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At least 1,063 records · Page 59

Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation

This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear strength and tensile strength are identified as independent variables for calibration purpose. Then a physics-informed iterative scheme is proposed to automatically approximate the bond parameters by viewing the micro-macro relation as an implicitly defined mathematical mapping function. As a result of highly non-convex features of this implicit mapping, the adaptive moment estimation (Adam), which is especially suitable for problems with noisy gradients, is adopted as the basic iterative scheme, in conjunction with other numerical techniques to approximately evaluate the partial derivatives involved. The whole procedure offers a simple and effective framework for bond parameter calibration. Finally, a numerical example of SiC ceramic is provided for validation. By compared with some existing calibration methods, the proposed method shows significant advantages in terms of calibration efficiency and accuracy.

42 ENGINEERING↗

Sensitivity of the Shallow‐To‐Deep Convective Transition to Moisture and Wind Shear in the Amazon

Deep convection is the primary influence on weather and climate in tropical regions. However, understanding and simulating the shallow‐to‐deep (STD) convective transition has long been challenging. Here, we conduct high‐resolution numerical simulations to assess the environmental controls on the evolution of isolated convection in the Amazon during the wet season. The large‐scale forcing derived through a constrained variational analysis approach for the GoAmazon2014/5 Experiment is used in the simulations. Through sensitivity experiments, we examine the relative importance of moisture and wind shear in controlling the shallow‐to‐deep convective transition for isolated convective events. Convection exhibits the greatest sensitivity to humidity within the lowest 1.5 km, where a 4 mm reduction in column water vapor nearly suppresses ice water formation on deep convective days. In contrast, a reduction in column water vapor in the free troposphere by a factor of two or more is necessary to produce a comparable impact on convection. Increasing low‐level wind speed from 6 to 9 m s -1 enhances afternoon deep convection, raising the cloud ice mixing ratio by approximately 25%. Conversely, upper‐level wind shear reveals the weakest correlation with daytime convection in our simulations. Our results help characterize the role of moisture and wind shear on the STD transition and our understanding of the underlying mechanisms.

environmental controls↗

Understanding the thermally activated charge transport in NaPb m SbQ m+2 (Q = S, Se, Te) thermoelectrics: weak dielectric screening leads to grain boundary dominated charge carrier scattering

Many thermoelectric materials feature irregular electrical conductivity with thermally activated transport below ~600 K and metallic behavior at high temperatures, despite possessing degenerate carrier concentrations. The suppression of the electrical conductivity ultimately degrades the thermoelectric performance on the cold side and limits the device energy conversion efficiency. As such, establishing the origin of the low temperature scattering and developing strategies to mitigate its effect are paramount issues. To date, the correct microscopic description of the low temperature carrier scattering remains an open issue, and there is little work addressing why some thermoelectric materials are more susceptible to the deleterious behavior. Here, we use the promising thermoelectric alloys of PbQ and NaSbQ 2 (Q = S, Se, Te) as model systems to address these concerns. We directly show the thermally activated transport stems from the scattering of charge carriers by the grain boundaries (GBs), and that the expected metallic electrical conductivity is recovered by preparing large grained samples with reduced densities of GBs. We furthermore study the electrical properties NaPb m SbSe m+2 as a function of NaSbSe 2 fraction, as well as those of the chalcogenide analogues, PbTe–NaSbTe 2 and PbS–NaSbS 2 , and demonstrate that the strength of GB scattering can be understood by utilizing simple chemical principles. By considering the polarizability of the host atoms, we directly relate the magnitude of GB scattering to the relative degree of charge carrier screening in each material, and demonstrate that GB scattering is strongest in the ionic NaSbQ 2 -rich compounds and weakest in more polarizable PbQ-rich phases. We finally show how these chemical arguments elegantly explain the strong GB scattering in numerous other thermoelectric materials. By uniting the deleterious charge transport properties exhibited by many different compounds into a common picture, we discuss how our work gives design principles for proper microstructure engineering in emerging thermoelectric materials.

