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Multi–LDAP Dynamic User Management Tool Utilizing Oracle Application Express and PL/SQL

A Center for Infrastructure Security Analysis (CISA) client system required support of multiple Lightweight Directory Access Protocol (LDAP) directories for multiple, varied user communities. The LDAP directories were all based upon different technologies, i.e., Microsoft Active Directory (AD), Microsoft Active Directory Lightweight Directory Services (ADLDS), and Oracle Internet Directory (OID), depending on system setup, security requirements, and legacy software. Research revealed that PL/SQL provided the capability to execute dynamic PL/SQL and SQL blocks. The dynamic capabilities were utilized along with several configuration tables to provide an object-oriented, polymorphic-like behavior. This architecture was chosen so that a top-level application programming interface (API) could be defined for all calls, no matter what type of LDAP was being manipulated, as each LDAP type has slightly different attributes and requirements. The dynamic nature of the user management system allowed for easy setup and utilization of any new LDAP directories, minimizing the time and effort expended on system changes.

97 MATHEMATICS AND COMPUTING↗

Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS “pathways,” or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with other experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

BCL-2 proteins and apoptosis: Recent insights and unknowns

Highlights: • The pro-apoptotic BCL-2 proteins can commit cells to apoptosis. • BAX and BAK are regulated by dynamic shuttling between mitochondria and cytosol of healthy cells. • BH3-only proteins, regulators of BAX and BAK, are not required for BAX activation. • Recent super-resolution microscopy studies provide novel insights into the active BAX complex. Proteins of the B-cell lymphoma-2 (BCL-2) family control the intrinsic apoptosis pathway. The pro-apoptotic BCL-2 proteins BAX and BAK can commit a cell to its programmed death by permeabilizing the outer mitochondrial membrane (OMM) and subsequent initiation of the caspase cascade. Therefore, the activities of BAX and BAK are precisely controlled by a complex network of proteins inside and outside the BCL-2 family. Cells survive by constant control of dynamic translocation and retrotranslocation of BAX and BAK to the mitochondria and back into the cytosol. Recent insights into BAX/BAK shuttling, BCL-2 protein interactions, the role of BH3-only proteins in apoptosis signaling and the active BAX complex set the stage for the development of novel strategies in cancer therapy and the analysis of cellular predisposition to apoptosis.

60 APPLIED LIFE SCIENCES↗

Development and Validation of SAM Multi-dimensional Flow Model for Thermal Mixing and Stratification Modeling

