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At least 55 records · Page 3

Exploring the Use of Large Immersive Display Systems in the Nuclear Industry

Large immersive display systems play a critical role in the nuclear industry by enabling advanced training, design reviews, scientific visualization, and safety simulations. These systems, such as CAVE and powerwalls, allow engineers and operators to interact with virtual nuclear environments in real-time, providing a deeper understanding of complex systems. Their ability to simulate real-world scenarios for testing and optimization in a safe, controlled environment ensures that operators and engineers can refine process, enhance safety protocols, and troubleshoot complex challenges. This article outlines key lessons learned from deploying these systems, practical insights into their applications, and considerations for future improvements, aiming to guide their broader adoption and effective use in the nuclear industry.

99 - GENERAL AND MISCELLANEOUS↗

LEGO ® Bricks as Building Blocks for Centimeter-Scale Biological Environments: The Case of Plants

LEGO bricks are commercially available interlocking pieces of plastic that are conventionally used as toys. We describe their use to build engineered environments for cm-scale biological systems, in particular plant roots. Specifically, we take advantage of the unique modularity of these building blocks to create inexpensive, transparent, reconfigurable, and highly scalable environments for plant growth in which structural obstacles and chemical gradients can be precisely engineered to mimic soil.

54 ENVIRONMENTAL SCIENCES↗

Quantum simulator of an open quantum system using superconducting qubits: exciton transport in photosynthetic complexes

Open quantum system approaches are widely used in the description of physical, chemical and biological systems. A famous example is electronic excitation transfer in the initial stage of photosynthesis, where harvested energy is transferred with remarkably high efficiency to a reaction center. This transport is affected by the motion of a structured vibrational environment, which makes simulations on a classical computer very demanding. Here we propose an analog quantum simulator of complex open system dynamics with a precisely engineered quantum environment. Our setup is based on superconducting circuits, a well established technology. As an example, we demonstrate that it is feasible to simulate exciton transport in the Fenna–Matthews–Olson photosynthetic complex. Our approach allows for a controllable single-molecule simulation and the investigation of energy transfer pathways as well as non-Markovian noise-correlation effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Role of Chemistry in Fracture Pattern Development and Opportunities to Advance Interpretations of Geological Materials

Abstract Fracture pattern development has been a challenging area of research in the Earth sciences for more than 100 years. Much has been learned about the spatial and temporal complexity inherent to these systems, but severe challenges remain. Future advances will require new approaches. Chemical processes play a larger role in opening‐mode fracture pattern development than has hitherto been appreciated. This review examines relationships between mechanical and geochemical processes that influence the fracture patterns recorded in natural settings. For fractures formed in diagenetic settings (~50 to 200 °C), we review evidence of chemical reactions in fractures and show how a chemical perspective helps solve problems in fracture analysis. We also outline impediments to subsurface pattern measurement and interpretation, assess implications of discoveries in fracture history reconstruction for process‐based models, review models of fracture cementation and chemically assisted fracture growth, and discuss promising paths for future work. To accurately predict the mechanical and fluid flow properties of fracture systems, a processes‐based approach is needed. Progress is possible using observational, experimental, and modeling approaches that view fracture patterns and properties as the result of coupled mechanical and chemical processes. A critical area is reconstructing patterns through time. Such data sets are essential for developing and testing predictive models. Other topics that need work include models of crystal growth and dissolution rates under geological conditions, cement mechanical effects, and subcritical crack propagation. Advances in machine learning and 3‐D imaging present opportunities for a mechanistic understanding of fracture formation and development, enabling prediction of spatial and temporal complexity over geologic timescales. Geophysical research with a chemical perspective is needed to correctly identify and interpret fractures from geophysical measurements during site characterization and monitoring of subsurface engineering activities.

58 GEOSCIENCES↗

Gripper Test Assembly Status Report (FY2020)

