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SU-C-201-07: Validation of a GATE Gamma Camera Model for the Siemens Symbia

Purpose: To develop a simulation model of a clinical gamma camera/SPECT system and to validate the model using experimental and published measurements from the clinical system. Methods: Geant4 Application for Tomographic Emission (GATE) was used to create a model of the Siemens Symbia gamma camera. A modular model was implemented that allows specifying combinations of crystal thickness (3/8”, 5/8”) and collimator (LEHR, MELP, HE). Shielding, energy resolution, intrinsic resolution, crystal thickness, and collimator properties were set based on manufacturer specifications. Validation of the model was performed by simulating NEMA 2007 gamma camera tests including spatial resolution and sensitivity for Tc99; these were compared with experimental and published data for the scanner. The simulated energy spectra of a Tc99 line source in acrylic blocks was visually compared with the corresponding experimental acquisition. For a 4 cm diameter sphere filled with Tc99, the attenuation maps were generated from simulation data, and the photopeak and scatter window were extracted from GATE output using ROOT to create DICOM files to use in the clinical reconstruction. Results: Simulated spatial resolutions for LEHR 3/8” crystal at 0, 10 cm, 10 cm (with scatter), and 30 cm were 4, 6.7, 7.9, and 14.5 mm FWHM; these were 9% less than published data. For 5/8” crystal the spatial resolutions were 4.5, 7.0, 8.5, and 14.7 mm FWHM; these were 4% to 10% less than published data. Simulated sensitivity was within 3.5% of published data for both LEHR 3/8” and 5/8”. The simulated energy spectra matched the photopeak and scatter window well, but did overestimate the counts below 90 keV. The simulated attenuation map and projection data were successfully reconstructed with the clinical software, and the passed visual inspection. Conclusions: Validation of a specific clinical scanner allows future studies of quantification accuracy for both planar and SPECT imaging. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA138986. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

60 APPLIED LIFE SCIENCES↗

Atomic Force Microscopy Measurement of the Resistivity of Semiconductors

The surface of silicon substrates has been studied experimentally and theoretically by the method of atomic force microscopy spreading resistance imaging, and measuring techniques for the spreading resistance of semiconductors have been developed based on these data. It has been shown that the resistivity of silicon can be determined reliably if the force with which the probe is pressed against the substrate exceeds some threshold. The influence of the environment on the values of currents in the probe–substrate system has been studied. It has been found that the electrical performance of semiconductors can be properly determined by atomic force microscopy spreading resistance imaging under high-vacuum conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

FY17 Status Report on the Initial Development of a Constitutive Model for Grade 91 Steel

Grade 91 is a candidate structural material for high temperature advanced reactor applications. Existing ASME Section III, Subsection HB, Subpart B simplified design rules based on elastic analysis are setup as conservative screening tools with the intent to supplement these screening rules with full inelastic analysis when required. The Code provides general guidelines for suitable inelastic models but does not provide constitutive model implementations. This report describes the development of an inelastic constitutive model for Gr. 91 steel aimed at fulfilling the ASME Code requirements and being included into a new Section III Code appendix, HBB-Z. A large database of over 300 experiments on Gr. 91 was collected and converted to a standard XML form. Five families of Gr. 91 material models were identified in the literature. Of these five, two are potentially suitable for use in the ASME code. These two models were implemented and evaluated against the experimental database. Both models have deficiencies so the report develops a framework for developing and calibrating an improved model. This required creating a new modeling method for representing changes in material rate sensitivity across the full ASME allowable temperature range for Gr. 91 structural components: room temperature to 650° C. On top of this framework for rate sensitivity the report describes calibrating a model for work hardening and softening in the material using genetic algorithm optimization. Future work will focus on improving this trial model by including tension/compression asymmetry observed in experiments and necessary to capture material ratcheting under zero mean stress and by improving the optimization and analysis framework.

36 MATERIALS SCIENCE↗

Use of the Wilshire Equations to Correlate and Extrapolate Creep Data of Inconel 617 and Nimonic 105

Advanced power plant alloys must endure high temperatures and pressures for durations at which creep data are often not available, necessitating the extrapolation of creep life. A recently developed creep life extrapolation method is the Wilshire equations, with which multiple approaches can be used to increase the goodness of fit of available experimental data and improve the confidence level of calculating long-term creep strength at times well beyond the available experimental data. In this article, the Wilshire equation is used to extrapolate the creep life of Inconel 617 and Nimonic 105 to 100,000 h. The use of (a) different methods to determine creep activation energy, (b) region splitting, (c) heat- and processing-specific tensile strength data, and (d) short-duration test data were investigated to determine their effects on correlation and extrapolation. For Inconel 617, using the activation energy of lattice self-diffusion as Q C * resulted in a poor fit with the experimental data. Additionally, the error of calculated rupture times worsened when splitting regions. For Nimonic 105, the error was reduced when heat- and processing-specific tensile strengths were used. Extrapolating Inconel 617 creep strength to 100,000 h life gave conservative results when compared to values calculated by the European Creep Collaborative Committee.

