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At least 1,765 records · Page 98

Mechanism of vacancy formation induced by hydrogen in tungsten

We report a hydrogen induced vacancy formation mechanism in tungsten based on classical molecular dynamics simulations. We demonstrate the vacancy formation in tungsten due to the presence of hydrogen associated directly with a stable hexagonal self-interstitial cluster as well as a linear crowdion. The stability of different self-interstitial structures has been further studied and it is particularly shown that hydrogen plays a crucial role in determining the configuration of SIAs, in which the hexagonal cluster structure is preferred. Energetic analysis has been carried out to prove that the formation of SIA clusters facilitates the formation of vacancies. Such a mechanism contributes to the understanding of the early stage of the hydrogen blistering in tungsten under a fusion reactor environment.

36 MATERIALS SCIENCE↗

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗

Differentiating the role of lithium and oxygen in retaining deuterium on lithiated graphite plasma-facing components

Laboratory experiments have been used to investigate the fundamental interactions responsible for deuterium retention in lithiated graphite. Oxygen was found to be present and play a key role in experiments that simulated NSTX lithium conditioning, where the atomic surface concentration can increase to >40% when deuterium retention chemistry is observed. Quantum-classical molecular dynamic simulations elucidated this oxygen-deuterium effect and showed that oxygen retains significantly more deuterium than lithium in a simulated matrix with 20% lithium, 20% oxygen, and 60% carbon. Simulations further show that deuterium retention is even higher when lithium is removed from the matrix. Experiments artificially increased the oxygen content in graphite to ∼16% and then bombarded with deuterium. X-ray photoelectron spectroscopy showed depletion of the oxygen and no enhanced deuterium retention, thus demonstrating that lithium is essential in retaining the oxygen that thereby retains deuterium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Distinct interactions of Na{sup +} and Ca{sup 2+} ions with the selectivity filter of the bacterial sodium channel Na{sub V}Ab

Highlights: ► Ca{sup 2+} translocates slowly in the filter, due to lack of “loose” knock-on mechanism. ► Identification of a high affinity binding site in Na{sub V}Ab selectivity filter. ► Changes of EEEE locus triggered by electrostatic interactions with Ca{sup 2+} ions. -- Abstract: Rapid and selective ion transport is essential for the generation and regulation of electrical signaling pathways in living organisms. In this study, we use molecular dynamics simulations and free energy calculations to investigate how the bacterial sodium channel Na{sub V}Ab (Arcobacter butzleri) differentiates between Na{sup +} and Ca{sup 2+} ions. Multiple nanosecond molecular dynamics simulations revealed distinct binding patterns for these two cations in the selectivity filter and suggested a high affinity calcium binding site formed by backbone atoms of residues Leu-176 and Thr-175 (S{sub CEN}) in the sodium channel selectivity filter.

60 APPLIED LIFE SCIENCES↗

Simulated Hydrological Dynamics and Coupled Iron Redox Cycling Impact Methane Production in an Arctic Soil

The fate of organic carbon (C) in permafrost soils is important to the climate system due to the large global stocks of permafrost C. Thawing permafrost can be subject to dynamic hydrology, making redox processes an important factor controlling soil organic matter (SOM) decomposition rates and greenhouse gas production. In iron (Fe)-rich permafrost soils, Fe(III) can serve as a terminal electron acceptor, promoting anaerobic respiration of SOM and increasing pH. Current large-scale models of Arctic C cycling do not include Fe cycling or pH interactions. Here, a geochemical reaction model was developed by coupling Fe redox reactions and C cycling to simulate SOM decomposition, Fe(III) reduction, pH dynamics, and greenhouse gas production in permafrost soils subject to dynamic hydrology. In this study we parameterized the model using measured CO 2 and CH 4 fluxes as well as changes in pH, Fe(II), and dissolved organic C concentrations from oxic and anoxic incubations of permafrost soils from polygonal permafrost sites in northern Alaska, United States. In simulations of repeated oxic-anoxic cycles, Fe(III) reduction during anoxic periods enhanced CO 2 production, while the net effect of Fe(III) reduction on cumulative CH 4 fluxes depended on substrate C availability. With lower substrate availability, Fe(III) reduction decreased total CH 4 production by further limiting available substrate. With higher substrate availability, Fe(III) reduction enhanced CH 4 production by increasing pH. Our results suggest that interactions among Fe-redox reactions, pH and methanogenesis are important factors in predicting CH 4 and CO 2 production as well as SOM decomposition rates in Fe-rich, frequently waterlogged Arctic soils.

