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At least 235 records · Page 13

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. An independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Screening and evaluation of biomass upgrading strategies for sustainable transportation fuel production with biomass-derived volatile fatty acids

Biomass conversion to fuels and chemicals is crucial to decarbonization, but choosing an advantageous upgrading pathway out of many options is challenging. Rigorously evaluating all candidate pathways (process simulation, product property testing) requires a prohibitive amount of research effort; even simple upgrading schemes have hundreds of possible permutations. We present a method enabling high-throughput screening by approximating upgrading unit operations and drop-in compatibility of products (e.g., fuel properties) and apply it to volatile fatty acid (VFA) conversion to liquid transportation fuels via a MATLAB script, VFA Upgrading to Liquid Transportation fUels Refinery Estimation (VULTURE). VULTURE selects upgrading configurations that maximize fuel blend bio-derived content. We validate VULTURE's approximations through surrogate fuel property testing and process simulation. Techno-economic and life cycle analyses suggest that VFA upgrading processes down-selected by VULTURE are profitable and have low carbon intensities, demonstrating the potential for the strategy to accelerate process development timelines at decreased costs.

09 BIOMASS FUELS↗

Tutorial: Langevin Dynamics methods for aerosol particle trajectory simulations and collision rate constant modeling

The Langevin Dynamics (LD) method (also known in the literature as Brownian Dynamics) is routinely used to simulate aerosol particle trajectories for transport rate constant calculations as well as to understand aerosol particle transport in internal and external fluid flows. This tutorial intends to explain the methodological details of setting up a LD simulation of a population of aerosol particles and to deduce rate constants from an ensemble of classical trajectories. We discuss the applicability and limitations of the translational Langevin equation to model the combined stochastic and deterministic motion of particles in fields of force or fluid flow. The drag force and stochastic “diffusion” force terms that appear in the Langevin equation are discussed elaborately, along with a summary of common forces relevant to aerosol systems (electrostatic, gravity, van der Waals, …); a commonly used first order and a fourth order Runge-Kutta time stepping schemes for linear stochastic ordinary differential equations are presented. A MATLAB® implementation of a LD code for simulating particle settling under gravity using the first order scheme is included for illustration. Scaling analysis of aerosol transport processes and the selection of timestep and domain size for trajectory simulations are demonstrated through two specific aerosol processes: particle diffusion charging and coagulation. Fortran® implementations of the first order and fourth order time-stepping schemes are included for simulating the 3D motion of a particle in a periodic domain. Lastly, potential applications and caveats to the usage of LD are included as a summary.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Deep neural networks have been extensively used for the solution of both the forward and the inverse problem for dynamical systems. However, their implementation necessitates optimizing a high-dimensional space of parameters and hyperparameters. This fact, along with the requirement of substantial computational resources, pose a barrier to achieving high numerical accuracy, but also interpretability. Here, to address the above challenges, we present Random Projection-based Operator Networks (RandONets): shallow networks with random projections and tailor-made numerical analysis methods that learn accurately and fast linear and nonlinear operators. Building on previous works, we prove that RandOnets are universal approximators of linear and nonlinear operators. Due to their simplicity, RandONets provide a one-step transformation of the input space, facilitating interpretability. For the evaluation of their performance, we focus on operators of PDEs. We show, that RandONets outperform by several orders of magnitude, both in terms of numerical approximation accuracy and computational cost, the “vanilla” DeepONets. Hence, we believe that our method will trigger further developments in the field of scientific machine learning, for the development of new ‘’light”schemes that will provide high accuracy while reducing dramatically the computational cost. A MATLAB toolbox for RandONets, including demos, is available on GitHub at https://github.com/GianlucaFabiani/RandONets.

