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At least 1,207 records · Page 67

Design of Defensive Cybersecurity Architectures for Sodium-Cooled Fast Reactors

This report presents the design of defensive cybersecurity architectures (DCSAs) for Sodium-Cooled Fast Reactors (SFRs). 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 SFR and how the template may be optimized for a given SFR design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

New Reactor Physics Benchmark Data in the March 2012 Edition of the IRPhEP Handbook

The International Reactor Physics Experiment Evaluation Project (IRPhEP) was established to preserve integral reactor physics experimental data, including separate or special effects data for nuclear energy and technology applications. Numerous experiments that have been performed worldwide, represent a large investment of infrastructure, expertise, and cost, and are valuable resources of data for present and future research. These valuable assets provide the basis for recording, development, and validation of methods. If the experimental data are lost, the high cost to repeat many of these measurements may be prohibitive. The purpose of the IRPhEP is to provide an extensively peer-reviewed set of reactor physics-related integral data that can be used by reactor designers and safety analysts to validate the analytical tools used to design next-generation reactors and establish the safety basis for operation of these reactors. Contributors from around the world collaborate in the evaluation and review of selected benchmark experiments for inclusion in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook). Several new evaluations have been prepared for inclusion in the March 2012 edition of the IRPhEP Handbook.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TH-CD-201-10: Highly Efficient Synchronized High-Speed Scintillation Camera System for Measuring Proton Range, SOBP and Dose Distributions in a 2D-Plane

Purpose: Proton therapy (PT) delivery is complex and extremely dynamic. Therefore, quality assurance testing is vital, but highly time-consuming. We have developed a High-Speed Scintillation-Camera-System (HS-SCS) for simultaneously measuring multiple beam characteristics. Methods: High-speed camera was placed in a light-tight housing and dual-layer neutron shield. HS-SCS is synchronized with a synchrocyclotron to capture individual proton-beam-pulses (PBPs) at ∼504 frames/sec. The PBPs from synchrocyclotron trigger the HS-SCS to open its shutter for programmed exposure-time. Light emissions within 30×30×5cm3 plastic-scintillator (BC-408) were captured by a CCD-camera as individual images revealing dose-deposition in a 2D-plane with a resolution of 0.7mm for range and SOBP measurements and 1.67mm for profiles. The CCD response as well as signal to noise ratio (SNR) was characterized for varying exposure times, gains for different light intensities using a TV-Optoliner system. Software tools were developed to analyze ∼5000 images to extract different beam parameters. Quenching correction-factors were established by comparing scintillation Bragg-Peaks with water scanned ionization-chamber measurements. Quenching corrected Bragg-peaks were integrated to ascertain proton-beam range (PBR), width of Spared-Out-Bragg-Peak (MOD) and distal.

