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DOE OSTI2016

Space-filling designs for computer experiments: A review

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conducted for optimizing a milling process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Monte Carlo simulation of PET and SPECT imaging of {sup 90}Y

Purpose: Yittrium-90 ({sup 90}Y) is traditionally thought of as a pure beta emitter, and is used in targeted radionuclide therapy, with imaging performed using bremsstrahlung single-photon emission computed tomography (SPECT). However, because {sup 90}Y also emits positrons through internal pair production with a very small branching ratio, positron emission tomography (PET) imaging is also available. Because of the insufficient image quality of {sup 90}Y bremsstrahlung SPECT, PET imaging has been suggested as an alternative. In this paper, the authors present the Monte Carlo-based simulation–reconstruction framework for {sup 90}Y to comprehensively analyze the PET and SPECT imaging techniques and to quantitatively consider the disadvantages associated with them. Methods: Our PET and SPECT simulation modules were developed using Monte Carlo simulation of Electrons and Photons (MCEP), developed by Dr. S. Uehara. PET code (MCEP-PET) generates a sinogram, and reconstructs the tomography image using a time-of-flight ordered subset expectation maximization (TOF-OSEM) algorithm with attenuation compensation. To evaluate MCEP-PET, simulated results of {sup 18}F PET imaging were compared with the experimental results. The results confirmed that MCEP-PET can simulate the experimental results very well. The SPECT code (MCEP-SPECT) models the collimator and NaI detector system, and generates the projection images and projection data. To save the computational time, the authors adopt the prerecorded {sup 90}Y bremsstrahlung photon data calculated by MCEP. The projection data are also reconstructed using the OSEM algorithm. The authors simulated PET and SPECT images of a water phantom containing six hot spheres filled with different concentrations of {sup 90}Y without background activity. The amount of activity was 163 MBq, with an acquisition time of 40 min. Results: The simulated {sup 90}Y-PET image accurately simulated the experimental results. PET image is visually superior to SPECT image because of the low background noise. The simulation reveals that the detected photon number in SPECT is comparable to that of PET, but the large fraction (approximately 75%) of scattered and penetration photons contaminates SPECT image. The lower limit of {sup 90}Y detection in SPECT image was approximately 200 kBq/ml, while that in PET image was approximately 100 kBq/ml. Conclusions: By comparing the background noise level and the image concentration profile of both the techniques, PET image quality was determined to be superior to that of bremsstrahlung SPECT. The developed simulation codes will be very useful in the future investigations of PET and bremsstrahlung SPECT imaging of {sup 90}Y.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2020

3D micromechanical simulation of PBX composites

Previous research studied the constitutive response and interface strength of a bonded bicrystal system containing two HMX explosive grains bound with a HTPB polymer binder by performing FE simulations on real geometry imaged with micro Computed Tomography (µCT). The parameters generated from this past study were successfully applied to 2D mesoscale simulations of µCT imaged HMX-HTPB polycrystal samples. Presently, the mechanical response of PBXs containing a Nitro-Plasticized Estane (NPE) binder with similar microstructural geometry to the HMX-HTPB polycrystal samples were studied. Imaging of a HMX-NPE bicrystal sample allowed for simulation of the new material pairing. However, imaging using µCT techniques on the new polycrystal samples was difficult due to the decrease in contrast between the HMX grains and the NPE binder. Mesoscale polycrystal simulations utilizing a single µCT imaged microstructure were performed on a 3D representative volume element (RVE) comparing the delamination behavior and mechanical response of both HMX-HTPB and HMX-NPE PBXs. Furthermore, this technique shows the ability to virtually explore the mechanical response of a range of hypothetical materials that share common microstructural geometric characteristics in addition to studying numerically altered geometries.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗

