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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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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

EVALUATION OF PRESSURE DROP CORRELATIONS FOR THE WIRE-WRAPPED ROD BUNDLES

The accurate prediction of pressure drop in the fuel rod bundle is of importance for the design and thermal-hydraulic analysis of nuclear reactor system. Due to very complex geometry of wire-wrapped fuel rod bundle geometry for the Sodium Fast Reactor (SFR), a simple method using hydraulic (equivalent) diameter is not sufficient to predict the pressure drop of rod bundle accurately. For several decades, many experimental works have been performed to develop an accurate correlation for wire-wrapped fuel bundle friction factor. In these works, the friction factor correlation of wire-wrapped fuel bundle has been developed as a function of Reynolds number of the flow and the design parameters such as fuel pin diameter, wire diameter, rod pitch, and wire lead length. The Cheng and Todreas correlations are well-known and used in many subchannel analysis code, such as CADET, TRIO-U, MATRA-LMW, SE2-ANL, etc. Novendstern model, Rehme model, Baxi and Dalle Donne model are also well-known and widely referred. Computational Fluid Dynamics is another typical approach to predict the pressure drop of wire-wrapped fuel rod bundle, but it requires the model validation because the accuracy of pressure drop prediction by the CFD simulation depends on what turbulence model is employed. The present work aims at evaluating the existing pressure drop correlations for the wire-wrapped fuel rod bundle and evaluating the pressure drop of 217-pin rod bundle by the CFD analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Development of a Thermodynamic Model for the Hanford Tank Waste Operations Simulator - 12193

The Hanford Tank Waste Operations Simulator (HTWOS) is the current tool used by the Hanford Tank Operations Contractor for system planning and assessment of different operational strategies. Activities such as waste retrievals in the Hanford tank farms and washing and leaching of waste in the Waste Treatment and Immobilization Plant (WTP) are currently modeled in HTWOS. To predict phase compositions during these activities, HTWOS currently uses simple wash and leach factors that were developed many years ago. To improve these predictions, a rigorous thermodynamic framework has been developed based on the multi-component Pitzer ion interaction model for use with several important chemical species in Hanford tank waste. These chemical species are those with the greatest impact on high-level waste glass production in the WTP and whose solubility depends on the processing conditions. Starting with Pitzer parameter coefficients and species chemical potential coefficients collated from open literature sources, reconciliation with published experimental data led to a self-consistent set of coefficients known as the HTWOS Pitzer database. Using Gibbs energy minimization with the Pitzer ion interaction equations in Microsoft Excel,1 a number of successful predictions were made for the solubility of simple mixtures of the chosen species. Currently, this thermodynamic framework is being programmed into HTWOS as the mechanism for determining the solid-liquid phase distributions for the chosen species, replacing their simple wash and leach factors. Starting from a variety of open literature sources, a collection of Pitzer parameters and species chemical potentials, as functions of temperature, was tested for consistency and accuracy by comparison with available experimental thermodynamic data (e.g., osmotic coefficients and solubility). Reconciliation of the initial set of parameter coefficients with the experimental data led to the development of the self-consistent set known as the HTWOS Pitzer database. Using Microsoft Excel to formulate the Gibbs energy minimization method and the multi-component Pitzer ion interaction equations, several predictions of the solubility of solute mixtures at various temperatures were made using the HTWOS Pitzer database coefficients. Examples of these predictions are shown in Figure 3 and Figure 4. A listing of the entire HTWOS Pitzer database can be found in RPP-RPT-50703. Currently, work is underway to install the Pitzer ion interaction model in HTWOS as the mechanism for determining the solid-liquid phase distributions of select waste constituents during tank retrievals and subsequent washing and leaching of the waste. Validation of the Pitzer ion interaction model in HTWOS will be performed with analytical laboratory data of actual tank waste. This change in HTWOS is expected to elicit shifts in mission criteria, such as mission end date and quantity of high-level waste glass produced by WTP, as predicted by HTWOS. These improvements to the speciation calculations in HTWOS, however, will establish a better planning basis and facilitate more effective and efficient future operations of the WTP. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Simplified Model and Approach to Transform Infrared Surface Temperature to Film Effectiveness in a Conjugate Heat Transfer Experiment