Refueling systems for fast reactors are designed to handle fresh and used core assemblies (fuel, reflector, and shield core assemblies) within the reactor vessel in an opaque coolant environment without visual reference. These refueling machines are designed to work in a sodium (or other fast reactor coolant) and argon vapor space environment and are engineered with the rotatable plug system to allow for the movement of fresh and spent fuel into and out of the reactor core. The refueling machines are a critical component in any reactor and thus need to undergo extensive testing in a prototypic environment to ensure that they will meet all of the system functions and requirements. Argonne has developed an innovative compact refueling system design for the Advanced Fast Reactor-100 that is based upon some mechanisms used in previous reactor designs, such as the U.K.’s Prototype Fast Reactor (PFR) and some mechanisms that have not been used in sodium. This compact refueling machine supports the reduction in size of the AFR-100’s reactor vessel, and if fully developed, would support and inform the development of the in-vessel refueling machines for such commercial reactors as the GEH PRISM reactor plant, the ARC Clean Energy’s ARC-100 reactor, and the Natrium reactor, among others. This refueling system is a vital component of a fast reactor that supports reducing the cost of the reactor and increasing its reliability. During the development of the compact fuel handling machine conceptual design for the AFR-100, a lack of testing data for many mechanical components in sodium under typical in-reactor loads and conditions was discovered. The reduction in lifetime of the various mechanical components in the liquid sodium environment needs to be quantified versus the calculated component lifetimes under normal conditions in the testing while they are subjected to typical loading profiles experienced in the past. The Gripper Test Assembly discussed here includes a full-size gripper device with appropriate mechanical features that will be tested in sodium to provide this testing data. The Gripper Test Assembly is used to test various mechanical fuel handling components submerged in high temperature liquid sodium. These mechanisms are gears, bearings, gripper jaws and head, universal joints and shafts, ball screws, among others. These components will be tested under the typical sodium environmental conditions experienced during refueling operations with appropriate loading conditions that simulate the removal and insertion of core assemblies into a fast reactor grid plate structure. This Gripper Test Assembly is the second in a series of refueling system mechanisms developed for testing in sodium. The first test assembly is the Gear Test Assembly (GTA) which was used to test the performance of gears and bearings operating in sodium. Because of the successful testing conducted with the GTA, it was decided to continue with the development of the Gripper Test Assembly which uses the same gears and bearings tested in GTA. Using the data collected during operation of this gripper test assembly, lifetime reduction factors of the various mechanical components can be calculated for the material combinations selected. These lifetime reduction factors can be used in the design of future mechanical systems which operate in these environments to accurately predict component end of life. In addition, an understanding of the ability of these components and mechanisms to operate under-sodium with the chosen materials will be accomplished. Again, this Gripper Test Assembly is the follow-on test article to the Gear Test Assembly which was testing the ability of gears and bearings operating in a sodium environment. Once fabricated and qualified, it will be tested in the Mechanism Engineering Test Loop (METL) facility located in Building 308 at Argonne National Laboratory.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Flex Fuel Optimized SI and HCCI Engine

The central objective of the proposed work is to demonstrate an HCCI (homogeneous charge compression ignition) capable SI (spark ignited) engine that is capable of fast and smooth mode transition between SI and HCCI combustion modes. The model-based control technique was used to develop and validate the proposed control strategy for the fast and smooth combustion mode transition based upon the developed control-oriented engine; and an HCCI capable SI engine was designed and constructed using production ready two-step valve-train with electrical variable valve timing actuating system. Finally, smooth combustion mode transition was demonstrated on a metal engine within eight engine cycles. The Chrysler turbocharged 2.0L I4 direct injection engine was selected as the base engine for the project and the engine was modified to fit the two-step valve with electrical variable valve timing actuating system. To develop the model-based control strategy for stable HCCI combustion and smooth combustion mode transition between SI and HCCI combustion, a control-oriented real-time engine model was developed and implemented into the MSU HIL (hardware-in-the-loop) simulation environment. The developed model was used to study the engine actuating system requirement for the smooth and fast combustion mode transition and to develop the proposed mode transition control strategy. Finally, a single cylinder optical engine was designed and fabricated for studying the HCCI combustion characteristics. Optical engine combustion tests were conducted in both SI and HCCI combustion modes and the test results were used to calibrate the developed control-oriented engine model. Intensive GT-Power simulations were conducted to determine the optimal valve lift (high and low) and the cam phasing range. Delphi was selected to be the supplier for the two-step valve-train and Denso to be the electrical variable valve timing system supplier. A test bench was constructed to develop control strategies for the electrical variable valve timing (VVT) actuating system and satisfactory electrical VVT responses were obtained. Target engine control system was designed and fabricated at MSU for both single-cylinder optical and multi-cylinder metal engines. Finally, the developed control-oriented engine model was successfully implemented into the HIL simulation environment. The Chrysler 2.0L I4 DI engine was modified to fit the two-step vale with electrical variable valve timing actuating system. A used prototype engine was used as the base engine and the cylinder head was modified for the two-step valve with electrical VVT actuating system. Engine validation tests indicated that cylinder #3 has very high blow-by and it cannot be reduced with new pistons and rings. Due to the time constraint, it was decided to convert the four-cylinder engine into a single cylinder engine by blocking both intake and exhaust ports of the unused cylinders. The model-based combustion mode transition control algorithm was developed in the MSU HIL simulation environment and the Simulink based control strategy was implemented into the target engine controller. With both single-cylinder metal engine and control strategy ready, stable HCCI combustion was achived with COV of 2.1% Motoring tests were conducted to validate the actuator transient operations including valve lift, electrical variable valve timing, electronic throttle, multiple spark and injection controls. After the actuator operations were confirmed, 15-cycle smooth combustion mode transition from SI to HCCI combustion was achieved; and fast 8-cycle smooth combustion mode transition followed. With a fast electrical variable valve timing actuator, the number of engine cycles required for mode transition can be reduced down to five. It was also found that the combustion mode transition is sensitive to the charge air and engine coolant temperatures and regulating the corresponding temperatures to the target levels during the combustion mode transition is the key for a smooth combustion mode transition. As a summary, the proposed combustion mode transition strategy using the hybrid combustion mode that starts with the SI combustion and ends with the HCCI combustion was experimentally validated on a metal engine. The proposed model-based control approach made it possible to complete the SI-HCCI combustion mode transition within eight engine cycles utilizing the well controlled hybrid combustion mode. Without intensive control-oriented engine modeling and HIL simulation study of using the hybrid combustion mode during the mode transition, it would be impossible to validate the proposed combustion mode transition strategy in a very short period.