DOE OSTI2013

QUANTIFYING OBSERVATIONAL PROJECTION EFFECTS USING MOLECULAR CLOUD SIMULATIONS

The physical properties of molecular clouds are often measured using spectral-line observations, which provide the only probes of the clouds' velocity structure. It is hard, though, to assess whether and to what extent intensity features in position-position-velocity (PPV) space correspond to 'real' density structures in position-position-position (PPP) space. In this paper, we create synthetic molecular cloud spectral-line maps of simulated molecular clouds, and present a new technique for measuring the reality of individual PPV structures. Using a dendrogram algorithm, we identify hierarchical structures in both PPP and PPV space. Our procedure projects density structures identified in PPP space into corresponding intensity structures in PPV space and then measures the geometric overlap of the projected structures with structures identified from the synthetic observation. The fractional overlap between a PPP and PPV structure quantifies how well the synthetic observation recovers information about the three-dimensional structure. Applying this machinery to a set of synthetic observations of CO isotopes, we measure how well spectral-line measurements recover mass, size, velocity dispersion, and virial parameter for a simulated star-forming region. By disabling various steps of our analysis, we investigate how much opacity, chemistry, and gravity affect measurements of physical properties extracted from PPV cubes. For the simulations used here, which offer a decent, but not perfect, match to the properties of a star-forming region like Perseus, our results suggest that superposition induces a ∼40% uncertainty in masses, sizes, and velocity dispersions derived from {sup 13}CO (J = 1-0). As would be expected, superposition and confusion is worst in regions where the filling factor of emitting material is large. The virial parameter is most affected by superposition, such that estimates of the virial parameter derived from PPV and PPP information typically disagree by a factor of ∼2. This uncertainty makes it particularly difficult to judge whether gravitational or kinetic energy dominate a given region, since the majority of virial parameter measurements fall within a factor of two of the equipartition level α ∼ 2.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Electron parametric instabilities in nonuniform plasma with a strong density gradient excited by femtosecond laser pulses of subrelativistic intensity

We consider the excitation of electron parametric instability in the oblique incidence of femtosecond laser radiation of subrelativistic intensity on a plasma with the nonuniformity scale length of the order of the radiation wavelength λ. Estimates are obtained for two-plasmon decay instability increments in this plasma, and the generation of plasma waves due to parametric instabilities is numerically simulated by the particle-in-cell technique. The spatial spectrum of these waves is shown to broaden to the level corresponding to several values of the wavenumber k{sub 0} of the component aligned with the electron density gradient and the wavenumbers of the component normal to the gradient have values ∼ k{sub 0}. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Neoclassical transport of tungsten ion bundles in total-f neoclassical gyrokinetic simulations of a whole-volume JET-like plasma

Here, the application of a bundling technique to model the diverse charge states of tungsten impurity species in total-f gyrokinetic simulations is demonstrated. The gyrokinetic bundling method strategically groups tungsten ions of similar charge, optimizing computational efficiency. The initial radial configuration of these bundles and their respective charges are derived from a coronal approximation and the quasi-neutrality of the plasma. A low-density JET H-mode like plasma is simulated using the neoclassical version of XGC across the entire plasma volume, spanning from the magnetic axis to the divertor. An accumulation of tungsten is observed at the pedestal top, as a result of low-Z tungsten ions moving inward from the scrape-off-layer into the core region and high-Z tungsten ions moving outward from the core into the pedestal. This organization of the fluxes cannot be captured by a single tungsten-ion simulation. Large up-down poloidal asymmetries of tungsten form in the pedestal and strongly influence the direction of neoclassical fluxes. The temperature screening effect and its correlation with asymmetries are analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Deep inference of simulated strong lenses in ground-based surveys

The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dark matter. However, leveraging the increased statistical power of such large samples will require further development of automated lens modeling techniques. We show that deep learning and simulation-based inference (SBI) methods produce informative and reliable estimates of parameter posteriors for strong lensing systems in ground-based surveys. We present the examination and comparison of two approaches to lens parameter estimation for strong galaxy-galaxy lenses — Neural Posterior Estimation (NPE) and Bayesian Neural Networks (BNNs). We perform inference on 1-, 5-, and 12-parameter lens models for ground-based imaging data that mimics the Dark Energy Survey (DES). We find that NPE outperforms BNNs, producing posterior distributions that are more accurate, precise, and well-calibrated for most parameters. For the 12-parameter NPE model, the calibration is consistently within <10% of optimal calibration for all parameters, while the BNN is rarely within 20% of optimal calibration for any of the parameters. Similarly, residuals for most of the parameters are smaller (by up to an order of magnitude) with the NPE model than the BNN model. This work takes important steps in the systematic comparison of methods for different levels of model complexity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

MO-D-PinS Room/Hall E-00: MR Simulation

MRI, with its excellent soft tissue contrast and its ability to provide physiological as well as anatomical information, is becoming increasingly used in radiation therapy for treatment planning, image-guided radiation therapy, and treatment evaluation. This session will explore solutions to integrating MRI into the simulation process. Obstacles for using MRI for simulation include distortions and artifacts, image acquisition speed, complexity of imaging techniques, and lack of electron density information. Partners in Solutions presents vendor representatives who will present their approaches to meeting these challenges and others. An increased awareness of how MRI simulation works will allow physicists to better understand and use this powerful technique. The speakers are all employees who are presenting information about their company’s products.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Final Report: Sublinear Algorithms for In-situ and In-transit Data Analysis at Exascale.