54 ENVIRONMENTAL SCIENCES↗

Pseudo-dynamic Aspen Plus{sup R} Model of the Defense Waste Processing Facility - 18475

The Defense Waste Processing Facility (DWPF) at the Savannah River Site converts legacy high-level waste from the Cold War into borosilicate glass for permanent disposal in a geological repository. The waste sludge is chemically adjusted by the addition of acid, mixed with frit, and concentrated in the DWPF Chemical Process Cell (CPC) to ensure that the final glass has the desired properties. The resulting mixture is fed into the melter where the waste is melted and poured into stainless steel storage canisters. We present an Aspen Plus{sup R} model of the DWPF CPC, which is being developed to aid chemical processing decisions pertaining to the current flowsheet and to aid decisions regarding optimizing future processing. Given a waste feed composition with acid and frit additions, the model will predict the sludge and off-gas compositions throughout the processing, as well as the final melter feed composition. This allows different processing scenarios to be investigated easily, reducing the reliance on experimental testing, and hence saving time and money. The model has multiple potential applications, including calculating the acid and frit additions required to give acceptable glass properties, off-gas permitting, tracking mercury steam-stripped from the waste in the off-gas system, tracking flammable gases in the offgas system, investigating the effect of reducing air purges in the condensers, and general process optimization. The waste is processed in the CPC in batches, requiring dynamic simulation to track the time-dependent operations. Accurate modeling of the processing also requires calculations of phase and electrolyte chemical equilibria and parallel rate-dependent reactions. Due to existing technical limitations with dynamic simulation of the complex chemical system, we have adopted a pseudo-dynamic approach in which time intervals are treated as consecutive steady-state operations in Aspen Plus{sup R}. Thus, the model consists of ∼100 replicas of the processing vessel and its off-gas system, with the sludge output by one replica (representing one time interval) becoming the feed to the next (representing the next time interval). By examining the results from these replicas in sequence, one can see the time evolution of the model. This general approach can be used wherever simultaneous calculation of phase and electrolyte chemical equilibria in a dynamically evolving system is needed. In addition to describing the general structure and chemistry of the model, we present results from tests of the model against experimental data. These data are from laboratory-scale process simulations of the CPC with a nonradioactive waste sludge simulant. These tests include the model's predictions of the offgas composition, the sludge pH, and the final sludge composition. We will also discuss planned future developments of the model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Simulations of particle interactions in a high-current RFQ

High-intensity beams of composite ions are susceptible to particle interactions that do not affect single ions, such as stripping of electrons and charge exchange. Beam dynamics simulation techniques used in accelerator design do not often include these particle interactions, and so the transmission of the real beam can be significantly different from the design simulations. We have modified the IMPACT-T code to include particle interactions as part of the beam dynamics simulations, including space-charge effects and beam losses. We have carried out validation simulations of interactions in a molecular hydrogen ion beam through an existing high-intensity deuteron RFQ design, as beam commissioning is often carried out using molecular hydrogen beams, to avoid deuteron-deuteron interactions in the accelerator leading to neutron activation. The new code framework successfully models the interactions within the beam, tracks the different source and product ions through the accelerator, and calculates the collective effects such as space charge from all particles together. Finally, we also discuss other simulation codes that could be modified to include similar interaction effects, and possible applications to other types of accelerators.