33 ADVANCED PROPULSION SYSTEMS↗

Environment and initial state engineered dynamics of quantum and classical correlations

Based on an open exactly solvable system coupled to an environment with nontrivial spectral density, we connect the features of quantum and classical correlations with some features of the environment, initial states of the system, and the presence of initial system–environment correlations. Some interesting features not revealed before are observed by changing the structure of environment, the initial states of system, and the presence of initial system–environment correlations. The main results are as follows. (1) Quantum correlations exhibit temporary freezing and permanent freezing even at high temperature of the environment, for which the necessary and sufficient conditions are given by three propositions. (2) Quantum correlations display a transition from temporary freezing to permanent freezing by changing the structure of environment. (3) Quantum correlations can be enhanced all the time, for which the condition is put forward. (4) The one-to-one dependency relationship between all kinds of dynamic behaviors of quantum correlations and the initial states of the system as well as environment structure is established. (5) In the presence of initial system–environment correlations, quantum correlations under local environment exhibit temporary multi-freezing phenomenon. While under global environment they oscillate, revive, and damp, an explanation for which is given. - Highlights: • Various interesting behaviors of quantum and classical correlations are observed in an open exactly solvable model. • The important effects of the bath structure on quantum and classical correlations are revealed. • The one-to-one correspondence between the type of dynamical behavior of quantum discord and the initial state is given. • Quantum correlations are given in the presence of initial qubits–bath correlations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Automated design synthesis of robotic/human workcells for improved manufacturing system design in hazardous environments [Slides]

Manufacturing tasks that are deemed too hazardous for workers require the use of automation, robotics, and/or other remote handling tools. The associated hazards may be radiological or non-radiological, and based on the characteristics of the environment and processing, a design may necessitate robotic labor, human labor, or both. There are also other factors such as cost, ergonomics, maintenance, and efficiency that also effect task allocation and other design choices. Handling the tradeoffs of these factors can be complex, and lack of experience can be an issue when trying to determine if and what feasible automation/robotics options exist. To address this problem, we utilize common engineering design approaches adapted more for manufacturing system design in hazardous environments. We limit our scope to the conceptual and embodiment design stages, specifically a computational algorithm for concept generation and early design evaluation. In regard to concept generation, we first develop the functional model or function structure for the process, using the common 'verb-noun' format for describing function. A common language or functional basis for manufacturing was developed and utilized to formalize function descriptions and guide rules for function decomposition. Potential components for embodiment are also grouped in terms of this functional language and are stored in a database. The properties of each component are given as quantitative and qualitative criteria. Operators are also rated for task-relevant criteria which are used to address task compatibility. Through the gathering of process requirements/constraints, construction of the component database, and development of the manufacturing basis and rule set, design knowledge is stored and available for computer use. Thus, once the higher level process functions are defined, the computer can automate the synthesis of new design concepts through alternating steps of embodiment and function structure updates/decomposition. In the process, criteria guide function allocation of components/operators and help ensure compatibility and feasibility. Through multiple function assignment options and varied function structures, multiple design concepts are created. All of the generated designs are then evaluated based on a number of relevant evaluation criteria: cost, dose, ergonomics, hazards, efficiency, etc. These criteria are computed using physical properties/parameters of each system based on the qualities an engineer would use to make evaluations. Nuclear processes such as oxide conversion and electrorefining are utilized to aid algorithm development and provide test cases for the completed program. Through our approach, we capture design knowledge related to manufacturing and other operations in hazardous environments to enable a computational program to automatically generate and evaluate system design concepts.