Post-Moore's law scaling is creating a disruptive shift in simulation workflows, as saving the entirety of raw data to persistent storage becomes expensive. We are moving away from a post-process centric data analysis paradigm towards a concurrent analysis framework, in which raw simulation data is processed as it is computed. Algorithms must adapt to machines with extreme concurrency, low communication bandwidth, and high memory latency, while operating within the time constraints prescribed by the simulation. Furthermore, in- put parameters are often data dependent and cannot always be prescribed. The study of sublinear algorithms is a recent development in theoretical computer science and discrete mathematics that has significant potential to provide solutions for these challenges. The approaches of sublinear algorithms address the fundamental mathematical problem of understanding global features of a data set using limited resources. These theoretical ideas align with practical challenges of in-situ and in-transit computation where vast amounts of data must be processed under severe communication and memory constraints. This report details key advancements made in applying sublinear algorithms in-situ to identify features of interest and to enable adaptive workflows over the course of a three year LDRD. Prior to this LDRD, there was no precedent in applying sublinear techniques to large-scale, physics based simulations. This project has definitively demonstrated their efficacy at mitigating high performance computing challenges and highlighted the rich potential for follow-on re- search opportunities in this space.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Measurement of areal density in the ablators of inertial-confinement-fusion capsules via detection of ablator (n, n Prime {gamma}) gamma-ray emission

We report the first gamma-ray-based measurements of the areal density of ablators in inertial-confinement-fusion capsule implosions. The measurements, made at the OMEGA laser [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)], used observations of gamma rays arising from inelastic scattering of 14.1-MeV deuterium-tritium (DT) neutrons on {sup 12}C nuclei in the compressed plastic ablators. The emission of {sup 12}C(n,n Prime {gamma}) gamma rays from the capsules is detected using the Gamma Reaction History instrument [H. W. Herrmann et al., J. Phys.: Conf. Ser. 244, 032047 (2010)] operating at OMEGA. From the ratio of a capsule's {sup 12}C(n,n Prime {gamma}) emission to the emission from the same processes in an in situ reference graphite 'puck' of known mass and geometry [N. M. Hoffman et al., in IFSA 2011 proceedings (submitted)], we determine the time-averaged areal density of {sup 12}C in the capsule's compressed ablator. Measured values of total ablator areal density for thirteen imploded capsules, in the range 23 {+-} 10 to 58 {+-} 14 mg/cm{sup 2}, are comparable to values calculated in 1D radiation-hydrodynamic simulations, and measured by charged-particle techniques.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Characterization of scatter in digital mammography from use of Monte Carlo simulations and comparison to physical measurements

Purpose: Monte Carlo simulations were performed with the goal of verifying previously published physical measurements characterizing scatter as a function of apparent thickness. A secondary goal was to provide a way of determining what effect tissue glandularity might have on the scatter characteristics of breast tissue. The overall reason for characterizing mammography scatter in this research is the application of these data to an image processing-based scatter-correction program. Methods: MCNPX was used to simulate scatter from an infinitesimal pencil beam using typical mammography geometries and techniques. The spreading of the pencil beam was characterized by two parameters: mean radial extent (MRE) and scatter fraction (SF). The SF and MRE were found as functions of target, filter, tube potential, phantom thickness, and the presence or absence of a grid. The SF was determined by separating scatter and primary by the angle of incidence on the detector, then finding the ratio of the measured scatter to the total number of detected events. The accuracy of the MRE was determined by placing ring-shaped tallies around the impulse and fitting those data to the point-spread function (PSF) equation using the value for MRE derived from the physical measurements. The goodness-of-fit was determined for each data set as a means of assessing the accuracy of the physical MRE data. The effect of breast glandularity on the SF, MRE, and apparent tissue thickness was also considered for a limited number of techniques. Results: The agreement between the physical measurements and the results of the Monte Carlo simulations was assessed. With a grid, the SFs ranged from 0.065 to 0.089, with absolute differences between the measured and simulated SFs averaging 0.02. Without a grid, the range was 0.28–0.51, with absolute differences averaging −0.01. The goodness-of-fit values comparing the Monte Carlo data to the PSF from the physical measurements ranged from 0.96 to 1.00 with a grid and 0.65 to 0.86 without a grid. Analysis of the data suggested that the nongrid data could be better described by a biexponential function than the single exponential used here. The simulations assessing the effect of breast composition on SF and MRE showed only a slight impact on these quantities. When compared to a mix of 50% glandular/50% adipose tissue, the impact of substituting adipose or glandular breast compositions on the apparent thickness of the tissue was about 5%. Conclusions: The findings show agreement between the physical measurements published previously and the Monte Carlo simulations presented here; the resulting data can therefore be used more confidently for an application such as image processing-based scatter correction. The findings also suggest that breast composition does not have a major impact on the scatter characteristics of breast tissue. Application of the scatter data to the development of a scatter-correction software program can be simplified by ignoring the variations in density among breast tissues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaView plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.