This paper describes a simplified engineering model based on a one-dimensional thermal resistance network. The model is used to develop a new method to relate film cooling effectiveness and heat transfer augmentation to local overall cooling effectiveness in a conjugate flat plate experiment. This paper presents experimental proof-of-concept data to demonstrate the potential for this model. In contrast to previous approaches, neither the wall heat flux nor the adiabatic wall temperature is required to estimate the local film cooling performance parameters. The model predicts surface temperatures that are within the experimental uncertainties over the range for which the model is trained, and to within five percent when the model is extrapolated to higher coolant channel Reynolds numbers. This paper is relevant to conjugate test rigs that can measure the hot surface temperature distribution with and without film cooling. This information may also be relevant to designers as a method to approximate surface temperatures or used as an approximate heat transfer model for optimization studies.

advanced gas turbines↗
DOE OSTI2018

Muon Borehole Detector Design for Use in 4-D Density Overburden Monitoring

The increase of atmospheric CO2 concentrations has initiated research into carbon sequestration methods. One possibility is to store CO2 in subsurface porous reservoirs. The monitoring of the injected CO2 plume is vital because escaping CO2 poses health and environmental risks. Typically, seismic reflection methods are used to determine the change in density due to the replacement of brine by CO2 in the reservoir, but this is expensive and not continuous. A potential alternative is to use cosmic muon tomography to measure density changes in the reservoir as a function of time. This paper describes the development of a muon detector that will be capable of being deployed in boreholes. The detector has the required dimensions, an angular resolution of approximately 2 degrees, and is robust. The design is based on alternating layers of scintillating rods, which can provide 4-D tomographic data to detect small changes in density at depths up to approximately 2 km. Geant4, a Monte Carlo simulation code, is being used to develop models to guide the design of the physical configuration. Preliminary testing and measurements have been performed to validate the simulation predictions and optimize the performance of the system. The simulation and preliminary experimental results are presented here.

Borehole Detector, CO¬2 Sequestration, Geant4, Muo↗
DOE OSTI2017

Validation and Verification of Multi-Material Split Rings

Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials coefficients of thermal expansion as well as the shrinkage upon cure exhibited by most thermoset polymer matrix materials. Depending upon the specific geometric details of the composite structure and the materials curing parameters, it is possible that these residual stresses can result in interlaminar delamination and fracture within the composite as well as plastic deformation in the structures metallic materials. It is important to consider potential residual stresses when designing composite parts and their manufacturing processes. However, the experimental determination of residual stresses in prototype parts can be prohibitive, both in terms of financial and temporal costs. As an alternative to physical measurement, it is possible for computational tools to be used to quantify potential residual stresses in composite prototype parts. A simplified method for simulating residual stresses was previously validated with two simple bi-material structures. Continuing on, the objective of this study is to further validate the simplified method for simulating residual stresses for bi-material split rings of different composites and layup variations. The validation process uses uncertainty quantification to develop a distribution of possible simulated residual stress states that are compared to experimentally measured residual stress states of fabricated structures similar to those simulated. The results of the comparisons indicate that the proposed finite element modeling approach is capable of accurately simulating the formation of residual stresses in composite structures and a temperature independent material model is adequate within the composites glassy region.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Generation IV Benchmarking of TRISO Fuel Performance Models Under Accident Conditions Final Report

