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DOE OSTI2021

Barriers to carriers: faults and recombination in non-stoichiometric perovskite scintillators

Abstract Tuning the efficiency and speed of charge carrier recombination in inorganic scintillators can potentially improve their performance in diverse applications. Recent work suggests that this maybe be achieved via a two-phase scintillator AB that naturally phase separates into A -rich and B -rich domains. In addition, a favorable electronic structure and band-edge alignment such that the charge carriers are confined or are thermodynamically driven to preferentially accumulate in one of the two domains, might lead to an improved radiative recombination rate. Here, we use density functional theory computations and ab initio molecular dynamics (AIMD), including non-adiabatic molecular dynamics (NAMD) simulations, to examine an alternative phase structure and its potential impact on recombination. Using a model perovskite SrTiO $$_3$$ 3 system with one-, two- and three-dimensional Ruddlesden–Popper (RP) phases, we demonstrate that RP faults induce band structure changes in the material that can act as barriers to carrier transport. Our AIMD/NAMD simulations indicate competing effects of a lower mean free path (potentially enhancing the desired radiative recombination and overall scintillating efficiency) and faster non-radiative recombination (undesired) due to enhanced electron–phonon coupling in the faulted system. Full exploitation of such a rational design approach would require tuning of the effective scintillation efficiency by varying the perovskite chemistry using appropriate arrangements of RP faults in the bulk material. Finally, other effects, such as the tendency of point defects to segregate at the interface, that might affect the overall performance, are briefly discussed. We expect the basic results found here to apply to other nanostructured scintillators. Graphical Abstract

36 MATERIALS SCIENCE↗

DOE OSTI2023

Structural inference of networked dynamical systems with universal differential equations

Networked dynamical systems are common throughout science in engineering; e.g., biological networks, reaction networks, power systems, and the like. For many such systems, nonlinearity drives populations of identical (or near-identical) units to exhibit a wide range of nontrivial behaviors, such as the emergence of coherent structures (e.g., waves and patterns) or otherwise notable dynamics (e.g., synchrony and chaos). Here, we seek to infer (i) the intrinsic physics of a base unit of a population, (ii) the underlying graphical structure shared between units, and (iii) the coupling physics of a given networked dynamical system given observations of nodal states. These tasks are formulated around the notion of the Universal Differential Equation, whereby unknown dynamical systems can be approximated with neural networks, mathematical terms known a priori (albeit with unknown parameterizations), or combinations of the two. We demonstrate the value of these inference tasks by investigating not only future state predictions but also the inference of system behavior on varied network topologies. The effectiveness and utility of these methods are shown with their application to canonical networked nonlinear coupled oscillators.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

EMPIRE-3.2 Malta: modular system for nuclear reaction calculations and nuclear data evaluation [User's Manual]

EMPIRE is a modular system of nuclear reaction codes, comprising various nuclear models, and designed for calculations over a broad range of energies and incident particles. The system can be used for theoretical investigations of nuclear reactions as well as for nuclear data evaluation work. Photons, nucleons, deuterons, tritons, helions (3He), α’s, and light or heavy ions can be selected as projectiles. The energy range starts just above the resonance region in the case of a neutron projectile, and extends up to few hundred MeV for heavy ion induced reactions. The code accounts for the major nuclear reaction models, such as optical model, Coupled Channels and DWBA (ECIS06 and OPTMAN), Multi-step Direct (ORION + TRISTAN), NVWY Multi-step Compound, exciton model (PCROSS), hybrid Monte Carlo simulation (DDHMS), and the full featured Hauser-Feshbach model including width fluctuations and the optical model for fission. Heavy ion fusion cross section can be calculated within the simplified coupled channels approach (CCFUS). A comprehensive library of input parameters based on the RIPL-3 library covers nuclear masses, optical model parameters, ground state deformations, discrete levels and decay schemes, level densities, fission barriers, and γ-ray strength functions. Effects of the dynamic deformation of a fast rotating nucleus can be taken into account in the calculations (BARFIT, MOMFIT). The results can be converted into the ENDF-6 format using the accompanying EMPEND code. Modules of the ENDF Utility Codes and the ENDF Pre-Processing codes are applied for ENDF file verification. The package contains the full EXFOR library of experimental data in computational format C4 that are automatically retrieved during the calculations. EMPIRE contains the resonance module that retrieves data from the electronic version of the Atlas of Neutron Resonances by Mughabghab (not provided with the EMPIRE distribution), to produce resonance section and related covariances for the ENDF-6 formatted files. EMPIRE can be used to determine covariances of the calculated data using either sensitivity matrices along with the KALMAN code or employing Monte Carlo approach to produce model generated covariances. In both cases experimental data can be taken into account, either directly (KALMAN) or by feeding the EMPIRE calculated Monte Carlo modelling covariance as a prior to the least square fitting GANDR system. Publication quality graphs can be obtained using the powerful and flexible plotting package ZVView. Interactive plots with ZVView comparing experimental results with calculations can be produced with ENDVER modules. The backbone of the EMPIRE system are bash-shell UNIX scripts that provide for seamless console operation of EMPIRE on Linux, Mac OS X, and Microsoft Windows with GNU gfortran compiler installed. Additionally, the graphical interface, provides for an easy operation of the system on Linux, Mac OS X and virtual Linux machines running on Microsoft Windows.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Development of a Severe Accident Analysis Engine Using Approximate Reasoning