Thermal mixing and stratification in large pools or enclosures are very important phenomena that are critical to nuclear reactor safety. Because of the wide ranges of time and length scales associated with such phenomena, accurate modeling and simulation of thermal mixing and stratification remain as the key unresolved, challenging problems for reactor transient analyses. In traditional system analysis codes, simplified zero-dimensional (0-D) models are widely used for their high numerical efficiency, but they generally suffer from very limited prediction accuracies or range of applicability. Like traditional system analysis codes, the current version of the SAM code has implemented such simplified 0-D and one-dimensional mixing models. On the other hand, high-resolution Computational Fluid Dynamics (CFD) tools are often used to model complex thermal mixing and stratification phenomena. They are, however, generally numerically expensive, and they require large amounts of computational resources. It is therefore desirable to implement advanced and efficient thermal mixing and stratification modeling capabilities embedded in a system analysis code. This approach will improve the accuracy of reactor safety analyses when thermal mixing and stratification are involved, and also avoid using the large computational resources needed for high-resolution CFD analysis. Currently, with the support of the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation program, an effort has been launched to develop and implement a multi-dimensional flow model in the system analysis code SAM, and demonstrate its applications to model thermal mixing and stratification phenomena in large enclosures. The main outcomes of this research and development activity are summarized in this report, which presents an attempt to include a built-in advanced multi-dimensional flow model in a system analysis code with the focus on overcoming the simulation challenges of thermal mixing and stratification phenomena. In this report, we start with the introduction of existing SAM code capabilities to simulate thermal mixing and stratification phenomena, which is followed by a short summary of the multi-dimensional model implemented in the SAM code, including both the physical model and the Finite Element Method code implementation. In this study, two options were implemented in the SAM code to model turbulent flows: a relatively simple built-in turbulence model and an interface to accept externally computed turbulent viscosities (e.g., from a high- resolution CFD simulation). Code validation studies on this newly added capability were then carried out to compare SAM simulation results with experimental data from the SUPERCAVNA facility, which was designed to study the complex flow recirculation and thermal stratification phenomena relevant to sodium fast reactor designs. In this study, one transient and two steady-state test cases were used for code validation. Different approaches have been used to model the complex turbulence flow fields in the SUPERCAVNA facility. A highly simplified zero-equation turbulence model was first used, but it was determined that it is too simple to capture the complex turbulence flow fields in these test cases. Subsequently, the code validation continued with the use of turbulent viscosity data from high-resolution STAR-CCM+ CFD simulations to improve the accuracy of the results. Using this approach, the SAM simulation results showed very good agreement with both the SUPERCAVNA experimental data and STAR-CCM+ simulation results. In this report, we demonstrate the development, implementation, and successful validation of a multi-dimensional flow model in the SAM code, which aims to improve the simulation accuracy for complex thermal mixing and stratification phenomena. Lessons have also been learned, including that in cases where the flow fields are not well predicted by the zero-equation model, the iinput of turbulent viscosities from an external source can enhance the overall predictive capabilities needed to accurately capture complex thermal-hydraulic phenomena. Therefore, future research will be needed to further improve the code’s capabilities, such as by developing a more efficient and robust approach to capture the turbulence effects in the SAM code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Molecular Epidemiology of Foot-and-Mouth Disease Virus in the Context of Transboundary Animal Movement in the Far North Region of Cameroon

Transboundary movement of animals is an important mechanism for foot-and-mouth disease virus (FMDV) spread in endemic regions, such as Cameroon. Several transboundary animal trade routes cross the Far North Region of Cameroon, and cattle moved on foot along these routes often come in contact with native (sedentary and transhumant) herds. The purpose of this study was to investigate the role of transboundary trade cattle in the epidemiology of FMDV in the Far North Region of Cameroon. A total of 582 oropharyngeal fluid (OPF) samples were collected from asymptomatic transboundary trade cattle at official border check points and 57 vesicle epithelial tissues were collected from clinically affected native cattle in the Far North Region of Cameroon during 2010–2014. Viral protein 1 (VP1) coding sequences were obtained from 6 OPF samples from transboundary cattle (4 serotype O, 2 serotype SAT2) and 19 epithelial tissue samples from native cattle (7 serotype O, 3 serotype SAT2, 9 serotype A). FMDV serotype O viruses belonged to two topotypes (East Africa-3 and West Africa), and phylogenetic analyses suggested a pattern of continuous transmission in the region. Serotype SAT2 viruses belonged to a single topotype (VII), and phylogenetic analysis suggested a pattern of repeated introductions of different SAT2 lineages in the region. Serotype A viruses belonged to topotype AFRICA/G-IV, and the pattern of transmission was unclear. Spearman rank correlation analysis of VP1 coding sequences obtained in this study from transboundary and native cattle showed a positive correlation between genetic distance and time for serotype O ( ρ = 0.71, p = 0.003) and between genetic distance and geographic distance for serotype SAT2 ( ρ = 0.54, p = 0.1). These data suggest that transboundary trade cattle participate in the transmission of FMDV in the Far North Region of Cameroon, however the dynamics and direction of transmission could not be determined in this study. Results of this study contribute to the understanding of transboundary FMDV epidemiology in Central Africa and will help to inform control programs in Cameroon and in the region.