The Generation IV International Forum (GIF) is a co-operative international endeavor of fourteen members organized to carry out the research and development needed to establish the feasibility and performance capabilities of the next generation nuclear energy systems. GIF selected six reactor technologies, amongst which is the Very High Temperature Reactor (VHTR) that is primarily dedicated to the cogeneration of electricity and hydrogen. The technical basis for VHTR is the tristructural isotropic (TRISO)-coated particle fuel, the graphite as the core structure, helium coolant, as well as the dedicated core layout and lower power density to removal decay heat in a natural way. At the heart of safety features of the VHTR concept lie the TRISO fuel particles that are designed to keep their structural integrity and retain fission products at temperatures up to 1600°C. As part as the design and future operation of VHTRs, a key aspect is the accurate prediction of fuel performance under irradiation and accident conditions. Modeling and simulation allow prediction of TRISO fuel behavior when subject to neutron flux and in high temperature accident scenarios. The refinement of the fuel performance models and codes is performed by comparison to in-pile and out-of-pile experimental data that reproduce the expected irradiation conditions in high temperature gas-cooled reactors (HTGRs). Historically, the International Atomic Energy Agency (IAEA) developed a benchmark dedicated to the validation of predictive methods for fuel and fission product behavior through the Coordinated Research Program CRP-2 (IAEA, 1997). CRP-2 was later updated to cover fuel fabrication, quality assurance, irradiation performance, safety testing, and spent fuel. The scope of the resulting CRP-6 benchmarks focused on HTGR fuel performance and fission product release (IAEA, 2012). Taking advantage of additional TRISO fuel fabrication, irradiation, and safety testing campaigns, GIF launched a Generation IV Benchmarking of TRISO Fuel Performance Models under Accident Conditions in late 2015. This GIF benchmark is a three-year program steered by Idaho National Laboratory (INL, USA). The other participants include the Japan Atomic Energy Agency (JAEA, Japan) and the Korea Atomic Energy Research Institute (KAERI, Korea). The objectives of the benchmark are to: follow on the IAEA CRP benchmarks, (2) model fission product release under accident conditions, (3) compare results obtained by the fuel performance modeling codes of the benchmark participants, and (4) compare these code predictions to experimental data. Safety tests chosen for modeling include the first and second experiments of the Advanced Gas Reactor program (AGR-1 and AGR-2) and the High Flux Reactor (HFR) EU1bis experiment. This report presents the results obtained by the three research institutions using their respective fuel performance modeling codes. Comparisons of the corresponding fission product release predictions are made with experimental data from AGR-1, AGR-2, and HFR-EU1bis. The benchmark results show good agreements between all participants but also show a general trend of over-prediction of the experimental release data, which is mainly attributed to the use of over-estimated diffusion coefficients.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Experimental Validation of a Resilient Monitoring and Control System

Complex, high performance, engineering systems have to be closely monitored and controlled to ensure safe operation and protect public from potential hazards. One of the main challenges in designing monitoring and control algorithms for these systems is that sensors and actuators may be malfunctioning due to malicious or natural causes. To address this challenge, this paper addresses a resilient monitoring and control (ReMAC) system by expanding previously developed resilient condition assessment monitoring systems and Kalman filter-based diagnostic methods and integrating them with a supervisory controller developed here. While the monitoring and diagnostic algorithms assess plant cyber and physical health conditions, the supervisory controller selects, from a set of candidates, the best controller based on the current plant health assessments. To experimentally demonstrate its enhanced performance, the developed ReMAC system is then used for monitoring and control of a chemical reactor with a water cooling system in a hardware-in-the-loop setting, where the reactor is computer simulated and the water cooling system is implemented by a machine condition monitoring testbed at Idaho National Laboratory. Results show that the ReMAC system is able to make correct plant health assessments despite sensor malfunctioning due to cyber attacks and make decisions that achieve best control actions despite possible actuator malfunctioning. Monitoring challenges caused by mismatches between assumed system component models and actual measurements are also identified for future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Toward Realistic Models of the Electrocatalytic Oxygen Evolution Reaction

The electrocatalytic oxygen evolution reaction (OER) supplies the protons and electrons needed to transform renewable electricity into chemicals and fuels. However, the OER is kinetically sluggish; it operates at significant rates only when the applied potential far exceeds the reversible voltage. The origin of this overpotential is hidden in a complex mechanism involving multiple electron transfers and chemical bond making/breaking steps. Our desire to improve catalytic performance has then made mechanistic studies of the OER an area of major scientific inquiry, though the complexity of the reaction has made understanding difficult. While historically, mechanistic studies have relied solely on experiment and phenomenological models, over the past twenty years ab initio simulation has been playing an increasingly important role in developing our understanding of the electrocatalytic OER and its reaction mechanisms. In this Review we cover advances in our mechanistic understanding of the OER, organized by increasing complexity in the way through which the OER is modeled. We begin with phenomenological models built using experimental data before reviewing early efforts to incorporate ab initio methods into mechanistic studies. We go on to cover how the assumptions in these early ab initio simulations-no electric field, electrolyte, or explicit kinetics-have been relaxed. Through comparison with experimental literature, we explore the veracity of these different assumptions. We summarize by discussing the most critical open challenges in developing models to understand the mechanisms of the OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

3D modeling of effects of increased oxygenation and activity concentration in tumors treated with radionuclides and antiangiogenic drugs

