wall length on the ultimate failure load. Stochastic computational modelling combining 3D non-linear Finite Element Analysis (FEA) and Monte Carlo Simulation (MCS) is used to account for bond strength variability when estimating the walls ultimate failure loads. For this assessment FEA MCS has been applied to a set of existing test data for walls 1, 2, 4, and 10 units long, by ten different masons. Models were also developed to consider walls in the intermediate length range, 7 units long, and walls outside of this range, 15 units long. For each set of simulations the peak pressure and load–displacement data was extracted and analysed, showing agreement with the results of wall test data. The panel strength is shown to increase with wall length from 1 to 4 units, then stabilize with further length increase. The variability of the failure load is shown to decrease with increasing wall length.

Deuterium‐tritium fuel impact ignition in the presence of degenerate plasma

AbstractThe impact ignition model is proposed based on the collision of a deuterium‐tritium (DT) layer accelerated to high velocities in a conical target. Simple mechanism, low cost, high coupling efficiency, and lack of the need for Petawatt laser pulses are the prominent advantages of this model. However, an increase in the productivity of this ignition mechanism is an important issue. In this regard, in this paper, the idea of impact ignition using the plasma degeneracy mechanism has been investigated. For this purpose, first, the ignition energy gain and stopping power of the DT beam in pure and impure fuels, by employing both degenerate and non‐degenerate plasmas, have been examined numerically. Then, in order to assess the penetration depth and range of the incident beam, simulations have been carried out using a three‐dimensional (3D) Monte Carlo code for two states of degenerate and non‐degenerate pre‐compressed pure fuel. The results imply that the state of degeneracy causes an increase by about 63% in the energy gain of impact ignition. In addition, the degeneracy condition leads to an approximate enhancement of 60% in the energy deposition of the pure fuel and about 67% for the impure fuel, with a mixed density ratio of 1.5%; therefore, the range and penetration depth decrease significantly in comparison to the non‐degenerate one. This can be indicative of the increasing efficiency of impact ignition conditions in the presence of degenerate plasma. The results of the range for the pure fuel have also been confirmed by a 3D Monte Carlo simulation code.

Confidence Sets for Cohen’s d effect size images

Current statistical inference methods for task-fMRI suffer from two fundamental limitations. First, the focus is solely on detection of non-zero signal or signal change, a problem that is exacerbated for large scale studies (e.g. UK Biobank, N=40,000+) where the ‘null hypothesis fallacy’ causes even trivial effects to be determined as significant. Second, for any sample size, widely used cluster inference methods only indicate regions where a null hypothesis can be rejected, without providing any notion of spatial uncertainty about the activation. In this work, we address these issues by developing spatial Confidence Sets (CSs) on clusters found in thresholded Cohen’s d effect size images. We produce an upper and lower CS to make confidence statements about brain regions where Cohen’s d effect sizes have exceeded and fallen short of a non-zero threshold, respectively. The CSs convey information about the magnitude and reliability of effect sizes that is usually given separately in a t-statistic and effect estimate map. We expand the theory developed in our previous work on CSs for %BOLD change effect maps (Bowring et al., 2019) using recent results from the bootstrapping literature. By assessing the empirical coverage with 2D and 3D Monte Carlo simulations resembling fMRI data, we find our method is accurate in sample sizes as low as N=60. We compute Cohen’s d CSs for the Human Connectome Project working memory task-fMRI data, illustrating the brain regions with a reliable Cohen’s d response for a given threshold. By comparing the CSs with results obtained from a traditional statistical voxelwise inference, we highlight the improvement in activation localization that can be gained with the Confidence Sets.

