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DOE OSTI2014

Advanced Simulation & Computing FY15 Implementation Plan Volume 2, Rev. 0.5

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counternuclear terrorism.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Advanced Simulation and Computing Implementation Plan, FY15, Rev. 1

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Dynamic analysis environment for nuclear forensic analyses

We report a Dynamic Analysis Environment (DAE) software package is introduced to facilitate group inclusion/exclusion method testing, evaluation and comparison for pre-detonation nuclear forensics applications. Employing DAE, the multivariate signatures of a questioned material can be compared to the signatures for different, known groups, enabling the linking of the questioned material to its potential process, location, or fabrication facility. Advantages of using DAE for group inclusion/exclusion include built-in query tools for retrieving data of interest from a database, the recording and documentation of all analysis steps, a clear visualization of the analysis steps intelligible to a non-expert, and the ability to integrate analysis tools developed in different programming languages. Two group inclusion/exclusion methods are implemented in DAE: principal component analysis, a parametric feature extraction method, and k nearest neighbors, a nonparametric pattern recognition method. Spent Fuel Isotopic Composition (SFCOMPO), an open source international database of isotopic compositions for spent nuclear fuels (SNF) from 14 reactors, is used to construct PCA and KNN models for known reactor groups, and 20 simulated SNF samples are utilized in evaluating the performance of these group inclusion/exclusion models. For all 20 simulated samples, PCA in conjunction with the Q statistic correctly excludes a large percentage of reactor groups and correctly includes the true reactor of origination. As a result, employing KNN, 14 of the 20 simulated samples are classified to their true reactor of origination.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Optimization of an aerostructural machining process using physics-guided Bayesian stability modelling

Existing algorithms for predicting milling chatter have not been widely adopted in industry since they require specialized instruments to measure the stability inputs. This study describes how the machining process for a meter-scale aluminum aerostructure was optimized using a physics-guided Bayesian stability model. The study was performed in collaboration with an industrial partner on production machines to evaluate the practicality of the proposed method under real-world conditions. For each cutting tool, the Bayesian approach automatically selected a small number of cutting tests, which were monitored using a microphone to observe the chatter frequency. The algorithm learned the system dynamics, cutting forces, and stability map from these test results. A novel algorithm for predicting tool bending stress was incorporated into the test selection algorithm to avoid tool breakage. On average, each set of optimized cutting parameters required less than six tests to identify and were 97% more productive than baseline parameters from the cutting tool manufacturer. The machining program was then further optimized using commercial feedrate scheduling software to remove cutting force spikes and reduce air cutting time. Five components were machined using the optimized process. These results demonstrate the potential for physics-guided Bayesian models to improve productivity in industrial settings.

Cornelius, Aaron [UT Knoxville]↗

DOE OSTI2025

COLUMBUS─An Efficient and General Program Package for Ground and Excited State Computations Including Spin–Orbit Couplings and Dynamics

The COLUMBUS program system provides the tools for performing high-level multireference (MR) computations, including the multireference configuration interaction (MRCI) method and its multireference averaged quadratic coupled cluster (MR-AQCC) extension, allowing computations on a wide range of fascinating atomic and molecular systems, including the treatment of open-shells and complicated excited state phenomena. The inclusion of spin−orbit coupling (SOC) directly within the MRCI step enables the description of systems containing heavy elements, such as lanthanides and actinides, whose properties are strongly influenced by SOC. Analytic energy gradients and nonadiabatic couplings at the correlated MRCI level provide the foundation for a variety of dynamics studies, giving insight into ultrafast photochemistry. New and ongoing method developments in COLUMBUS include the computation of spin densities, improved descriptions of ionic states, enhancements to the AQCC method, and the porting of COLUMBUS to graphical processing units (GPUs). New external interfaces enable an enhanced description of electronic resonances and molecules in strong laser fields. This work highlights these new developments while providing a detailed account of the diverse applications of COLUMBUS in recent years.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich data challenges existing data storage and access technologies, therefore precluding informatics advancements. Here we present MZA™ (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed by a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and efficient programmatic access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Tracking HIV-1 recombination to resolve its contribution to HIV-1 evolution in natural infection