36 MATERIALS SCIENCE↗

CHALLENGES IN DATA INTENSIVE ANALYSIS AT SCIENTIFIC EXPERIMENTAL USER FACILITIES

This chapter will discuss the critical data intensive analysis and visualiza-tion challenges faced by the experimental science community at large scale and laboratory based facilities. The chapter will further highlight initial solutions under development through community efforts and lay out perspectives for the future, such as the potential of more closely linked experimental and computational science approaches, methods to achieve real time analysis capabilities and the challenges and opportunities of data integration across experimental scales, levels of theory and varying techniques.

Chemical Imaging↗

Reactor physics benchmark experiments at the JSI TRIGA MARK II reactor - Current status and future outlook

Full text of publication follows. With the development of new high-fidelity computational methods, improvement of nuclear data, and multiphysics modelling, there is an increased need for benchmark experiments to experimentally validate the models, methods and input data. Many of the nuclear facilities designed to perform reactor physics benchmark experiments have been shut down. Therefore, research reactors offer a great opportunity for benchmark experiments, if they are well designed and performed with great care and accuracy. In this presentation we provide an overview of the past and ongoing activities related to benchmark experiments at the Jozef Stefan Institute TRIGA Mark II research reactor. The following experiments have been performed: criticality with fresh fuel, {sup 197}Au(n,γ) and {sup 27}Al(n,α) reaction rates in irradiation channels, absolute and relative {sup 197}Au(n,γ), {sup 235}U(n,f) and {sup 238}U(n,f) reaction rates in the core, burnup, kinetic parameters, control rod worth, isothermal reactivity coefficient, self-shielding, slow and fast (pulse) transients, nuclear heating, delayed and prompt gamma ray production, temperature profiles for multi-physics. Since the existing fleet of research reactors is ageing very rapidly and new experiments are needed, new research reactors should be designed and built to meet the needs of future advanced reactors, education and training, and other technologies in the coming years. We will review planned activities at the JSI TRIGA reactors and plans for the new research reactor in Slovenia. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental demonstration of real-time electron temperature profile control in DIII-D

Future tokamak reactor operation will require the ability to maintain a given plasma scenario for extended periods of time. This will necessitate the capability to react to changes in the plasma state and return the plasma to the target scenario; the principal method to achieve this is through feedback control. Thus, it is necessary to develop and test feedback controllers for the plasma profiles that define a target scenario. In this work, a feedback controller for the electron temperature (Te) profile is tested experimentally in DIII-D. This experiment relied on the ability to ascertain the electron temperature profile in real time, which was achieved using an observer algorithm. The observer relies on both diagnostic data and a predictive model of the electron temperature profile evolution; this predictive model includes contributions from neural network surrogate models. Because of these dependencies, a number of capabilities needed to be added to the real-time PCS for DIII-D in order to support the Te profile control experiment. The neural network surrogates needed to be integrated into the PCS to be called in real time. An observer algorithm for the Te profile needed to be added and connected to the Thomson scattering system to allow access to the current state of the profile in real time. When tested, the observer was shown to produce Te profiles that are consistent with the shape of the Thomson scattering data while rejecting much of the noise in the diagnostic data. Finally, the controller itself was tested in real time. This experiment showed that the controller is capable of tracking the electron temperature target at locations across the spatial profile.

