Particle Acceleration in Mildly Relativistic Outflows of Fast Energetic Transient Sources

Recent discovery of fast blue optical transients (FBOTs)—a new class of energetic transient sources—can shed light on the long-standing problem of supernova—long gamma-ray burst connections. A distinctive feature of such objects is the presence of modestly relativistic outflows which place them in between the non-relativistic and relativistic supernovae-related events. Here we present the results of kinetic particle-in-cell and Monte Carlo simulations of particle acceleration and magnetic field amplification by shocks with the velocities in the interval between 0.1 and 0.7 c. These simulations are needed for the interpretation of the observed broad band radiation of FBOTs. Their fast, mildly to moderately relativistic outflows may efficiently accelerate relativistic particles. With particle-in-cell simulations we demonstrate that synchrotron radiation of accelerated relativistic electrons in the shock downstream may fit the observed radio fluxes. At longer timescales, well beyond those reachable within a particle-in-cell approach, our nonlinear Monte Carlo model predicts that protons and nuclei can be accelerated to petaelectronvolt (PeV) energies. Therefore, such fast and energetic transient sources can contribute to galactic populations of high energy cosmic rays.

Моделирование источника ультрахолодных нейтронов на реакторе ПИК

The paper presents the simulation of a complex of reserch with ultracold neutrons at the reactor PIK (Gatchina, Russia). The complex is being built on the basis of a high-intensity source of ultracold neutrons at the channel GEK-4. A Monte Carlo model has been developed, which includes a source, a neutron guide system and an experimental setup for search for the electric dipole moment of a neutron, taking into account their real location in the main hall of the reactor. Using the developed computer model the density of ultracold neutrons in the setup was obtained, which is 200 ^-3. It is 50 times higher than at the source at the Institut Laue-Langevin (Grenoble, France). This density will allow to achieve a sensitivity of measurements in the experiment of 1·10^-27 е·cm/year.

Technical Advances in Aviation Electrification: Enhancing Strategic R&D Investment Analysis through Simulation Decomposition

Computational decision-making in “real world” environmental and sustainability contexts frequently requires the need to contrast numerous uncertain factors and difficult-to-capture dimensions. Monte Carlo simulation modelling has frequently been employed to integrate the uncertain inputs and to construct probability distributions of the resulting outputs. Visual analytics and data visualization can be used to support the processing, analyzing, and communicating of the influence of multi-variable uncertainties on the decision-making process. In this paper, the novel Simulation Decomposition (SimDec) analytical technique is used to quantitatively examine carbon emission impacts resulting from a transformation of the aviation industry toward a state of greater airline electrification. SimDec is used to decompose a Monte Carlo model of the flying range of all-electric aircraft based upon improvements to batteries and motor efficiencies. Since SimDec can be run concurrently with any Monte Carlo model with only negligible additional overhead, it can easily be extended into the analysis of any environmental application that employs simulation. This generalizability in conjunction with its straightforward visualizations of complex stochastic uncertainties makes the practical contributions of SimDec very powerful in environmental decision-making.

Temperature and Stress Dependence of Screw Dislocation Mobility in Nb-V-Ta Alloys Using Kinetic Monte Carlo Simulations

In this work we present simulations of thermally-activated screw dislocation motion in Nb-Ta-V alloys for two distinct scenarios, one where kink propagation is solely driven by chemical energy changes, i.e., thermodynamic energy differences, and another one where a migration barrier of 1.0 eV is added to such changes. The simulations have been performed using a kinetic Monte Carlo model for screw dislocation kinetics modified for complex lattice-level chemical environments. At low stresses, we find that dislocation motion in the case with no barrier is controlled by long waiting times due to slow nucleation rates and extremely fast kink propagation. Conversely, at high stress, the distribution of sampled time steps for both kink-pair nucleation and kink propagation events are comparable, resulting in continuous motion and faster velocities. In the case of the 1.0-eV kink propagation energy barrier, at low stresses kink motion becomes the rate-limiting step, leading to slow dynamics and large kink lateral pileups, while at high stresses both kink pair nucleation and kink propagation coexist on similar time scales. In the end, dislocation velocities differ by more than four orders of magnitude between both scenarios, emphasizing the need to have accurate calculations of kink energy barriers in the complex chemical environments inherent to these alloys.