In hypothetical severe accident scenarios, nuclear power plant safety is challenged by core degradation and release of fission products. To aid the plant operator and technical support center staff, research has been performed to develop understanding of severe accident phenomenology, assessing their risk and devise measures to mitigate accident consequences (Sehgal, 2011). Nuclear power plant accidents involve highly complex physical and chemical interactions, a large number of safety related systems, and emergency operating procedures (EOP) and severe accident management guidelines (SAMG). Large number of factors with uncertainty and stress can overwhelm the operators. The overall objective of the present research is to develop a methodology and tools that an operator can use to predict severe accident progression and make effective decisions to arrest and manage the accident under large uncertainties. Towards this goal, this study examines a novel approach that brings to bear a combined use of techniques in artificial intelligence (Russel and Norvig, 2010), including Bayesian Network (BN), Answer Set Programming (ASP) and Fuzzy Inference (FI) to achieve faster-than-real-time, yet sufficiently accurate analysis of severe accident progression. Bayesian network (BN) is a type of probabilistic graphical models that can be used to represent knowledge and conditional dependencies about an uncertain realm. It is useful for capturing the causal relationships in a complex system. It also allows prediction via Bayesian inference (Kelly and Smith, 2012). It is composed of nodes and edges, which express random variables and probabilistic relationships between the nodes, respectively. This relationship, given by conditional probability is calculated using stochastic methods. The BN is used in several systems for analysis and management of accident risk; e.g. (Knochenhauer and Frid, 2010). In those systems, the nodes or so-called 'effective factors' are presumably known within the network by system descriptions in SAMGs. There are two steps to configure the BN, namely (i) identifying compositions within the network and (ii) defining conditional dependency between nodes. The first step is performed following the spirit of ASP (Baral, 2003) using Prolog (Wielemaker, 2005). Knowledge representation is used to build databases required for processing by ASP. Knowledge representation is defined as the expression of knowledge in a way that is understandable to both human and computers. Originally knowledge indicates data, information and facts. To focus, knowledge should be formed to achieve a goal. In a severe accident, key physics and safety related components status are defined according to a failure mode. The conditional dependencies between nodes are generated by approximate reasoning using Fuzzy inference (Zadeh, 1995). Fuzzy logic is a multiple-valued logic to treat ambiguous features such as linguistic description. It indicates possibility, which is distinguished from probability. Fuzzy set consists of linguistic variables according to the fixed rule. In other words, even uncertain states could be expressed as not binary logic, but as many-value logic by rule-based technology. Fuzzy control system is comprised of Fuzzy inference engine that is performed based on the 'If-Then Rule'. The 'If-Then Rule' is of the following form. If Y1 is B11 and Y2 is B12 then Z is C1. If Y1 is B21 and Y2 is B22 then Z is C2. Y1 and Y2 are inputs, which indicate conditional variables. Z indicates decision-making and both B and C are linguistic variables. With this rule-based technique, the approximate reasoning can be realized by Fuzzy inference. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Structural variability in Cu(I) and Ag(I) coordination polymers with a flexible dithione ligand: Synthesis, crystal structure, microbiological and theoretical studies

