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At least 559 records · Page 31

Grid Cyber-Security Strategy in an Attacker-Defender Model

The progression of cyber-attacks on the cyber-physical system is analyzed by the Probabilistic, Learning Attacker, and Dynamic Defender (PLADD) model. Although our research does apply to all cyber-physical systems, we focus on power grid infrastructure. The PLADD model evaluates the effectiveness of moving target defense (MTD) techniques. We consider the power grid attack scenarios in the AND configurations and OR configurations. In addition, we consider, for the first time ever, power grid attack scenarios involving both AND configurations and OR configurations simultaneously. Cyber-security managers can use the strategy introduced in this manuscript to optimize their defense strategies. Specifically, our research provides insight into when to reset access controls (such as passwords, internet protocol addresses, and session keys), to minimize the probability of a successful attack. Our mathematical proof for the OR configuration of multiple PLADD games shows that it is best if all access controls are reset simultaneously. For the AND configuration, our mathematical proof shows that it is best (in terms of minimizing the attacker's average probability of success) that the resets are equally spaced apart. We introduce a novel concept called hierarchical parallel PLADD system to cover additional attack scenarios that require combinations of AND and OR configurations.

97 MATHEMATICS AND COMPUTING↗

Development of Multiresolution Capabilities for the Holistic Energy Resource Optimization Network (HERON) tool A progress update

INL researchers work on technoeconomic analyses for integrated energy systems (IES) using the Framework for Optimization of ResourCes and Economics (FORCE). Within FORCE, researchers use the Holistic Energy Resource Optimization Network (HERON) tool to conduct optimization of grid portfolios under uncertain market conditions. These optimizations determine optimal capacities for all IES components and strategies for resource dispatch which maximize some economic metric (e.g., net present value). Resource dispatch occurs on finer timescales (typically hours) and thus are asked to respond to a given time series (e.g. hourly load demand profiles for a grid, or pre-determined electricity prices). Volatile and complex bidding dynamics as well as poorly forecasted weather events within deregulated markets add uncertainty to the time series; FORCE can address this uncertainty by training a reduced order model on historical time series and generate unique synthetic time series which represent individual scenarios or realizations of the market. The IES configuration can be simulated under these different sampled realizations and a stochastic optimization is conducted which optimizes the expected value of the desired economic metric. The training of a synthetic time series generator is limited by the chosen time resolution; dynamics can occur on different time scales. Seasonal demand trends can dominate faster dynamical events (such as power outages from certain sectors or severe weather events) which might not get captured correctly by the trained model. In this report, we investigate different ways of addressing the training and generation of time series on multiple time scales using three main algorithms: wavelet decomposition, dynamic mode decomposition, and generative adversarial networks for time series. We demonstrate a time series analysis that yields information on not just the frequency space but also temporal space: where a fast Fourier transform can provide what frequencies dominate, the new algorithms can provide when the frequencies dominate as well. These analyses can help improve IES optimization by allowing researchers to couple simulations at different timescales when it is most needed - seasonal, day-ahead, and real time optimization - with greater computational efficiency. Future work will include implementation of a subset of the proposed algorithms into the FORCE toolset and application of these analyses into multiple timescale optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A hybrid approach to excited-state-specific variational Monte Carlo and doubly excited states

We extend our hybrid linear-method/accelerated-descent variational Monte Carlo optimization approach to excited states and investigate its efficacy in double excitations. In addition to showing a superior statistical efficiency when compared to the linear method, our tests on small molecules show good energetic agreement with benchmark methods. We also demonstrate the ability to treat double excitations in systems that are too large for a full treatment by using selected configuration interaction methods via an application to 4-aminobenzonitrile. Finally, we investigate the stability of state-specific variance optimization against collapse to other states’ variance minima and find that symmetry, Ansatz quality, and sample size all have roles to play in achieving stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗

A critical literature review of the advances in methane dehydroaromatization over multifunctional metal-promoted zeolite catalysts

