Monte Carlo modeling and simulation of electron beam irradiation optimization for screwworm fly eradication through sterile insect technique
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Mulyana, Dany (ORCID:0000000307143306)↗
SEARCH · Engineering Papers
Results for “Electron Beam Modeling and Simulation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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3D Nanoprinting Replication Enhancement Using a Simulation-Informed Analytical Model for Electron Beam Exposure Dose Compensation
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Physics-constrained machine learning for electrodynamics without gauge ambiguity based on Fourier transformed Maxwell’s equations
We utilize a Fourier transformation-based representation of Maxwell’s equations to develop physics-constrained neural networks for electrodynamics without gauge ambiguity, which we label the Fourier–Helmholtz–Maxwell neural operator method. In this approach, both of Gauss’s laws and Faraday’s law are built in as hard constraints, as well as the longitudinal component of Ampère–Maxwell in Fourier space, assuming the continuity equation. An encoder–decoder network acts as a solution operator for the transverse components of the Fourier transformed vector potential, $\hat{A}_⟂(k,t)$, whose two degrees of freedom are used to predict the electromagnetic fields. This method was tested on two electron beam simulations. Among the models investigated, it was found that a U-Net architecture exhibited the best performance as it trained quicker, was more accurate and generalized better than the other architectures examined. We demonstrate that our approach is useful for solving Maxwell’s equations for the electromagnetic fields generated by intense relativistic charged particle beams and that it generalizes well to unseen test data, while being orders of magnitude quicker than conventional simulations. We show that the model can be re-trained to make highly accurate predictions in as few as 20 epochs on a previously unseen data set.
97 MATHEMATICS AND COMPUTING↗
Self-Consistent Relativistic Electron Scattering using the Sherlock Scattering Model for X-ray Diagnostics
We present on a new, self-consistent, arbitrary-temperature Romberg integration scheme for modeling electron scattering in materials in a LANL Lagrangian Shock Hydro (LSH) code. Electron beam-target interactions are fundamental to a wide range of scientific and technological applications. When high-energy electron beams hit their target, they may scatter, deposit energy, or ionize the source. These processes govern the behavior and outcomes in nanotechnology manufacturing, electron microscopy, and modern X-ray diagnostics. Simulating these interactions is essential for interpreting experimental results, predicting material responses, and designing efficient tools and experiments. At Los Alamos, this is done using a LSH code, which is a multi-dimension, multi-material, massively parallel, multi-physics code used to simulate applications from asteroid impacts to electron beam interactions. By effectively and efficiently modeling the way that electrons scatter from the beam we can bolster these simulations and more accurately predict experimental outcomes. The model currently implemented in the LSH of interest is based on work by Papp and does not self-consistently preserve momentum in the slightly relativistic regime; here we adopt a model proposed by Braams and Karney and implement a Romberg integration scheme to compute the diffusion tensor. In this paper we will provide background on the Braams-Karney diffusion tensor as well as the Romberg integration scheme we employed to numerically solve for it. We will show that our integration scheme is accurate in solving for the set of scalar potentials used to re-express the diffusion tensor in differential form, and in solving for the diffusion coefficients in the larger LSH code. By using this diffusion tensor rather than the existing Papp one, and numerically integrating it with a Romberg method, we produce much more accurate, self-consistent results.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Latest Updates on JSPEC - An IBS and Electron Cooling Simulation Program
JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab, which simulates the evolution of the ion beam under the influence of both IBS and electron cooling effects. In this paper, we will report the latest updates to JSPEC. Firstly, we have added theoretical and numerical models that simulate the effect of the electron beam dispersion on non-magnetized cooling. Secondly, the cooler can now be treated as an element with length, rather than a thin lens. This change will impact the modelling of the ions and the electrons in the cooling rate calculation for both magnetized and non-magnetized cooling. Numeri-cal results will be provided to demonstrate the perfor-mance of the new models.