Purpose: Formation of new blood vessels (angiogenesis) in response to hypoxia is a fundamental event in the process of tumor growth and metastatic dissemination. However, abnormalities in tumor neovasculature often induce increased interstitial pressure (IP) and further reduce oxygenation (pO{sub 2}) of tumor cells. In radiotherapy, well-oxygenated tumors favor treatment. Antiangiogenic drugs may lower IP in the tumor, improving perfusion, pO{sub 2} and drug uptake, by reducing the number of malfunctioning vessels in the tissue. This study aims to create a model for quantifying the effects of altered pO{sub 2}-distribution due to antiangiogenic treatment in combination with radionuclide therapy. Methods: Based on experimental data, describing the effects of antiangiogenic agents on oxygenation of GlioblastomaMultiforme (GBM), a single cell based 3D model, including 10{sup 10} tumor cells, was developed, showing how radionuclide therapy response improves as tumor oxygenation approaches normal tissue levels. The nuclides studied were {sup 90}Y, {sup 131}I, {sup 177}Lu, and {sup 211}At. The absorbed dose levels required for a tumor control probability (TCP) of 0.990 are compared for three different log-normal pO{sub 2}-distributions: {mu}{sub 1} = 2.483, {sigma}{sub 1} = 0.711; {mu}{sub 2} = 2.946, {sigma}{sub 2} = 0.689; {mu}{sub 3} = 3.689, and {sigma}{sub 3} = 0.330. The normal tissue absorbed doses will, in turn, depend on this. These distributions were chosen to represent the expected oxygen levels in an untreated hypoxic tumor, a hypoxic tumor treated with an anti-VEGF agent, and in normal, fully-oxygenated tissue, respectively. The former two are fitted to experimental data. The geometric oxygen distributions are simulated using two different patterns: one Monte Carlo based and one radially increasing, while keeping the log-normal volumetric distributions intact. Oxygen and activity are distributed, according to the same pattern. Results: As tumor pO{sub 2} approaches normal tissue levels, the therapeutic effect is improved so that the normal tissue absorbed doses can be decreased by more than 95%, while retaining TCP, in the most favorable scenario and by up to about 80% with oxygen levels previously achieved in vivo, when the least favourable oxygenation case is used as starting point. The major difference occurs in poorly oxygenated cells. This is also where the pO{sub 2}-dependence of the oxygen enhancement ratio is maximal. Conclusions: Improved tumor oxygenation together with increased radionuclide uptake show great potential for optimising treatment strategies, leaving room for successive treatments, or lowering absorbed dose to normal tissues, due to increased tumor response. Further studies of the concomitant use of antiangiogenic drugs and radionuclide therapy therefore appear merited.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Raman − Ramsey pulsed excitation of coherent population trapping resonances in a {sup 87}Rb cell with a buffer gas

We report the results of experimental investigation of the Raman – Ramsey method of pulsed excitation of coherent population trapping (CPT) resonances in a rubidium vapour cell filled with a mixture of Ar and Ne buffer gases. For the development of compact quantum microwave frequency standards, this method is an alternative to the pulsed optical pumping method recently implemented using the same rubidium cell. Both methods have advantages over the traditional double radio-optical resonance technique, the main of which is the substantial suppression of the light shift of the clock transition frequency, since the evolution of the coherence of atomic states forming the clock transition occurs in the absence of laser radiation in the cell. The narrow (110 – 240 Hz) Raman – Ramsey resonances are obtained using the scheme of pulsed excitation of CPT resonances on the D{sub 1} lines of the {sup 87}Rb atom with the same linear (lin||lin) polarisations of the bichromatic laser radiation components. The process of optimising the central fringe linewidth, its contrast, and the linewidth-to-contrast ratio is described. The magnetic dependence of the Raman – Ramsey line central fringe linewidth is experimentally investigated. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning

We report building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation codes are used to model ICF implosions, incomplete physics and the need for approximations deteriorate their predictive capability. Identification of relationships between controllable design inputs and measurable outcomes can help guide the future design of experiments and development of simulation codes, which can potentially improve the accuracy of the computational models used to simulate ICF implosions. In this article, we leverage developments in machine learning (ML) and methods for ML feature importance/sensitivity analysis to identify complex relationships in ways that are difficult to process using expert judgment alone. We present work using random forest (RF) regression for prediction of yield, velocity, and other experimental outcomes given a suite of design parameters, along with an assessment of important relationships and uncertainties in the prediction model. We show that RF models are capable of learning and predicting on ICF experimental data with high accuracy, and we extract feature importance metrics that provide insight into the physical significance of different controllable design inputs for various ICF design configurations. These results can be used to augment expert intuition and simulation results for optimal design of future ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Advanced Diagnostics for High Pressure Spray Combustion.

