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Automating neutron resonances classification with Machine Learning [Slides]

Team reported the following accomplishments: the development of a Machine-Learning method to properly assign spins to neutron resonances (automated, general, reproducible); full integration with evaluated resonances in the Atlas (automation of new editions); training and optimization in synthetic data; validation and deployment to real experimental resonances. Future perspectives include exploration of other classifiers and hyper-parameter combinations, further validation with well-known nucleus (e.g. 235 U), and publication pipeline.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Method for Determining Bulk Density, Material Density, and Porosity of Melter Feed During Nuclear Waste Vitrification

Glassmelting efficiency largely depends on heat transfer to reacting glass batch (melter feed), which in turn is influenced by the bulk density (ρ b ) and porosity (ϕ) of the reacting feed as functions of temperature ( T ). Neither ρ b ( T ) nor ϕ( T ) functions are readily accessible from direct measurements. For the determination of ρ b , we monitored the profile area of heated feed pellets and calculated the pellet volume using numerical integration. For the determination of ϕ, we measured the material density of feeds quenched at various stages of conversion via pycnometry and then computed the feed density at heat‐treatment temperature using thermal expansion values of basic feed constituents.

Hilliard, Zachary↗

Retaining Systems Engineering Model Meaning Through Transformation: Demo 2

Digital engineering strategies typically assume that digital engineering models interoperate seamlessly across the multiple different engineering modeling software applications involved, such as model- based systems engineering (MBSE), mechanical computer-aided design (MCAD), electrical computer-aided design (ECAD), and other engineering modeling applications. The presumption is that the data schema in these modeling software applications are structured in the familiar flat- tabular schema like any other software application. Engineering domain-specific applications (e.g., systems, mechanical, electrical, simulation) are typically designed to solve domain-specific problems, necessarily excluding explicit representations of non-domain information to help the engineer focus on the domain problems (system definition, design, simulation). Such exclusions become problematic in inter-domain information exchange. The obvious assumptions of one domain might not be so obvious to experts in another domain. Ambiguity in domain-specific language can erode the ability to enable different domain modeling applications to interoperate, unless the underlying language is understood and used as the basis for translation from one application to another. The engineering modeling software application industry has struggled for decades to enable these applications to interoperate. Industry standards have been developed, but they have not unified the industry. Why is this? The authors assert that the industry has relied on traditional database integration methods. The basic issue prohibiting successful application integration then is that traditional database-driven integration does not consider the distinct languages of each domain. An engineering models meaning is expressed through the underlying language of that engineering domain. In essence, traditional integration methods do not retain the semantic context (meaning) of the model. The basis of this research stems from the widely held assumption that systems engineering models are (or can be) structured according to the underlying semantic ontology of the model. This assumption can be imagined from two thoughts. 1) Digital systems engineering models are often represented using graph theory (the graph of a complex systems model can contain millions of nodes and edges). When examining the nodes one at a time and following the outbound edges of each node one by one, one can end up with rudimentary statements about the model (i.e., node A relates to node B), as in a semantic graph. 2) Likewise, from the study of natural languages, a sentence can be structured into unambiguous triples of subject-predicate-object within formal and highly expressive semantic ontologies. The rudimentary statements about a systems model discerned with graph theory closely mimic the triples used in the ontologies that try to structure natural languages. In other words, a systems models semantic graph can be (or is) structured into an ontology. Additionally, it is well established in industry that through natural language processing (NLP), which provides the means to create language structures, that computers can interpret ontological graphs. Therefore, the authors hypothesized that if the integrity of the underlying semantic structure of a systems model is retained, the contextual meaning of the model is retained. By structuring system models into the triples of the underlying ontology during the transformation from one MBSE application to another, the authors have provided a proof of the concept that the meaning of a system model can be retained during transformation. The authors assert that this is the missing ingredient in effective systems model-to-model interoperability. ACKNOWLEDGEMENTS The authors would like to thank the FY19 Model Interoperability team members who provided a solid foundation for the FY20 team to leverage: John McCloud, for the work he did to guide us toward the right use of technology that will appropriately discover and manipulate ontologies. Carlos Tafoya, for the work he did to develop an application programming interface (API)/Adapter that would export ontology-based data from GENESYS. Peter Chandler, for the work he did to architect our overall integration solution, with an eye toward the future that would influence a large-scale federated production-level systems engineering digital model ecosystem.