07 ISOTOPE AND RADIATION SOURCES↗

Level-2 Milestone 4468: Lorenz Simulation Interface Beta Release

The goal of Lorenz is to develop a sophisticated web-based framework as a front end to Livermore Computing Center resources. The primary features include: a personalized dashboard for each user, giving an at-a-glace overview of all computing center resources; a front-end to job submission and management; and a software framework to extend the convenience of web interfaces into simulation codes, including support for setting up, launching, steering, and monitoring simulations. Because the breadth of desktop operating systems in use both inside and outside LLNL spans all flavors of Linux, Mac, and Windows, the decision was made to use exclusively web-based technologies in Lorenz. Recent advancements in AJAX and Javascript programming, along with coming advances in the form of HTML5 and CSS3, made the browser the preferred development platform. The goal is to provide the user with a robust application interface that requires nothing more than a modern, standards-based web browser. This approach not only provides convenient access to Lorenz for internal and external users, but also has significant advantages over conventional applications in terms of rapid deployment and updates. The first phase of the Lorenz project is a system “dashboard”, known as MyLC, that gives LC users a rich set of portal applications, or “portlets”, from which to choose. Information that previously required knowledge of dozens of different commands, files, and web pages is now available in one convenient location. This includes account information, bank and disk usage, quotas, cluster utilization, news items, active jobs on LC systems, and more. The extensible software design of the dashboard allows users and staff members to develop their own portlets, and for them to be shared with all users or just within work groups. The second major phase of Lorenz was built on the idea that HPC centers are managed around batch processing, and “jobs” (or “runs”) progress through several discrete stages: setup, submission, queuing/waiting, running, completion, analysis, and archiving. Lorenz aims to ultimately tie all of these pieces together, including integration with the dashboard and application portals. In addition to helping guide users through the process of defining batch parameters, monitoring job progress, and interacting with jobs and job output, Lorenz also aims to promote access to additional tools and capabilities which to this point have been limited to use by power users. Ultimately Lorenz will assist users in choosing the appropriate resources, such as cluster and file system, given the requirements of a job. The third major phase of Lorenz, the subject of this milestone, is the development of an application portal. This involves teaming with application codes to provide a simple graphical interface to the simulations, which in turn seamlessly ties into job submission and monitoring. This will allow users to directly define simulation parameters and launch applications using a simple but powerful web front-end. Because many complex multi-physics codes can have thousands of inputs, providing a general GUI for building an input deck from scratch is impractical. However, most users of large applications start with an existing input file, and make some number of small changes to it. The application portal will feature a process that combines trusted and validated input files with a GUI that guides the user toward making the relatively minor changes needed for their particular problem. The input files will be in the form of templates, containing most of the data needed for a particular problem along with parameterization of changeable inputs. For expert users, there ultimately will be a way to edit the final input file directly - in the event that there are input changes needed that were not captured in the GUI.

97 MATHEMATICS AND COMPUTING↗

2020 Exascale Computing Project Annual Meeting (Executive Summary Report)