Two new compounds namely [Cu(SCN)(µ-L)]{sub n} (1) and ([Ag (µ{sub 2}-L)](ClO{sub 4})){sub n} (2) have been synthesized at room temperature by one-pot reactions between the 1,1-(1,4-butanediyl)bis(1,3-dihydro-3-methyl-1H-imidazole- 2-thione) (L) and appropriate copper(I) and silver(I) salts. These polymers have been characterized by single crystal X-ray diffraction, XRPD, TGA, elemental analysis, infrared spectroscopy, antibacterial activity and scanning probe microscopy studies. In the crystal structure of 1, copper atoms have a distorted trigonal planar geometry with a CuS{sub 2}N coordination environment. Each of the ligands in the structure of 1 acting as a bidentate S-bridging ligand to form a 1D chain structure. Additionally, the adjacent 1D chains are interconnected by the intermolecular C-H…S interactions to create a 2D network structure. In contrast to 1, in the cationic 3D structure of 2 each of the silver atoms exhibits an AgS{sub 4} tetrahedral geometry with 4-membered Ag{sub 2}S{sub 2} rings. In the structure of 2, the flexible ligand adopts two different conformations; gauche-anti-gauche and anti-anti-anti. The antibacterial studies of these polymers showed that polymer 2 is more potent antibacterial agent than 1. Scanning probe microscopy (SPM) study of the treated bacteria was carried out to investigate the structural changes cause by the interactions between the polymers and target bacteria. Theoretical study of polymer 1 investigated by the DFT calculations indicates that observed transitions at 266 nm and 302 nm in the UV–vis spectrum could be attributed to the π→π* and MLCT transitions, respectively. - Graphical abstract: Two new Cu(I) and Ag(I) coordination polymers have been have been synthesized by one-pot reactions. Copper complex has a 2D non-covalent structure, but silver compound is a 3D coordination compound. These compounds have effective antibacterial activity. - Highlights: • Cu(I) and Ag(I) based coordination polymers have different network structures. • Ag(I) polymer has more antibacterial activity than Cu(I) polymer. • DFT calculations of Cu(I) polymer has been investigated. • Cu(I) and Ag(I) polymers can destroy the structure of chromosomal and plasmid DNA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs

When there are constraints on resources, an unreplicated factorial or fractional factorial design can allow efficient exploration of numerous factor and interaction effects. A half-normal plot is a common graphical tool used to compare the relative magnitude of effects and to identify important effects from these experiments when no estimate of error from the experiment is available. An alternative is to use a least absolute shrinkage and selection operation plot to examine the pattern of model selection terms from an experiment. We examine how both the half-normal and least absolute shrinkage and selection operation plots are impacted by the absence of individual observations or an outlier, and the robustness of conclusions obtained from these 2 techniques for identifying important effects from factorial experiments. As a result, the methods are illustrated with 2 examples from the literature.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

K{sub 1.33}Mn{sub 8}O{sub 16} as an electrocatalyst and a cathode

Density functional theory (DFT) calculations are carried out to investigate the electronic, magnetic and thermoelectric properties of bulk and nanosheet K{sub 1.33}Mn{sub 8}O{sub 16} materials. The catalytic activity and cathodic performance of bulk and nanosheet structures are examined using the Tran-Blaha modified Becke-Johnson (TB-mBJ) exchange potential. Electronic structure calculations reveal an anti-ferromagnetic ground state, with a TB-mMBJ band gap in bulk K{sub 1.33}Mn{sub 8}O{sub 16} that is in agreement with experimental results. Density of state plots indicate a partial reduction of Mn{sup 4+} ions to Mn{sup 3+}, without any obvious sign of Jahn-Teller distortion. Moreover, use of the O p-band center as a descriptor of catalytic activity suggests that the nanosheet has enhanced catalytic activity compared to the bulk structure. Thermoelectric parameters such as the Seebeck coefficient, electrical conductivity, and thermal conductivity are also calculated, and it is found that the Seebeck coefficients decrease with increasing temperature. High Seebeck coefficients for both spin-up and spin-down states are found in the nanosheet relative to their value in the bulk K{sub 1.33}Mn{sub 8}O{sub 16} structure, whereas the electrical and thermal conductivity are reduced relative to the bulk. In addition, figures of merit values are calculated as a function of the chemical potential and it is found that the nanosheet has a figure of merit of ~1 at room temperature, compared to 0.5 for the bulk material. All results suggest that K{sub 1.33}Mn{sub 8}O{sub 16} nanosheets can be used both as a material in waste heat recovery and as an electrocatalyst in fuel cells and batteries. - Graphical abstract: K{sub 1.33}Mn{sub 8}O{sub 16}: bulk and nanosheet. - Highlights: • Electronic properties of bulk and nanosheet forms of K{sub 1.33}Mn{sub 8}O{sub 16} have been studied. • The K{sub 1.33}Mn{sub 8}O{sub 16} nanosheet is a semiconductor while the bulk is a metal. • K{sub 1.33}Mn{sub 8}O{sub 16} Nanosheet is a more efficient electrocatalyst than bulk K{sub 1.33}Mn{sub 8}O{sub 16}. • High figure of merit of K{sub 1.33}Mn{sub 8}O{sub 16} nanosheet makes it an efficient cathode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