Zhang, H.↗
Summer Student Internship: Experimental and modeling experiences
My internship at the Los Alamos National Laboratory has been an information-filled summer. Loren Espada-Castillo brought me into her project and helped mentor and guide me through the summer. The project that I was brought into was the process of shooting materials with electrons. The electron beam we used conducts a series of shots in which electrons are generated and then fired towards a target, the sample holder. The sample holder holds either a single sample or three samples. The sample holder also consists of multiple calorimeters surrounding the sample/s. The goal is to shoot certain materials and then analyze how they react to the exposure of the electrons. We shot titanium, which was meant to serve as a containment vessel window.
36 MATERIALS SCIENCE↗
Full wave modeling of radio-frequency beams in tokamaks in the electron cyclotron frequency range
Simulation of full wave, without paraxial approximation, high-resolution solution of wave equations in frequency domain in the electron cyclotron resonance (ECR) frequency range for realistic Tokamak plasma parameters became possible by using recently formulated hybrid iterative algorithm [Svidzinski et al., Phys. Plasmas 25, 082509 (2018)] for numerically solving discretized wave equations. This approach combines time evolution and iterative relaxation techniques into iteration cycles. This algorithm is implemented in 2D code FullWave, solving wave equations in Tokamaks in cold and hot plasma models, and it has been tested in 3D full wave iterative RF beams simulation tool, which is presently being developed to model 3D ECRH RF beams in fusion devices using dynamic grid adaptation. The results of 2D full wave modeling, assuming specified toroidal mode number, of ECRH RF beams in DIII-D plasma, performed in the cold and hot plasma models for outboard and top launch scenarios using FullWave are presented. Nonlocal hot plasma response model, based on accurate numerical solution of linearized Vlasov equation, is used to model beam propagation and absorption in the 2nd electron cyclotron harmonic region. Demonstration of capability of the hybrid iterative algorithm to model ECRH RF beams in 3D is made by simulating a substantial part of realistic beam in DIII-D, launched from outboard side of the machine. All relevant physics of RF beam propagation, most of which is not captured in paraxial approximation, such as beam's divergence, interference between the X and O modes in the beam, X-O mode conversion, beam splitting into the X and O mode beams, transformation of beam's cross section, and absorption at the 2nd electron cyclotron harmonic, is captured in the simulations. A numerical technique to find an optimal beam polarization at the launcher to launch a nearly pure X or O mode beam in plasma is developed and tested.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Study of Particle Loss in Synchrotron Phase Space Injection for ESR Using Weak-Strong Beam-Beam Simulation with Nonlinear Lattice
In this report, we use tracking simulations to investigate synchrotron phase space injection for electron accumulation in the electron storage ring of the Electron Ion Collider. Our simulation model accounts for both beam-beam interactions and lattice nonlinearities. Specifically, we examine how particle loss is influenced by various parameters. Additionally, we conduct a theoretical analysis and derive an analytical formula for the rapid evaluation of particle loss. Our results demon strate the feasibility of synchrotron phase-space injection for the electron storage ring and provide insights to guide parameter selection for the design of the injection line.
43 PARTICLE ACCELERATORS↗
Experimental study of energy-dependent angular broadening of MeV electron beams for high-resolution imaging in thick samples
In scanning transmission electron microscopy (STEM), spatial resolution is primarily influenced by the projected size of the electron probe within the specimen. In thin samples, a large semi-convergence angle enables a tightly focused beam and sub-nanometer resolution. However, in thick specimens, resolution is fundamentally limited by transverse beam broadening from multiple large-angle scattering events—for example, a probe with 10 mrad angular divergence can broaden by ∼100 nm over a 10 μm path. Since this broadening scales inversely with beam energy, MeV-STEM offers a promising route for high-resolution imaging in thick materials. To quantitatively assess this effect, we performed high-precision measurements at UCLA’s PEGASUS beamline, characterizing beam divergence and intensity profiles for 3–8 MeV electrons transmitted through a wedged-silicon sample of varying thickness. Our results reconcile discrepancies among analytical models and validate Monte Carlo simulations. Here, we find that increasing beam energy from 3.0 to 5.8 MeV reduces angular broadening by a factor of 2.6, with diminishing returns observed at 7.6 MeV. These findings provide a quantitative framework for optimizing MeV-STEM parameters in high-resolution imaging of thick biological and microelectronic specimens, and for guiding beam energy selection in other advanced imaging modes beyond STEM.