Interpretable machine learning↗

Quantifying the effect of hydride microstructure on zirconium alloys embrittlement using image analysis

Since hydride microstructure can significantly influence Zr alloy nuclear fuel cladding’s ductility, a new metric has been developed to quantify hydride microstructure in 2D micrographs and relate it to crack propagation. As cladding failure usually results from a hoop stress, this new metric, called the Radial Hydride Continuous Path (RHCP), is based on quantifying the continuity of brittle hydride particles along the radial direction of the cladding tube. Compared to previous metrics, this approach more closely relates to the propensity of a crack to propagate radially through the cladding tube thickness. The RHCP takes into account hydride length, orientation, and connectivity to choose the optimal path for crack propagation through the cladding thickness. The RHCP can therefore be more closely linked to hydride embrittlement of the Zr alloy material, thus creating a relationship between material structure, properties, and performance. The new definition, along with previously proposed metrics such as the Radial Hydride Fraction (RHF), the Hydride Continuity Coefficient (HCC), and the Radial Hydride Continuity Factor (RHCF), have been implemented and automated in MATLAB. These codes are made available with this publication as supplementary materials. These metrics were verified by comparing their predictions of hydride morphology against expected values in simple cases, and the implementation of the new metric was validated by comparing its predictions with manual measurements of hydride microstructure performed on ImageJ. The RHCP was also validated against experimental measurements of fracture behavior and it was shown to correlate with cladding failure better than previous metrics. The information provided by these metrics will help accurately assess cladding integrity during operation, transportation, and storage.

36 MATERIALS SCIENCE↗

Current interrupt method for calculating the electrochemical impedance in a solid oxide electrolysis stack

Here, in this work the time domain response of Solid Oxide Electrolysis Cells (SOEC) to a current interruption was transformed into the frequency domain using a carrier function Laplace transform, which is fit to the experimental data using a MATLAB Complex Nonlinear Least Squares (CNLS) solver. The hardware implementation, consisting principally of a high-speed switch and a fast-logging Analog to Digital Converter (ADC), was assembled and tested using a calibration module to assess the accuracy, repeatability, and speed of acquisition of the prototype device as compared against a calibrated commercial impedance spectrometer. Additionally, the current interrupt device and commercial FRA were used to acquire the impedance spectra of a four cell SOEC stack with a large, 300 cm 2 , active cell area.

SOEC↗

Tutorial: Crystal orientations and EBSD — Or which way is up?

Electron backscatter diffraction (EBSD) is an automated technique that can measure the orientation of crystals in a sample very rapidly. There are many sophisticated software packages that present measured data. Unfortunately, due to crystal symmetry and differences in the set-up of microscope and EBSD software, there may be accuracy issues when linking the crystal orientation to a particular microstructural feature. In this paper we outline a series of conventions used to describe crystal orientations and coordinate systems. These conventions have been used to successfully demonstrate that a consistent frame of reference is used in the sample, unit cell, pole figure and diffraction pattern frames of reference. We establish a coordinate system rooted in measurement of the diffraction pattern and subsequently link this to all other coordinate systems. A fundamental outcome of this analysis is to note that the beamshift coordinate system needs to be precisely defined for consistent 3D microstructure analysis. This is supported through a series of case studies examining particular features of the microscope settings and/or unambiguous crystallographic features. These case studies can be generated easily in most laboratories and represent an opportunity to demonstrate confidence in use of recorded orientation data. Finally, we include a simple software tool, written in both MATLAB® and Python, which the reader can use to compare consistency with their own microscope set-up and which may act as a springboard for further offline analysis. - Highlights: • Presentation of conventions used to describe crystal orientations • Three case studies that outline how conventions are consistent • Demonstrates a pathway for calibration and validation of EBSD based orientation measurements • EBSD computer code supplied for validation by the reader.

36 MATERIALS SCIENCE↗

An automated procedure built on MTEX for reconstructing deformation twin hierarchies from electron backscattered diffraction datasets of heavily twinned microstructures

