How Does Transverse MHD Wave-driven Turbulence Influence the Density Filling Factor in the Solar Corona?

It is well established that transverse MHD waves are ubiquitous in the solar corona. One of the possible mechanisms for heating both open (e.g., coronal holes) and closed (e.g., coronal loops) magnetic field regions of the solar corona is MHD wave-driven turbulence. In this work, we study the variation of the filling factor of overdense structures in the solar corona due to the generation of transverse MHD wave-driven turbulence. Using 3D MHD simulations, we estimate the density filling factor of an open magnetic structure by calculating the fraction of the volume occupied by the overdense plasma structures relative to the entire volume of the simulation domain. Next, we perform forward modeling and generate synthetic spectra of Fe xiii 10749 Å and 10800 Å density-sensitive line pairs using FoMo. Using the synthetic images, we again estimate the filling factors. The estimated filling factors obtained from both methods are in reasonable agreement. Also, our results match fairly well with the observations of filling factors in coronal holes and loops. Our results show that the generation of turbulence increases the filling factor of the solar corona.

Numerical Assessment of the Hybrid Approach for Simulating Three-Dimensional Flow and Advective Transport in Fractured Rocks

This study presents a hybrid approach for simulating flow and advective transport dynamics in fractured rocks. The developed hybrid domain (HD) model uses the two-dimensional (2D) triangular mesh for fractures and tetrahedral mesh for the three-dimensional (3D) rock matrix in a simulation domain and allows the system of equations to be solved simultaneously. This study also illustrates the HD model with two numerical cases that focus on the flow and advective transport between the fractures and rock matrix. The quantitative assessments are conducted by comparing the HD results with those obtained from the discrete fracture network (DFN) and equivalent continuum porous medium (ECPM) models. Results show that the HD model reproduces the head solutions obtained from the ECPM model in the simulation domain and heads from the DFN model in the fractures in the first case. The particle tracking results show that the mean particle velocity in the HD model can be 7.62 times higher than that obtained from the ECPM mode. In addition, the developed HD model enables detailed calculations of the fluxes at intersections between fractures and cylinder objects in the case and obtains relatively accurate flux along the intersections. The solutions are the key factors to evaluate the sources of contaminant released from the disposal facility.

Nearest Neighbors Search Using Multi-GPU

Meshless methods are increasingly gaining space in the study of electromagnetic phenomena as an alternative to traditional mesh-based methods. One of their biggest advantages is the absence of a mesh to describe the simulation domain. Instead, the domain discretization is done by spreading nodes along the domain and its boundaries. Thus, meshless methods are based on the interactions of each node with all its neighbors, and determining the neighborhood of the nodes becomes a fundamental task. The k-nearest neighbors (kNN) is a well-known algorithm used for this purpose, but it becomes a bottleneck for these methods due to its high computational cost. One of the alternatives to reduce the kNN high computational cost is to use spatial partitioning data structures (e.g., planar grid) that allow pruning when performing the k-nearest neighbors search. Furthermore, many of these strategies employed for kNN search have been adapted for graphics processing units (GPUs) and can take advantage of its high potential for parallelism. Thus, this paper proposes a multi-GPU version of the grid method for solving the kNN problem. It was possible to achieve a speedup of up to 1.99x and up to 3.94x using two and four GPUs, respectively, when compared against the single-GPU version of the grid method.

Molecular Dynamics Study of Bulk Properties of Polycrystalline NiTi

Molecular dynamics (MD) simulations were carried out to study the bulk polycrystalline properties of NiTi. Thermally driven phase transitions of NiTi between martensite and austenitewere simulated using single crystalline simulation domains. With external stress boundary conditions, MD simulation successfully predicted experimentally observed phase transformation temperatures of bulk polycrystalline. Elastic characteristics of NiTi martensite were simulated using polycrystalline simulation domains that consist of realistic disorientations and grain boundary structures. The existence of grain disorientation and grain boundary lowered the potential energy of the simulation domain, which led to more realistic elastic modulus prediction. Analysis of simulation domains that predicted realistic bulk polycrystalline properties showed that the major difference between single crystalline and polycrystalline structures is atomic stress distribution.