42 ENGINEERING↗

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An Integrated Two-Factor Authentication Solution Using Pulse Connect Secure and Apache HTTP Server

Complex system requirements can often lead to a situation wherein no single product or platform can provide a solution. In these cases, a solution integrating the features of multiple products and platforms is needed. Recently, a program sponsor required discontinued use of a third-party Security Assertion Markup Language Identity Provider that was being used to implement a two-factor authentication (2FA) solution that fully integrated with Pulse Connect Secure (PCS). PCS alone could not provide the features necessary to meet all the requirements of a new 2FA solution. The challenge was to leverage the features of additional platforms to design an integrated solution to meet all requirements. This paper presents a solution that integrates the features of PCS, Apache HyperText Transfer Protocol Server, and a custom application that meets all requirements, including a requirement to defend against Uniform Resource Locator manipulation as means to gain unauthorized access to backend applications.

97 MATHEMATICS AND COMPUTING↗

CPsuperH2.3: an Updated Tool for Phenomenology in the MSSM with Explicit CP Violation

We describe the Fortran code CPsuperH2.3, which incorporates the following updates compared with its predecessor CPsuperH2.0. It implements improved calculations of the Higgs-boson masses and mixing including stau contributions and finite threshold effects on the tau-lepton Yukawa coupling. It incorporates the LEP limits on the processes e^+e^-->H_iZ,H_iH_j and the CMS limits on H_i->@t@?@t obtained from 4.6 fb^-^1 of data at a center-of-mass energy of 7 TeV. It also includes the decay mode H_i->Z@c and the Schiff-moment contributions to the electric dipole moments of Mercury and Radium 225, with several calculational options for the case of Mercury. These additions make CPsuperH2.3 a suitable tool for analyzing possible CP-violating effects in the MSSM in the era of the LHC and a new generation of EDM experiments. Program summary: Program title: CPsuperH2.3 Catalogue identifier: ADSR_v3_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSR_v3_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 24058 No. of bytes in distributed program, including test data, etc.: 158721 Distribution format: tar.gz Programming language: Fortran77. Computer: PC running under Linux and computers in Unix environment. Operating system: Linux. RAM: 32 MB Classification: 11.1. Does the new version supersede the previous version?: Yes Catalogue identifier of previous version: ADSR_v2_0 Journal reference of previous version: Comput. Phys. Comm. 180(2009)312 Nature of problem: The calculations of mass spectrum, decay widths and branching ratios of the neutral and charged Higgs bosons in the Minimal Supersymmetric Standard Model with explicit CP violation have been improved. The program is based on renormalization-group-improved diagrammatic calculations that include dominant higher-order logarithmic and threshold corrections, b-quark and @t-lepton Yukawa-coupling resummation effects and improved treatment of Higgs-boson pole-mass shifts. The couplings of the Higgs bosons to the Standard Model gauge bosons and fermions, to their supersymmetric partners and all the trilinear and quartic Higgs-boson self-couplings are also calculated. Also included are a full treatment of the 4x4 (2x2) neutral (charged) Higgs propagator matrix together with the center-of-mass dependent Higgs-boson couplings to gluons and photons, and an integrated treatment of several B-meson observables. The new implementations include the EDMs of Thallium, neutron, Mercury, Deuteron, Radium, and muon, as well as the anomalous magnetic moment of muon, (g_@m-2), the top-quark decays, improved calculations of the Higgs-boson masses and mixing including stau contributions, the LEP limits, and the CMS limits on H_i->@t@t@?. It also implements the decay mode H_i->Z@c and includes the corresponding Standard Model branching ratios of the three neutral Higgs bosons in the array GAMBRN(IM,IWB = 2,IH). Solution method: One-dimensional numerical integration for several Higgs-decay modes and EDMs, iterative treatment of the threshold corrections and Higgs-boson pole masses, and the numerical diagonalization of the neutralino mass matrix. Reasons for new version: Mainly to provide the full calculations of the EDMs of Thallium, neutron, Mercury, Deuteron, Radium, and muon as well as (g_@m-2), improved calculations of the Higgs-boson masses and mixing including stau contributions, the LEP limits, the CMS limits on H_i->@t@t@?, the top-quark decays, H_i->Z@c decay, and the corresponding Standard Model branching ratios of the three neutral Higgs bosons. Summary of revisions: Full calculations of the EDMs of Thallium, neutron, Mercury, Deuteron, Radium, and muon as well as (g_@m-2). Improved treatment of Higgs-boson masses and mixing including stau contributions. The LEP limits. The CMS limits on H_i->@t@t@?. The top-quark decays. The H_i->Z@c decay. The corresponding Standard Model branching ratios of the three neutral Higgs bosons. Running time: Less than 1.0 s.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Single-particle dynamics in a nonlinear accelerator lattice: attaining a large tune spread with octupoles in IOTA