36 MATERIALS SCIENCE↗
Modeling electron beam irradiation of methane
We built a chemical kinetic model for the electron beam irradiation of methane and report simulation results with dose rates ranging from 2 to 200 kGy s -1 at 298 K and 1 atm pressure. The model contains 92 species and 778 gas-phase reactions. We report the time evolution of concentrations of stable products (including H 2 , C 2 H 6 , C 3 H 8 , C 2 H 4 , C 3 H 6 , C 4 H 10 , C 2 H 2 , and C 3 H 4 ) as well as some radicals and ions. Here we discuss how yields of products depend on dose rate and how they change during the course of irradiation. To understand the processes controlling product formation, we quantify the extent to which various reactions produce and destroy major products and the key radicals and ions. Normalized sensitivity coefficients are computed for the production of stable products to gain further insight into factors controlling product yields. We were able to reduce the mechanism to 63 species and 331 reactions while incurring less than 5% error in the final concentrations of stable products.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Diffusion model approach to simulating electron-proton scattering events
Generative artificial intelligence is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for simulating electron-proton collisions relevant to experiments like the Continuous Electron Beam Accelerator Facility and the future Electron-Ion Collider (EIC). These experiments play a critical role in advancing our understanding of nucleons and nuclei in terms of quark and gluon degrees of freedom. The use of generative models for simulating collider events faces several challenges such as the sparsity of the data, the presence of global or eventwide constraints, and steeply falling particle distributions. In this work, we focus on the implementation of diffusion models for the simulation of electron-proton scattering events at EIC energies. Our results demonstrate that diffusion models can reproduce relevant observables such as momentum distributions and correlations of particles, momentum sum rules, and the leading electron kinematics, all of which are of particular interest in electron-proton collisions. Although the sampling process is relatively slow compared to other machine-learning architectures, we find diffusion models can generate high-quality samples. We foresee various applications of our work including inference for nuclear structure, interpretable generative machine learning, and searches of physics beyond the Standard Model. Published by the American Physical Society 2024
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Characterization of uncertainties in electron-argon collision cross sections
Abstract The predictive capability of a plasma discharge model depends on accurate representations of electron-impact collision cross sections, which determine the corresponding reaction rates and electron transport properties. The values of cross sections can be known only approximately either through experiments or simulations and are thus subject to uncertainties. Quantifying the uncertainties in plasma simulations allows us to assess the reliability of simulations and to provide a basis for interpreting discrepancies between simulations and experiments. For such uncertainty quantification of plasma simulations, it is essential to quantify the uncertainties of the underlying cross sections. Although much effort has been committed to calibrate the cross section values, their uncertainties are not well investigated. We characterize uncertainties in electron-argon atom collision cross sections using a Bayesian framework. Six collision processes—elastic momentum transfer, ionization, and four excitations—are characterized with semi-empirical models, which effectively capture the features important to the macroscopic properties of the plasma. A probability model for the uncertain parameters of these semi-empirical models is developed. Specifically, a Gaussian-process likelihood model is proposed to capture discrepancies among data sets, as well as the model-form inadequacies of the semi-empirical models. Two other likelihood models are compared with the proposed Gaussian-process model, to illustrate the importance of the choice of the likelihood model. The cross section models are calibrated using the electron-beam experiments and ab-inito quantum simulations. The resulting calibrated uncertainties capture well the scattering among the data sets. The calibrated cross section models are further validated against swarm-parameter experiments and zero-dimensional Boltzmann equation simulations of widely used cross section datasets.