Recombination in HIV-1 is well documented, but its importance in the low-diversity setting of within-host diversification is less understood. Here we develop a novel computational tool (RAPR (Recombination Analysis PRogram)) to enable a detailed view of in vivo viral recombination during early infection, and we apply it to near-full-length HIV-1 genome sequences from longitudinal samples. Recombinant genomes rapidly replace transmitted/founder (T/F) lineages, with a median half-time of 27 days, increasing the genetic complexity of the viral population. We identify recombination hot and cold spots that differ from those observed in inter-subtype recombinants. Furthermore, RAPR analysis of longitudinal samples from an individual with well-characterized neutralizing antibody responses shows that recombination helps carry forward resistance-conferring mutations in the diversifying quasispecies. These findings provide insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis and have implications for studies of HIV transmission and evolution in vivo.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

ARIADNE – a program estimating covariances in detail for neutron experiments

The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently, it is designed to aid in the uncertainty quantification of prompt fission neutron spectra, and was employed to estimate experimental covariances for CIELO and ENDF/B-VIII.0 evaluations. It provides a streamlined way to estimate detailed covariances by (1) implementing uncertainty quantification algorithms specific to the observables, (2) defining input quantities for typically encountered uncertainty sources and correlation shapes, and (3) automatically generating plots of data, uncertainties and correlations, GND formatted XML and plain text output files. Covariances of the same and between different datasets can be estimated, and tools are provided to assemble a database of experimental data and covariances for an evaluation based on ARIADNE outputs. The underlying IPython notebook files can be easily stored, including all assumptions on uncertainties, leading to more reproducible inputs for nuclear data evaluations. Here, the key inputs and outputs are shown along with a representative example for the current version of ARIADNE to illustrate its usability and to open a discussion on how it could address further needs of the nuclear data evaluation community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Optical properties of InAsBi and optimal designs of lattice-matched and strain-balanced III-V semiconductor superlattices

The optical properties of bulk InAs{sub 0.936}Bi{sub 0.064} grown by molecular beam epitaxy on a (100)-oriented GaSb substrate are measured using spectroscopic ellipsometry. The index of refraction and absorption coefficient are measured over photon energies ranging from 44 meV to 4.4 eV and are used to identify the room temperature bandgap energy of bulk InAs{sub 0.936}Bi{sub 0.064} as 60.6 meV. The bandgap of InAsBi is expressed as a function of Bi mole fraction using the band anticrossing model and a characteristic coupling strength of 1.529 eV between the Bi impurity state and the InAs valence band. These results are programmed into a software tool that calculates the miniband structure of semiconductor superlattices and identifies optimal designs in terms of maximizing the electron-hole wavefunction overlap as a function of transition energy. These functionalities are demonstrated by mapping the design spaces of lattice-matched GaSb/InAs{sub 0.911}Sb{sub 0.089} and GaSb/InAs{sub 0.932}Bi{sub 0.068} and strain-balanced InAs/InAsSb, InAs/GaInSb, and InAs/InAsBi superlattices on GaSb. The absorption properties of each of these material systems are directly compared by relating the wavefunction overlap square to the absorption coefficient of each optimized design. Optimal design criteria are provided for key detector wavelengths for each superlattice system. The optimal design mid-wave infrared InAs/InAsSb superlattice is grown using molecular beam epitaxy, and its optical properties are evaluated using spectroscopic ellipsometry and photoluminescence spectroscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Coherent states, quantum gravity, and the Born- Oppenheimer approximation. II. Compact Lie groups