We report the drastic rise in shale gas production has encouraged the quest for alternative uses of methane as a chemical feedstock in the manufacturing industry. While two-step syngas routes for methane valorization are deployed commercially, direct one-step routes for methane conversion are attracting much attention. As steam cracking installations have shifted from using oil-based naphtha to shale-based natural gas liquids, production of aromatics has dropped. Methane dehydroaromatization (MDA) is a one-step reaction capable of valorizing methane to hydrogen and benzene. Challenges with the MDA reaction are two-fold: the reaction is thermodynamically limited with low one-pass methane conversion and even the best catalytic systems, Mo/zeolites, suffer rapid deactivation from coking. A catalyst design strategy to improve stability is the use of multifunctional Mo-X/zeolite systems where X is a dopant capable of modulating the stability. In this paper we provide a complete overview of the main Mo-X/zeolite systems used in MDA and critically draw connections among the different types of dopants (X) employed, as a function of the role they play in the reaction/deactivation pathway. We have also dedicated a section to emerging trends with non-Mo based catalysts. The goal of this review article is to establish a basis that will facilitate the identification of useful multifunctional catalytic systems, and recognize gaps in the knowledge of these systems that deserve more attention. Improving MDA systems to the point to which they can be commercially deployed requires a multifaceted approach that combines optimization of the designs of both the catalyst and the reactor configuration. We therefore also provide a brief overview of the most recent advances in process intensification strategies employed with different reactor configurations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sorbent-based oxygen separation with YBC114 for energy storage systems

In our report we aimed to design, build, and evaluate an oxygen separation system to provide an inert sweep gas with low oxygen partial pressure (pO2) to redox-active thermochemical energy conversion reactors for a range of applications, including two-step redox cycles for thermochemical energy storage, water splitting, and carbon-dioxide splitting. The separation is based on an oxygen-selective sorbent, YBaCo4O7+δ (YBC114), which has excellent oxygen sorption and desorption properties demonstrated in our previous work. The oxygen separation performance of YBC114 was comprehensively studied by thermogravimetric analysis, sorption breakthrough experiments, and temperature swing sorption - desorption cycles. The results reveal that YBC114 can produce inert sweep gas with an oxygen concentration of less than 100 ppmv for at least 20 min during the thermal swing adsorption (TSA) cycle with the current sorption bed configuration, and the performance is consistent from cycle to cycle. The optimal sorption and desorption temperatures for the TSA process with YBC114 are determined to be 300 °C and 500 °C, respectively. Although challenges remain for the current separation system (e.g., high sorption temperature and slow kinetics), this study demonstrates the potential to use the oxygen-selective sorbent to produce an inert sweep gas, the feasibility of the oxygen separation concept, and guides new sorbent material development to make this application economically practical. A simple procedure is described for designing the YBC114 oxygen separation process.

42 ENGINEERING↗

Revisiting point defect thermodynamics in group IVB and VB transition metal carbides

We present a comprehensive re-examination of point defect thermodynamics in group IVB and VB transition metal carbides (TMCs) with the rocksalt structure using a combination of density functional theory (DFT) calculations and a statistical mechanical Wagner-Schottky model within the canonical ensemble. The most stable configurations of point defects were discovered using basin-hopping global optimization, driven by either a machine learning interatomic potential (MLIP) or DFT. A key finding is the identification of previously unreported dicarbon antisites—a C–C dimer occupying a metal site—as the structural (constitutional) defects on the carbon-rich side of stoichiometry in all group IVB and VB TMCs except TaC. Furthermore, dicarbon antisite-containing thermal defect complexes, such as quadruple and interbranch defects, can dominate in TMCs under specific stoichiometric and temperature conditions. In conclusion, by incorporating dicarbon antisites into the defect landscape, this work provides a revised understanding of the thermodynamics of point defects in TMCs.