36 MATERIALS SCIENCE↗

Drift-ordered fluid vorticity equation with energy consistency

Although drift-ordered fluid models are widely applied in tokamak edge turbulence simulations, the models used are acknowledged not to conserve energy or even electrical charge. The present paper aims to remove many of the existing pitfalls in drift-fluid models, however, with the objective of finding a solution simple enough to be implemented in numerical applications. Our main result is an improved version of the drift-Braginskii equations involving a generalized vorticity function. In the new drift-Braginskii system, the quasi-neutrality condition translates into a transport equation for a generalized vorticity, expressed in conservation form, and related to the total mass-weighted circulation. It is found that kinetic energy conservation can be achieved if the polarization flow is defined recursively. In conclusion, the resulting model conserves the kinetic energy associated with E×B and diamagnetic flows and retains the associated perpendicular kinetic energy flux.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impacts of noise and structure on quantum information encoded in a quantum memory

As larger, higher-quality quantum devices are built and demonstrated in quantum information applications, such as quantum computation and quantum communication, the need for high-quality quantum memories to store quantum states becomes ever more pressing. Future quantum devices likely will use a variety of physical hardware, some being used primarily for processing of quantum information and others for storage. Here we study the correlation of the structure of quantum information with physical noise models of various possible quantum memory implementations. Through numerical simulation of different noise models and approximate analytical formulas applied to a variety of interesting quantum states, we provide comparisons between quantum hardware with different structure, including both qubit- and qudit-based quantum memories. Our findings point to simple, experimentally relevant formulas for the relative lifetimes of quantum information in different quantum memories and have relevance to the design of hybrid quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Langevin theory for two coupled phase-conjugated electromagnetic waves

We provide a general macroscopic phenomenological formula of quantum Langevin equations for two coupled phase-conjugated electromagnetic fields with linear loss (gain) and complex nonlinear coupling coefficient. The macroscopic phenomenological formula is obtained from the coupling matrix to preserve the field commutation relations and correlations, which does not require knowing the microscopic details of light-matter interaction and internal atomic structures. To validate this phenomenological formula, we take spontaneous four-wave mixing in a double-Λ four-level atomic system as an example to numerically confirm that our macroscopic phenomenological result is consistent with that obtained from the microscopic Heisenberg-Langevin theory. We find that a complex-valued nonlinear coupling coefficient can lead to noises even without linear gain or loss. Lastly, we apply the quantum Langevin equations to study the effects of linear gain and loss, complex phase mismatching, as well as complex nonlinear coupling coefficient in entangled photon pair (biphoton) generation, particularly to their temporal quantum correlations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radar Retrieval Evaluation and Investigation of Dendritic Growth Layer Polarimetric Signatures in a Winter Storm

Abstract This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.

Meteorology & Atmospheric Sciences↗

Collaborative Research: Natural Organic Matter and Microbial Controls on Mobilization/Immobilization of I and Pu in Soils and Waters Affected by Radionuclide Releases in USA and Japan