Reliability of fNIRS for noninvasive monitoring of brain function and emotion in sheep

The aim of this work was to critically assess if functional near infrared spectroscopy (fNIRS) can be profitably used as a tool for noninvasive recording of brain functions and emotions in sheep. We considered an experimental design including advances in instrumentation (customized wireless multi-distance fNIRS system), more accurate physical modelling (two-layer model for photon diffusion and 3D Monte Carlo simulations), support from neuroanatomical tools (positioning of the fNIRS probe by MRI and DTI data of the very same animals), and rigorous protocols (motor task, startling test) for testing the behavioral response of freely moving sheep. Almost no hemodynamic response was found in the extra-cerebral region in both the motor task and the startling test. In the motor task, as expected we found a canonical hemodynamic response in the cerebral region when sheep were walking. In the startling test, the measured hemodynamic response in the cerebral region was mainly from movement. Overall, these results indicate that with the current setup and probe positioning we are primarily measuring the motor area of the sheep brain, and not probing the too deeply located cortical areas related to processing of emotions.

Validation of 4D Monte Carlo dose calculations using a programmable deformable lung phantom

PurposeTo validate the accuracy of 4D Monte Carlo (4DMC) simulations to calculate dose deliveries to a deforming anatomy in the presence of realistic respiratory motion traces. A previously developed deformable lung phantom comprising an elastic tumor was modified to enable programming of arbitrary motion profiles. 4D simulations of the dose delivered to the phantom were compared with the measurements. MethodsThe deformable lung phantom moving with irregular breathing patterns was irradiated using static and VMAT beam deliveries. Using the RADPOS 4D dosimetry system, point doses were measured inside and outside the tumor. Dose profiles were acquired using films along the motion path of the tumor (S-I). In addition to dose measurements, RADPOS was used to record the motion of the tumor during dose deliveries. Dose measurements were then compared against 4DMC simulations with EGSnrc/4DdefDOSXYZnrc using the recorded tumor motion. ResultsThe agreements between dose profiles from measurements and simulations were determined to be within 2%/2 mm. Point dose agreements were within 2σ of experimental and/or positional/dose reading uncertainties. 4DMC simulations were shown to accurately predict the sensitivity of delivered dose to the starting phase of breathing motions. We have demonstrated that our 4DMC method, combined with RADPOS, can accurately simulate realistic dose deliveries to a deforming anatomy moving with realistic breathing traces. This 4DMC tool has the potential to be used as a quality assurance tool to verify treatments involving respiratory motion. Adaptive treatment delivery is another area that may benefit from the potential of this 4DMC tool.

Attachment characteristics of charged magnetic cubic particles to two parallel electrodes (3D Monte Carlo simulations)

ABSTRACT The cubic particles magnetised along a diagonal direction are negatively charged and confined between two parallel electrode walls. These particles have a tendency to migrate toward and attach to the positive electrode together with the formation of chain-like clusters. We here have focused on three cases of external magnetic field direction. In the case of an external magnetic field applied in the oblique direction to the electrode wall, almost all the constituent particles of the chain-like clusters attach to the positive electrode wall in a face-to-face contact manner. In the case of an external magnetic field applied along the surface of the electrode wall, the chain-like clusters are formed in the space of the two parallel walls. In the case of an external magnetic field applied normal to the electrode wall, the tendency for the particles to form chain-like clusters along the electrode wall is the weaker among the three field directions. In this situation, the cubic particles attach to the wall surface with a vertex of the cube contacting with the surface, and from the anchored particle, a chain-like cluster is formed in the space between the two parallel walls.

3D Monte Carlo simulation of light distribution in mouse brain in quantitative photoacoustic computed tomography.