The MELCOR Analysis of Chinshan Nuclear Power Plant Spent Fuel Pool for Fukushima-like Accident

The safety analysis of the nuclear power plant (NPP) is very important work in the NPP safety. Especially after the Fukushima NPP accident occurred, the importance of NPP safety analysis has been raised and there is more concern for the safety of NPPs in Taiwan. Because the earthquake and tsunami occurred, the cooling system of spent fuel pool failed and the safety issue of spent fuel pool generated in Japan's Fukushima NPP. Chinshan NPP is the first NPP in Taiwan which is BWR/4 plant and OLTP (Original Licensed Thermal Power) for each unit is 1775 MWt. Chinshan NPP finished SPU (stretch power uprate) and the operating power is 103.66% of the OLTP, which is 1840 MWt now. After Fukushima NPP accident occurred, in order to concern the safety of Chinshan NPP spent fuel pool, we performed the safety analysis of spent fuel pool by using MELCOR/SNAP which also assumed the cooling system of spent fuel pool failed. The geometry of Chinshan NPP spent fuel pool is 12.17 m x 7.87 m x 11.61 m and the initial condition is 60 deg. (water temperature) / 1.013 x 10{sup 5} Pa. And, the total power of the fuels is roughly 8.9 MWt initially. MELCOR is developed by Sandia National Laboratories. MELCOR is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor NPPs, including containment response and leakage of activity to the environment. A broad spectrum of severe accident phenomena in both BWRs and PWRs is treated in MELCOR in a unified framework. These include thermalhydraulic response in the reactor coolant system, reactor cavity, containment, and confinement buildings; core heatup, degradation, and relocation; core-concrete attack; hydrogen production, transport, and combustion; fission product release and transport behavior. Current uses of MELCOR include estimation of severe accident source terms and their sensitivities and uncertainties in a variety of applications. According to Dr. Carbajo's paper, MELCOR was used to perform the study of spent fuel pool of Fukushima Daiichi Unit 4. Niina E. Koenoenen used MELCOR to establish the spent fuel pool model of a Nordic BWR. The loss-of-pool-cooling accidents was simulated and analyzed by this model. The above studies indicate that MELCOR is capable of handling the simulation of the spent fuel pool. An increasing number of researchers are using MELCOR code to analyze test facilities and nuclear power plants. Jun Wang et al. used MELCOR to perform core degradation simulation and MELCOR results were compared with CORA experimental data. Through this work, they reviewed the performance of MELCOR COR package in detail. Tae Woon Kim et al. developed MELCOR model of APR1400 (an advanced pressurized water reactor). They used this model to perform the LBLOCA transient simulation and sensitivity study. Longze Li et al. established the MELCOR model of CPR1000 (a Chinese pressurized reactor 1000-MW power plant). The station blackout (SBO) with failure of the steam generator (SG) safety relief valve (SRV) transient was simulated and analyzed by this model. SNAP is a graphic user interface program that processes the inputs and outputs of MELCOR. In addition, there is an animation function in SNAP which can present the animation of analysis results. There are two main steps in this research. The first step was the establishment of Chinshan NPP spent fuel pool MELCOR/SNAP model. And the transient analysis of Chinshan NPP spent fuel pool MELCOR/SNAP model under the cooling system failure condition was performed. The next step was the comparison among the MELCOR, TRACE and CFD data. TRACE and CFD data were from INER reports. In addition, the animation model of Chinshan NPP spent fuel pool was presented by using the animation function of SNAP with MELCOR/SNAP analysis results. This study has developed MELCOR/SNAP model of Chinshan NPP spent fuel pool successfully. By using the above model, the safety analysis of the spent fuel pool was performed under the cooling system of spent fuel pool failed condition. The analysis results of MELCOR, TRACE and CFD were similar in this case. It indicated that there was a respectable accuracy in MELCOR/SNAP model. The analysis results depicted that the uncovered of the fuels occurred at 2.6 day and the metal-water reaction of fuels occurred roughly at 3.7 day after the cooling system failed. The above results indicated that the failure of cladding occurred after 3.7 day. This study's results can help to evaluate the safety issue of Chinshan NPP spent fuel pool. In addition, the cooling system and some mitigation measures of spent fuel pool is not simulated in the above model. However, we will do it in the future. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Graph-Based Similarity Metrics for Comparing Simulation Model Causal Structures