Numerical Modelling of the Powder Metallurgical Manufacturing Chain of High Strength Sintered Gears

This paper presents a digital model for the powder metallurgical (PM) production chain of high-performance sintered gears based on an integrated computational materials engineering (ICME) platform. Discrete and finite element methods (DEM and FEM) were combined to describe the macroscopic material response to the thermomechanical loads and process conditions during the entire production process. The microstructural evolution during the sintering process was predicted on the meso-scale using a Monte-Carlo Model. The effective elastic properties were determined by a homogenization method based on modelling a representative volume element (RVE). The results were subsequently used for the FE modelling of the heat treatment process. Through the development of multi-scale models, it was possible obtain characteristics of the microstructural features. The predicted hardness and residual stress distributions allowed the calculation of the tooth root load bearing capacity of the heat-treated sintered gears.

Measurement of the angular distribution of wavelength-shifted light emitted by TPB

We present measurements of the angular distribution of re-emitted light from tetraphenyl butadiene thin films when exposed to 128 nm light, which is the peak of the liquid Argon (LAr) scintillation spectrum, in vacuum. Films ranging from 250 nm to 5.5 μm in thickness are measured. All films were fabricated by evaporation deposition on ultraviolet transmitting (UVT) acrylic substrates. Preliminary comparisons of the angular distribution to that produced by a detailed Monte Carlo model are also presented. The current shortcomings of the model are discussed and future plans briefly outlined.

Spatial and Temporal Modelling of Hoki Distribution using Gaussian Markov Random Fields

<p>In order to carry out assessment of marine stock levels, an accurate estimate of the current year's population abundance must be formulated. Standardized catch per unit of effort (CPUE) values are, in theory, proportional to population abundance. However, this only holds if the species catchability is constant over time. In almost all cases it is not, due to the existence of spatial and temporal variation. In this thesis, we fit various models to test different combinations and structures of spatial and temporal autocorrelation within hoki (Macruronus novaezelandiae) CPUE. A Bayesian approach was taken, and the spatial and temporal components were modelled using Gaussian Markov random fields. The data was collected from summer research trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA) and the Ministry for Primary Industries (MPI). It allowed us to model spatial distribution using both areal and point reference approaches. To fit the models, we used the software Stan (Gelman et al., 2015) which implements Hamiltonian Monte Carlo. Model comparison was carried out using the Watanabe-Akaike information criterion (WAIC, (Watanabe, 2010)). We found that trawl year was the most important factor to explain variation in research survey hoki CPUE. Furthermore, the areal approach provided better indices of abundance than the point reference approach.</p>

Spatial and Temporal Modelling of Hoki Distribution using Gaussian Markov Random Fields

<p>In order to carry out assessment of marine stock levels, an accurate estimate of the current year's population abundance must be formulated. Standardized catch per unit of effort (CPUE) values are, in theory, proportional to population abundance. However, this only holds if the species catchability is constant over time. In almost all cases it is not, due to the existence of spatial and temporal variation. In this thesis, we fit various models to test different combinations and structures of spatial and temporal autocorrelation within hoki (Macruronus novaezelandiae) CPUE. A Bayesian approach was taken, and the spatial and temporal components were modelled using Gaussian Markov random fields. The data was collected from summer research trawl surveys carried out by the National Institute of Water and Atmospheric Research (NIWA) and the Ministry for Primary Industries (MPI). It allowed us to model spatial distribution using both areal and point reference approaches. To fit the models, we used the software Stan (Gelman et al., 2015) which implements Hamiltonian Monte Carlo. Model comparison was carried out using the Watanabe-Akaike information criterion (WAIC, (Watanabe, 2010)). We found that trawl year was the most important factor to explain variation in research survey hoki CPUE. Furthermore, the areal approach provided better indices of abundance than the point reference approach.</p>