Photoacoustic computed tomography (PACT) detects light-induced ultrasound (US) waves to reconstruct the optical absorption contrast of the biological tissues. Due to its relatively deep penetration (several centimeters in soft tissue), high spatial resolution, and inherent functional sensitivity, PACT has great potential for imaging mouse brains with endogenous and exogenous contrasts, which is of immense interest to the neuroscience community. However, conventional PACT either assumes homogenous optical fluence within the brain or uses a simplified attenuation model for optical fluence estimation. Both approaches underestimate the complexity of the fluence heterogeneity and can result in poor quantitative imaging accuracy. To optimize the quantitative performance of PACT, we explore for the first time 3D Monte Carlo (MC) simulation to study the optical fluence distribution in a complete mouse brain model. We apply the MCX MC simulation package on a digital mouse (Digimouse) brain atlas that has complete anatomy information. To evaluate the impact of the brain vasculature on light delivery, we also incorporate the whole-brain vasculature in the Digimouse atlas. k-wave toolbox was used to investigate the effect of inhomogeneous illumination on the reconstructed images and chromophore concentration estimation. The simulation results clearly show that the optical fluence in the mouse brain is heterogeneous at the global level and can decrease by a factor of five with increasing depth. Moreover, the strong absorption and scattering of the brain vasculature also induce the fluence disturbance at the local level. Both global and local fluence heterogeneity contributes to the reduced quantitative accuracy of the reconstructed PACT images of mouse brain. Correcting the optical fluence distribution can improve the quantitative accuracy of PACT.

Simulations of Fusion Power Measurements by Monitors of Neutron Flux in Evolving ITER Plasma

We describe the synthetic diagnostics (SD) of the preliminary design of divertor neutron flux monitor (DNFM) dedicated for simulations of the neutron flux measurements in ITER. It is based on the technique developed for fast simulation of plasma evolution keeping the accuracy of comprehensive 3D Monte Carlo simulations. The developed technique is also applicable to simulations of diagnostics signals for a range of neutron and optical diagnostics in tokamak plasmas and enables fast simulations of the local radiation fields and diagnostic signals for arbitrarily distributed volumetric sources. The capabilities of the DNFM SD are demonstrated for simulations of the ITER baseline scenario.

Spatial confidence sets for raw effect size images

The mass-univariate approach for functional magnetic resonance imaging (fMRI) analysis remains a widely used statistical tool within neuroimaging. However, this method suffers from at least two fundamental limitations: First, with sufficient sample sizes there is high enough statistical power to reject the null hypothesis everywhere, making it difficult if not impossible to localize effects of interest. Second, with any sample size, when cluster-size inference is used a significant p-value only indicates that a cluster is larger than chance. Therefore, no notion of confidence is available to express the size or location of a cluster that could be expected with repeated sampling from the population.In this work, we address these issues by extending on a method proposed by Sommerfeld et al. (2018) (SSS) to develop spatial Confidence Sets (CSs) on clusters found in thresholded raw effect size maps. While hypothesis testing indicates where the null, i.e. a raw effect size of zero, can be rejected, the CSs give statements on the locations where raw effect sizes exceed, and fall short of, a non-zero threshold, providing both an upper and lower CS.While the method can be applied to any mass-univariate general linear model, we motivate the method in the context of blood-oxygen-level-dependent (BOLD) fMRI contrast maps for inference on percentage BOLD change raw effects. We propose several theoretical and practical implementation advancements to the original method formulated in SSS, delivering a procedure with superior performance in sample sizes as low as N=60. We validate the method with 3D Monte Carlo simulations that resemble fMRI data. Finally, we compute CSs for the Human Connectome Project working memory task contrast images, illustrating the brain regions that show a reliable %BOLD change for a given %BOLD threshold.

Electron beam lithography on curved or tilted surfaces: Simulations and experiments

There is a growing interest for patterning on curved or tilted surfaces using electron beam lithography. Computational proximity correction techniques are well established for flat surfaces and perpendicular exposure, but for curved and tilted surfaces adjustments are needed as the dose distribution is no longer cylindrically symmetric with respect to the surface normal. A graphical processing unit -accelerated 3D Monte Carlo simulation, based on first-principle scattering models, is used to simulate the asymmetric dose distribution. Based on that, an approximate adjustment is made to an existing high-performance proximity effect correction (PEC) algorithm aimed at the correct exposure of a pattern of nanowires on a 17° tilted surface. It was experimentally verified that using the adjusted PEC indeed leads to a more uniform exposure on tilted surfaces.