In this article, the second of three, we discuss and develop the basis of a Weyl quantisation for compact Lie groups aiming at loop quantum gravity-type models. This Weyl quantisation may serve as the main mathematical tool to implement the program of space adiabatic perturbation theory in such models. As we already argued in our first article, space adiabatic perturbation theory offers an ideal framework to overcome the obstacles that hinder the direct implementation of the conventional Born-Oppenheimer approach in the canonical formulation of loop quantum gravity. Additionally, we conjecture the existence of a new form of the Segal-Bargmann-Hall “coherent state” transform for compact Lie groups G, which we prove for G = U(1){sup n} and support by numerical evidence for G = SU(2). The reason for conjoining this conjecture with the main topic of this article originates in the observation that the coherent state transform can be used as a basic building block of a coherent state quantisation (Berezin quantisation) for compact Lie groups G. But, as Weyl and Berezin quantisation for ℝ{sup 2d} are intimately related by heat kernel evolution, it is natural to ask whether a similar connection exists for compact Lie groups as well. Moreover, since the formulation of space adiabatic perturbation theory requires a (deformation) quantisation as minimal input, we analyse the question to what extent the coherent state quantisation, defined by the Segal-Bargmann-Hall transform, can serve as basis of the former.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Coherent states, quantum gravity, and the Born-Oppenheimer approximation. III.: Applications to loop quantum gravity

In this article, the third of three, we analyse how the Weyl quantisation for compact Lie groups presented in the second article of this series fits with the projective-phase space structure of loop quantum gravity-type models. Thus, the proposed Weyl quantisation may serve as the main mathematical tool to implement the program of space adiabatic perturbation theory in such models. As we already argued in our first article, space adiabatic perturbation theory offers an ideal framework to overcome the obstacles that hinder the direct implementation of the conventional Born-Oppenheimer approach in the canonical formulation of loop quantum gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

On Parallelizing Single Dynamic Simulation Using HPC Techniques and APIs of Commercial Software

Time-domain simulations are heavily used in today’s planning and operation practices to assess power system transient stability and post-transient voltage/frequency profiles following severe contingencies to comply with industry standards. Because of the increased modeling complexity, it is several times slower than real time for state-of-the-art commercial packages to complete a dynamic simulation for a large-scale model. With the growing stochastic behavior introduced by emerging technologies, power industry has seen a growing need for performing security assessment in real time. This paper presents a parallel implementation framework to speed up a single dynamic simulation by leveraging the existing stability model library in commercial tools through their application programming interfaces (APIs). Several high performance computing (HPC) techniques are explored such as parallelizing the calculation of generator current injection, identifying fast linear solvers for network solution, and parallelizing data outputs when interacting with APIs in the commercial package, TSAT. The proposed method has been tested on a WECC planning base case with detailed synchronous generator models and exhibits outstanding scalable performance with sufficient accuracy.

Diao, Ruisheng↗

DOE OSTI2012

Automated size-specific CT dose monitoring program: Assessing variability in CT dose