Veterinary Sciences↗

First Measurements of Nonlinear Decoherence in the IOTA Ring

The Integrable Optics Test Accelerator (IOTA), at Fermi National Laboratory is aimed at testing nonlinear optics for the next generation of high intensity rings. Through use of a special magnetic element the ring is designed to induce a large tune spread with amplitude while maintaining integrable motion. This will allow for the suppression of instabilities in high-intensity beams without significant reduction in dynamic aperture. One important aspect of this is the nonlinear decoherence that occurs when a beam is injected off axis or receives a transverse kick while circulating in the ring. This decoherence has been studied in detail, with simulations, for protons in IOTA both with and without space-charge. However, it has yet to be demonstrated experimentally. During the first phase of the IOTA experimental program, the ring is operated with 100 MeV electrons, allowing for the study of nonlinear optics without the complications introduced by space charge. Here we present measurements taken during the IOTA commissioning, and an analysis of the results.

43 PARTICLE ACCELERATORS↗

A long-term study of aerosol–cloud interactions and their radiative effect at the Southern Great Plains using ground-based measurements

Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regarding the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).

54 ENVIRONMENTAL SCIENCES↗

Stage-resolved gene regulatory network analysis reveals developmental reprogramming and genes with robust stem-preferred expression in sorghum

Sorghum bicolor is a deep-rooted, heat- and drought-tolerant crop that thrives on marginal lands and is increasingly valued for its applications in biofuel, bioenergy, and biopolymer production. The sorghum stem, which can reach 4–5 m in length, serves as the primary reservoir of both lignocellulosic biomass and soluble sugars, making it a promising bioenergy feedstock. Although recent advances in genetic, genomic, and transcriptomic resources have improved our understanding of sorghum biology, comprehensive genome-wide analyses of functional dynamics across diverse organ types and developmental stages remain limited. In particular, candidate genes with stem preferred expression pattern or their associated cis-regulatory elements, which may program key stem-related functions and enable organ- or tissue-specific engineering, have not yet been identified.

59 BASIC BIOLOGICAL SCIENCES↗

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Advancing Ethanol-to-Jet cost Effectiveness via direct conversion to n -Butene-Rich olefins and Co-Product Valorization

Ethanol is a promising feedstock for sustainable aviation fuel production; however, conventional routes face significant energy and cost challenges, particularly due to the ethanol dehydration step to ethylene. Here, this study leverages breakthrough experimental data to perform comprehensive techno-economic and life-cycle assessments of an innovative ethanol-to-jet process. The process employs a single-step catalytic conversion, enabled by multifunctional Cu-ZrO 2 /SBA-16 catalyst, to directly upgrade ethanol into a mixed olefin stream rich in n-butene. The single-step conversion eliminates the costly ethanol dehydration step in the conventional process. High selectivity toward n-butene offers key advantages: it simplifies downstream oligomerization into jet-range hydrocarbons and enables the co-production of renewable n-butene alongside sustainable aviation fuel. The analysis estimates a minimum fuel selling price as low as $\$$2.50 per gallon, whether using corn ethanol or cellulosic ethanol from corn stover. Life cycle CO 2 equivalent emissions are projected to be as low as 10.6 g CO 2 eq/MJ sustainable aviation fuel, representing over 70% reduction compared to conventional petroleum-based jet fuel. This one-step ethanol upgrading approach not only facilitates SAF and n-butene co-production but also provides operational flexibility. The ability to tailor product outputs allows the ethanol-to-jet process to adapt to varying feedstocks, incentive programs, and market dynamics, ultimately enhancing the economic viability of sustainable aviation fuel production.