The Exascale Computing Project (ECP) delivers specific applications, software products, and outcomes on DOE computing facilities. Integration across these elements for specific hardware technologies for exascale system instantiations is fundamental to ECP success. The outcome of the ECP is the delivery of a capable exascale computing ecosystem to provide breakthrough solutions addressing our most critical challenges in scientific discovery, energy assurance, economic competitiveness, and national security. This outcome is not a matter of ensuring more powerful computing systems. The ECP is designed to create more valuable and rapid insights from a wide variety of applications (“capable”), which requires a much higher level of inherent efficacy in all methods, software tools, and ECP-enabled computing technologies to be acquired by DOE laboratories (“ecosystem”). The ECP annual meeting provides a unique opportunity for the core technical expertise in the United States focused on achieving this next plateau of computational science and computing performance to engage in direct discussions on project execution. Face-to-face gatherings in technical communities like this are common and needed for the exchange of scientific ideas and technical performance. The ECP annual meeting stands apart from other technical conferences and meetings in the computing community as it is uniquely and solely focused on the execution of the ECP and the integration of technical activities leading to the creation of the exascale computing ecosystem for the future. The direct interaction of key critical technical staff, who are leaders in their respective fields, and the resulting give-and-take between software, applications, and hardware and the technical co-design therein, is unique and essential to the effective execution of the ECP. The first annual meeting was held in Knoxville, Tennessee, January 31 – February 2, 2017 and brought together, for the first time, a diverse collection of researchers from 16 DOE national laboratories as well as university computer and computational science researchers to discuss shared problems and joint solutions for the development of a capable exascale computing ecosystem. These interactions resulted in focused technical plans and an energized community centered on advances for ECP. The second annual meeting was held in Knoxville, Tennessee, February 5–9, 2018. It included 643 individual thought leaders and performers in application development, software research and deployment, and hardware research and integrators, all of whom are part of the multifaceted, billion dollar HPC community. This meeting provided a platform to discuss and disseminate numerous examples where researchers with common goals and synergistic solutions came together for the first time to deliver tangible results. Additionally, at the 2018 meeting, ECP researchers had the opportunity to digest all US HPC vendor R&D product roadmaps pointing to exascale – not only to learn how their research can play a role, but, more importantly, to influence those roadmaps to ensure successful delivery on DOE applications that will contribute to (if not solve) problems of national interest in national security, science, energy, and health, as well as growing security threats. The third annual meeting was held in Houston, Texas, January 14–17, 2019. With a 19% increase in the number of registrations (768 people), and the change in location, the third annual meeting was considered the most impactful of the three at the time. The new website provided a better platform for the dissemination of the content, the new venue as a meeting hotel instead of a conference center facilitated interactions and discussions after event hours, and the addition of an award-winning mobile event conference app (Whova) transformed dramatically the attendee experience at the event. This fourth annual meeting was held in Houston, Texas, February 3-7, 2020. This meeting had an increase in the number of attendees for a total of 824 people registered (782 attendees) and included numerous enhancements based on feedback and lessons learned from previous meetings, some of which are listed here: Improved quality of the sessions, their material and the whole program.; Had more industry participation and addition of external collaborators from overseas.; Published the full agenda earlier to better accommodate attendance and travel plans based on schedule.; Centralized all sessions in one venue.; Provided additional hotels and room blocks for the attendees.; Improved communication with the audience (links, material, directions, notifications, etc.) to go paperless.; Enhanced side meeting scheduling, management and user experience.; Made available additional space and tables for impromptu meetings and side discussions.; Improved IT and A/V solutions for speakers. In addition, our final survey captured the following points as opportunities for improvement in future meetings: consider a different meeting location that is more pedestrian friendly, reduce talks during working meals to allow more collaboration and informal time, adapt the agenda to acknowledge attendees from different timezones, consider recording some of the tutorials and/or sessions to share broadly with the HPC community, have a larger poster room, provide additional power strips, and improve the WiFi.