47 OTHER INSTRUMENTATION↗

Simulating spin dynamics of supersolid states in a quantum Ising magnet

Motivated by a recent experimental study on the quantum Ising magnet K 2 Co(SeO 3 ) 2 that presented spectroscopic evidence of zero-field supersolidity (Chen et al., arXiv:2402.15869), we simulate the excitation spectrum of the corresponding microscopic XXZ model for the compound, using the recently developed excitation ansatz for infinite projected entangled-pair states. Here, we map out the ground state phase diagram and compute the dynamical spin structure factors across a range of magnetic field strengths, focusing especially on the two supersolid phases found near zero and saturation fields. Our simulated excitation spectra for the zero-field supersolid “Y” phase are in excellent agreement with the experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Simulation and Non-Simulation Based Human Reliability Analysis Approaches

Part of the U.S. Department of Energy’s Light Water Reactor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Characterization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk model. In this report, we review simulation-based and non-simulation-based human reliability assessment (HRA) methods. Chapter 2 surveys non-simulation-based HRA methods. Conventional HRA methods target static Probabilistic Risk Assessments for Level 1 events. These methods would require significant modification for use in dynamic simulation of Level 2 and Level 3 events. Chapter 3 is a review of human performance models. A variety of methods and models simulate dynamic human performance; however, most of these human performance models were developed outside the risk domain and have not been used for HRA. The exception is the ADS-IDAC model, which can be thought of as a virtual operator program. This model is resource-intensive but provides a detailed model of every operator action in a given scenario, along with models of numerous factors that can influence operator performance. Finally, Chapter 4 reviews the treatment of timing of operator actions in HRA methods. This chapter is an example of one of the critical gaps between existing HRA methods and the needs of dynamic HRA. This report summarizes the foundational information needed to develop a feasible approach to modeling human interactions in the RISMC simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Melting point of iron at high pressure: An assessment of uncertainties and effect of electronic temperature

An accurate calculation of the melting point of iron at various pressures in the Earth's core is important for understanding the core structure, geodynamo, and the Earth's history. Previous studies have assessed the melt line of iron at these extreme conditions using various experimental measurement techniques as well as both ab initio and classic molecular dynamics simulations. However, experimental measurements have uncertainties up to several hundred Kelvin, and inconsistencies remain among simulation results. Here in this work, we propose an iterative framework that couples density functional theory (DFT) calculations and molecular dynamics simulations performed using an ensemble of interatomic potentials to assess the effect of electronic temperature on the melting point. We systematically validate the potentials by comparing lattice constants and phonon dispersion curves at 0 K and enthalpy differences between liquid and HCP, FCC, BCC phases of iron close to the melt line at 300 GPa with DFT. Our results show that HCP iron melts at 6144 K (at 300 GPa), BCC phase is thermodynamically unstable, and FCC is metastable at this temperature. The melting points of FCC and BCC phases at 300 GPa are 5858 and 5647 K, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Intelligently Partitioned Phasor-EMT Hybrid Simulations of Large-Scale, High-IBR Power Systems

As the penetration level of power electronics-interfaced renewables such as photovoltaics (PV) and wind has surged in modern electric grids, new operational risks caused by the dynamics of those inverter-based resources (IBRs) are emerging in parallel. Lessons learned from various grid events include that the impact of IBRs on system-level grid stability will become prominent along with the increase of renewables and that the short-timescale dynamic impacts of IBRs on grid stability are not fully captured by current commercial dynamic simulation tools [1] [2]. For example, IBRs can be controlled to mitigate those destabilizing interactions, but conventional phasor-domain tools (e.g. PSS/E, PSLF) often cannot capture that; likewise, the existing electromagnetic transient (EMT) simulation tools (e.g. PSCAD, EMTP) can simulate detailed IBR controls, but for large power systems with many IBRs, slow simulation speeds severely impede the ability to study dynamic events [3] [4]. Massively paralleling simulations using high-performance computing (HPC) can help address this, especially now that cloud-based HPC capability is widely available, but today s EMT tools are not HPC-compatible, and parallelization of dynamic simulation solvers is not trivial because each region can dynamically affect the others. Thus, dynamic simulation of grids with very large numbers of IBRs potentially poses a barrier to the ongoing energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗

System dynamics and simulation of LSS

Large Space Structures have many unique problems arising from mission objectives and the resulting configuration. Inherent in these configurations is a strong coupling among several of the designing disciplines. In particular, the coupling between structural dynamics and control is a key design consideration. The solution to these interactive problems requires efficient and accurate analysis, simulation and test techniques, and properly planned and conducted design trade studies. The discussion presented deals with these subjects and concludes with a brief look at some NASA capabilities which can support these technology studies.

Ryan, R. F.↗

Multi-mode quasi-static excitation for systems with nonlinear joints

Finite element models can be used to model and predict the hysteresis and energy dissipation exhibited by nonlinear joints in structures. As a result of the nonlinearity, the frequency and damping of a mode is dependent on excitation amplitude, and when the modes remain uncoupled, quasi-static modal analysis has been shown to efficiently predict this behavior. However, in some cases the modes have been observed to couple such that the frequency and damping of one mode is dependent on the amplitude of other modes. To model the interactions between modes, one must integrate the dynamic equations in time, which is several orders of magnitude more expensive than quasi-static analysis. This work explores an alternative where quasi-static forces are applied in the shapes of two or more modes of vibration simultaneously, and the resulting load–displacement curves are used to deduce the effect of other modes on the effective frequency and damping of the mode in question. This methodology is demonstrated on a simple 2D cantilever beam structure with a single bolted joint which exhibits micro-slip nonlinearity over a range of vibration amplitudes. The predicted frequency and damping are compared with those extracted from a few expensive dynamic simulations of the structure, showing that the quasi-static approach produces reasonable albeit highly conservative bounds on the observed dynamics. This framework is also demonstrated on a 3D structure where dynamic simulations are infeasible.

42 ENGINEERING↗

A surface ice module for wind turbine dynamic response simulation using FAST

It is a fact that developing offshore wind energy has become more and more serious worldwide in recent years. Many of the promising offshore wind farm locations are in cold regions that may have ice cover during wintertime. The challenge of possible ice loads on offshore wind turbines raises the demand of modeling capacity of dynamic wind turbine response under the joint action of ice, wind, wave, and current. The simulation software FAST is an open source computer-aided engineering (CAE) package maintained by the National Renewable Energy Laboratory. In this paper, a new module of FAST for assessing the dynamic response of offshore wind turbines subjected to ice forcing is presented. In the ice module, several models are presented which involve both prescribed forcing and coupled response. For conditions in which the ice forcing is essentially decoupled from the structural response, ice forces are established from existing models for brittle and ductile ice failure. For conditions in which the ice failure and the structural response are coupled, such as lock-in conditions, a rate-dependent ice model is described, which is developed in conjunction with a new modularization framework for FAST. In this paper, analytical ice mechanics models are presented that incorporate ice floe forcing, deformation, and failure. For lower speeds, forces slowly build until the ice strength is reached and ice fails resulting in a quasi-static condition. For intermediate speeds, the ice failure can be coupled with the structural response and resulting in coinciding periods of the ice failure and the structural response. A third regime occurs at high speeds of encounter in which brittle fracturing of the ice feature occurs in a random pattern, which results in a random vibration excitation of the structure. An example wind turbine response is simulated under ice loading of each of the presented models. This module adds to FAST the capabilities for analyzing the response of wind turbines subjected to forces resulting from ice impact on the turbine support structure. The conditions considered in this module are specifically addressed in the International Organization for Standardization (ISO) standard 19906:2010 for arctic offshore structures design consideration. Special consideration of lock-in vibrations is required due to the detrimental effects of such response with regard to fatigue and foundation/soil response. Finally, the use of FAST for transient, time domain simulation with the new ice module is well suited for such analyses.

