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At least 1,783 records · Page 99

TU-C-17A-12: Towards a Passively Optimized Phase-Space Monte Carlo (POPMC) Treatment Planning Method: A Proof of Principle

Purpose: The advent of on-line/off-line adaptive, and biologically-conformal radiation therapy has led to a need for treatment planning solutions that utilize voxel-specific penalties, requiring optimization over a large solution space that is performed quickly, and the dose in each voxel calculated accurately. This work proposes a “passive” optimization framework, which is executed concurrently during Monte Carlo dose calculation, evaluating the cost/benefit of each history during transport, and creates a passively optimized fluence map. Methods: The Monte Carlo code Geant4 v9.6 was used for this study. The standard voxel geometry implementation was modified to support the passive optimization framework, with voxel-specific optimization parameters. Dose-benefit functions, which will increase a particle history’s weight upon dose deposition, were defined in a central collection of voxels to effectively create target structures. Histories that deposit energy to voxels are reweighted based on a voxel’s dose multiplied by its cost/benefit value. Upon full termination of each history, the dose contributions of that history are reweighted to reflect a contribution proportional to the history’s final weight. A parallel-planar 1.25 MeV photon fluence is transported through the geometry, and re-weighted at each dose deposition step. The resulting weight is tallied with the incident spatial and directional coordinates in a phase-space distribution. Results: A uniform incident fluence was reweighted during MC dose calculations to create an optimized fluence map which would generate dose profiles in target volumes that exhibit the same dose characteristics as the prescribed optimization parameters. An optimized dose profile, calculated concurrently with the phase-space, reflects the resulting dose distribution. Conclusion: This study demonstrated the feasibility of passively optimizing an incident fluence map during Monte Carlo dose calculations. The flexibility of the voxel-specific optimization framework allows a variety and combination of optimization parameters to be calculated for each voxel at every transportation step. This work is partially supported by Varian. This work is partially supported by the NIH.

07 ISOTOPE AND RADIATION SOURCES↗

Systematic comparison and cross-validation of fixed-node diffusion Monte Carlo and phaseless auxiliary-field quantum Monte Carlo in solids

Quantum Monte Carlo (QMC) methods are some of the most accurate methods for simulating correlated electronic systems. Here, we investigate the compatibility, strengths, and weaknesses of two such methods, namely, diffusion Monte Carlo (DMC) and auxiliary-field quantum Monte Carlo (AFQMC). The multideterminant trial wave functions employed in both approaches are generated using the configuration interaction using a perturbative selection made iteratively (CIPSI) technique. Complete basis-set full configuration interaction energies estimated with CIPSI are used as a reference in this comparative study between DMC and AFQMC. By focusing on a set of canonical finite–size solid-state systems, we show that both QMC methods can be made to systematically converge towards the same energy once basis-set effects and systematic biases have been removed. AFQMC shows a much smaller dependence on the trial wave function than DMC while simultaneously exhibiting a much larger basis-set dependence. We outline some of the remaining challenges and opportunities for improving these approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Monte Carlo analysis of satellite debris footprint dispersion

A comprehensive study is performed to investigate satellite debris impact point dispersion using a combination of Monte Carlo statistical analysis and parametric methods. The Monte Carlo technique accounts for nonlinearities in the entry point dispersion, which is represented by a covariance matrix of position and velocity errors. Because downrange distance of impact is a monotonic function of debris ballistic coefficient, a parametric method is useful for determining dispersion boundaries. The scheme is applied in the present analysis to estimate the Skylab footprint dispersions for a controlled reentry. A significant increase in the footprint dispersion is noticed for satellite breakup above a 200,000-ft altitude. A general discussion of the method used for analysis is presented together with some typical results obtained for the Skylab deboost mission, which was designed before NASA abandoned plans for a Skylab controlled reentry.