97 MATHEMATICS AND COMPUTING↗

Insert Modeling in UNF ST&DARDS

The Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) is a software tool that integrates a used nuclear fuel (UNF) or spent nuclear fuel (SNF) relational database and key analysis capabilities to simplify and automate numerous UNF management and fuel cycle–related activities. UNF-ST&DARDS is being developed for the US Department of Energy’s Office of Nuclear Energy Spent Fuel and Waste Disposition program. UNF-ST&DARDS provides an integrated framework that uses advanced modeling and simulation to predict the behavior of SNF over the timescales associated with permanent disposal in a geologic repository. After leaving the spent fuel pool, SNF is transferred to dry storage in a dual-purpose canister (DPC). DPCs are considered “dual purpose” because they are designed for both storage and transportation, removing the need to transfer the fuel to a separate transportation cask. However, much research has been conducted investigating the feasibility of directly disposing of DPCs in geologic repositories. Direct disposal of DPCs could reduce worker exposure during repackaging, reducing the amount of low-level waste from the discarded DPCs and potentially saving billions of dollars. Therefore, direct disposal of as-loaded DPCs is desirable if it can be done safely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A method of dose reconstruction for moving targets compatible with dynamic treatments

Purpose: To develop a method that allows a commercial treatment planning system (TPS) to perform accurate dose reconstruction for rigidly moving targets and to validate the method in phantom measurements for a range of treatments including intensity modulated radiation therapy (IMRT), volumetric arc therapy (VMAT), and dynamic multileaf collimator (DMLC) tracking. Methods: An in-house computer program was developed to manipulate Dicom treatment plans exported from a TPS (Eclipse, Varian Medical Systems) such that target motion during treatment delivery was incorporated into the plans. For each treatment, a motion including plan was generated by dividing the intratreatment target motion into 1 mm position bins and construct sub-beams that represented the parts of the treatment that were delivered, while the target was located within each position bin. For each sub-beam, the target shift was modeled by a corresponding isocenter shift. The motion incorporating Dicom plans were reimported into the TPS, where dose calculation resulted in motion including target dose distributions. For experimental validation of the dose reconstruction a thorax phantom with a moveable lung equivalent rod with a tumor insert of solid water was first CT scanned. The tumor insert was delineated as a gross tumor volume (GTV), and a planning target volume (PTV) was formed by adding margins. A conformal plan, two IMRT plans (step-and-shoot and sliding windows), and a VMAT plan were generated giving minimum target doses of 95% (GTV) and 67% (PTV) of the prescription dose (3 Gy). Two conformal fields with MLC leaves perpendicular and parallel to the tumor motion, respectively, were generated for DMLC tracking. All treatment plans were delivered to the thorax phantom without tumor motion and with a sinusoidal tumor motion. The two conformal fields were delivered with and without portal image guided DMLC tracking based on an embedded gold marker. The target dose distribution was measured with a radiochromic film in the moving rod and compared with the reconstructed doses using gamma tests. Results: Considerable interplay effects between machine motion and target motion were observed for the treatments without tracking. For nontracking experiments, the mean 2 mm/2% gamma pass rate over all investigated scenarios was 99.6% between calculated and measured doses. For tracking experiments, the mean gamma pass rate was 99.4%. Conclusions: A method for accurate dose reconstruction for moving targets with dynamic treatments was developed and experimentally validated in a variety of delivery scenarios. The method is suitable for integration into TPSs, e.g., for reconstruction of the dose delivered to moving tumors or calculation of target doses delivered with DMLC tracking.

60 APPLIED LIFE SCIENCES↗

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗

Status of SPCA-ANL Software Development, Software Quality Assurance, and Application (FY2025)

SPCA-ANL is a simulation tool used to perform deterministic analyses of sodium spray and pool fires. Development of the SPCA-II (Spray Pool Combustion Analysis) code began in the mid- 1980s as part of the Clinch River Breeder Reactor (CRBR) Project. At that time, development of SPCA-II, which was led by Rockwell International, was focused on treatment of large-scale sodium spray, stream, and pool fires that were anticipated to be prototypic of the steam generator building cells in CRBR. Under more recent DOE NE programmatic activities, the SPCA-II code was recovered from existing literature and underwent minor modifications to generate a stable executable. This recovered version of the code was not formally released. As part of the Versatile Test Reactor (VTR) Project in the 2010s, the SPCA-II code underwent key modifications to improve stability, address modeling deficiencies, improve consistency between the code manual and software, and address numerous bugs. At this point, SPCA-II was renamed SPCA-ANL. Given that SPCA-II served as the original basis for SPCA-ANL, both codes share an integrated history. Following termination of the VTR Project, the DOE NE Fast Reactor Program resumed support of the software with the goal of building and maintaining software infrastructure that can enable commercial-grade dedication of SPCA-ANL by an end user. Version 1.0, the first external release of SPCA-ANL, was generated in June 2024. This report summarizes the development and maintenance activities completed for SPCAANL in FY2025. This year’s work was focused on improving quality and usability of the code. The provisional Software Quality Assurance (SQA) program has been established and was used to test the procedures for infrastructure improvements, code development, bug fixes, and code releases, as described in the following sections of this report. A code Version 1.0.1 was released in FY25, as described in Chapter 4.

97 MATHEMATICS AND COMPUTING↗

Microstructural-Level Fuel Performance Modeling of U-Mo Monolithic Fuel

As the physics that governs the microstructural evolution of nuclear fuel span various time and spatial scales, to fully understand the fuel behavior inevitably involves atomic to mesoscale resolution that can be difficult to determine experimentally. Microstructural-level modeling and simulations can be used to develop physics-based materials models that can provide physical understanding to inform fabrication process control, as well as a valuable feedback mechanism between post-irradiation examination (PIE) results and fabrication parameters. In accordance with the program schedule, the primary goals of the microstructure modeling effort are to: 1. Address critical microstructural questions and provide practical guidance to the fabricator via the fuel product specification; 2. Provide mechanistic inputs for the existing fuel performance code to improve its descriptive and predictive capability at the macroscopic scale. In fiscal year (FY)-21, the work scope consisted of six main facets: (1) the effect of carbides on fuel performance; (2) gas diffusivity in different phases; (3) integration of microstructural fuel performance modeling; (4) property degradation; (5) irradiation creep; and (6) historical analysis of microstructure data. Brief summaries of each are included below.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Prototype Software to Demonstrate a Data Catalog for Hanford Environmental Datasets