Fermilab is constructing the Integrable Optics Test Accelerator (IOTA) as the centerpiece of the Accelerator R&D Program towards high-intensity circular machines. One of the factors limiting the beam intensity in present circular accelerators is collective instabilities, which can be suppressed by a spread of betatron frequencies (tunes) through the Landau damping mechanism or by an external damper, if the instability is slow enough. The spread is usually created by octupole magnets, which introduce the tune dependence on the amplitude and, in some cases, by a chromatic spread (tune dependence on particle's momentum). The introduction of octupoles usually lead to a resonant behavior and a reduction of the dynamic aperture. One of the goals of the IOTA research program is to achieve a high betatron tune spread, while retaining a large dynamic aperture using conventional octupole magnets in a special but realistic accelerator configuration. In this report, we present results of computer simulations of an electron beam in the IOTA by particle tracking and the Frequency Map Analysis. The results show that the ring's octupole magnets can be configured to provide a betatron tune shift of 0.08 (for particles at large amplitudes) with the dynamical aperture of over 20 beam sigma for a 150-MeV electron beam. The influence of the synchrotron motion, lattice errors, and magnet imperfections is insignificant for the parameters and levels of tolerances set by the design of the ring. Here, the described octupole insert could be beneficial for suppression of space-charge induced instabilities in high intensity machines.

43 PARTICLE ACCELERATORS↗

A computerized scheme for lung nodule detection in multiprojection chest radiography

Purpose: Our previous study indicated that multiprojection chest radiography could significantly improve radiologists' performance for lung nodule detection in clinical practice. In this study, the authors further verify that multiprojection chest radiography can greatly improve the performance of a computer-aided diagnostic (CAD) scheme. Methods: Our database consisted of 59 subjects, including 43 subjects with 45 nodules and 16 subjects without nodules. The 45 nodules included 7 real and 38 simulated ones. The authors developed a conventional CAD scheme and a new fusion CAD scheme to detect lung nodules. The conventional CAD scheme consisted of four steps for (1) identification of initial nodule candidates inside lungs, (2) nodule candidate segmentation based on dynamic programming, (3) extraction of 33 features from nodule candidates, and (4) false positive reduction using a piecewise linear classifier. The conventional CAD scheme processed each of the three projection images of a subject independently and discarded the correlation information between the three images. The fusion CAD scheme included the four steps in the conventional CAD scheme and two additional steps for (5) registration of all candidates in the three images of a subject, and (6) integration of correlation information between the registered candidates in the three images. The integration step retained all candidates detected at least twice in the three images of a subject and removed those detected only once in the three images as false positives. A leave-one-subject-out testing method was used for evaluation of the performance levels of the two CAD schemes. Results: At the sensitivities of 70%, 65%, and 60%, our conventional CAD scheme reported 14.7, 11.3, and 8.6 false positives per image, respectively, whereas our fusion CAD scheme reported 3.9, 1.9, and 1.2 false positives per image, and 5.5, 2.8, and 1.7 false positives per patient, respectively. The low performance of the conventional CAD scheme may be attributed to the high noise level in chest radiography, and the small size and low contrast of most nodules. Conclusions: This study indicated that the fusion of correlation information in multiprojection chest radiography can markedly improve the performance of CAD scheme for lung nodule detection.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation

Tight oil formations such as those in the Bakken petroleum system are known to hold hundreds of billions of barrels of oil in place; however, the primary recovery factor for these plays is typically less than 10%. Tight oil formations, including the Bakken Formation, therefore, may be attractive candidates for enhanced oil recovery (EOR) using CO 2 . Multiphase fluid behavior and flow in fluid-rich shales can vary substantially depending on the size of pore throats, and properties such as fluid viscosity and density are much different in nanoscale pores than in macroscale pores. Thus it is critical to understand the nature and distribution of nano-, micro-, and macroscale pores and fracture networks. To address these issues, the Energy & Environmental Research Center (EERC) has been conducting a research program entitled “Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation.” The objectives of the project are 1) the use of advanced characterization methods to better understand and quantify the petrophysical and geomechanical factors that control CO 2 and oil mobility within tight oil formation samples, 2) the determination of CO 2 permeation and oil extraction rates in tight reservoir rocks and organic-rich shales of the Bakken, and 3) the integration of the laboratory-based CO 2 permeation and oil extraction data and the characterization data into geologic models and dynamic simulations to develop predictions of CO 2 storage resource and EOR in the Bakken tight oil formation. A combination of standard and advanced petrophysical characterization techniques were applied to characterize samples of Bakken Formation tight reservoir rock and shales from multiple wells. Techniques included advanced computer tomography (CT) imaging, scanning electron microscopy (SEM) techniques, whole-core and micro x-ray CT imaging, field emission (FE) SEM, and focused ion beam (FIB) SEM. Selected samples were also analyzed for geomechanical properties. X-ray CT imaging yielded information on the occurrence of fractures, bedding planes, fossils, and bioturbation in core, as well as data on bulk density and photoelectric factor logs, which were used to interpret porosity, organic content, and mineralogy. FESEM was used for characterization of nano- and microscale features, including nanoscale pore visualization and micropore and pore throat mineralogy. FIBSEM yielded micro- to nanoscale visualization of fracture networks, porosity and pore-size distribution, connected versus isolated porosity, and distribution of organics. Results from the characterization activities provide insight on nanoscale fracture properties, pore throat mineralogy and connectivity, rock matrix characteristics, mineralogy, and organic content. Laboratory experiments demonstrated that CO 2 can permeate the tight matrix of Bakken shale and nonshale reservoir samples and mobilize oil from those samples. Geologic models were created at scales ranging from the core plug to the reservoir, and dynamic simulations were conducted. The data from the characterization and laboratory-based activities were integrated into modeling research activities to determine the fundamental mechanisms controlling fluid transport in the Bakken, which support EOR scheme design and estimation of CO 2 storage potential in tight oil formations. Simulation results suggest a CO 2 storage resource estimate range of 169 million to 1.5 billion tonnes for the Bakken in North Dakota, possibly resulting in 1.8 billion to 16 billion barrels of incremental oil.