In this project, the relationship between natural organic matter (NOM) and two radioactive elements that are relevant to nuclear waste disposal were studied: Plutonium (Pu) and Iodine. The human and environmental risks associated with Pu stem mainly from the very long half-lives of several of its isotopes ( 238 Pu, 88 yr; 239 Pu, 24,100 yr; 240 Pu, 6560 yr) and its radiotoxicity. Understanding Pu biogeochemical behavior in both near-field (>10-11M) and far-field scales (<10-11M) is imperative to the development of approaches for reprocessing Pu, remediation of Pu contamination and accurate assessment of risks posed by disposal practices for Pu-bearing wastes. The environmental mobility of Pu can be affected by redox potential, pH, adsorption, precipitation, complexation, colloid formation, and microbial activity, of which the first characteristic has the most profound influence. Numerous studies have shown high affinity of Pu towards NOM, as well as to mineral phases. NOM is ubiquitous in the environment, e.g., both fulvic and humic acids are able to reduce Pu(V,VI) to Pu(IV) and the redox potential of NOM is positively related to the abundance of phenolic/acidic OH groups. NOM can either facilitate or limit actinide migration, depending on specific biogeochemical conditions including pH, mineral and organic matter characteristics, etc. The other radionuclide of interest is radioiodine ( 129 I). 129I is a major by-product of nuclear fission and of serious concern to the Department of Energy (DOE) as it is among the top risk drivers at existing and potential radiowaste-contaminated sites. The risk of 129 I stems largely from its high bioconcentration factor (90% of the body’s iodine is accumulated in the thyroid), a high inventory at source terms, a very long-half life (16M years), and rapid mobility in the subsurface environment. As a consequence, 129 I has the lowest drinking water standard (1 pCi/L) among all radionuclides in the Federal Register. With a novel and sensitive gas chromatography-mass spectrometry (GC-MS) method developed in our lab, it is possible to quickly and simultaneously determine the distribution of 129 I and stable 127 I forms in environments, as low as 2 pCi/L for 129 I. This method was subsequently validated using accelerator mass spectroscopy, AMS. IO 3 - and organo-I were determined as major species in the groundwater of SRS and the Hanford Site, contrary to thermodynamic predictions that I- should be the dominant species at these sites. Mobility of 129 I was also demonstrated to depend greatly on the I species and its concentration, sediment pH, and redox state, with times to achieve equilibrium taking up to 12 weeks. Along the groundwater pathway in the F-Area of SRS, 129 I- supplied from the seepage basins was transformed to 129 IO 3 - and organo- 129 I with increasing iodine sediment sorption, causing the lower total 127 I and 129 I concentrations along the gradient transect of the waste plume. By contrast, groundwater 129 I concentrations in the wetlands (as high as 1617.3 pCi/L) were greatly elevated with respect to the source term (159.3 pCi/L). While the NOM promoted the uptake of 129 I to the wetland sediment, it also promoted the formation of soluble organic fraction. A small fraction of NOM that is bound to iodine can behave as a mobile organo-I source. Iodide was enzymatically incorporated into NOM, whereas both iodide and iodate were abiotically bound to NOM, under certain conditions. Iodate removal from the mobile aqueous phase can also occur through incorporation into carbonate (e.g., at the Hanford Site, USA). Thus immobilization and re-mobilization of iodine species were influenced by pH, Eh and the presence of NOM and metal oxides, which adds to the complexity of site remediation action. A ground-breaking result was to elucidate the products (i.e. organo-iodine moieties formed via enzymatic and non-enzymatic processes) at the molecular level by nuclear magnetic resonance (NMR) and electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICRMS). We found that iodine-NOM interactions may be influenced by NOM hydrophobic aliphatic moieties. From the perspective of ESI-FTICRMS, organo-iodine formulas were ascribed to the groups of unsaturated hydrocarbons, lignins and proteins. Iodate is likely abiotically reduced to reactive iodine species by lignin- and tannin-like compounds or carboxylic-rich alicyclic molecules (CRAM). We also investigated microbial mechanisms in iodine incorporation into NOM. We established that soil bacteria isolated from F-Area of SRS did not accumulate significant amounts of I- (0.2-2%). Intracellular uptake of I- decreases with increasing pH when pH ranged from 4 to 6. In contrast, 44 out of 84 strains isolated from the F-Area of SRS can transform I- to IO 3 - and organo-iodine. In some cases, oxidation was facilitated in the presence of H 2 O 2 . Microbes can also excrete organic acids that enhance I- oxidation by lowering the ambient pH and reacting with H 2 O 2 to form peroxy carboxylic acids. At lower pH values (≤5), H 2 O 2 hydrolysis was the driving force for iodide-oxidation; whereas, at pH ≥ 6, spontaneous decomposition of peroxy carboxylic acids, originating from H 2 O 2 and organic acids were the primary cause of iodide oxidation. Lastly, it was determined that microbial processes involved in Mn (II) are capable of directly oxidizing I- via enzymatic catalysis (i.e., multicopper oxidases), or indirectly through the formation of reactive oxygen species (ROS) and/or biogenic manganese oxides. ROS-mediated oxidation of I- was found to predominate at pH >5, whereas the enzymatic and Mn oxide pathways were more active at pH < 5. Together, this project has resulted in 9 publications in high-impact journals, and the training of 1 Ph.D and 4 undergraduate students.