Rao, P. P.↗

Performance of particle in cell methods on highly concurrent computational architectures

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson’s equation or more generally Maxwell’s equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Oxygen transport in off-stoichiometric uranium dioxide mediated by defect clustering dynamics

Oxygen transport is central to many properties of oxides such as stoichiometric changes, phase transformation, and ionic conductivity. In this paper, we report a mechanism for oxygen transport in uranium dioxide (UO{sub 2}) in which the kinetics is mediated by defect clustering dynamics. In particular, the kinetic Monte Carlo method has been used to investigate the kinetics of oxygen transport in UO{sub 2} under the condition of creation and annihilation of oxygen vacancies and interstitials as well as oxygen interstitial clustering, with variable off-stoichiometry and temperature conditions. It is found that in hypo-stoichiometric UO{sub 2−x}, oxygen transport is well described by the vacancy diffusion mechanism while in hyper-stoichiometric UO{sub 2+x}, oxygen interstitial cluster diffusion contributes significantly to oxygen transport kinetics, particularly at high temperatures and high off-stoichiometry levels. It is also found that di-interstitial clusters and single interstitials play dominant roles in oxygen diffusion while other larger clusters have negligible contributions. However, the formation, coalescence, and dissociation of these larger clusters indirectly affects the overall oxygen diffusion due to their interactions with mono and di-interstitials, thus providing an explanation of the experimental observation of saturation or even drop of oxygen diffusivity at high off-stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-F-T-507: Modeling Cerenkov Emissions From Medical Linear Accelerators: A Monte Carlo Study

Purpose: Cerenkov emissions are a natural byproduct of MV radiotherapy but are typically ignored as inconsequential. However, Cerenkov photons may be useful for activation of drugs such as psoralen. Here, we investigate Cerenkov radiation from common radiotherapy beams using Monte Carlo simulations. Methods: GAMOS, a GEANT4-based framework for Monte Carlo simulations, was used to model 6 and 18MV photon beams from a Varian medical linac. Simulations were run to track Cerenkov production from these beams when irradiating a 50cm radius sphere of water. Electron contamination was neglected. 2 million primary photon histories were run for each energy, and values scored included integral dose and total track length of Cerenkov photons between 100 and 400 nm wavelength. By lowering process energy thresholds, simulations included low energy Bremsstrahlung photons to ensure comprehensive evaluation of UV production in the medium. Results: For the same number of primary photons, UV Cerenkov production for 18MV was greater than 6MV by a factor of 3.72 as determined by total track length. The total integral dose was a factor of 2.31 greater for the 18MV beam. Bremsstrahlung photons were a negligibly small component of photons in the wavelength range of interest, comprising 0.02% of such photons. Conclusion: Cerenkov emissions in water are 1.6x greater for 18MV than 6MV for the same integral dose. Future work will expand the analysis to include optical properties of tissues, and to investigate strategies to maximize Cerenkov emission per unit dose for MV radiotherapy.

60 APPLIED LIFE SCIENCES↗

Verification and validation of the maximum entropy method for reconstructing neutron flux, with MCNP5, Attila-7.1.0 and the GODIVA experiment

Verification and validation of reconstructed neutron flux based on the maximum entropy method is presented in this paper. The verification is carried out by comparing the neutron flux spectrum from the maximum entropy method with Monte Carlo N Particle 5 version 1.40 (MCNP5) and Attila-7.1.0-beta (Attila). A spherical 100% 235U critical assembly is modeled as the test case to compare the three methods. The verification error range for the maximum entropy method is 15–21% where MCNP5 is taken to be the comparison standard. Attila relative error for the critical assembly is 20–35%. Validation is accomplished by comparing a neutron flux spectrum that is back calculated from foil activation measurements performed in the GODIVA experiment (GODIVA). The error range of the reconstructed flux compared to GODIVA is 0–10%. The error range of the neutron flux spectrum from MCNP5 compared to GODIVA is 0–20% and the Attila error range compared to the GODIVA is 0–35%. The maximum entropy method is shown to be a fast reliable method, compared to either Monte Carlo methods (MCNP5) or 30 multienergy group methods (Attila) and with respect to the GODIVA experiment.