The causal structure of a simulation is a major determinant of both its character and behavior, yet most methods we use to compare simulations focus only on simulation outputs. We introduce a method that combines graphical representation with information theoretic metrics to quantitatively compare the causal structures of models. The method applies to agent-based simulations as well as system dynamics models and facilitates comparison within and between types. Comparing models based on their causal structures can illuminate differences in assumptions made by the models, allowing modelers to (1) better situate their models in the context of existing work, including highlighting novelty, (2) explicitly compare conceptual theory and assumptions to simulated theory and assumptions, and (3) investigate potential causal drivers of divergent behavior between models. We demonstrate the method by comparing two epidemiology models at different levels of aggregation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Graph-based featurization methods for classifying small molecule compounds

For over a decade, drug-induced liver injury (DILI) has posed significant drawbacks in the synthesis and development of drugs and remains a consequential concern. With finite success within the existing preclinical models, DILI is one of the main causes of drug withdrawal or termination from the market. Particularly, this withdrawal occurs during the late stages of drug development (Kullak-Ublick, 2017). Since DILI is difficult to diagnose and treat, it has become an obstacle in the drug production market that in turn affects clinicians, pharmaceutical companies, and consumers. We propose a method for learning features of DILI-positive drugs based on the graphical relationships and patterns they possess within a network of biological databases. We also train various statistical and machine learning models on these learned features in order to classify the drugs as DILI-positive or negative. Our methods include Random Forest, Neural networks, and logistic regression classification. We utilize labeled DILI-positive and DILI-negative datasets, which were developed by the FDA and the National center for toxicological research, as well as additional literature datasets (Thakkar, 2020) in order to validate our results and assess our featurization and model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

JLIFE: THE JEFFERSON LAB INTERACTIVE FRONT END FOR THE OPTICAL PROPAGATION CODE

We present details on a graphical interface for the open source software program Optical Propagation Code, or OPC. This interface, written in Java, allows a user with no knowledge of OPC to create an optical system, with lenses, mirrors, apertures, etc. and the appropriate drifts between them. The Java code creates the appropriate Perl script that serves as the input for OPC. The mode profile is then output at each optical element. The display can be either an intensity profile along the x axis, or as an isometric 3D plot which can be tilted and rotated. These profiles can be saved. Examples of the input and output will be presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

SU-F-T-231: Improving the Efficiency of a Radiotherapy Peer-Review System for Quality Assurance