42 ENGINEERING↗

Lessons Learned Concerning the Onsite Disposal Facility at the Fernald Preserve, Harrison, Ohio - 16176

An onsite disposal facility (OSDF) was constructed at the Fernald Preserve, Ohio, for the disposal of contaminated soil and debris generated during a Comprehensive Environmental Response, Compensation, and Liability Act site cleanup. Completed in October of 2006, the 30 ha facility contains 2.26 million m{sup 3} of waste materials, has a maximum height of approximately 19.8 m, and consists of eight individual cells. The dimensions of cells 1-7 are approximately 213 m x 122 m each, or 26,000 m{sup 2} (2.60 ha). The dimensions of cell 8 (the last cell constructed) are larger than those of the other cells (approximately 3.8 ha). Each cell was constructed with a leachate collection system (LCS) that collected rainwater and storm-water runoff during waste placement and prevented it from entering the underlying environment. Other engineered features include a multilayer composite liner system, a leak detection system (LDS) positioned beneath the primary liner, and a multilayer composite cover that was placed over each cell following the completion of waste-placement activities. The LCS and LDS layers are designed to convey (by gravity) any leachate/fluid that enters the system through pipes to the west side of the facility and into tanks located in valve houses. From there, leachate can be sampled and conveyed to treatment. Groundwater is monitored beneath each cell via monitoring wells. In November 2006, the US DOE Office of Legacy Management (LM) assumed responsibility for the long-term care and maintenance of the OSDF. LM has nine years of monitoring and maintenance experience with the Fernald OSDF. Monitoring data is reported each year in the Fernald Annual Site Environmental Report. The data collected and inspections conducted indicate that the facility is operating as designed. The past nine years has provided LM with the opportunity to evaluate how well many of the design and as-built features of the facility have functioned over time as they pertain to environmental monitoring, valve-house operation and maintenance, and leachate transmission. Lessons learned concerning the long-term care and maintenance of the OSDF at the Fernald Preserve are presented. The main lessons learned include the following: How bivariate plots can be used to address environmental monitoring challenges created by installing an engineered disposal facility in a location where contamination is above the background level but below cleanup standards. How valve-house design decisions can help to alleviate long-term monitoring challenges. How scale buildup can lead to leachate transmission issues. Some additional minor lessons learned are also presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Diverse electron carriers drive syntrophic interactions in an enriched anaerobic acetate-oxidizing consortium

Abstract In many anoxic environments, syntrophic acetate oxidation (SAO) is a key pathway mediating the conversion of acetate into methane through obligate cross-feeding interactions between SAO bacteria (SAOB) and methanogenic archaea. The SAO pathway is particularly important in engineered environments such as anaerobic digestion (AD) systems operating at thermophilic temperatures and/or with high ammonia. Despite the widespread importance of SAOB to the stability of the AD process, little is known about their in situ physiologies due to typically low biomass yields and resistance to isolation. Here, we performed a long-term (300-day) continuous enrichment of a thermophilic (55 °C) SAO community from a municipal AD system using acetate as the sole carbon source. Over 80% of the enriched bioreactor metagenome belonged to a three-member consortium, including an acetate-oxidizing bacterium affiliated with DTU068 encoding for carbon dioxide, hydrogen, and formate production, along with two methanogenic archaea affiliated with Methanothermobacter_A. Stable isotope probing was coupled with metaproteogenomics to quantify carbon flux into each community member during acetate conversion and inform metabolic reconstruction and genome-scale modeling. This effort revealed that the two Methanothermobacter_A species differed in their preferred electron donors, with one possessing the ability to grow on formate and the other only consuming hydrogen. A thermodynamic analysis suggested that the presence of the formate-consuming methanogen broadened the environmental conditions where ATP production from SAO was favorable. Collectively, these results highlight how flexibility in electron partitioning during SAO likely governs community structure and fitness through thermodynamic-driven mutualism, shedding valuable insights into the metabolic underpinnings of this key functional group within methanogenic ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Correlation control of the Mott transition in LaTiO 3 /SrTiO 3 heterostructures