17 WIND ENERGY↗

Role of interfaces in damage process of irradiated lithium aluminate nanocrystals

Molecular dynamics simulations were performed to understand the differences in the response of single crystal and nanocrystalline ?-LiAlO2 to energy deposition by 10 keV Li recoils. The simulations are performed at 573 K and focus on the damage production in the absence of thermal annealing. The grain boundaries in the nanocrystals are found to be amorphous. Analyses of the fate of the beam ions show that the amorphous grain boundaries and differently oriented nanograins increase the number of back-scattered ions and decrease the number of transmitted ions. Damaged regions protruding from the grain boundaries provide a direct evidence of the role of the grain boundaries as scattering centers in collision cascades. The simulations show that the defect density produced in the nanocrystals is about twice that in the single crystals. In both samples, Li defects account for 70% of the defects, demonstrating that LiO4 tetrahedra is much more susceptible to damage than AlO4 tetrahedra. Furthermore, Li defects occur preferentially near grain boundaries. Diffusion simulations confirm the limited thermal diffusion of defects at 573 K, effectively separating the damage production from thermal annealing in the irradiation simulations. Nevertheless, the mean square displacements of grain boundary defects are found to be larger than lattice defects and surface defects.

lithium aluminate, interfaces, irradiation, molecu↗

Dynamics of simulated Atlantic upwelling annual cycle in CMIP5 models

As one of the prominent climatic component of tropical climate system, the annual cycle of the equatorial Atlantic cold tongue region has been a subject of significant research. In this work, we examine the fidelity of the key part of the annual cycles, namely, the upwelling annual cycles, from the simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Utilizing the simple framework we have recently developed based on the Zebiak–Cane (ZC) ocean model, we first tested the validity of the simple framework of upwelling as a combination of the local wind–driven Ekman upwelling and nonlocal wind–driven wave upwelling. It is demonstrated that the theoretically reconstructed upwelling annual cycles to large extent are in good agreement with the simulations in these coupled climatic models. Comparing with observations, we show that the semiannual component of the upwelling is systematically too strong. This significant bias is attributable to the dynamic amplification to the wind–driven wave upwelling originated from a less significant bias in the semiannual harmonic component in the central equatorial wind field. The latter is dynamically amplified in the wind–driven wave upwelling owing to its relatively fast time scale. Furthermore, the realistic simulations of equatorial annual cycles may sensitively depend on good simulations of the semiannual harmonic components in equatorial wind fields.

54 ENVIRONMENTAL SCIENCES↗

Measurement-based Power System Dynamic Model Reductions

Interconnected power systems have experienced a significant increase in its size and complexity, due to continuous topology and operating condition changes. It is computationally burdensome to represent entire system models in detail to conduct power system analysis. In the large-scale power system dynamic simulations, the models in the study area need to be retained in detail while the external area can be reduced without compromising accuracy, which can preserve the full system dynamic properties. This paper develops measurement-based continuous-time dynamic equivalents for power systems in order to both improve the model accuracy of the reduced system and increase the speed of dynamic simulation. Our method is based on a set of measurements at the boundary nodes between the study area and external area. Case studies demonstrate that the measurement-based model can capture the full system behavior sufficiently, and improve computational efficiency.Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. Therefore, the model of the study system must be retained in detail while the external system can be reduced using system reduction techniques. This paper proposes a measurement-based dynamic equivalent in order to increase both model accuracy and simulation speed. The proposed method uses a set of measurements at the boundary nodes between the study area and external area for model parameter identification. Case studies demonstrate that the measurement-based technique can capture the main system behaviors accurately and improve computational efficiency.

Xue, Yaosuo↗