99 GENERAL AND MISCELLANEOUS↗

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Abstract Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model’s ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Engineering↗

Quantum Monte Carlo calculations in configuration space with three-nucleon forces

Neutron matter, through its connection to neutron stars as well as systems like cold atom gases, is one of the most interesting yet computationally accessible systems in nuclear physics. The Configuration-Interaction Monte Carlo (CIMC) method is a stochastic many-body technique allowing to tackle strongly coupled systems. In contrast to other Quantum Monte Carlo methods employed in nuclear physics, the CIMC method can be formulated directly in momentum space allowing for an efficient use of non-local interactions. In this work we extend CIMC method to include three-nucleon interactions through the normal-ordered two-body approximation. Here, we present results for the equation of state of neutron matter in line with other many-body calculations that employ low resolution chiral interactions, and provide predictions for the momentum distribution and the static structure factor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis and simulation for a model of electron impact excitation/deexcitation and ionization/recombination

This paper describes a kinetic model and a corresponding Monte Carlo simulation method for excitation/deexcitation and ionization/recombination by electron impact in a plasma free of external fields. The atoms and ions in the plasma are represented by continuum densities and the electrons by a particle distribution. A Boltzmann-type equation is formulated and a corresponding H-theorem is formally derived. An efficient Monte Carlo method is developed for an idealized analytic model of the excitation and ionization collision cross sections. To accelerate the simulation, the reduced rejection method and binary search method are used to overcome the singular rate in the recombination process. Numerical results are presented to demonstrate the efficiency of the method on spatially homogeneous problems. The evolution of the electron distribution function and atomic states is studied, revealing the possibility under certain circumstances of system relaxation towards stationary states that are not the equilibrium states, a potential non-ergodic behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adjoint DSMC for nonlinear spatially-homogeneous Boltzmann equation with a general collision model

We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in Caflisch et al., which was restricted to the case of Maxwell molecules, for which the collision rate is constant. The main difficulty in generalizing the previous results is that a rejection sampling step is required in the DSMC algorithm in order to handle the variable collision rate. We find a new term corresponding to the so-called score function in the adjoint equation and a new adjoint Jacobian matrix capturing the dependence of the collision parameter on the velocities. The new formula works for a much more general class of collision models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian Monte-Carlo Framework: New Methods for Resonance Parameter Evaluation [Slides]

BMC evaluation is a tool to address imperfect data & models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allow for variance, covariance, skewness, etc. To better predict criticality, we could document non-normal parameter PDFs (i.e. asymmetric uncertainty), consider non-linear sensitivity of $\kappa$ eff to resonance parameters, and reduce uncertainty in key resonance parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electronic excitation spectra of molecular hydrogen in phase I from quantum Monte Carlo and many-body perturbation methods

Here, we study the electronic excitation spectra in solid molecular hydrogen (phase I) at ambient temperature and 5- to 90-GPa pressures using quantum Monte Carlo methods and many-body perturbation theory. In this range, the system changes from a wide-gap molecular insulator to a semiconductor, altering the nature of the excitations from localized to delocalized. Computed gaps and spectra agree with experiments, proving the ability to predict accurately band gaps of many-body systems in the presence of nuclear quantum and thermal effects.