Morosohk, Shira [Oak Ridge Associated Universities↗

A systematic method for selecting molecular descriptors as features when training models for predicting physiochemical properties

Machine learning has proven to be a powerful tool for accelerating biofuel development. Although numerous models are available to predict a range of properties using chemical descriptors, there is a trade-off between interpretability and performance. Neural networks provide predictive models with high accuracy at the expense of some interpretability, while simpler models such as linear regression often lack in accuracy. In addition to model architecture, feature selection is also critical for developing interpretable and accurate predictive models. We present a method for systematically selecting molecular descriptor features and developing interpretable machine learning models without sacrificing accuracy. Our method simplifies the process of selecting features by reducing feature multicollinearity and enables discoveries of new relationships between global properties and molecular descriptors. To demonstrate our approach, we developed models for predicting melting point, boiling point, flash point, yield sooting index, and net heat of combustion with the help of the Tree-based Pipeline Optimization Tool (TPOT). For training, we used publicly available experimental data for up to 8351 molecules. Our models accurately predict various molecular properties for organic molecules (mean absolute percent error (MAPE) ranges from 3.3% to 10.5%) and provide a set of features that are well-correlated to the property. This method enables researchers to explore sets of features that significantly contribute to the prediction of the property, offering new scientific insights. To help accelerate early stage biofuel research and development, we also integrated the data and models into a open-source, interactive web tool.

09 BIOMASS FUELS↗

Comparing Global Spray Combustion Characteristics and Local Shot-to-Shot Variations in a Reacting n -Heptane Spray

In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.

42 ENGINEERING↗

Photoionization of P + : Experiment and theory

An experimental and theoretical study of the single photoionization cross section of the P + cation of phosphorus is presented. Photoionization (PI) cross sections are instrumental for the determination of abundances in the interstellar medium. The experiment was performed by merging an ion beam with a photon beam. The photon beam was nearly monochromatic and had an energy resolution of 24 meV. Calculations were carried out using the Breit–Pauli R-matrix method. The combined study was developed in the photon energy interval from 18 eV (68.9 nm) to 50 eV (24.8 nm). Comparison between the measured and the calculated cross section shows good agreement in general and identifies features of the process and existence of states in the experimental beam. Here the present results should provide for more accurate modeling of P + .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SU-E-T-644: QuAArC: A 3D VMAT QA System Based On Radiochromic Film and Monte Carlo Simulation of Log Files

Purpose: VMAT involves two main sources of uncertainty: one related to the dose calculation accuracy, and the other linked to the continuous delivery of a discrete calculation. The purpose of this work is to present QuAArC, an alternative VMAT QA system to control and potentially reduce these uncertainties. Methods: An automated MC simulation of log files, recorded during VMAT treatment plans delivery, was implemented in order to simulate the actual treatment parameters. The linac head models and the phase-space data of each Control Point (CP) were simulated using the EGSnrc/BEAMnrc MC code, and the corresponding dose calculation was carried out by means of BEAMDOSE, a DOSXYZnrc code modification. A cylindrical phantom was specifically designed to host films rolled up at different radial distances from the isocenter, for a 3D and continuous dosimetric verification. It also allows axial and/or coronal films and point measurements with several types of ion chambers at different locations. Specific software was developed in MATLAB in order to process and evaluate the dosimetric measurements, which incorporates the analysis of dose distributions, profiles, dose difference maps, and 2D/3D gamma index. It is also possible to obtain the experimental DVH reconstructed on the patient CT, by an optimization method to find the individual contribution corresponding to each CP on the film, taking into account the total measured dose, and the corresponding CP dose calculated by MC. Results: The QuAArC system showed high reproducibility of measurements, and consistency with the results obtained with the commercial system implemented in the verification of the evaluated treatment plans. Conclusion: A VMAT QA system based on MC simulation and high resolution dosimetry with film has been developed for treatment verification. It shows to be useful for the study of the real VMAT capabilities, and also for linac commissioning and evaluation of other verification devices.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Progress in end-to-end optimization of fundamental physics experimental apparata with differentiable programming

In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the specification of a software pipeline including all factors impacting performance — from the data-generating processes to their reconstruction and the inference on the parameters of interest — along with the careful specification of a utility function well aligned with the end goals of the experiment. Building on previous studies originated within the MODE Collaboration, we focus specifically on applications involving instruments for particle physics experimentation, as well as industrial and medical applications that share the detection of radiation as their data-generating mechanism. This report illustrates the most recent advancements in the area, and outlines, for each of the discussed applications as well as for automatic differentiation itself, ongoing and future work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparative Assessment of Experimental Testing of Instrument with an Embedded Digital Device Using Model-Based and Conventional Methods