Xu, Yiling [Pacific Northwest National Laboratory ↗

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

Advanced Computing, Data Science, and Artificial Intelligence Research Opportunities for Energy-Focused Transportation Science

The Energy Efficient Mobility Systems (EEMS) technology landscape is complex and rapidly evolving, which provides both tremendous opportunities and formidable challenges. Significant alterations to the mobility landscape are underway due to the advent of vehicle and infrastructure connectivity, autonomous driving, and rapid passenger- and freight-vehicle electrification. Advanced computing will play an increasingly important role in enabling the EEMS program to understand and identify the most important levers to improve the energy productivity of future integrated mobility systems. It is also driving new approaches to mobility and the research to unlock an affordable, efficient, safe, and accessible transportation future. Driving much of this change is the collection, analysis, and strategic use of massive amounts of diverse, complex data from infrastructure and vehicles with on-board sensors and data storage and transmission capabilities. Diverse and representative data are key to implementing approaches to maximize mobility energy productivity. While high-fidelity modeling of integrated transportation networks has strengthened our understanding of dynamic movement and behavior patterns, existing tools must be expanded beyond their current focus. This work necessitates data infrastructure investments (e.g., secure-streaming data platforms driven by ubiquitous sensors and video analytics) as well as investments in critical capabilities for large-scale automated analysis and organization using modern machine learning, statistics, and artificial intelligence. Other chief needs include agile, large-scale storage that can be quickly searched and queried for relevant data to support validation and model development, data-sharing agreements, and formatting standards for key data types. The future of public transit must be explored in greater detail, research must inform design, and opportunities must be identified for improving the mobility productivity of public transit in both urban and rural America.

33 ADVANCED PROPULSION SYSTEMS↗

Logical design of anti-prion agents using NAGARA

To accelerate the logical drug design procedure, we created the program “NAGARA,” a plugin for PyMOL, and applied it to the discovery of small compounds called medical chaperones (MCs) that stabilize the cellular form of a prion protein (PrP{sup C}). In NAGARA, we constructed a single platform to unify the docking simulation (DS), free energy calculation by molecular dynamics (MD) simulation, and interfragment interaction energy (IFIE) calculation by quantum chemistry (QC) calculation. NAGARA also enables large-scale parallel computing via a convenient graphical user interface. Here, we demonstrated its performance and its broad applicability from drug discovery to lead optimization with full compatibility with various experimental methods including Western blotting (WB) analysis, surface plasmon resonance (SPR), and nuclear magnetic resonance (NMR) measurements. Combining DS and WB, we discovered anti-prion activities for two compounds and tegobuvir (TGV), a non-nucleoside non-structural protein NS5B polymerase inhibitor showing activity against hepatitis C virus genotype 1. Binding profiles predicted by MD and QC are consistent with those obtained by SPR and NMR. Free energy analyses showed that these compounds stabilize the PrP{sup C} conformation by decreasing the conformational fluctuation of the PrP{sup C}. Because TGV has been already approved as a medicine, its extension to prion diseases is straightforward. Finally, we evaluated the affinities of the fragmented regions of TGV using QC and found a clue for its further optimization. By repeating WB, MD, and QC recursively, we were able to obtain the optimum lead structure. - Highlights: • NAGARA integrates docking simulation, molecular dynamics, and quantum chemistry. • We found many compounds, e.g., tegobuvir (TGV), that exhibit anti-prion activities. • We obtained insights into the action mechanism of TGV as a medical chaperone. • Using QC, we obtained useful information for optimization of the lead compound, TGV. • NAGARA is a convenient platform for drug discovery and lead optimization.

60 APPLIED LIFE SCIENCES↗

A morphology independent methodology for quantifying planview river change and characteristics from remotely sensed imagery