Chung, Seung Whan (ORCID:0000000302501549)↗
Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition
We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Determination of the mean energy of fast electron losses and anisotropies through thick-target emission on WEST
Abstract A new method to obtain the mean energy of fast electron losses in fusion plasmas using a versatile multi-energy hard x-ray (HXR) detector is presented. The method is based on measuring the thick-target emission of tungsten in the divertor region produced by fast electron losses interacting with the target and modeling the tungsten spectra by a Monte Carlo code which simulates the interaction between a beam of electrons and a solid target. The mean energy of the fast electron losses is determined through the comparison between the experimental and synthetic emission. The results show that fast electron losses during lower hybrid current drive discharges at WEST have a mean energy of 90–140 keV and represent only 2% of the total heat flux at the target. Additionally, anisotropic HXR emission has been detected for the first time at the WEST core and edge plasma, with opposite directions. It is due to the forward-peak emission of two distinctive populations of fast electrons: co-current fast electrons in the core and counter-current fast electron losses at the inner strike point. In view of future experiments like ITER where electron cyclotron current drive will generate a fast electron population, this technique could serve as a real-time monitor of fast electron losses and eventually feed an actuator on the current drive generation.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Startup regime of high-efficiency tapering-enhanced FEL oscillator
In this paper, we present a design of a high-efficiency high-gain free-electron laser oscillator based on the use of a strongly tapered undulator for extracting energy from high-brightness electron beams. We provide an analytical model of the setup followed by numerical simulations for lasing at the wavelength of 13.5 nm. We discuss the optimization of the system in steady state and the conditions necessary for the pass-per-pass buildup of the power from shot noise level. We propose the use of fast phase shifters as a way to accelerate the buildup. Finally, we present time-dependent simulations of the oscillator and discuss the role of spectral filtering. The optimized working point yields a total energy conversion efficiency from the electron beam to output radiation above 1% at the wavelength of 13.5 nm.
Beam dynamics↗
Ion Trapping Studies and Mitigation Strategies for the EIC ERL-Based Strong Hadron Cooler
An Energy Recovery Linac based strong hadron cooler was previously considered for the Electron-Ion Collider. The required electron beam parameters for variable-energy strong hadron cooling place significant constraints on ion trapping and collective effects. This paper presents initial studies of these constraints through a combination of analytical modelling and numerical simulations of ion production, trapping behaviour, and mitigation strategies. A multi-bunch tracking framework based on ELEGANT with the ionEffects module is used to simulate machine operation over millisecond time scales, corresponding to more than 3 × 10^5 electron bunches. The simulations include modelling of ionisation processes together with transverse electron–ion dynamics, allowing the evolution and accumulation of ions to be investigated. Analytical expressions based on Gaussian beam distributions are used to estimate ion trapping conditions and benchmark the simulation results. A bi-periodic bunch spacing scheme is also investigated as a possible mitigation method by detuning the ion oscillation frequency. These studies provide an initial assessment of ion trapping in the strong hadron cooler and demonstrate possible approaches for reducing beam–ion effects.
Bi, R. [Lancaster University, Cockcroft Institute]↗
JSPEC: A Program for IBS and Electron Cooling Simulation
JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab to simulate the evolution of the ion beam under the intrabeam scattering effect and/or the electron cooling effect. JSPEC includes various models of the ion beam, the electron beam, and the friction force, aiming to reflect the latest advances in the field and to provide a useful tool to the community. JSPEC has been benchmarked against other cooling simulation codes and experimental data. It has been used to support the cooler design for JLEIC, an earlier JLab design for the Electron-Ion Collider. A Python wrapper of the C++ code, pyJSPEC, for Python 3.x environment has also been developed and released. It allows users to run JSPEC simulations in a Python environment and makes it possible for JSPEC to collaborate with other accelerator and beam modeling programs, as well as plentiful Python tools in data visualization, optimization, machine learning, etc. In this report, we introduce the features of JSPEC, with a focus on the latest development, and demonstrate how to use JSPEC and pyJSPEC with sample codes and numerical examples.
Accelerator Physics↗
Coherent frequency combs from electrons colliding with a laser pulse
Highly coherent and powerful light sources capable of generating soft x-ray frequency combs are essential for high precision measurements and rigorous tests of fundamental physics. In this work, we derive the analytical conditions required for the emission of coherent radiation from an electron beam colliding with a laser pulse, modeled as a plane wave. These conditions are applied in a series of numerical simulations, where we show that a soft x-ray frequency comb can be produced if the electrons are regularly-spaced and sufficiently monoenergetic. High quality beams of this kind may be produced in the near future from laser-plasma interactions or linear accelerators. Furthermore, we highlight the advantageous role of employing few-cycle laser pulses in relaxing the stringent monoenergeticity requirements for coherent emission. The conditions derived here can also be used to optimize coherent emission in other frequency ranges, such as the terahertz domain.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