Purpose: The potential health risks associated with low levels of ionizing radiation have created a movement in the radiology community to optimize computed tomography (CT) imaging protocols to use the lowest radiation dose possible without compromising the diagnostic usefulness of the images. Despite efforts to use appropriate and consistent radiation doses, studies suggest that a great deal of variability in radiation dose exists both within and between institutions for CT imaging. In this context, the authors have developed an automated size-specific radiation dose monitoring program for CT and used this program to assess variability in size-adjusted effective dose from CT imaging. Methods: The authors radiation dose monitoring program operates on an independent health insurance portability and accountability act compliant dosimetry server. Digital imaging and communication in medicine routing software is used to isolate dose report screen captures and scout images for all incoming CT studies. Effective dose conversion factors (k-factors) are determined based on the protocol and optical character recognition is used to extract the CT dose index and dose-length product. The patient's thickness is obtained by applying an adaptive thresholding algorithm to the scout images and is used to calculate the size-adjusted effective dose (ED{sub adj}). The radiation dose monitoring program was used to collect data on 6351 CT studies from three scanner models (GE Lightspeed Pro 16, GE Lightspeed VCT, and GE Definition CT750 HD) and two institutions over a one-month period and to analyze the variability in ED{sub adj} between scanner models and across institutions. Results: No significant difference was found between computer measurements of patient thickness and observer measurements (p= 0.17), and the average difference between the two methods was less than 4%. Applying the size correction resulted in ED{sub adj} that differed by up to 44% from effective dose estimates that were not adjusted by patient size. Additionally, considerable differences were noted in ED{sub adj} distributions between scanners, with scanners employing iterative reconstruction exhibiting significantly lower ED{sub adj} (range: 9%-64%). Finally, a significant difference (up to 59%) in ED{sub adj} distributions was observed between institutions, indicating the potential for dose reduction. Conclusions: The authors developed a robust automated size-specific radiation dose monitoring program for CT. Using this program, significant differences in ED{sub adj} were observed between scanner models and across institutions. This new dose monitoring program offers a unique tool for improving quality assurance and standardization both within and across institutions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Poster — Thur Eve — 12: Implementation of a Clinical Lung Tumour High Dose Containment Verification Procedure using Respiratory Cone-Beam CT (4DCBCT) on a Varian TrueBeam Linac

Lung tumours move due to respiratory motion. This is managed during planning by acquiring a 4DCT and capturing the excursion of the GTV (gross tumour volume) throughout the breathing cycle within an IGTV (Internal Gross Tumour Volume) contour. Patients undergo a verification cone-beam CT (CBCT) scan immediately prior to treatment. 3D reconstructed images do not consider tumour motion, resulting in image artefacts, such as blurring. This may lead to difficulty in identifying the tumour on reconstructed images. It would be valuable to create a 4DCBCT reconstruction of the tumour motion to confirm that does indeed remain within the planned IGTV. CBCT projections of a Quasar Respiratory Motion Phantom are acquired in Treatment mode (half-fan scan) on a Varian TrueBeam accelerator. This phantom contains a mobile, low-density lung insert with an embedded 3cm diameter tumour object. It is programmed to create a 15s periodic, 2cm (sup/inf) displacement. A Varian Real-time Position Management (RPM) tracking-box is placed on the phantom breathing platform. Breathing phase information is automatically integrated into the projection image files. Using in-house Matlab programs and RTK (Reconstruction Tool Kit) open-source toolboxes, the projections are re-binned into 10 phases and a 4DCBCT scan reconstructed. The planning IGTV is registered to the 4DCBCT and the tumour excursion is verified to remain within the planned contour. This technique successfully reconstructs 4DCBCT images using clinical modes for a breathing phantom. UBC-BCCA ethics approval has been obtained to perform 4DCBCT reconstructions on lung patients (REB#H12-00192). Clinical images will be accrued starting April 2014.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

District EnErgy Planner (DEEP) v2

The District EnErgy Planner - DEEP is an Mixed Integer Linear Programming (MILP) optimization software tool to solve district energy system, technology configuration, operation strategies, and energy retail business schemes. DEEP takes user input energy demand on heating, cooling and electricity demand. Energy loss through pipeline is calculated for heating and cooling from central plants. The optimal system configuration to minimize the district energy system life cycle cost or minimize CO2 emission is calculated based on energy balance equations and various constraints. The recent update on DEEP include a feature of waste heat utilization energy balance based optimization to take into accounts of different temperature bands of heat into account to maximize system efficiency. Another feature is to optimize district energy retail by provide optimal pricing scheme for heating, cooling and electricity to end users to incorporate district to grid demand response.