Remotely sensed imagery of rivers has long served as a means for characterizing channel properties and detection of planview change. In the last decade the dramatic increase in the availability of satellite imagery and processing tools has created the potential to greatly expand the spatial and temporal scale of our understanding of river morphology and dynamics. To date, the majority of GIS and automated analyses of planview changes in rivers from remotely sensed data has been developed for single-threaded meandering river systems. These methods have limited applicability to many of the earth's rivers with complex multi-channel planforms. Here we present the methodologies of a set of analysis algorithms collectively called Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM). SCREAM analyzes planview river metrics regardless of river morphology. These algorithms quantify both the erosion and accretion rates of riverbanks from binary masks of channels generated from imagery acquired at two time periods. Additionally, the program quantifies the area of change between river channels and the surrounding floodplain and area of islands lost or formed between these two time periods. To examine variations in erosion rates in relation to local channel attributes and make rate comparisons between river systems of varying sizes, the program determines channel widths and bank curvature at every bank pixel. SCREAM was developed and tested on rivers with diverse and complex planform morphologies in imagery acquired from a range of observational platforms with varying spatial resolutions. Here, validation and verification of SCREAM-generated metrics against manual measurements show no significant measurement errors in determination of channel width, erosion, and bank aspects. SCREAM has the potential to provide data for both the quantitative examination of the controls on erosion rates and for the comparison of these rates across river systems ranging broadly in size and planform morphology.

47 OTHER INSTRUMENTATION↗

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Combined Heat and Power Systems Technology Development and Demonstration 370 kW High Efficiency Microturbine

The C370 Program was awarded in October 2010 with the ambitious goal of designing and testing the most electrically efficient recuperated microturbine engine at a rated power of less than 500 kW. The aggressive targets for electrical efficiency, emission regulatory compliance, and the estimated price point make the system state-of-the-art for microturbine engine systems. These goals will be met by designing a two stage microturbine engine identified as the low pressure spool and high pressure spool that are based on derivative hardware of Capstone’s current commercially available engines. The development and testing of the engine occurred in two phases. Phase I focused on developing a higher power and more efficient engine, that would become the low pressure spool which is based on Capstone’s C200 (200kW) engine architecture. Phase II integrated the low pressure spool created in Phase I with the high pressure spool, which is based on Capstone’s C65 (65 kW) commercially available engine. Integration of the engines, based on preliminary research, would allow the dual spool engine to provide electrical power in excess of 370 kW, with electrical efficiency approaching 42%. If both of these targets were met coupled with the overall CHP target of 85% total combined heating and electrical efficiency California Air Resources Board (CARB) level emissions, and a price target of $600 per kW, the system would represent a step change in the currently available commercial generation technology. Phase I of the C370 program required the development of the C370 low pressure spool. The goal was to increase the C200 engine power by a minimum of 25% — 250 kW — and efficiency from 32% to 37%. These increases in the C200 engine output were imperative to meet the power requirements of the engine when both spools were integrated. An additional benefit of designing and testing the C370 low pressure spool was the possibility of developing a stand-alone product for possible commercialization. The low pressure spool design activity focused on an aeropath derivative of the current C200 engine. The aeropath derivative included changes to the compressor section —compressor and inducer — and to the turbine nozzle. The increased power also necessitated a larger, more powerful generator and generator controller to support the increased power requirements. These two major design changes were completed by utilizing both advanced 3D modeling and computational fluid dynamics modelling. After design, modeling, and analysis, the decision was made to acquire and integrate the components for testing. The second task of Phase I was to integrate and test the components of the low pressure spool to validate power and efficiency. Acquisition of the components for the low pressure spool was completed utilizing Capstone’s current supplier base. Utilization of Capstone’s supply base for integration of the test article would allow — if the decision was made —expedited commercialization of the product. After integration of the engine components, the engine was tested and evaluated for performance and emissions. Test data analysis confirmed that the engine met all power and efficiency requirements and did so while maintaining CARB level emissions. The emissions were met without the use of any post processing or catalyst. After testing was completed, the DOE authorized — via a milestone review — proceeding to Phase II: the development of the integrated C370 engine. The C370 high pressure spool design activity required significant changes to the C65 engine architecture. The engine required a high power density generator, completely redesigned compressor stage, turbine section, recuperator, controls architecture, and intercooler stage asThe two most critical design challenges were the turbine section (the nozzle and turbine) and the controls architecture. The design and analysis of all of the components was completed and integrated into a system model. The system model — after numerous iterations — indicated that, once integrated, the engine will meet or exceed all system requirements. Unfortunately, the turbine section’s life requirements remain a technical challenge and will require continued refinement of the bi-metallic turbine wheel design and manufacturing approach to meet the life requirement at theses high temperatures. The current controls architecture requires substantial effort to develop a system capable of handling the high-speed, near real-time controls requirement, but it was determined not to be a technical roadblock for the project. The C370 Program has been a significant effort with state-of-the-art technical targets. The targets have pushed Capstone’s designers to the limits of current technology. The program has been fortunate to see many successes: the successful testing of the low pressure spool (C250), the development of new material processes, and the implementation of new design practices. The technology and practices learned during the program will be utilized in Capstone’s current product lines and future products. The C370 Program has been a resounding success on many fronts for the DOE and for Capstone.