Here we present a set of algorithms built on the MTEX and MATLAB graph toolboxes for automatic reconstruction of deformation twin hierarchies from Electron Backscatter Diffraction (EBSD) datasets with a focus on developing methods for heavily twinned microstructures (twin fractions >0.5). The algorithms address key issues arising at large strains, mainly: missing twin relationships, grouping of heavily deformed grain fragments into families of similar orientation originating from a single initial grain, identification of parent fragments for large twin volume fractions, and classification of families having twin relationships with multiple families. To facilitate the development of these algorithms, large-grained ultra-high purity α-Ti deformed in compression along two directions is investigated. Graphs are utilized to handle non-local geometric merging and to represent relationships throughout the reconstruction process. When determining if a grain fragment is from the undeformed microstructure, the combined metrics of the fragment's orientation volume fraction in the initial texture and the directed graph centrality measure of out-closeness (the number of nodes reached in a graph from a given node) are essential. To address automation in reconstructing the sequence of twinning and relating fragments originating from a single grain in the initial microstructure, the twin family tree is formulated as a minimum spanning tree emanating from the initial grain family. A scheme constructing the distances associated with twin relationship comprising the spanning tree is developed, and a novel quasi-directional Prim spanning tree algorithm is used to determine the twin family tree. The procedure is demonstrated to significantly improve the level of automation in reconstructing twin hierarchies in heavily twinned microstructure compared to other methodologies in literature. The procedure can readily be applied to analyses of twinning in metals, as well as provide an approach for routinely extracting twin statistics at larger deformation levels than previously possible. Significantly, the procedure is demonstrated to be capable of identifying third generation twinning in α-Ti microstructures.

36 MATERIALS SCIENCE↗

Clinical analysis of the approximate, 3-dimensional, biological effective dose equation in multiphase treatment plans

A multiphase, approximate biological effective dose (BED{sub A}) equation was introduced because most treatment planning systems (TPS) are incapable of calculating the true BED (BED{sub T}). This work investigates the accuracy and precision of the multiphase BED{sub A} relative to the BED{sub T} in clinical cases. Ten patients with head and neck cancer and 10 patients with prostate cancer were studied using their treatment plans from Pinnacle{sup 3} 9.2 (Philips Medical, Fitchburg, WI). The organs at risk (OARs) that were studied are the normal brain, left and right optic nerves, optic chiasm, spinal cord, brainstem, bladder, and rectum. BED{sub A} and BED{sub T} distributions were calculated using MATLAB 2010b (MathWorks, Natick, MA) and analyzed on a voxel basis for percent error, percent error volume histograms (PEVHs), Pearson correlation coefficient, and Bland-Altman analysis. The maximum BED values that were calculated using the BED{sub A} and BED{sub T} methods were also analyzed. BED{sub A} was found to always underestimate BED{sub T}. The accuracy and precision of BED{sub A} distributions varied between the organs: for optic chiasm and brainstem, 50% of the patients had an overall BED{sub A} percent error of A percent error of A percent error of A distributions had maximum errors ranging from 2% to 11%, with the 11% error occurring for bladder. BED{sub A} produced much more accurate maximum BED values with adjacent organs such as normal brain, bladder, and rectum. This study has shown that BED{sub A} can calculate BED distributions with acceptable accuracy under certain circumstances. However, its consistency and accuracy strongly depend on the dose distributions of the different treatment phases. One should be cautious when using BED{sub A}.

61 RADIATION PROTECTION AND DOSIMETRY↗

Dissolved gas recovery from water using a sidestream hollow-fiber membrane module: First principles model synthesis and steady-state validation

This paper presents a first-principles model for the recovery of dissolved gases from liquids using a sidestream hollow-fiber membrane module. The model avoids the use of new empirical coefficients, thus providing a parametric understanding of the process behavior for future design and optimization of membrane modules. This type of first-principles model could be particularly useful when gas recovery is beneficial to biological or chemical reactions of interest, such as the acetogenesis reactions in two-stage anaerobic digesters. The steady-state behavior of the model was validated against both new experimental data for the recovery of H 2 , CH 4 and H 2 –CH 4 mixtures from pure water, as well as existing published data. The modeled gas recovery predictions agreed with experimental data to an absolute average error of 13%, and an average R value of 0.98. Parametric analysis of mixed-gas recovery suggests possible key transition points in the composition of the recovered gases. For example, at 40 °C, increasing trans-membrane pressure while keeping hydraulic residence time (HRT) under 0.5 s will result in an increase in the ratio of H 2 to CH 4 recovered. Otherwise, increasing trans-membrane pressure will instead decrease the ratio of H 2 to CH 4 recovered. The model has potential to be extended to transient analysis, but has yet to be validated with transient experimental data. Furthermore, this model was successfully implemented in both Python and MATLAB, and provides valuable insights for future net-energy optimization for anaerobic digestion systems with in-situ gas recovery.