Carbides↗

Development of an interatomic potential for the Ta–Li system

A new interatomic potential for the Ta–Li system is introduced to facilitate the study of phase stability, mechanical properties and non-equilibrium dynamics after Li implantation in Ta. Here, this potential is based on a generalization of the embedded atom method (GEAM) and includes contributions from embedding energy, explicit two- and three-body interactions, and nonlocal many-body interaction terms. The parameters of the potential are optimized using energies and atomic forces for a wide range of configurations obtained from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, including elastic constants, equations of state, phonon dispersion curves, point defect properties, and melting temperatures for different compositions. Although our potential is trained on a small dataset, its accuracy is comparable to that of available machine learning potentials for Li and Ta. Our simulations show that at temperatures below 500 K, Li atoms in Ta–Li alloys form clusters separated by Ta-rich domains, and we find no evidence of ordered phase formation. For Li concentrations below a few percent, Li atoms preferentially segregate to surfaces and grain boundaries. However, in alloys containing more than ~10% Li, the accumulation of Li in symmetric-tilt grain boundaries can lead to one of the following effects: formation of amorphous-like regions, changes in grain boundary structural units, or lateral movement of the grain boundary.

GEAM potential↗

Sputter-deposited CdMgTe for rear contact to CdSeTe/CdTe solar cells

CdTe-based photovoltaic device performance improvement is predominantly limited by open-circuit voltage. This work approaches the voltage deficit challenge through the incorporation of a cadmium magnesium telluride (CdMgTe) electron reflector layer at the back of 1.5- μm CdSeTe/CdTe absorbers to reduce back-surface recombination through a conduction band offset. A sputtered CdMgTe electron reflector layer permitted low fabrication temperatures and circumvented the intolerance of CdMgTe to thermal processing present in traditional close-space sublimation (CSS)-deposited CdMgTe devices. Here, we demonstrate that sputtered CdMgTe simultaneously promotes the retention of chlorine passivation and magnesium which is not feasible with CSS fabrication. We also show the importance of the Cu and Te back contact order in CdMgTe devices. Through the optimization of the sputtered CdMgTe substrate temperature, doping, and back structure configuration, 1.5 μm CdSeTe/CdTe devices with a sputtered CdMgTe layer achieved an efficiency of 16.0%, significantly higher than with CSS CdMgTe, and demonstrated partial enactment of electron-reflector behavior.

14 SOLAR ENERGY↗

Modeling of transverse stimulated Raman scattering in KDP/DKDP in large-aperture plates suitable for polarization control

Transverse stimulated Raman scattering (TSRS) in potassium dihydrogen phosphate (KDP) and deuterated potassium dihydrogen phosphate (DKDP) plates for large-aperture, inertial confinement fusion (ICF)-class laser systems is a well-recognized limitation giving rise to parasitic energy conversion and laser-induced damage. The onset of TSRS is manifested in plates exposed to the ultraviolet section of the beam. TSRS amplification is a coherent process that grows exponentially and is distributed nonuniformly in the crystal and at the crystal surfaces. To understand the growth and spatial distribution of TSRS energy in various configurations, a modeling approach has been developed to simulate the operational conditions relevant to ICF-class laser systems. Specific aspects explored in this work include (i) the behavior of TSRS in large-aperture crystal plates suitable for third-harmonic generation and use as wave plates for polarization control in current-generation ICF-class laser system configurations; (ii) methods, and their limitations, of TSRS suppression and (iii) optimal geometries to guide future designs.

47 OTHER INSTRUMENTATION↗

Spontaneous dynamical disordering of borophenes in MgB2 and related metal borides

Abstract Layered boron compounds have attracted significant interest in applications from energy storage to electronic materials to device applications, owing in part to a diversity of surface properties tied to specific arrangements of boron atoms. Here we report the energy landscape for surface atomic configurations of MgB 2 by combining first-principles calculations, global optimization, material synthesis and characterization. We demonstrate that contrary to previous assumptions, multiple disordered reconstructions are thermodynamically preferred and kinetically accessible within exposed B surfaces in MgB 2 and other layered metal diborides at low boron chemical potentials. Such a dynamic environment and intrinsic disordering of the B surface atoms present new opportunities to realize a diverse set of 2D boron structures. We validated the predicted surface disorder by characterizing exfoliated boron-terminated MgB 2 nanosheets. We further discuss application-relevant implications, with a particular view towards understanding the impact of boron surface heterogeneity on hydrogen storage performance.