Electrical percolation of silicone rubber filled by carbon black and carbon nanotubes researched by the Monte Carlo simulation

ABSTRACTElectrical percolation of carbon black (CB) and carbon nanotubes (CNTs) filled into silicone rubber (SR) is analyzed by the three‐dimensional (3D) Monte Carlo simulation. First, the 3D models and simulation parameters of CB and CNTs are researched to narrow the deviation between simulation and experimental results of CB/SR and CNTs/SR. The degree of agglomeration is the most important parameter in simulation for CB. The 3D model of CNTs is the most important factor in simulation for CNTs. Then, the 3D Monte Carlo simulation for CB/CNTs/SR is developed based on the optimized 3D models and parameters of CB and CNTs. The results yielded by the simulation with optimized parameters are similar to the experiments and synergistic conductive effect of two hybrid fillers in nanocomposites exists. This work has demonstrated that the quantification of the electrical percolation of two hybrid fillers in nanocomposites by Monte Carlo simulation is feasible. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 48222.

Quantitative Reconstruction of Absorption Coefficients for Photoacoustic Tomography

Photoacoustic (PA) tomography (PAT) is a cutting-edge imaging modality for visualizing the internal structure and light-absorption distribution in tissue. However, reconstruction of the absorption distribution has been limited by nonuniform light fluence. This paper introduces a novel method for quantitative reconstruction of the distribution of optical absorption coefficients in tissue. In this method, we implement an iterative algorithm for recovering absorption coefficients from optical absorbed energy maps based on a 3D Monte Carlo simulation of light transport and integrated with fluence compensation to obtain the initialization parameters. In the iteration algorithm, we calculate the deviation between the detected and the computed absorbed energy distribution at each iteration. By minimizing the deviation in the absorbed energy, the recovered values converge to the true absorption distribution. The results of numerical simulation and phantom experiment theoretically and experimentally demonstrate that the proposed method performs an accurately quantitative estimate of the distribution of optical absorption coefficients. This work expects to provide accurate quantitative information for absorbers within tissues or organs, and thereby broaden the clinical applications of PAT.

The potential of scalability in high efficiency hybrid perovskite thin film luminescent solar concentrators

Hybrid metal-halide perovskite (PVSK) thin films have recently demonstrated exciting potential as candidates for broadband luminescent solar concentrators (LSCs). Here, we examine the correlation between film thickness, lead halide sources in the precursors, and film morphology, with the optical efficiency of planar PVSK LSCs with a view to optimizing device performance. After synthesizing and testing sixteen different types of PVSK samples, we report a maximum optical efficiency of 34.7% in CH3NH3PbI3 LSC made with Pb(Ac)2 precursor, and with optimal thickness in the 150–300 nm range. Using 3D Monte Carlo simulations that incorporate experimental results, we accurately estimate self-absorption and surface losses, and most importantly, demonstrate the possibility of scaling these LSCs up to almost 100 cm, thereby providing a route toward optimizing thin film PVSK materials for these and other optoelectronic and photovoltaic applications.

Electron-Induced Effects at Diagnostics and Modification of Ferroelectrics: Mathematical Modelling, Simulation and Optimal Control

The paper is devoted to developing the theoretical basis of the mathematical modelling and computer simulation intended to analyze and control the electron beam-stimulated effects in ferroelectric materials. In order to simulate the electron beam-induced charging dynamics of ferroelectrics the modification of drift-reaction-diffusion model was proposed. The calculation was based on the numerical solution of the continuity equation and Poisson equation. The parameters of the electron irradiation doze and source function were estimated by 3D Monte-Carlo simulation of electron trajectories in the solid specimen. The computation was associated with typical ferroelectrics (LiNbO3, LiTaO3) irradiated by intermediate-energy electron bunches specified for SEM. The contribution roles of drift component as well as diffusion component during dynamic charging process were discussed. The simulation results enable us to predict charge distribution, dynamic of the potential distribution, electric field and electron beam-induced component of polarization at the given experimental parameters. These findings can be used to control polarization switching in ferroelectrics electron beam-irradiated by the SEM techniques.