Ensuring that data on long-term environmental remediation at the Hanford Site is high-quality, traceable, and easily accessible is an ongoing challenge, complicated by decades of data collection, multiple contractors maintaining data sources, and the wide range of data types. A centralized data catalog, known as the Hanford Environmental Information and Data Index (HEIDI), has been under development as part of the Hanford Environmental Data Management (HEDM) program to address these challenges. HEIDI fulfills a critical need to bring together a wide range of data types and sizes from multiple authoritative data sources, while documenting the data pedigree and quality information (i.e., traceable to the data source/originator). This document describes additional development and maturation of the HEIDI prototype. Key accomplishments included deploying the catalog software, Esri Geoportal Server, on a server accessible to Hanford Local Area Network users, conducting cybersecurity evaluations, investigating integrated authentication solutions, and conducting functional testing of the catalog prototype. The server-based deployment enabled targeted feedback, leading to enhancements including improved accessibility features and an expanded metadata schema. Specifications for the server-based deployment of the prototype catalog and the HEIDI metadata schema are provided in this document to support subsequent HEIDI deployment by the U.S. Department of Energy Richland Operations Office.

54 ENVIRONMENTAL SCIENCES↗

Test Plan for the Horizontal Dry Cask Simulator

The thermal performance of commercial spent nuclear fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission(NRC). Canistered dry storage cask systems rely on ventilation between the inner canister and the overpack to convect heat away from the canister to the surrounding environment for both horizontal and vertical configurations. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. Carefully measured data sets generated from testing of full sized casks or smaller cask analogs are widely recognized as vital for validating these models. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of the investigation described in this test plan is to produce data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator(HDCS) has been designed to generate this benchmark data and add to the existing knowledgebase. The pressure vessel representing the canister has been designed, fabricated, and pressure tested for a maximum allowable pressure(MAWP)rating of 2,400 kPa at400 °C. An existing electrically heated but otherwise prototypic boiling water reactor(BWR), Incoloy-clad test assembly will be deployed inside of a representative storage basket and canister. An insulated sheet metal enclosure will be used to mimic the thermal properties of the concrete vault enclosure used in a modern horizontal storage system. Radial and axial temperature profiles along with induced cooling air flow will be measured for a wide range of decay powers and representative(and higher)cask pressures using various backfills of helium, argon, or air. The single assembly geometry with well-controlled boundary conditions simplifies computational requirements while preserving relevant physics. The proposed test apparatus integrates all the underlying thermal-hydraulics important to defining the performance of a modern horizontal storage system. These include combined-mode heat transfer from the electrically-heated assembly to the canister walls and the primarily natural-convective heat transfer from the canister to the cooling air flow passing through the horizontal vault enclosure. The objective of the HDCS is not to reproduce the performance of a commercial dry storage system for any given set of operational parameters. Rather ,the objective is to capture the dominant physics in a well-characterized test apparatus. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate is of particular importance. While incorporating the best available information based on thermal-hydraulic scaling arguments as well as previous vertical testing, this test plan is subject to changes due to improved understanding or from as built deviations to designs. As-built conditions and actual procedures will be documented in the final test report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integration of scanning probe microscope with high-performance computing: Fixed-policy and reward-driven workflows implementation

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements toward operationalization of the automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for scientific discovery. Here, we build a Python interface library that enables controlling an SPM from either a local computer or a remote high-performance computer, which satisfies the high computation power need of machine learning algorithms in autonomous workflows. We further introduce a general platform to abstract the operations of SPM in scientific discovery into fixed-policy or reward-driven workflows. Furthermore, our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

47 OTHER INSTRUMENTATION↗

Constrained Bayesian optimization of criticality experiments

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. Furthermore, we demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗

Department of Energy's Biological and Environmental Research Strategic Data Roadmap for Earth System Science