Anaerobic Digestion↗

SHarD: A beam dynamics simulation code for dielectric laser accelerators based on spatial harmonic field expansion

In order to demonstrate acceleration of electrons to relativistic scales by an on chip dielectric laser accelerator (DLA), a ponderomotive focusing scheme capable of capturing and transporting electrons through nanometer-scale apertures over extended interaction lengths has been proposed. Here we present a Matlab-based numerical code (SHarD) utilizing a spatial harmonic expansion of the fields within the dielectric structure to simulate the evolution of the beam phase space distribution in this scheme. The code can be used to optimize key-parameters for the accelerator performance such as the final energy, transverse spot size evolution and total number of electrons accelerated through currently fabricated structures. Eventually, the simulation model will be applied to inform the phase mask profile to be added to a pulse front tilt drive laser pulse using a liquid crystal mask in the experimental setup being assembled at UCLA Pegasus Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

$\mathrm{REX}$: An analytical tool for reactor operating envelope expansion through fuel-clad thermo-mechanics

Here REX, an analytical reactor design tool for the identification and expansion of reactor operating envelopes, is introduced and detailed. Written in MATLAB, REX takes core geometries and axially discretized detector and depletion output from the Serpent neutron transport code and performs full-core, pin-specific thermal-hydraulic and thermo-mechanical calculations. REX identifies the operating envelopes of advanced, solid-fuel nuclear reactors on the basis of their fuel-cladding, fuel-gas, and coolant-cladding interfacial thermo-mechanics. It iteratively pushes coolant inlet temperatures and modifies fuel pin geometries to induce mechanical failure in their original cladding materials at the fullest extent of their fuel cycle lengths and permissible coolant inlet temperatures. It then attempts to expand their operating envelopes by determining the mechanical responses of alternative cladding materials under the same geometric conditions. The result of the REX calculation sequence is a set of 5-D variables describing the temperatures, pressures, geometries, and mechanics of the core as functions of assembly, fuel pin, axial zone, depletion step, and coolant inlet temperature for each candidate cladding material with the limiting fuel pin geometry for the original material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design of a prototypical natural circulation water-based reactor cavity cooling system (RCCS) for a pebble-bed generic FHR

A prototypical natural circulation water-based reactor cavity cooling system (RCCS) for the UC Berkeley Mark-1 pebble-bed gFHR is designed based on one-dimensional thermal hydraulics modeling and optimization implemented in an in-house MATLAB code. The model employs a lumped core consisting of fuel pebble and graphite pebble regions, while the graphite reflector, vessel, and RCCS are represented as separate but energy-coupled regions. The model is derived based on steady state energy balance equations accounting for conductive heat transfer from the lumped core to the vessel and subsequent radiative heat transfer to the RCCS and convective heat transfer in the water. Further, mass flow rate is calculated based on momentum and thermal energy balance in the RCCS. Starting with ANL’s water NSTF as baseline, effects of RCCS design parameters such as size of the plate between pipes, pipe diameter, source-to-sink distance, surface emissivity, and pitch from the core are examined in an integral effects framework which accounts for subsequent variation of the mass flow rate, number of pipes, convection coefficient, mean region and surface temperatures, radiative view factors, and water outlet temperature. The importance of including a prototypical reactor design in RCCS design calculations is emphasized as the calculations show that temperature drops from the core to the RCCS fluid to transfer the heat tend to be the limitation not the heat removal capacity of the fluid. A closed-loop design is obtained with capability to safely remove up to 0.72% of the nominal reactor power at maximum estimated peak conditions and 0.40% at shutdown. The design is based on physics calculations and does not account for economic optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Miniature DC electromagnetic pumps of molten lead and sodium to support development of Gen-IV nuclear reactors