36 MATERIALS SCIENCE↗

Assessment of vertical stability for negative triangularity pilot plants

Abstract Negative triangularity (NT) tokamak configurations may be more susceptible to magneto-hydrodynamic instability, posing challenges for recent reactor designs centered around their favorable properties, such as improved confinement and operation free of edge-localized modes. In this work, we assess the vertical stability of plasmas with NT shaping and develop potential reactor solutions. When coupled with a conformal wall, NT equilibria are confirmed to be less vertically stable than equivalent positive triangularity (PT) configurations. Unlike PT, their vertical stability is degraded at higher poloidal beta. Furthermore, improvements in vertical stability at low aspect ratio do not translate to the NT geometry. NT equilibria are stabilized in PT vacuum vessels due to the increased proximity of the plasma and the wall on the outboard side, but this scenario is found to be undesirable due to reduced vertical gaps which give less spatial margin for control recovery. Instead, we demonstrate that informed positioning of passively conducting plates can lead to improved vertical stability in NT configurations on par with stability metrics expected in PT scenarios. An optimal setup for passive plates in highly elongated NT devices is presented, where plates on the outboard side of the device reduce vertical instability growth rates to 16% of their baseline value. For lower target elongations, integration of passive stabilizers with divertor concepts can lead to significant improvements in vertical stability. Plates on the inboard side of the device are also uniquely enabled in NT geometries, providing opportunity for spatial separation of vertical stability coils and passive stabilizers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum Chemical Treatment of Strongly Correlated Magnetic Systems Based on Heavy Elements. Final Report

The objective of this project over the years has been to develop novel quantum chemical methods and employ them to study the chemistry of systems containing actinides, and transactinides. We have focused on their electronic and spectroscopic properties, their reactivity and utilization as single molecule magnets. We have developed wave-function based methods that are optimal to treat strongly correlated systems, namely systems with many electronic configurations that are all important and should be treated on an equal foot. Moreover, relativistic effects have to be included in the model, with special focus on spin-orbit coupling. We have derived our theories and developed our codes and made them available to the community as parts of open source packages. We have modelled systems in collaboration with experimentalists in the program, so that we could address some of the questions that are relevant to this community. We have also worked in collaboration with people at Lawrence Livermore National Laboratories on a project on super-heavy atoms. We hope that our theoretical predictions will inspire novel experiments. We have trained about 10 students/postdocs during this period, which are now faculty, researchers at national laboratories and in companies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Feasibility Study of Millimeter Wave Radars For Safeguards Applications

Containment and surveillance are fundamental measures in nuclear safeguards. Techniques such as video surveillance and laser curtain for containment provide effective monitoring in areas where maintaining continuity of knowledge is required. These systems, however, can be susceptible to loss of monitoring capabilities under certain environmental conditions such as poor visibility (i.e. low light conditions, smoke, fog, etc.) or extended power loss past the duration that the backup power system is designed for. Brookhaven National Laboratory has been investigating the feasibility of millimeter waves (mmWave) as a new perimeter seal in which radio frequency waves in the range of 60-64 GHz are used to detect and monitor objects of interest. Signals in this frequency range are not susceptible to environmental conditions. For proof-of-concept tests, mmWave sensors from Texas Instruments (TI), specificallyIWR6843, are used in a test bed at BNL's Waste Management facility to simulate the operations at nuclear facilities. The unique design of TI mmWave sensors requires less memory and power consumption compared to counterpart systems. These devices are capable of exporting 3D point-cloud data, which is visualized graphically and compared to videos recorded at the same time to validate the performance of the mmWave sensor. A set of experiments were planned to test the feasibility of the mmWave in this application, including monitoring static containers in a storage area and detecting intrusions at the boundaries of the area. In addition, the experiments also identify potential blind spots relative to sensor position and utilize multiple operating sensors simultaneously to reduce or eliminate such blind spots. The optimal positioning of multiple sensors was determined for the experimental room configuration. In this paper, we will discuss the details of this novel perimeter sealing concept and present the test results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Observation and rationalization of nitrogen oxidation enabled only by coupled plasma and catalyst