54 ENVIRONMENTAL SCIENCES↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Idealized simulations of wind farm interactions with intermittent turbulence in stable boundary layer conditions

Stable atmospheric boundary layer conditions typically correspond to weak turbulence levels, but intermittent periods of elevated turbulence can occur during otherwise quiescent conditions. The interaction between intermittent turbulence and wind turbines is not well understood because of sparse observations, as well as the difficulty in realistically resolving small-scale turbulence during strongly stable conditions with numerical simulations. In this study, an explicit filtering and reconstruction approach for large-eddy simulation (LES) is used to simulate weakly and strongly stable conditions, with surface cooling rates of −0.2 and −2.0 K h −1 , respectively. This approach can sustain resolved background turbulence at relatively coarse grid spacing and stronger stratification compared to conventional closures, permitting more realistic intermittent stable boundary layer (SBL) turbulence. The idealized LES capability of the Weather Research and Forecasting model is employed with turbine rotors parameterized using generalized actuator disks to examine (1) how the presence of turbine wakes affects SBL evolution and (2) the effect of intermittent turbulence on power production and wake recovery. Wakes increase mixing and deepen the SBL, with a stronger effect under strongly stable conditions, primarily because the SBL is shallower and closer to the top of the wind turbine rotor layer. Intermittent turbulence does not have a significant impact on mean power generation and wake recovery because the relevant intermittent turbulent structures in this study only affect the bottom half of the rotor disk. Power production is, however, more variable during periods of elevated turbulence, demonstrating the impact of SBL intermittency. This study uses an idealized configuration, focusing on LES model performance and physical understanding, with the goal of informing future simulations of the conditions observed during the American Wake Experiment.

Energy - Wind↗

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Preparation, Properties, and Application of Lignocellulosic-Based Fluorescent Carbon Dots

We report that carbon dots (CDs) are a relatively new type of fluorescent carbon material with excellent performance and widespread application. As the most readily available and widely distributed biomass resource, lignocellulosics are a renewable bioresource with great potential. Research into the preparation of CDs with lignocellulose (LC-CDs) has become the focus of numerous researchers. Compared with other carbon sources, lignocellulose is low cost, rich in structural variety, exhibits excellent biocompatibility, and the structures of CDs prepared by lignin, cellulose, and hemicellulose are similar. This Review summarized research progress in the preparation of CDs from lignocellulosics in recent years and reviewed traditional and new preparation methods, physical and chemical properties, optical properties, and applications of LC-CDs, providing guidance for the formation and improvement of LC-CDs. In addition, the challenges of synthesizing LC-CDs were also highlighted, including the interaction of different lignocellulose components on the formation of LC-CDs and the nucleation and growth mechanism of LC-CDs; from this, current trends and opportunities of LC-CDs were examined, and some research methods for future research were put forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High‐order symmetric cubature rules for tetrahedra and pyramids

Abstract In this article, we present an algorithm to construct high‐order fully symmetric cubature rules for tetrahedral and pyramidal elements, with positive weights and integration points that are in the interior of the domain. Cubature rules are fully symmetric if they are invariant to affine transformations of the domain. We divide the integration points into symmetry orbits where each orbit contains all the points generated by the permutation stars. These relations are represented by equality constraints. The construction of symmetric cubature rules require the solution of nonlinear polynomial equations with both inequality and equality constraints. For higher orders, we use an algorithm that consists of five sequential phases to produce the cubature rules. In the literature, symmetric numerical integration rules are available for the tetrahedron for orders p = 1 – 10, 14 , and for the pyramid up to p = 10 . We have obtained fully symmetric cubature rules for both of these elements up to order p = 20 . Numerical tests are presented that verify the polynomial‐precision of the cubature rules. Convergence studies are performed for the integration of exponential, weakly singular, and trigonometric test functions over both elements with flat and curved faces. With increase in p , improvements in accuracy is realized, though nonmonotonic convergence is observed.

Jaśkowiec, Jan↗

Neutrino transport in general relativistic neutron star merger simulations

Abstract Numerical simulations of neutron star–neutron star and neutron star–black hole binaries play an important role in our ability to model gravitational-wave and electromagnetic signals powered by these systems. These simulations have to take into account a wide range of physical processes including general relativity, magnetohydrodynamics, and neutrino radiation transport. The latter is particularly important in order to understand the properties of the matter ejected by many mergers, the optical/infrared signals powered by nuclear reactions in the ejecta, and the contribution of that ejecta to astrophysical nucleosynthesis. However, accurate evolutions of the neutrino transport equations that include all relevant physical processes remain beyond our current reach. In this review, I will discuss the current state of neutrino modeling in general relativistic simulations of neutron star mergers and of their post-merger remnants. I will focus on the three main types of algorithms used in simulations so far: leakage, moments, and Monte-Carlo scheme. I will review the advantages and limitations of each scheme, as well as the various neutrino–matter interactions that should be included in simulations. We will see that the quality of the treatment of neutrinos in merger simulations has greatly increased over the last decade, but also that many potentially important interactions remain difficult to take into account in simulations (pair annihilation, oscillations, inelastic scattering).