Inconsistency of Simulation and Practice in Delay-based Strong PUFs

The developments in the areas of strong Physical Unclonable Functions (PUFs) predicate an ongoing struggle between designers and attackers. Such a combat motivated the atmosphere of open research, hence enhancing PUF designs in the presence of Machine Learning (ML) attacks. As an example of this controversy, at CHES 2019, a novel delay-based PUF (iPUF) has been introduced and claimed to be resistant against various ML and reliability attacks. At CHES 2020, a new divide-and-conquer modeling attack (splitting iPUF) has been presented showing the vulnerability of even large iPUF variants.Such attacks and analyses are naturally examined purely in the simulation domain, where some metrics like uniformity are assumed to be ideal. This assumption is motivated by a common belief that implementation defects (such as bias) may ease the attacks. In this paper, we highlight the critical role of uniformity in the success of ML attacks, and for the first time present a case where the bias originating from implementation defects hardens certain learning problems in complex PUF architectures. We present the result of our investigations conducted on a cluster of 100 Xilinx Artix 7 FPGAs, showing the incapability of the splitting iPUF attack to model even small iPUF instances when facing a slight non-uniformity. In fact, our findings imply that non-ideal conditions due to implementation defects should also be considered when developing an attack vector on complex PUF architectures like iPUF. On the other hand, we observe a relatively low uniqueness even when following the suggestions made by the iPUF’s original authors with respect to the FPGA implementations, which indeed questions the promised physical unclonability.

Evaluation of the Nowcasting and very Short-Range Prediction System of the National Meteorological Service of Cuba

The evaluation of the Nowcasting and very short-range prediction system of the National Meteorological Service of Cuba is presented. The WRF numerical weather model is the primary tool employed in the system. The assessment is done for the relative humidity, precipitation, temperature, wind, and pressure during 2019 and for the simulation domain of highest spatial resolution (3 km). The measurements of the meteorological surface stations were used in the analysis. As result, the system has good ability to forecast the aforementioned variables, and its behavior is better in the pressure and temperature fields, while the worst results were obtained for precipitation. Although there was not much difference between the four initialization (0000, 0600, 1200, and 1800 UTC), the initialization at 1200 UTC stood out among the others because, in general, it had better performance in the forecast of the variables studied.

Accelerated Time and High-Resolution 3D Modeling of the Flow and Dispersion of Noxious Substances over a Gigantic Urban Area—The EMERGENCIES Project

Accidental or malicious releases in the atmosphere are more likely to occur in built-up areas, where flow and dispersion are complex. The EMERGENCIES project aims to demonstrate the operational feasibility of three-dimensional simulation as a support tool for emergency teams and first responders. The simulation domain covers a gigantic urban area around Paris, France, and uses high-resolution metric grids. It relies on the PMSS modeling system to model the flow and dispersion over this gigantic domain and on the Code_Saturne model to simulate both the close vicinity and the inside of several buildings of interest. The accelerated time is achieved through the parallel algorithms of the models. Calculations rely on a two-step approach: the flow is computed in advance using meteorological forecasts, and then on-demand release scenarios are performed. Results obtained with actual meteorological mesoscale data and realistic releases occurring both inside and outside of buildings are presented and discussed. They prove the feasibility of operational use by emergency teams in cases of atmospheric release of hazardous materials.