42 ENGINEERING↗

DOE OSTI2016

MO-D-PinS Room/Hall E-01: Integrating MR into Radiation Therapy

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-D-PinS Room/Hall E-03: Ingenia MR-RT with MRCAT for MR-Based Radiotherapy Simulation

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Series Resistance Measurements of Perovskite Solar Cells Using J sc – V oc Measurements

The fill factor (FF) of perovskite solar cells is considerably lower than that of gallium arsenide and silicon cells, though they have similar open–circuit voltage deficits. To probe the FF loss, which mainly comes from series resistance, the J sc –V oc characterization technique is applied to perovskite solar cells. A continuous–lamp solar simulator with an array of neutral density filters is used instead of the quasi–steady–state photoconductance technique commonly employed for silicon cells, which allows us to tune sweep parameters to accommodate the complex behavior of perovskites such as hysteresis. It is found that, for Cs 0.25 FA 0.75 Pb(Br 0.2 I 0.8 ) 3 (CsFA) perovskite cells, sweeping from positive to negative voltage yields the same series resistance regardless of sweep speed, whereas this is not the case if the sweep is reversed. However, for CH 3 NH 3 PbI 3 perovskite cells, the series resistance is independent of the sweep speed in both sweep directions. Furthermore, it is also found that, for a poly[bis(4–phenyl)(2,4,6–trimethylphenyl)amine] (PTAA) hole contact, increasing the PTAA thickness barely changes the recombination–limited pseudo–FF, but reduces the FF due to increased series resistance. A maximum FF of 80.9% was achieved with the PTAA hole contact on a CsFA perovskite absorber.

14 SOLAR ENERGY↗

DOE OSTI2016

A Cartesian cut cell method for rarefied flow simulations around moving obstacles

For accurate simulations of rarefied gas flows around moving obstacles, we propose a cut cell method on Cartesian grids: it allows exact conservation and accurate treatment of boundary conditions. Our approach is designed to treat Cartesian cells and various kinds of cut cells by the same algorithm, with no need to identify the specific shape of each cut cell. This makes the implementation quite simple, and allows a direct extension to 3D problems. Such simulations are also made possible by using an adaptive mesh refinement technique and a hybrid parallel implementation. This is illustrated by several test cases, including a 3D unsteady simulation of the Crookes radiometer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Contextual subspace variational quantum eigensolver calculation of the dissociation curve of molecular nitrogen on a superconducting quantum computer

Abstract We present an experimental demonstration of the Contextual Subspace Variational Quantum Eigensolver on superconducting hardware. Calculating the potential energy curve of molecular nitrogen proves challenging for many conventional quantum chemistry techniques, since static correlation dominates in the dissociation limit. Our quantum simulations retain good agreement with the Full Configuration Interaction energy, outperforming all benchmarked single-reference wavefunction techniques in capturing the bond-breaking appropriately. Moreover, our methodology is competitive with multiconfigurational approaches but at a saving of quantum resource, meaning larger active spaces can be treated for a fixed qubit allowance. To achieve this result, we deploy an error mitigation/suppression strategy comprised of Dynamical Decoupling, Measurement-Error Mitigation and Zero-Noise Extrapolation. Circuit parallelization also provides passive noise-averaging and improves the effective shot yield to reduce the measurement overhead. Furthermore, we introduce a modified adaptive ansatz construction algorithm that incorporates hardware awareness into our variational circuits, minimizing the transpilation cost for the target qubit topology.

Physics↗