Purpose: To improve the efficiency of a radiotherapy peer-review system using a commercially available software application for plan quality evaluation and documentation. Methods: A commercial application, FullAccess (Radialogica LLC, Version 1.4.4), was implemented in a Citrix platform for peer-review process and patient documentation. This application can display images, isodose lines, and dose-volume histograms and create plan reports for peer-review process. Dose metrics in the report can also be benchmarked for plan quality evaluation. Site-specific templates were generated based on departmental treatment planning policies and procedures for each disease site, which generally follow RTOG protocols as well as published prospective clinical trial data, including both conventional fractionation and hypo-fractionation schema. Once a plan is ready for review, the planner exports the plan to FullAccess, applies the site-specific template, and presents the report for plan review. The plan is still reviewed in the treatment planning system, as that is the legal record. Upon physician’s approval of a plan, the plan is packaged for peer review with the plan report and dose metrics are saved to the database. Results: The reports show dose metrics of PTVs and critical organs for the plans and also indicate whether or not the metrics are within tolerance. Graphical results with green, yellow, and red lights are displayed of whether planning objectives have been met. In addition, benchmarking statistics are collected to see where the current plan falls compared to all historical plans on each metric. All physicians in peer review can easily verify constraints by these reports. Conclusion: We have demonstrated the improvement in a radiotherapy peer-review system, which allows physicians to easily verify planning constraints for different disease sites and fractionation schema, allows for standardization in the clinic to ensure that departmental policies are maintained, and builds a comprehensive database for potential clinical outcome evaluation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-TeP1-15: Toward a Novel GPU Accelerated Deterministic Solution to the Linear Boltzmann Transport Equation

Purpose: To develop a Graphic Processor Unit (GPU) accelerated deterministic solution to the Linear Boltzmann Transport Equation (LBTE) for accurate dose calculations in radiotherapy (RT). A deterministic solution yields the potential for major speed improvements due to the sparse matrix-vector and vector-vector multiplications and would thus be of benefit to RT. Methods: In order to leverage the massively parallel architecture of GPUs, the first order LBTE was reformulated as a second order self-adjoint equation using the Least Squares Finite Element Method (LSFEM). This produces a symmetric positive-definite matrix which is efficiently solved using a parallelized conjugate gradient (CG) solver. The LSFEM formalism is applied in space, discrete ordinates is applied in angle, and the Multigroup method is applied in energy. The final linear system of equations produced is tightly coupled in space and angle. Our code written in CUDA-C was benchmarked on an Nvidia GeForce TITAN-X GPU against an Intel i7-6700K CPU. A spatial mesh of 30,950 tetrahedral elements was used with an S4 angular approximation. Results: To avoid repeating a full computationally intensive finite element matrix assembly at each Multigroup energy, a novel mapping algorithm was developed which minimized the operations required at each energy. Additionally, a parallelized memory mapping for the kronecker product between the sparse spatial and angular matrices, including Dirichlet boundary conditions, was created. Atomicity is preserved by graph-coloring overlapping nodes into separate kernel launches. The one-time mapping calculations for matrix assembly, kronecker product, and boundary condition application took 452±1ms on GPU. Matrix assembly for 16 energy groups took 556±3s on CPU, and 358±2ms on GPU using the mappings developed. The CG solver took 93±1s on CPU, and 468±2ms on GPU. Conclusion: Three computationally intensive subroutines in deterministically solving the LBTE have been formulated on GPU, resulting in two orders of magnitude speedup. Funding support from Natural Sciences and Engineering Research Council and Alberta Innovates Health Solutions. Dr. Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta bi-planar linac MR for commercialization).

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

Purpose: This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. Methods: The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and MATLAB. While the basic platform is constructed in MATLAB, the computationally intensive segments are coded in c + +, which are linked via a MEX interface. Results: A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. Conclusions: The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case

solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.

14 SOLAR ENERGY↗

DOE OSTI2017

Graph-based optimization of epitope coverage for vaccine antigen design

Epigraph is a recently developed algorithm that enables the computationally efficient design of single or multi-antigen vaccines to maximize the potential epitope coverage for a diverse pathogen population. Potential epitopes are defined as short contiguous stretches of proteins, comparable in length to T-cell epitopes. This optimal coverage problem can be formulated in terms of a directed graph, with candidate antigens represented as paths that traverse this graph. Epigraph protein sequences can also be used as the basis for designing peptides for experimental evaluation of immune responses in natural infections to highly variable proteins. The epigraph tool suite also enables rapid characterization of populations of diverse sequences from an immunological perspective. Fundamental distance measures are based on immunologically relevant shared potential epitope frequencies, rather than simple Hamming or phylogenetic distances. Here, we provide a mathematical description of the epigraph algorithm, include a comparison of different heuristics that can be used when graphs are not acyclic, and we describe an additional tool we have added to the web-based epigraph tool suite that provides frequency summaries of all distinct potential epitopes in a population. Lastly, we also show examples of the graphical output and summary tables that can be generated using the epigraph tool suite and explain their content and applications.

60 APPLIED LIFE SCIENCES↗