Three-dimensional magnetic reconnection in particle-in-cell simulations of anisotropic plasma turbulence

We use three-dimensional (3-D) fully kinetic particle-in-cell simulations to study the occurrence of magnetic reconnection in a simulation of decaying turbulence created by anisotropic counter-propagating low-frequency Alfvén waves consistent with critical-balance theory. We observe the formation of small-scale current-density structures such as current filaments and current sheets as well as the formation of magnetic flux ropes as part of the turbulent cascade. The large magnetic structures present in the simulation domain retain the initial anisotropy while the small-scale structures produced by the turbulent cascade are less anisotropic. To quantify the occurrence of reconnection in our simulation domain, we develop a new set of indicators based on intensity thresholds to identify reconnection events in which both ions and electrons are heated and accelerated in 3-D particle-in-cell simulations. According to the application of these indicators, we identify the occurrence of reconnection events in the simulation domain and analyse one of these events in detail. The event is related to the reconnection of two flux ropes, and the associated ion and electron exhausts exhibit a complex 3-D structure. We study the profiles of plasma and magnetic-field fluctuations recorded along artificial-spacecraft trajectories passing near and through the reconnection region. Our results suggest the presence of particle heating and acceleration related to small-scale reconnection events within magnetic flux ropes produced by the anisotropic Alfvénic turbulent cascade in the solar wind. These events are related to current structures of the order of a few ion inertial lengths in size.

Impact of Biomass Burning on Ozone, Carbon Monoxide, and Nitrogen Dioxide in Northern Thailand

The problem of smoke haze pollution in Northern Thailand affects both the environment and residents. The main sources of smoke are wildfires and open burning during the dry season, which release many pollutants, especially surface O3, impacting health and causing an air pollution crisis. The aim of this research was to study the impact of biomass burning on the surface O3, CO, and NO2 levels in Northern Thailand using the Weather Research and Forecasting Model with Chemistry (WRF-Chem). The simulation domain was configured with two domains with a grid spacing of 50 and 10 km in March 2014. To elucidate the effect of biomass burning, the model simulation was conducted for two cases: 1) a simulation with anthropogenic, biogenic, and biomass burning emissions; and 2) a simulation excluding biomass burning emissions. Owing to the model performance, the diurnal temperature and precipitation were consistent with observations, as indicated by the index of agreement (IOA) ranges of 0.74–0.76, while those of O3, CO, and NO2 were in the ranges of 0.12–0.71. The results show that biomass burning increased O3, CO, and NO2 levels by 9, 51, and 96%, respectively.

Towards an integrated study of urban CO2 emissions

<p>High-resolution monitoring is the basis for CO<sub>2</sub> emissions tracking and attribution in urban areas. This work is an important step towards an integrated urban CO<sub>2</sub> emissions monitoring system. Three middle-cost nondispersive infrared (NDIR) sensors of 500€ to 3000€ are characterised. Furthermore, CO<sub>2</sub> emissions of large, regional point sources are simulated to analyse their effect on these sensors’ signals.</p><p>The three sensors are Vaisala GMP343, Senseair HPP3 and SmartGas FlowEvo CO<sub>2</sub>. Their analysis and characterisation is achieved by co-locating them with a Picarro G2401 cavity ringdown spectrometer for 40 days. Co-locating different middle-cost sensors is novel and enables a direct performance comparison. While the HPP3 is the only one to reach a 1 min mean standard deviation under 1 ppm, the GMP343 is the most linear and stable with a drift of 0.03(2) × 10<sup>−1</sup> ppm per day and the SmartGas sensor provides the best price-to-performance ratio. For all sensors, precisions (the 1 min mean error’s lower bound) of under 0.8 ppm are determined. In general, temperature stabilisation turns out to be one of the most promising avenues of performance improvement for all sensors.</p><p>The sensors’ in-situ measurements are combined with meso-scale meteorological simulations for the Rhine-Neckar region using the Weather Research and Forecasting model (WRF). In two case-studies, simulated excess CO<sub>2</sub> due to large, regional point sources and measured CO<sub>2</sub> concentration are compared. Both simulations show qualitative agreement with the measurements. The differences between measurements and simulation, however, highlight aspects to be refined. These include increasing the horizontal and vertical resolution of the simulation domain as well improving as the parametrisation of the planetary and urban boundary layer.</p>