Turbulence: Numerical Analysis, Modelling and Simulation

The problem of accurate and reliable simulation of turbulent flows is a central and intractable challenge that crosses disciplinary boundaries. As the needs for accuracy increase and the applications expand beyond flows where extensive data is available for calibration, the importance of a sound mathematical foundation that addresses the needs of practical computing increases. This Special Issue is directed at this crossroads of rigorous numerical analysis, the physics of turbulence and the practical needs of turbulent flow simulations. It seeks papers providing a broad understanding of the status of the problem considered and open problems that comprise further steps

Hadronization of a Quark-Gluon Plasma in the Chromodielectric Model

We have carried out simulations of the hadronization of a hot, ideal but effectively massive quark-gluon gas into color neutral clusters in the framework of the semi-classical SU(3) chromodielectric model. We have studied the possible quark-gluon compositions of clusters as well as the final mass distribution and spectra, aiming to obtain an insight into relations between hadronic spectral properties and the confinement mechanism in this model.Comment: 34 pages, 37 figure

Deep Learning to Improve the Sustainability of Agricultural Crops Affected by Phytosanitary Events: A Financial-Risk Approach

open access article.Given the challenges in reducing greenhouse gases (GHG), one of the sectors that have attracted the most attention in the Sustainable Development Agenda 2030 (SDA-2030) is the agricultural sector. In this context, one of the crops that has had the most remarkable development worldwide has been oil-palm cultivation, thanks to its high productive potential and being one of the most efficient sources of palmitic acid production. However, despite the significant presence of oil palm in the food sector, oil-palm crops have not been exempt from criticism, as its cultivation has developed mainly in areas of ecological conservation around the world. This criticism has been extended to other crops in the context of the Sustainable Development Goals (SDG) due to insecticides and fertilisers required to treat phytosanitary events in the field. To reduce this problem, researchers have used unmanned aerial vehicles (UAVs) to capture multi-spectral aerial images (MAIs) to assess fields’ plant vigour and detect phytosanitary events early using vegetation indices (VIs). However, detecting phytosanitary events in the early stages still suggests a technological challenge. Thus, to improve the environmental and financial sustainability of oil-palm crops, this paper proposes a hybrid deep-learning model (stacked–convolutional) for risk characterisation derived from a phytosanitary event, as suggested by lethal wilt (LW). For this purpose, the proposed model integrates a Lagrangian dispersion model of the backward-Gaussian-puff-tracking type into its convolutional structure, which allows describing the evolution of LW in the field for stages before a temporal reference scenario. The results show that the proposed model allowed the characterisation of the risk derived from a phytosanitary event, (PE) such as lethal wilt (LW), in the field, promoting improvement in agricultural environmental and financial sustainability activities through the integration of financial-risk concepts. This improved risk management will lead to lower projected losses due to a natural reduction in insecticides and fertilisers, allowing a balance between development and sustainability for this type of crop from the RSPO standards

Numerical Simulations of Mass Transfer in Close and Contact Binaries Using Bipolytropes

We present the first self-consistent, three dimensional study of hydrodynamic simulations of mass transfer in close and contact binary systems, with both stars represented as bipolytropes (composite polytopes). The project is motivated by the recent eruption of V1309 Scorpii which was proved to be the merger of a contact binary system. The final eruption is assumed to be the disruption of the core of the secondary inside the more massive star. The initial, equilibrium binary models are rotating synchronously in circular orbits and are obtained using the Bipolytropic Self Consistent Field (BSCF) technique, which is a modi cation of Hachisu\u27s Self Consistent Field (HSCF) method. Both stars have a fully resolved core and envelope structure where the difference in equation of state is represented by different polytropic indices and the difference in composition is represented as the ratio of the average molecular weights. The validity of the BSCF method is confirmed by constructing single, rapidly rotating stars and toroidal disks and comparing their properties with well established numerical as well as analytical results. We simulate mass transfer and mergers of bipolytropic binary systems using two fully three-dimensional grid-based Eulerian codes, Flow-ER and Octotiger, at two different resolutions. We discuss the suitability of both the codes to simulate bipolytropic stellar binaries faithfully. The simulations conducted using the Flow-ER code show certain numerical artifacts due to the limited resolving capacity of the implemented fixed cylindrical grid. We compare the results of these simulations with ones carried out using Octotiger with Adaptive Mesh Refinement (AMR) capabilities, where most of the limitations have been improved upon. The initial conditions for each simulation across the codes are chosen to match as closely as possible so that the simulations can be used as benchmarks. Although there are some key differences, the detailed comparison of the simulations suggests that there is remarkable agreement between the results obtained using the two codes. With the comparison across the resolutions, we found that both the hydrodynamic codes are convergent. This study enables us to confidently simulate mass transfer and merger scenarios of binary systems involving bipolytropic components