Rapid advances in experimental, sensor, and computational technologies and techniques are driving exponential growth in the volume, acquisition rate, variety, and complexity of scientific data. This wealth of scientifically meaningful data has tremendous potential to lead to scientific discovery. However, to achieve scientific breakthroughs, these data must be exploitable—they must be analyzed effectively and efficiently and the results shared and communicated easily within the wider Department of Energy’s (DOE’s) Biological and Environmental Research (BER) Climate and Environmental Sciences Division (CESD) community. The explosion in data complexity and scale makes these tasks exceedingly difficult to achieve, particularly given that an increasing number of disciplines are working across techniques, integrating simulation and experimental or observational results (see Table 5 in Appendix 2). Consequently, we need new approaches to data management, analysis, and visualization that provide research teams with easy-to-use and scalable end-to-end solutions. These solutions must facilitate (and where feasible, automate and capture) every stage in the data lifecycle (shown in Figure 1), from collection to management, annotation, sharing, discovery, analysis, and visualization. In addition, the core functionalities are the same across climate science communities, but they require customization to adapt to specific needs and fit into research and analysis workflows. To this end, the mission of CESD’s Data and Informatics Program is to integrate all existing and future distributed CESD data holdings into a seamless and unified environment for the acceleration of Earth system science.

54 ENVIRONMENTAL SCIENCES↗

Polarized Substructural Session Types

Concurrent processes can be extremely difficult to reason about, both for programmers and formally. One approach to coping with this difficulty is to study new programming languages and type features such as Session Types. Session types take as their conceptual notion of concurrency as a collection of processes linked together via channels and provide type-level coordination between processes using these channels. Logically motivated programming languages exploit the idea that providing a proof of a theorem in a logic is similar to proving that a given term has a particular type in a programming language and vice versa. These connections can be interesting for a few different reasons. First, when language and logic are independently discovered and independently useful, the existence of a connection suggests that both are onto some fundamentally important idea. Additionally, a connection provides a basis both for sanity checking our ideas and also can be fruitful grounds for inspiration by seeing how variants of either the logic or the language are reflected through the connection. This thesis primarily describes an exploration of logically motivated session types, SILL. Polarization, classifying propositions as either positive or negative, provides a natural way to describe a logically based session typing language with asynchronous communication while retaining a semantics that is reasonably implementable. Additionally, polarization gives us a way to smoothly integrate synchronous channels into SILL without needing a semantic extension. When combined with Adjoint Logic, this gives us an ability to incorporate a variety of modalities with relatively little work. From a practical perspective, this gives SILL access to persistent processes and garbage collection. We additionally explore a trio of loosely related extensions to SILL, and their logical connections, inspired by the above results: bundled message passing to reduce the number of communications performed by processes; racy programs, enabled by a select/epoll-like mechanism; and asynchronous receiving, an almost generalization of the basic asynchronous semantics. We have three different implementations of SILL: a simple but relatively full featured interpreter written in OCaml; a fragment of SILL as an embedded domain specific language in Haskell; and a cleaner version of the same in Idris. Lastly, we show that Liquid Types and Session Types are compatible. This gives us one notion of a dependently session typed language.

97 MATHEMATICS AND COMPUTING↗

Test and Evaluation of Systems with Embedded Machine Learning Components

As Machine Learning (ML) continues to advance, it is being integrated into more systems. Often, the ML component represents a significant portion of the system that reduces the burden on the end user or significantly improves task performance. However, the ML component represents an unknown complex phenomenon that is learned from collected data without the need to be explicitly programmed. Despite the improvement in task performance, the models are often black boxes. Evaluating the credibility and the vulnerabilities of ML models poses a gap in current test and evaluation practice. For high consequence applications, the lack of testing and evaluation procedures represents a significant source of uncertainty and risk. To help reduce that risk, here we present considerations to evaluate systems embedded with an ML component within a red-teaming inspired methodology. We focus on (1) cyber vulnerabilities to an ML model, (2) evaluating performance gaps, and (3) adversarial ML vulnerabilities.

97 MATHEMATICS AND COMPUTING↗