The use of digital equipment has not been widespread in U.S. nuclear facilities. A major contributing factor to this situation arises from regulatory concerns about common cause failures (CCFs) stemming from the use of identical software in redundant systems, questions as to how to quantify the reliability of software-based products, validity of tools that are used for software verification and validation (V&V), and the effectiveness of software QA procedures. Compounding the concerns are sporadic incidents of digital equipment malfunctions in nuclear power plants, including lockups resulting from software memory leaks, feedwater control malfunctions due to excessive traffic on Ethernet networks, software logic errors, and other problems leading to plant trips. Additionally, the limited amount of demonstrated research and a lack of industry consensus on quantitative software reliability methodologies has hindered the widespread adoption of digital I&C in the nuclear industry. In a recent Regulatory Issue Summary (RIS), the U.S. Nuclear Regulatory Commission (NRC) identified concerns about the impact of greater use of instrumentation and control (I&C) equipment with an embedded digital device (EDD) [1]. Specifically, the NRC staff states that increased use of such devices “may increase a facility’s vulnerability to a CCF” (i.e., common-cause failure). The prevailing NRC guidance regarding software CCF (SCCF) identifies two design attributes that are acceptable for eliminating CCF concerns: (1) diversity or (2) testability (specifically, 100% testability). Either solution can result in high costs and remaining licensing uncertainty (i.e., how much diversity is enough? how to ensure test coverage of every possible sequence of device states?). Consequently, many utilities and reactor designers have limited or avoided more extensive use of digital technology to minimize licensing, scheduling, and financial risk. Without development of cost effective qualification methods to satisfy regulatory requirements and address the potential for CCF vulnerability associated with EDDs, the nuclear power industry may not be able to realize the benefits of digital technology achieved by other industries. In order to address these challenges, the U.S. Department of Energy (DOE) is sponsoring this research to assess the prospect of CCF in digital I&C equipment. The purpose of the current research is to develop an effective approach employing science-based methods to resolve concerns about CCF vulnerability that serve to inhibit deployment of advanced instrumentation (e.g., sensors, actuators, microcontrollers) with EDDs in nuclear power applications. The research objectives address the challenge of establishing high levels of safety and reliability assurance needed for the qualification of EDDs (e.g., microprocessors, programmable logic devices) that are subject to software design faults, complex failure modes, and CCF vulnerability. Specific objectives are: (1) assess the regulatory context for treatment of CCF vulnerability a graded approach to their qualification, (3) develop and extend model-based testing methods to enable effective demonstration of whether devices are subject to CCF, which may arise from vulnerabilities introduced at any stage of the design lifecycle, (4) establish a cost-effective testing framework that incorporates automation and test scenario prioritization, and (5) demonstrate the qualification approach through selection and testing of candidate digital device(s). This report documents an assessment of the results from experimental testing of a representative instrument with an embedded digital device. The experiment serves as a proof-of-concept demonstration of a model-based testing (MBT) framework. The objective of MBT is to ensure that an EDD undergoes suitably comprehensive testing to establish that it is not subject to SCCF. The approach by which MBT accomplishes this objective is through development and application of an effective test suite that provides the appropriate coverage to detect the full range of postulated faults that may arise at the requirements, design, and code (implementation) level of the EDD software. The findings of the experiment involve the application of the MBT framework by Ohio State University (OSU) through testing of the selected demonstration instrument (i.e., the prototype smart pressure sensor developed by Virginia Commonwealth University, VCU). In addition, the experiment findings also involve application of a more conventional black-box testing approach that serves as a baseline against which the MBT methodology can be compared. The primary outcome documented in this report is the comparative analysis of the capabilities demonstrated for each method. The results of the analysis demonstrate clear benefits that arise from the MBT methodology. The comparison indicates greater effectiveness from the more comprehensive evidence available through MBT and enhanced efficiency achieved through automation within the MBT framework. The structure of the report addresses the approach and application of each test method as well as the comparative analysis of the experimental results. Chapter 2 gives a summary overview of the demonstration approach. Chapter 3 covers the baseline testing and Chapter 4 documents the model-based testing. Chapter 5 describes the findings of the comparative analysis and presents the conclusions that can be drawn about the effectiveness and efficiency of the MBT methodology.