The Mott metal-insulator transition arises from electron-electron interactions determined by the ratio of Coulomb to kinetic energy scales (U/t). While temperature, pressure, and doping can induce Mott transitions, direct control of U in solid-state systems remains largely unexplored, particularly in the inhomogeneous environments of emerging neuromorphic devices, where conductive filaments create complex gradients of local properties. Here we show that interface-induced screening can continuously tune the electron-electron interaction strength U to drive an isothermal Mott transition. Using thickness-graded LaTiO3/SrTiO3 heterostructures, we used diffraction and photoemission spectroscopy to reveal a continuous, isothermal quantum phase transition from a Fermi liquid quasiparticle with incoherent excitations to a Mott insulator with Hubbard bands. The primary determinant of the transition is the enhanced local screening environment, which directly influences the interaction strength U, driving the system metallic. This demonstrates that interface engineering of the local screening environment provides a promising approach to manipulate Mott physics through correlation control, beyond traditional bandwidth or filling approaches.

Electronic and spintronic devices↗

Scaling up nanoscale water-driven energy conversion into evaporation-driven engines and generators

Evaporation is a ubiquitous phenomenon in the natural environment and a dominant form of energy transfer in the Earth’s climate. Engineered systems rarely, if ever, use evaporation as a source of energy, despite myriad examples of such adaptations in the biological world. In this work, we report evaporation-driven engines that can power common tasks like locomotion and electricity generation. These engines start and run autonomously when placed at air–water interfaces. They generate rotary and piston-like linear motion using specially designed, biologically based artificial muscles responsive to moisture fluctuations. Using these engines, we demonstrate an electricity generator that rests on water while harvesting its evaporation to power a light source, and a miniature car (weighing 0.1 kg) that moves forward as the water in the car evaporates. Evaporation-driven engines may find applications in powering robotic systems, sensors, devices and machinery that function in the natural environment.

42 ENGINEERING↗

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with information on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.

97 MATHEMATICS AND COMPUTING↗

In Situ Chemical Monitoring and Imaging of Contents within Microfluidic Devices Having a Porous Membrane Wall Using Liquid Microjunction Surface Sampling Probe Mass Spectrometry

The ability to observe dynamic chemical processes (e.g., signaling, transport, etc.) in vivo or in situ using nondestructive chemical imaging opens a new door to understanding the complex dynamics of developing biological systems. With the advent of “biology-on-a-chip” devices has come the ability to monitor dynamic chemical processes in a controlled environment, using these engineered habitats to capture key features of natural systems while allowing visual observation of system development. Having the capability to spatially and temporally map the chemical signals within these devices may yield new insights into the forces that drive biosystem development. Here, a porous membrane sealed microfluidic device was designed to allow normal microfluidic operation while enabling continuous, location specific sampling and chemical characterization by liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS). LMJ-SSP was used to extract fluids with nL-to-μL/min flow rates directly from selected areas of the microfluidic device without negatively impacting the device function. These extracts were subsequently characterized using MS. This technique was used to acquire MS images of the entirety of several multi-input microfluidic devices having different degrees of fluid mixing. LMJ-SSP MS imaging visualized the spatial distribution of chemical components within the microfluidic channels and could visualize chemical reactions occurring in the device. These microfluidic devices with a porous membrane wall are wholly compatible with the construction of biology-on-a-chip devices. This ultimately would enable correlation of biosystem physical structure with an evolving chemical environment

47 OTHER INSTRUMENTATION↗

Targeted Biomining and Machine Learning Approaches in Critical Minerals Revealed by a Biogeochemical Survey of a Coal Mine Drainage Remediation System

Abandoned coal mine drainage (AMD) remediation systems in Pennsylvania can concentrate critical minerals and materials (CMM) at levels comparable to mining-grade ores. Remediation systems have varying engineering features and are open to the environment, resulting in diverse microbial colonization and seasonal climate influences that may impact CMM speciation. The location of CMMs, the types of bacterial communities tolerant of these pollutant conditions, and the influence of localized climate on CMM rich remediation systems are not well characterized. Through a one-year spatiotemporal survey of biogeochemistry at a remediation system, we have initiated the process to address these questions. Rare Earth Elements (REE) ranged 180-1,200 ppm and greater than 1,500 bacterial ASVs were classified via 16S sequencing. Analyses indicate biogeochemical differences are heavily influenced by engineering features. Additionally, REE precipitants correlate strongly with the elements Al, Cu, Zn, Be, and U. Unearthing these trends has refined our line of inquiry to explore biological mining opportunities more closely with these metals. Furthermore, we created a Machine Learning Model for predicting AMD REE content, with 89% accuracy, using the data from this study and several others. Further training data is required to create a more reputable model. Recently, global research efforts have prioritized modeling work or the use of the few historical surveys to design experiments. Through our data, we challenge this approach, emphasizing the importance of expanding fundamental survey efforts prior to advanced product design and experimentation.