08 HYDROGEN↗

Correlation function distributions for O ( N ) lattice field theories in the disordered phase

Numerical computations in strongly interacting quantum field theories are often performed using Monte Carlo sampling methods. A key task in these calculations is to estimate the value of a given physical quantity from the distribution of stochastic samples that are generated using the Monte Carlo method. Typically, the sample mean and sample variance are used to define the expectation values and uncertainties of computed quantities. However, the Monte Carlo sample distribution contains more information than these basic properties, and it is useful to investigate it more generally. In this work, the exact form of the probability distributions of two-point correlation functions at zero momentum in O ( N ) lattice field theories in the disordered phase and in infinite volume are determined. These distributions allow for a robust investigation of the efficacy of the Monte Carlo sampling procedure and are shown also to allow for improved estimators of the target physical quantity to be constructed. The theoretical expectations are shown to agree with numerical calculations in the O ( 2 ) model. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Monte Carlo simulation of the dose response of a novel 2D silicon diode array for use in hybrid MRI–LINAC systems

Purpose: MRI-guided radiation therapy systems (MRIgRT) are being developed to improve online imaging during treatment delivery. At present, the operation of single point dosimeters and an ionization chamber array have been characterized in such systems. This work investigates a novel 2D diode array, named “magic plate,” for both single point calibration and 2D positional performance, the latter being a key element of modern radiotherapy techniques that will be delivered by these systems. Methods: GEANT4 Monte Carlo methods have been employed to study the dose response of a silicon diode array to 6 MV photon beams, in the presence of in-line and perpendicularly aligned uniform magnetic fields. The array consists of 121 silicon diodes (dimensions 1.5 × 1.5 × 0.38 mm{sup 3}) embedded in kapton substrate with 1 cm pitch, spanning a 10 × 10 cm{sup 2} area in total. A geometrically identical, water equivalent volume was simulated concurrently for comparison. The dose response of the silicon diode array was assessed for various photon beam field shapes and sizes, including an IMRT field, at 1 T. The dose response was further investigated at larger magnetic field strengths (1.5 and 3 T) for a 4 × 4 cm{sup 2} photon field size. Results: The magic plate diode array shows excellent correspondence (< ± 1%) to water dose in the in-line orientation, for all beam arrangements and magnetic field strengths investigated. The perpendicular orientation, however, exhibits a dose shift with respect to water at the high-dose-gradient beam edge of jaw-defined fields [maximum (4.3 ± 0.8)% over-response, maximum (1.8 ± 0.8)% under-response on opposing side for 1 T, uncertainty 1σ]. The trend is not evident in areas with in-field dose gradients typical of IMRT dose maps. Conclusions: A novel 121 pixel silicon diode array detector has been characterized by Monte Carlo simulation for its performance inside magnetic fields representative of current prototype and proposed MRI–linear accelerator systems. In the in-line orientation, the silicon dose is directly proportional to the water dose. In the perpendicular orientation, there is a shift in dose response relative to water in the highest dose gradient regions, at the edge of jaw-defined and single-segment MLC fields. The trend was not observed in-field for an IMRT beam. The array is expected to be a valuable tool in MRIgRT dosimetry.

07 ISOTOPE AND RADIATION SOURCES↗

SU-E-T-525: Ionization Chamber Perturbation in Flattening Filter Free Beams

Purpose: Changing the characteristic of a photon beam by mechanically removing the flattening filter may impact the dose response of ionization chambers. Thus, perturbation factors of cylindrical ionization chambers in conventional and flattening filter free photon beams were calculated by Monte Carlo simulations. Methods: The EGSnrc/BEAMnrc code system was used for all Monte Carlo calculations. BEAMnrc models of nine different linear accelerators with and without flattening filter were used to create realistic photon sources. Monte Carlo based calculations to determine the fluence perturbations due to the presens of the chambers components, the different material of the sensitive volume (air instead of water) as well as the volume effect were performed by the user code egs-chamber. Results: Stem, central electrode, wall, density and volume perturbation factors for linear accelerators with and without flattening filter were calculated as a function of the beam quality specifier TPR{sub 20/10}. A bias between the perturbation factors as a function of TPR{sub 20/10} for flattening filter free beams and conventional linear accelerators could not be observed for the perturbations caused by the components of the ionization chamber and the sensitive volume. Conclusion: The results indicate that the well-known small bias between the beam quality correction factor as a function of TPR20/10 for the flattening filter free and conventional linear accelerators is not caused by the geometry of the detector but rather by the material of the sensitive volume. This suggest that the bias for flattening filter free photon fields is only caused by the different material of the sensitive volume (air instead of water)