This work developed designs of submerged, dual-regions, miniature DC-EM pumps for circulating molten lead and liquid sodium at ≤500 °C without active cooling for use in ex-pile and in-pile test loops to support of materials and fuel developments for Gen-IV sodium and molten lead fast nuclear reactor. These pumps with two pumping regions are 57 mm, 66.8 mm, 95.4 mm, and 133.5 mm in diameter and have two Alnico 5 permanent magnets with Hiperco-50 pole pieces for focusing the magnetic field lines in the flow duct. The Equivalent Circuit Model (ECM) linked to the Finite Element Method Magnetics (FEMM) software in MATLAB platform calculated the pumps characteristics for a wide range of parameters. Also determined are the pumps dimensions for the highest cumulative pumping power and peak efficiency. These dimensions are the height, width, and length of the flow duct, the thickness of the Alnico magnets, the length of current electrodes, and the separation distance between the two pumping regions. For molten lead, the pumping power increases from 368 W to 728 W, and the peak efficiency from 14.7% to 31.6% with increased pump diameter from 57 mm to 133.5 mm. In conclusion, for liquid sodium, both the pumping power and peak efficiency are higher, increasing from 392 W to 767 W and from 44.3 to 51.2%, respectively, with increased pump diameter from 57 mm to 133.5 mm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Second-order wave excitation forces in WEC-Sim/MOST: Implementation, experimental validation, and code-to-code comparison

Accurate prediction of second-order hydrodynamic loads is essential for floating bodies, including floating offshore wind turbines, wave energy converters, and hybrid wind–wave platforms. These nonlinear effects, arising from both sum- and difference-frequency forcing, are critical for capturing key response characteristics but remain challenging to model efficiently. In this work, we extend the open-source Wave Energy Converter Simulator / MATLAB for Offshore Simulation Tool by implementing second-order wave excitation forces, supporting both the full Quadratic Transfer Function formulation and the Newman approximation. The full Quadratic Transfer Function method is used for all code-to-code comparisons and experimental validation, while the Newman approximation is provided as a computationally lighter alternative. To benchmark the new capability, we perform a code-to-code comparison with OpenFAST and OrcaFlex. We then validate the enhanced model using wave-tank measurements of a 1:96 scale DeepCwind semi-submersible, showing that second-order effects are required to reproduce platform motions. The implementation employs a computationally efficient pre-computation strategy for second-order wave excitation forces, reducing simulation cost while maintaining engineering accuracy. Overall, this work advances the tool as an open-source and versatile tool for modelling floating offshore renewable-energy systems requiring second-order hydrodynamic fidelity.

17 WIND ENERGY↗

Theoretical power-law relationship between permeability and formation factor

Permeability k and formation factor F are important petrophysical properties that have broad applications to reservoir engineering. Although well-log analysis has advanced reservoir characterizations, direct measurement of k is still not available. Accordingly, resistivity logs and more particularly formation factor have been frequently used to estimate k. In this study, we present a theoretical framework to relate k to F. We use power-law scaling from continuum percolation theory to develop a theoretic relationship between k and F, which is similar in form to a published power-law equation with empirical coefficients. Our result gives a physical interpretation to this empirical relationship. We also compare power-law scaling laws from percolation theory with data derived from experimental measurements and numerical simulations in the literature. Finally, using the Curve Fitting toolbox of MATLAB, the parameters of the power-law equations are determined, and the significance of the non-universal power laws are discussed.

42 ENGINEERING↗

Uncertainty evaluation for twist drilling stability model

This paper describes the first uncertainty analysis for drilling stability using a frequency-domain drilling stability model. The stability model inputs include: the modal parameters for the torsional-axial vibration mode from the twist drill-holder-spindle axial frequency response function; and the mechanistic coefficients that relate the torque and thrust force to chip area for the selected drill-workpiece material combination. Furthermore, Monte Carlo simulation is applied to propagate the input uncertainties to output uncertainty in the predicted stability map, which separates stable from unstable (chatter) zones in the spindle speed-chip width parameter space. Additionally, the mean stability boundary and its 95% confidence intervals are determined for five cases: varying all four inputs simultaneously and varying them individually. This enables the individual sensitivities to be compared. Experimental results from drilling tests are included for comparison to the prediction. Additionally, Matlab code is provided to implement the stability model and Monte Carlo uncertainty analysis.

42 ENGINEERING↗