04 OIL SHALES AND TAR SANDS↗

Design of Defensive Cybersecurity Architectures for High Temperature, Gas-Cooled Reactors

This report presents the design of defensive cybersecurity architectures (DCSAs) for High Temperature, Gas-Cooled Reactors (HTGRs). A DCSA is a cybersecurity design feature that places systems into security zones in a graded approach according to the importance of the functions performed by the systems. DCSA design efforts for advanced reactors may commence as early as the system-level design phase. This design approach is consistent with the draft regulatory guide for advanced reactor cybersecurity programs (DG-5075) and enables advanced reactor designers to consider the effects of security-by-design (SeBD) features on their DCSAs. Integration of DCSA design and other cybersecurity activities with the traditional design process as part of a SeBD framework may enable advanced reactor designers to improve the security posture of their plants while reducing implementation and operating costs. This report provides a DCSA template for an exemplar HTGR and describes a DCSA design process using event tree analysis so that the template may be optimized for a given HTGR design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Increased accuracy of multiphysics simulations through flexible execution, transient algorithms, and modular physics

The MOOSE framework is a foundational capability used by the NEAMS program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple time integrators in the same input file, initial design of framework Components, an input file Application block, extension of NetGen to 3D geometries in MOOSE, and deployment of executors in the multi-system paradigm. These five additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗

Integration of Dynamical System Scaling to RAVEN and Facility Application

As part of the design optimization and model validation effort within the hybrid energy systems program, the research to implement dynamical system scaling (DSS) code to RAVEN is funded under the Integrated Energy System program in collaboration with the Digital Reactor Technology & Development department. The DSS data processing algorithm has been coded within the RAVEN framework along with other metrics and postprocessing models. The implemented code was tested using a gravity-driven draining tank draining case modeled in RELAP5-3D and generated data was successfully postprocessed based on the scaling analyses defined by DSS. Postprocessed data concluded less agreement for the tank exit velocity and indicated that the modeled input deck for RELAP5-3D requires modification to enforce minimal pressure differential effects to the draining process.

97 MATHEMATICS AND COMPUTING↗

Zgoubi Users' Guide

The computer code zgoubi calculates trajectories of charged particles in magnetic and electric fields. At the origin specially adapted to the definition and adjustment of beam lines and magnetic spectrometers, it has so evolved that it allows the study of systems including complex sequences of optical elements such as dipoles, quadrupoles, arbitrary multipoles, FFAG magnets and other magnetic or electric devices, and is able as well to handle periodic structures. Compared to other codes, it presents several peculiarities, as follows - a non-exhaustive list : • a numerical method for integrating the Lorentz equation, based on Taylor series, which optimizes computing time and provides high accuracy and strong symplecticity, • spin tracking, using the same numerical method as for the Lorentz equation, • account of stochastic photon emission, and its effects on particle dynamics, • calculation of the synchrotron radiation electric field and spectra in arbitrary magnetic fields, from the ray-tracing outcomes, • the possibility of using a mesh, which allows ray-tracing from simulated or measured (1-D, 2-D or 3-D) electric and magnetic field maps, • a number Monte Carlo procedures : unlimited number of trajectories, in-flight decay, stochastic radiation, etc., • built-in fitting procedures allowing arbitrary variables and a large variety of constraints, easily expandable, • multi-turn tracking in circular accelerators including features proper to machine parameter calculation and survey, • simulation of time-varying power supplies, and • simulation of arbitrary radio-frequency programs. The initial version of zgoubi was dedicated to ray-tracing in magnetic elements, beam lines, spectrometers. It was perfected for the purpose of studying, and operating, the four spectrometers SPES I, II, III, IV at the Laboratoire National SATURNE (CEA-Saclay, France), and, later, SPEG at GANIL (Caen, France). Developments regarding spin tracking and ray-tracing in combined electric and magnetic fields were implemented, in the late 1980s and early 1990s respectively. In the mid-1990s, the computation of synchrotron radiation electromagnetic impulse and spectra was introduced, for the purpose of synchrotron radiation diagnostic R&D at LEP, and further applied to the design of the SR diagnostics installations at LHC in the early 2000s. In the mean time, several new optical elements were added, such as electro-magnetic and other electrostatic lenses. Used since several years for special studies in periodic machines (e.g., SATURNE at Saclay, COSY at Julich, LEP and LHC at CERN), zgoubi has also undergone extensive developments regarding storage ring related features. Many developments have been accomplished since the early 2000s in the frame of a number of project design and beam dynamics studies, as the neutrino factory, lepton and hadron colliders, spin studies at AGS and RHIC, etc. As a consequence the list of optical elements and the compendium of numerical methods, so-called “Glossary of Keywords” list, pp. 7 and 169, has stretched with new simulation and computing procedures, ranging from fitting (FIT2 procedure ; additional constraints) to overlapping magnetic field capabilities (DIPOLES, FFAG), spin manipulation (SPINR), optical elements (BEAMBEAM), radiation damping tools (SRLOSS) and many others (FAISTORE, MAP2D-E, OPTICS, PICKUPS, TWISS, etc.). The graphic interface to zgoubi (zpop, Part D) has undergone extensive developments, making it a convenient companion tool to the use of zgoubi.