60 APPLIED LIFE SCIENCES↗

SU-G-TeP1-03: Beam Quality Correction Factors for Linear Accelerator with and Without Flattening Filter

Purpose: The impact of removing the flattening filter on absolute dosimetry based on IAEA’s TPR-398 and AAPM’s TG-51 was investigated in this study using Monte Carlo simulations. Methods: The EGSnrc software package was used for all Monte Carlo simulations performed in this work. Five different ionization chambers and nine linear accelerator heads have been modeled according to technical drawings. To generate a flattening filter free radiation field the flattening filter was replaced by a 2 mm thick aluminum layer. Dose calculation in a water phantom were performed to calculate the beam quality correction factor k{sub Q} as a function of the beam quality specifiers %dd(10){sub x}, TPR{sub 20,10} and mean photon and electron energies at the point of measurement in photon fields with (WFF) and without flattening filter (FFF). Results: The beam quality correction factor as a function of %dd(10){sub x} differs systematically between FFF and WFF beams for all investigated ionization chambers. The largest difference of 1.8% was observed for the largest investigated Farmer-type ionization chamber with a sensitive volume of 0.69 cm{sup 3}. For ionization chambers with a smaller nominal sensitive volume (0.015 – 0.3 cm{sup 3}) the deviation was less than 0.4% between WFF and FFF beams for %dd(10){sub x} > 62%. The specifier TPR{sub 20,10} revealed only a good correlation between WFF and FFF beams (< 0.3%) for low energies. Conclusion: The results confirm that %dd(10){sub x} is a suitable beam quality specifier for FFF beams with an acceptable bias. The deviation depends on the volume of the ionization chamber. Using %dd(10){sub x} to predict k{sub Q} for a large volume chamber in a FFF photon field may lead to not acceptable errors according to the results of this study. This bias may be caused by the volume effect due to the inhomogeneous photon fields of FFF linear accelerators.

60 APPLIED LIFE SCIENCES↗

Characterization of cartridge filters from the IEA-R1 Nuclear Reactor

The management of radioactive waste ensures safety to human health and the environment nowadays and for the future, without overwhelming the upcoming generations. The primary characterization of radioactive waste is one of the main steps in the management of radioactive waste. This step permits to choose the best treatment for the radioactive waste before forwarding it to its final disposal. The aim of the present work is the primary characterization of cartridge filters from the IEA-R1 nuclear reactor utilizing gamma-ray spectrometry, and the method of Monte Carlo for calibration. The IEA-R1 is located in the Nuclear and Energy Research Institute (IPEN - CNEN) in the city of Sao Paulo, Brazil. Cartridge filters are used for purification of the cooling water that is pumped through the core of the pool type nuclear research reactors. Once worn out, these filters are replaced and then become radioactive waste. Determination of the radioactive inventory is of paramount importance in the management of such radioactive waste, and one of the main methods for doing so is the gamma-ray spectrometry, which can identify and quantify high energy photon emitters. The technique chosen for the characterization of radioactive waste in the present work is the gamma-ray spectrometry with High purity Germanium (HPGe) detectors. From the energy identified in the experimental spectrum, three radioisotopes were identified in the cartridge filter: {sup 108m}Ag, {sup 110m}Ag, {sup 60}Co. For the estimated activity of the filter, the calibration in efficiency was made utilizing the MCNP4C code of the Monte Carlo method. Such method was chosen because there is no standard source available in the same geometry of the cartridge filter, therefore a simulation had to be developed in order to reach a calibration equation, necessary to estimate the activity of the radioactive waste. The results presented an activity value in the order of MBq for all radioisotopes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