The development of accurate predictive engine simulations requires experimental data to both inform and validate the models, but very limited information is presently available about the chemical structure of high pressure spray flames under engine- relevant conditions. Probing such flames for chemical information using non- intrusive optical methods or intrusive sampling techniques, however, is challenging because of the physical and optical harshness of the environment. This work details two new diagnostics that have been developed and deployed to obtain quantitative species concentrations and soot volume fractions from a high-pressure combusting spray. A high-speed, high-pressure sampling system was developed to extract gaseous species (including soot precursor species) from within the flame for offline analysis by time-of-flight mass spectrometry. A high-speed multi-wavelength optical extinction diagnostic was also developed to quantify transient and quasi-steady soot processes. High-pressure sampling and offline characterization of gas-phase species formed following the pre-burn event was accomplished as well as characterization of gas-phase species present in the lift-off region of a high-pressure n-dodecane spray flame. For the initial samples discussed in this work several species were identified, including polycyclic aromatic hydrocarbons (PAH); however, quantitative mole fractions were not determined. Nevertheless, the diagnostic developed here does have this capability. Quantitative, time-resolved measurements of soot extinction were also accomplished and the novel use of multiple incident wavelengths proved valuable toward characterizing changes in soot optical properties within different regions of the spray flame.

Skeen, Scott A.↗
DOE OSTI2012

Experimental and Theoretical Study of Confined Charged Fermions: Multielectron Bubbles

The goal of this research was to study multielectron bubbles (MEBs), both experimentally and theoretically. MEBs are two-dimensional electron liquids (2DEGS) on a spherical surface; in this research, they are formed in liquid helium, so that within the helium a hollow spherical bubble filled with a few to billions of electrons is formed, with the electrons on the inner surface. The radius can be a few nanometers to millimeters depending on the number N of electrons that are confined. MEBs can be visually observed, but to now their lifetimes have been a few milliseconds due the method of production. The objective is to produce MEBs with a method such that the lifetime is indefinitely long so that they can be easily studied with precision, and to develop guiding theory of the properties that might be expected. We shall first discuss theoretical results, then experimental.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Benchmarking characterization methods for noisy quantum circuits

Effective methods for characterizing the noise in quantum computing devices are essential for programming and debugging circuit performance. Existing approaches vary in the information obtained as well as the amount of quantum and classical resources required, with more information generally requiring more resources. Here we benchmark the characterization methods of gate set tomography, Pauli channel noise reconstruction, and empirical direct characterization for developing models that describe noisy quantum circuit performance on a 27-qubit superconducting transmon device. We evaluate these models by comparing the accuracy of noisy circuit simulations with the corresponding experimental observations. Here, we find that the agreement of noise model to experiment does not correlate with the information gained by characterization and that the underlying circuit strongly influences the best choice of characterization approach. Empirical direct characterization scales best of the methods we tested and produced the most accurate characterizations across our benchmarks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Poster - 40: Treatment Verification of a 3D-printed Eye Phantom for Proton Therapy

Purpose: Ocular melanoma is a form of eye cancer which is often treated using proton therapy. The benefit of the steep proton dose gradient can only be leveraged for accurate patient eye alignment. A treatment-planning program was written to plan on a 3D-printed anatomical eye-phantom, which was then irradiated to demonstrate the feasibility of verifying in vivo dosimetry for proton therapy using PET imaging. Methods: A 3D CAD eye model with critical organs was designed and voxelized into the Monte-Carlo transport code FLUKA. Proton dose and PET isotope production were simulated for a treatment plan of a test tumour, generated by a 2D treatment-planning program developed using NumPy and proton range tables. Next, a plastic eye-phantom was 3D-printed from the CAD model, irradiated at the TRIUMF Proton Therapy facility, and imaged using a PET scanner. Results: The treatment-planning program prediction of the range setting and modulator wheel was verified in FLUKA to treat the tumour with at least 90% dose coverage for both tissue and plastic. An axial isotope distribution of the PET isotopes was simulated in FLUKA and converted to PET scan counts. Meanwhile, the 3D-printed eye-phantom successfully yielded a PET signal. Conclusions: The 2D treatment-planning program can predict required parameters to sufficiently treat an eye tumour, which was experimentally verified using commercial 3D-printing hardware to manufacture eye-phantoms. Comparison between the simulated and measured PET isotope distribution could provide a more realistic test of eye alignment, and a variation of the method using radiographic film is being developed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