Foucart, Francois (ORCID:0000000346174738)↗

Concentration dependent properties and plastic deformation facilitate instability of the solid-electrolyte interphase in Li-ion batteries

Lithium-ion batteries (LIBs) often suffer from capacity fading and poor cyclic performance due to mechanical degradation of the solid-electrolyte interphase (SEI). Here we perform numerical simulations and theoretical analysis to elucidate the role of plasticity in wrinkling and ratcheting behaviors of an SEI/electrode system. A coupled diffusion and finite deformation framework is formulated and numerically implemented as a user-element subroutine (UEL) to describe transient lithium diffusion and accompanying elastic–viscoplastic deformation of the electrode. It is found that concentration dependent properties and plastic deformation facilitate wrinkling in such a system. A wrinkled morphology may further lead to ratcheting and related failure under cycling. A phase diagram of four types of cyclic behaviorsis identified in terms of the charging rate and time. Our analysis suggests several potential strategies to avoid wrinkling and ratcheting instabilities, such as charging/discharging the electrode at a sufficiently slow rate, and/or introducing a thick artificial SEI with a pre-tension.

25 ENERGY STORAGE↗

Emergence of Unstable Focused Flow Induced by Variable‐Density Flows in Vertical Fractures

Abstract Fluids with different densities often coexist in subsurface fractures and lead to variable‐density flows that control subsurface processes such as seawater intrusion, contaminant transport, and geologic carbon sequestration. In nature, fractures have dip angles relative to gravity, and density effects are maximized in vertical fractures. However, most studies on flow and transport through fractures are often limited to horizontal fractures. Here, we study the mixing and transport of variable‐density fluids in vertical fractures by combining three‐dimensional (3D) pore‐scale numerical simulations and visual laboratory experiments. Two miscible fluids with different densities are injected through two inlets at the bottom of a fracture and exit from an outlet at the top of the fracture. Laboratory experiments show the emergence of an unstable focused flow path, which we term a “runlet.” We successfully reproduce the unstable runlet using 3D numerical simulations and elucidate the underlying mechanisms triggering the runlet. Dimensionless number analysis shows that the runlet instability arises due to the Rayleigh‐Taylor instability (RTI), and flow topology analysis is applied to identify 3D vortices that are caused by the RTI. Even under laminar flow regimes, fluid inertia is shown to control the runlet instability by affecting the size and movement of vortices. Finally, we confirm the emergence of a runlet in rough‐walled fractures. Since a runlet dramatically affects fluid distribution, residence time, and mixing, the findings in this study have direct implications for the management of groundwater resources and subsurface applications.

Environmental Sciences & Ecology↗

Drift waves enstrophy, zonal flow, and nonlinear evolution of the modulational instability

The interaction of the drift wave (DW) turbulence and zonal flow (ZF) is investigated with the modified Hasegawa–Mima equation taking into account the backreaction of ZF velocity on DW turbulence. It is shown that the y-averaged enstrophy of DW turbulence and the velocity of ZF are intrinsically related. By utilizing this feature, a nonlinear stage of DW modulational instability is considered within the framework of the wave kinetic equation. It is shown that in this approximation, the nonlinear stage of the modulational instability results in the collapsing solutions, accompanied by the “wave breaking” phenomenon. Numerical simulations based on the Hasegawa–Mima equation show that for a weak DW turbulence, Φ ̃ = ( e φ ̃ / T e ) ( L n / ρ s ) ⪝ 1 , the collapsing-like features on both ZF and y-averaged enstrophy of DW turbulence decay in time and then re-emerge again at different locations. For the case of a strong DW turbulence, Φ ̃ > 1 , where nonlinear interactions of DW harmonics dominate, stable spatial structures of ZF and y-averaged enstrophy of DW turbulence emerge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