43 PARTICLE ACCELERATORS↗

Toward more mechanistic representations of biogeochemical processes in river networks: Implementation and demonstration of a multiscale model

A recently introduced multiscale model for representing the effects of small-scale hyporheic-zone biogeochemical processes is extended from the reach scale to river network scales. The model uses advection-dispersion-reaction equations for the channel network and one-dimensional advection-reaction subgrid models for the hyporheic zone. We summarize implementation in the integrated surface/subsurface hydrology modeling system Amanzi-ATS. The extension uses topologically defined meshes to represent stream/river networks and associates a hyporheic subgrid model with each channel grid cell. Biogeochemical reaction modeling capability residing in community software is accessed through an application programming interface. The implementation is verified against independent numerical solutions on a single reach. Mesh convergence studies show that commonly used semi-distributed representations can introduce significant spatial discretization error. Denitrification of farm runoff in a subbasin of the Portage River Basin in Ohio, USA is used to demonstrate the general-purpose reactive transport capability.

54 ENVIRONMENTAL SCIENCES↗

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g. height, color and grayscale values; all as functions of a location in a plane projection). It is the objective of this project to produce a user-friendly interface that incorporated all operations needed to perform surface examination. For this reason, a Matlab-based Graphical User Interface (GUI) was created to integrate data input with software developed for processing and evaluation. In summary, the GUI permits selective downloading of binary data, interrogation of attributes, data labeling, flagging of significant features, execution of Machine Learning (ML) algorithms, output of parameters for trained ML algorithms, reports of ML model accuracy with respect to labeled data, and generation of graphical representations of various analyses.

3013 corrosion↗

RAMSeS: Rapid Analysis of Mission Software Systems

Over the past few decades, software has become ubiquitous as it has been integrated into nearly every aspect of society, including household appliances, consumer electronics, industrial control systems, public utilities, government operations, and military systems. Consequently, many critical national security questions can no longer be answered convincingly without understanding software, including its purpose, its capabilities, its flaws, its communication, or how it processes and stores data. As software continues to become larger, more complex, and more widespread, our ability to answer important mission questions and reason about software in a timely way is falling behind. Today, to achieve such understanding of third-party software, we rely predominantly on the ability of reverse engineering experts to manually answer each particular mission question for every software system of interest. This approach often requires heroic human effort that nevertheless fails to meet current mission needs and will never scale to meet future needs. The result is an emerging crisis: a massive and expanding gap between the national security need to answer mission questions about software and our ability to do so. Sandia National Laboratories has established the Rapid Analysis of Mission Software Systems (RAMSeS) effort, a collaborative long-term effort aimed at dramatically improving our nation’s ability to answer mission questions about third-party software by growing an ecosystem of tools that augment the human reverse engineer through automation, interoperability, and reuse. Focusing on static analysis of binary programs, we are attempting to identify reusable software analysis components that advance our ability to reason about software, to automate useful aspects of the software analysis process, and to integrate new methodologies and capabilities into a working ecosystem of tools and experts. We aim to integrate existing tools where possible, adapt tools when modest modifications will enable them to interoperate, and implement missing capability when necessary. Although we do hope to automate a growing set of analysis tasks, we will approach this goal incrementally by assisting the human in an ever-widening range of tasks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