Abstract Heterogeneous catalysts coupled with non-thermal plasmas (NTP) are known to achieve reaction yields that exceed the contributions of the individual components. Rationalization of the enhancing potential of catalysts, however, remains challenging because the background contributions from NTP or catalysts are often non-negligible. Here, we first demonstrate platinum (Pt)-catalyzed nitrogen (N 2 ) oxidation in a radio frequency plasma afterglow at conditions at which neither catalyst nor plasma alone produces significant concentrations of nitric oxide (NO). We then develop reactor models based on reduced NTP- and surface-microkinetic mechanisms to identify the features of each that lead to the synergy between NTP and Pt. At experimental conditions, NTP and thermal catalytic NO production are suppressed by radical reactions and high N 2 dissociation barrier, respectively. Pt catalyzes NTP-generated radicals and vibrationally excited molecules to produce NO. The model construction further illustrates that the optimization of productivity and energy efficiency involves tuning of plasma species, catalysts properties, and the reactor configurations to couple plasma and catalysts. These results provide unambiguous evidence of synergism between plasma and catalyst, the origins of that synergy for N 2 oxidation, and a modeling approach to guide material selection and system optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimal Droop Setting for Congestion Reduction in a 100% Grid-Forming Inverter-based Power System

he high penetration of inverter-based resources (IBRs) introduces new challenges to power systems due to the complex inverter control. However, IBRs can be configured to maximize their benefits to improve system resilience and reliability. This paper proposes a steady-state optimization model that aims to mitigate transmission congestion in a 100% grid- forming (GFM) IBR-based power system. This goal is achieved by determining the optimal droop settings for the GFM IBRs under different congestion conditions due to renewable energy and load variations. The numerical solution is rigorously verified by a high-fidelity model of the IEEE 39-bus test system with detailed GFM IBR control in the time-domain electromagnetic transient (EMT) simulation tool PSCAD. The numerical solution and simulation results show a significant congestion reduction while meeting all other operating requirements. It is also observed that the numerical solving time is substantially less compared to the EMT simulation time.

Nguyen, Quan H.↗

Off-design performance of molten salt-driven Rankine cycles and its impact on the optimal dispatch of concentrating solar power systems

This paper presents a model for improving off-design performance predictions for molten salt-driven Rankine power cycles, such as in concentrating solar power tower applications. The model predicts cycle off-design performance under various boundary conditions, including molten salt inlet temperature, mass flow rate, and ambient temperature. The model is validated using industry performance data and benchmarked with results from the literature. A complete concentrating solar power plant, inclusive of solar heliostat field and receiver, is then considered, by implementing the Rankine cycle off-design performance results into the National Renewable Energy Laboratory’s System Advisor Model software, which includes a tool that determines optimal power production schedules. The work improves upon the current System Advisor Model by updating off-design performance characteristics. A case study demonstrates the impact of cycle off-design behavior on annual performance for a stand-alone concentrating solar power system and a concentrating solar power-photovoltaic hybrid system. In addition, we demonstrate how cycle off-design performance influences optimal operator dispatch decisions and, thereby, overall system design and economics. We conclude that off-design cycle performance impacts “optimal” sub-system sizing, especially for a concentrating solar power-photovoltaic hybrid configuration in which concentrating solar power must dispatch in conjunction with photovoltaic generation.

14 SOLAR ENERGY↗

Optimizing the HSX stellarator for microinstability by coil-current adjustments

Abstract The optimization of helically symmetric experiment (HSX) for reduced microinstability has been achieved by examining a large set of configurations within a neighborhood of the standard operating configuration. This entailed generating a database of more than 10 6 magnetic-field configurations for HSX by varying the currents in external coils. Using a set of volume-averaged metrics and gyrokinetic simulations, this database has helped to identify a set of configurations that can be used to regulate trapped-electron-mode stability in HSX. This set of configurations is also found to correlate flux-surface elongation and triangularity with an increase in magnetic-well depth, an increase in rotational transform, and low neoclassical heat-flux relative to the standard quasi-helically-symmetric configuration. These results demonstrate sensitivity of plasma behavior in response to changes in a 3D magnetic field to both neoclassical and gyrokinetic models, and the experimental potential in HSX to explore turbulence optimization. This perturbative optimization approach is not unique to HSX, and can readily be deployed on existing fusion devices to identify novel magnetic-fields to be used in turbulence-optimization experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