critical minerals↗

On the impact of temperatures up to 200°C in clay repositories with bentonite engineer barrier systems: A study with coupled thermal, hydrological, chemical, and mechanical modeling

One of the most important design variables for a geological nuclear waste repository is the temperature limit up to which the engineered barrier system (EBS) and the natural geologic environment can be exposed. Up to now, almost all design concepts that involve bentonite-backfilled emplacement tunnels have chosen a maximum allowable temperature of about 100°C. Such a choice is largely based on the consideration that in clay-based materials illitization and the associated mechanical changes in the bentonite (and perhaps the clay host rock) could affect the barrier attributes of the EBS. However, existing experimental and modeling studies on the occurrence of illitization and related performance impacts are not conclusive, in part because the relevant couplings between the thermal, hydrological, chemical, and mechanical (THMC) processes have not been fully represented in the models. This work presents a fully coupled THMC simulation of a nuclear waste repository in a clay formation with a bentonite-backfilled EBS for 1000 years. Two scenarios were simulated for comparison: a case in which the temperature in the bentonite near the waste canister can reach about 200°C and a case in which the temperature in the bentonite near the waste canister peaks at about 100°C. The model simulations demonstrate some degree of illitization in both the bentonite buffer and the surrounding clay formation. Other chemical alterations include the dissolution of K-feldspar and calcite, and precipitation of quartz, chlorite, and kaolinite. In general, illitization in the bentonite and the clay formation is enhanced at higher temperature. However, the quantity of illitization is affected by many chemical factors and therefore varies a great deal. The most important chemical factors are the concentration of K in the pore water as well as the abundance and dissolution rate of K-feldspar; less important ones are the concentration of sodium and the quartz precipitation rate. In our modeling scenarios, the calculated decrease in smectite volume fraction in bentonite ranges from 1 to 8% of the initial volume fraction of smectite in the 100°C scenario and 1–27% in the 200°C scenario. Chemical changes in the 200°C scenario could also lead to a reduction in swelling stress up to 15–18% whereas those in the 100°C scenario result in about 14–15% reduction in swelling stress for the base case scenario. Model results also show that the 200°C scenario results in a much higher total stress than the 100°C scenario, mostly due to thermal pressurization. While cautions should be taken regarding the model results due to some limitations in the models, the modeling work is illustrative in light of the relative importance of different processes occurring in EBS bentonite and clay formation at higher than 100°C conditions, and could be of greater use when site specific data are available.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Program Development Tools and Infrastructures: Activities by ASC CSSE/CCE and Partners

Exascale class machines will exhibit a new level of complexity: they will feature an unprecedented number of cores and threads, will most likely be heterogeneous and deeply hierarchical, and offer a range of new hardware techniques (such as speculative threading, transactional memory, programmable prefetching, and programmable accelerators), which all have to be utilized for an application to realize the full potential of the machine. Additionally, users will be faced with less memory per core, fixed total power budgets, and sharply reduced MTBFs. At the same time, it is expected that the complexity of applications will rise sharply for exascale systems, both to implement new science possible at exascale and to exploit the new hardware features necessary to achieve exascale performance. This is particularly true for many of the NNSA codes, which are large and often highly complex integrated simulation codes that push the limits of everything in the system including language features. To overcome these limitations and to enable users to reach exascale performance, users will expect a new generation of tools that address the bottlenecks of exascale machines, that work seamlessly with the (set of) programming models on the target machines, that scale with the machine, that provide automatic analysis capabilities, and that are flexible and modular enough to overcome the complexities and changing demands of the exascale architectures. Further, any tool must be robust enough to handle the complexity of large integrated codes while keeping the user's learning curve low. With the ASC program, in particular the CSSE (Computational Systems and Software Engineering) and CCE (Common Compute Environment) projects, we are working towards a new generation of tools that fulfill these requirements and that provide our users as well as the larger HPC community with the necessary tools, techniques, and methodologies required to make exascale performance a reality.

43 PARTICLE ACCELERATORS↗