Dynamics of Patterns

Patterns and nonlinear waves arise in many applications. Mathematical descriptions and analyses draw from a variety of fields such as partial differential equations of various types, differential and difference equations on networks and lattices, multi-particle systems, time-delayed systems, and numerical analysis. This workshop brought together researchers from these diverse areas to bridge existing gaps and to facilitate interaction

Meshfree and Particle Methods in Biomechanics: Prospects and Challenges

The use of meshfree and particle methods in the field of bioengineering and biomechanics has significantly increased. This may be attributed to their unique abilities to overcome most of the inherent limitations of mesh-based methods in dealing with problems involving large deformation and complex geometry that are common in bioengineering and computational biomechanics in particular. This review article is intended to identify, highlight and summarize research works on topics that are of substantial interest in the field of computational biomechanics in which meshfree or particle methods have been employed for analysis, simulation or/and modeling of biological systems such as soft matters, cells, biological soft and hard tissues and organs. We also anticipate that this review will serve as a useful resource and guide to researchers who intend to extend their work into these research areas. This review article includes 333 references

大質量連星系内での重力崩壊型超新星爆発に関する数値シミュレーション

早大学位記番号:新7524早稲田大

Simulating The Impact of Emissions Control on Economic Productivity Using Particle Systems and Puff Dispersion Model

A simulation platform is developed for quantifying the change in productivity of an economy under passive and active emission control mechanisms. The program uses object-oriented programming to code a collection of objects resembling typical stakeholders in an economy. These objects include firms, markets, transportation hubs, and boids which are distributed over a 2D surface. Firms are connected using a modified Prim’s Minimum spanning tree algorithm, followed by implementation of an all-pair shortest path Floyd Warshall algorithm for navigation purposes. Firms use a non-linear production function for transformation of land, labor, and capital inputs to finished product. A GA-Vehicle Routing Problem with multiple pickups and drop-offs is implemented for efficient delivery of commodities across multiple nodes in the economy. Boids are autonomous agents which perform several functions in the economy including labor, consumption, renting, saving, and investing. Each boid is programmed with several microeconomic functions including intertemporal choice models, Hicksian and Marshallian demand function, and labor-leisure model. The simulation uses a Puff Dispersion model to simulate the advection and diffusion of emissions from point and mobile sources in the economy. A dose-response function is implemented to quantify depreciation of a Boid’s health upon contact with these emissions. The impact of emissions control on productivity and air quality is examined through a series of passive and active emission control scenarios. Passive control examines the impact of various shutdown times on economic productivity and rate of emissions exposure experienced by boids. The active control strategy examines the effects of acceptable levels of emissions exposure on economic productivity. The key findings on 7 different scenarios of passive and active emissions controls indicate that rate of productivity and consumption in an economy declines with increased scrutiny of emissions from point sources. In terms of exposure rates, the point sources may not be the primary source of average exposure rates, however they significantly impact the maximum exposure rate experienced by a boid. Tightening of emissions control also negatively impacts the transportation sector by reducing the asset utilization rate as well as reducing the total volume of goods transported across the economy