47 OTHER INSTRUMENTATION↗

Metal Big Area Additive Manufacturing: Process Modeling and Validation

Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology for printing large-scale 3D objects. mBAAM is based on the gas metal arc welding process and uses a continuous feed of welding wire to manufacture an object. An electric arc forms between the wire and the substrate, which melts the wire and deposits a bead of molten metal along the predetermined path. In general, the welding process parameters and local conditions determine the shape of the deposited bead. The sequence of the bead deposition and the corresponding thermal history of the manufactured object determine the long range effects, such as thermal-induced distortions and residual stresses. Therefore, the resulting performance or final properties of the manufactured object are dependent on its geometry and the deposition path, in addition to depending on the basic welding process parameters. Physical testing is critical for gaining the necessary knowledge for quality prints, but traversing the process parameter space in order to develop an optimized build strategy for each new design is impractical by pure experimental means. Computational modeling and optimization may accelerate development of a build process strategy and saves time and resources. Because computational modeling provides these opportunities, we have developed a physics-based Finite Element Method (FEM) simulation framework and numerical models to support the mBAAM process s development and design. In this paper, we performed a sequentially coupled heat transfer and stress analysis for predicting the final deformation of a small rectangular structure printed using the mild steel welding wire. Using the new simulation technologies, material was progressively added into the FEM simulation as the arc weld traversed the build path. In the sequentially coupled heat transfer and stress analysis, the heat transfer was performed to calculate the temperature evolution, which was used in a stress analysis to evaluate the residual stresses and distortions. In this formulation, we assume that physics is directionally coupled, i.e. the effect of stress of the component on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

Additive Manufacturing↗

New contactless method for thermal diffusivity measurements using modulated photothermal radiometry

Modulated photothermal radiometry is a non-destructive and contactless technique for the characterization of materials. It has two major advantages: a good signal-to-noise ratio through a synchronous detection and a low dependence on the heating power and the optical properties of the sample surface. This paper presents a new method for characterizing the thermal diffusivity of a material when the phase shift between a modulated laser power signal and the thermal signal of a plate sample is known at different frequencies. The method is based on a three-dimensional analytical model which is used to determine the temperature amplitude and the phase in the laser heating of the plate. A new simple formula was developed through multi-parametric analysis to determine the thermal diffusivity of the plate with knowledge of the frequency at the minimum phase shift, the laser beam radius r{sub 0} and the sample thickness L. This method was developed to control the variation of the thermal diffusivity of nuclear components and it was first applied to determine the thermal diffusivity of different metals: 304 L stainless steel, nickel, titanium, tungsten, molybdenum, zinc, and iron. The experimental results were obtained with 5%–10% accuracy and corresponded well with the reference values. The present paper also demonstrates the limit of application of this method for plate with thickness r{sub 0}/100 ≤ L ≤ r{sub 0}/2. The technique is deemed interesting for the characterization of barely accessible components that require a contactless measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

General Diffuse-Interface Theories and an Approach to Predictive Tumor Growth Modeling

While a large and growing literature exists on mathematical and computational models of tumor growth, to date tumor growth models are largely qualitative in nature, and fall far short of being able to provide predictive results important in life-and-death decisions. This is largely due to the enormous complexity of evolving biological and chemical processes in living tissue and the complex interactions of many cellular and vascular constituents in living organisms. Several new technologies have emerged, however, which could lead to significant progress in this important area: (i) the development of so-called phase-field, or diffuse-interface models, which can be developed using continuum mixture theory, and which provide a general framework for modeling the action of multiple interacting constituents. These are based on generalizations of the Cahn–Hilliard models for spinodal decomposition, and have been used recently in certain tumor growth theories; (ii) the emergence of predictive computational methods based on the use of statistical methods for calibration, model validation, and uncertainty quantification; (iii) advances in imaging, experimental cell biology, and other medical observational methodologies; and (iv) the advent of petascale computing that makes possible the resolution of features at scales and at speeds that were unattainable only a short time in the past. Here we develop a general phenomenological thermomechanical theory of mixtures that employs phase-field or diffuse interface models of surface energies and reactions and which provides a framework for generalizing existing theories of the types that are in use in tumor growth modeling. In principle, the framework provides for the effects of M solid constituents, which may undergo large deformations, and for the effect of N - M fluid constituents, which could include highly nonlinear, non-Newtonian fluids. We then describe several special cases which have the potential of providing acceptable models of tumor growth. We then describe the beginning steps of the development of Bayesian methods for statistical calibration, model validation, and uncertainty quantification, which, with further work, could produce a truly predictive tool for studying tumor growth. In particular, we outline the processes of statistical calibration and validation that can be employed to determine if tumor growth models, drawn from the broad class of models developed here, are valid for prediction of key quantities of interest critical to making decisions on various medical protocols. We also describe how uncertainties in such key quantities of interest can be quantified in ways that can be used to establish confidence in predicted outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-physics melt pool modeling and process optimization for laser direct energy deposition of Nb-based refractory C103: Defect formation, geometric precision, and process mapping

Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.

Defect formation and geometric precision↗