none↗

Computational Fluid Dynamic Modeling of Dry Cask Simulator with Crosswind

The purpose of this study is to create a STAR-CCM+ model of a Belowground Vertical Dry Cask Simulator (BVDCS) at Sandia National Laboratories (SNL) and validate the model with SNL’s experimental results. The BVDCS consists of a single boiling water reactor assembly fitted with electric heaters encompassed by a containment vessel and shell to represent a belowground spent nuclear fuel (SNF) dry storage system. Blowers are located near the inlet and outlet of the BVDCS to simulate crosswind conditions. In addition to the experimental results, the STAR-CCM+ model developed for this study is compared with a previous computational fluid dynamics (CFD) model in a different software program, which is used as a software-to-software benchmark. The experimental results provide a dataset to compare the STAR-CCM+ model results for a variety of different conditions. The main objective is to validate and improve STAR-CCM+ CFD models for spent nuclear fuel storage systems with explicitly modeled external environments and “wind driven” crossflows. These CFD models aide in the study of external particle deposition in spent nuclear fuel storage systems, which is important to predicting the significance of chloride induced stress corrosion cracking (CISCC). In addition to experimental comparison, a sensitivity analysis study is performed using the STAR-CCM+ model. The sensitivity analysis provides a quantitative assessment of the sensitivity of various parameters. This helps provide information on various parameters that are of particular importance to constructing a model representative of real life systems. The STAR-CCM+ model compared well to the experimental results showing similar responses to changes in cross wind flow, and a number of parameters are identified for model improvement.

Jensen, Ben J.↗

An introduction to neuromorphic computing and its potential impact for unattended ground sensors

Neuromorphic computers are hardware systems that mimic the brain’s computational process phenomenology. This is in contrast to neural network accelerators, such as the Google TPU or the Intel Neural Compute Stick, which seek to accelerate the fundamental computation and data flows of neural network models used in the field of machine learning. Neuromorphic computers emulate the integrate and fire neuron dynamics of the brain to achieve a spiking communication architecture for computation. While neural networks are brain-inspired, they drastically oversimplify the brain’s computation model. Neuromorphic architectures are closer to the true computation model of the brain (albeit, still simplified). Neuromorphic computing models herald a 1000x power improvement over conventional CPU architectures. Sandia National Labs is a major contributor to the research community on neuromorphic systems by performing design analysis, evaluation, and algorithm development for neuromorphic computers. Space-based remote sensing development has been a focused target of funding for exploratory research into neuromorphic systems for their potential advantage in that program area; SNL has led some of these efforts. Recently, neuromorphic application evaluation has reached the NA-22 program area. This same exploratory research and algorithm development should penetrate the unattended ground sensor space for SNL’s mission partners and program areas. Neuromorphic computing paradigms offer a distinct advantage for the SWaP-constrained embedded systems of our diverse sponsor-driven program areas.

97 MATHEMATICS AND COMPUTING↗