Feng, Wei↗

DOE OSTI2019

NEUTRON-IRRADIATION–INDUCED DAMAGE ASSESSMENT IN CONCRETE USING COMBINED PHASE CHARACTERIZATION AND NONLINEAR FAST FOURIER TRANSFORM SIMULATION

Understanding irradiation effects in concrete cavities of light water reactors is critical to the long-term operation (60+ years) of US nuclear power plants. Susceptibility of concrete to neutron irradiation greatly varies as a function of its constituents: coarse aggregates, sand, and hardened cement paste (hcp). In particular, higher irradiation–susceptibility of aggregates was found to be a direct function of radiation-induced volumetric expansion (RIVE), or the propensity of aggregates to swell as a function of mineral contents, structures and textures. Irradiation-induced amorphization is accompanied by significant swelling, especially in silicates. For example, the maximum volumetric expansions of quartz and feldspars have been shown to be as large as ≈ 18% and ≈ 8%, respectively, while the change of density in calcite remains rather low (≈ 0.3–0.5%). High swelling is associated with a high number of covalent bonds (Si–O) and a high degree of polymerization of [SiO4] tetrahedrons. Differential RIVEs between rock-forming minerals cause high stresses and may potentially develop cracking within the aggregates at the interface between aggregates and the hcp and within the hcp. Modeling neutron-irradiation effects in concrete requires addressing the problem at a scale that captures both the details of the aggregates’ mineralogy and texture, which is <~ 100 μm, and the representative size of concrete, which is ~ 10 cm. This requires high-resolution, large mapping capabilities. To this end, the US Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program developed an original tool suite called Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) in which Nonlinear 2D-fast Fourier transform (FFT) techniques are employed to model mechanical or irradiation-induced cracking of high-resolution complex microstructures derived from combined mapping techniques, including micro x-ray fluorescence (m-XRF), energy-dispersive x-ray spectroscopy (EDS), electron backscatter diffraction (EBSD), ellipsometry, and scanning electron microscopy (SEM). Irradiated mineral properties are derived from the Irradiated Minerals, Aggregate and Concrete (IMAC) database, which includes available relevant literature data. Rigorous coupled damage-creep simulations are obtained through sequential linear analysis. Illustrations of actual accelerated irradiation-damage propagation in a complex microstructures are presented herein.

Le Pape, Yann↗

DOE OSTI2012

DOE Basic Overview of Occupational Radiation Exposure 2011 (Pamphlet)

This pamphlet focusses on two HSS activities that help ensure radiation exposures are accurately assessed and recorded, namely: 1) the quality and accuracy of occupational radiation exposure monitoring, and 2) the recording, reporting, analysis, and dissemination of the monitoring results. It is intended to provide a short summary of two specific HSS programs that aid in the oversight of radiation protection activities at DOE. The Department of Energy Laboratory Accreditation Program (DOELAP) is in place to ensure that radiation exposure monitoring at all DOE sites is precise and accurate, and conforms to national and international performance and quality assurance standards. The DOE Radiation Exposure Monitoring Systems (REMS) program provides for the collection, analysis, and dissemination of occupational radiation exposure information. The annual REMS report is a valuable tool for managing radiological safety programs and for developing policies to protect individuals from occupational exposure to radiation. In tandem, these programs provide DOE management and workers an assurance that occupational radiation exposures are accurately measured, analyzed, and reported.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

Multiscale atomistic simulation of metal-oxygen surface interactions: Methodological development, theoretical investigation, and correlation with experiment

The purpose of this grant is to develop the multi-scale theoretical methods to describe the nanoscale oxidation of metal thin films, as the PI (Yang) extensive previous experience in the experimental elucidation of the initial stages of Cu oxidation by primarily in situ transmission electron microscopy methods. Through the use and development of computational tools at varying length (and time) scales, from atomistic quantum mechanical calculation, force field mesoscale simulations, to large scale Kinetic Monte Carlo (KMC) modeling, the fundamental underpinings of the initial stages of Cu oxidation have been elucidated. The development of computational modeling tools allows for accelerated materials discovery. The theoretical tools developed from this program impact a wide range of technologies that depend on surface reactions, including corrosion, catalysis, and nanomaterials fabrication.

36 MATERIALS SCIENCE↗