A simplified mathematical study of thermochemical preparation of particle oxide under counterflow configuration for use in biomedical applications

This study mathematically presents a counterflow non-premixed thermochemical technique for preparing a particle oxide used for cancer diagnosis and treatment. For this purpose, preheating, reaction, melting, and oxidation processes were simulated considering an asymptotic concept. Mass and energy conservation equations in dimensional and non-dimensional forms were solved using MATLAB®. To preserve the continuity in the system and calculate the locations of melting and flame fronts, promising jump conditions were derived. In this research, variations in flame temperature, flame front location and mass fractions of the particle, particle oxide and oxidizer, with position, Lewis number and initial temperature of the particles were investigated. The simulation results were compared with those obtained from an earlier experimental study under the same conditions. Regarding the comparison, an appropriate compatibility was observed between the results. Based on the simulation results, flame temperature was found to be about 1310 K. Positions of flame and melting fronts were found to be − 1.8 mm and − 1.78 mm, respectively

Multiscale Discrete Simulation of Complex Systems

Complex systems exist in many aspects of nature and society and a ect our daily life signi cantly. Computational mod- eling is a powerful tool to complement theories and exper- iments for leveraging the knowledge on the fundamental mechanisms in complex systems. Discrete methods account for a large portion in the modeling of complex systems, whose advantages over traditional continuum methods are, for example, mathematical concision, easy implementation, and high parallelization. us, it is highly necessary to track the latest progress on the discrete simulation of complex systems. is special issue consists of papers on the development and application of discrete approaches in modeling of complex systems. Although the selected papers in this special issue cannot represent all aspects of the discrete simulation of complex systems, they stand at the frontier of the area and we are pleased to share these valuable papers with readers. In the paper entitled “Dynamic Modeling and Optimal Control for Complex Systems with Statistical Trajectory” L. Guo et al. proposed a novel discrete-time nonlinear working state class dynamic mathematical model through -means cluster method for sintering machines. Based on the working state class dynamic modeling, an optimal control method was developed to track trajectory for sintering machines. e proposed optimal control method for trajectory tracking was proved to be e ective. In the paper entitled “Algorithms for Routing Optimiza- tion in Multipoint to Multipoint 4PL System” J. Li et al. studied the multipoint to multipoint 4PL system routing optimization taking into account reliability constraint and objective factors. e established mathematical model for the system routing optimization was solved by the so-called messy genetic algorithm. Experimental results were used to validate the optimization algorithm. In the paper entitled “System Dynamics Simulation of Large-Scale Generation System for Designing Wind Power Policy in China” L. Hou focused on the renewable energy policy in China, especially about the wind power. A system dynamics model was built to simulate and compare the wind power generation policies and a scenario analysis was performed to compare their e ectiveness. In the paper entitled “Research on the Development Approach for Reusable Model in Parallel Discrete Event Sim- ulation” the model reuse in parallel discrete event simulation was investigated by J. Li et al. A model description which completes reusable component model framework (RCMF) was represented through their development tool—SuKit. Along with a model-customized description le with the con gured information, SuKit is able to generate a skeleton RCMF model. Case study indicates that SuKit has good capability of developing RCMF models and the well-formed description le is well suited to be used for model reuse and integration. In the paper entitled “Forecasting Beijing Transportation Hub Areas’s Pedestrian Flow Using Modular Neural Net- work” S. Wang et al. studied the issue of forecasting Beijing transportation hub areas’ pedestrian ow by a modular neural network approach. More than thirty typical sidewalks in Beijing transportation hub areas were selected to obtain about 2200 e ective data samples. A correlation analysis was conducted to analyze the relationship between pedestrian 2 Discrete Dynamics in Nature and Society ow and its in uential factors and a forecasting model was built. e forecasting modular neural network model was tested with good predictive capability. In the paper entitled “Cognitive Emotional Regulation Model in Human-Robot Interaction” X. Liu et al. investigated the human intelligence for human-robot interaction through the cognitive emotional regulation model. In their study, robot’s emotional state was controlled and determined by the cognitive energy. e model was veri ed by an emotional robot with di erent degrees of freedom and kinds of facial expressions. Veri cation indicates that robot with cognitive emotional regulation model performs more intelligently. In the paper entitled “Automation Countermeasure Sys- tem for Intersection Optimization” the method of automation countermeasure system intersection optimization was inves- tigated by H. Lu et al. based on a multiobjective programming model. e e ciency and applicability of the proposed modeling and computing methods were tested based on real- world intersection in Beijing, China. In the paper entitled “Stability Analysis and Design of a Nonlinear Controller for Hot Rolling Coiler” R. Li et al. studied the algorithm about di erential geometry design nonlinear controller. Under the rotating orthogonal coordi- nate system condition, the h nonlinear motor model was employed as the control benchmark. It was shown by the experimental results that the algorithm is suitable for highly order tracking control system with time-varying parameters

GPU-accelerated adaptive particle splitting and merging in SPH

Graphical processing unit (GPU) implementation of adaptive particle splitting and merging (APS) in the framework of smoothed particle hydrodynamics (SPH) is presented. Particle splitting and merging process are carried out based on a prescribed criterion. Multiple time stepping technology is used to reduce computational cost further. Detailed implementations on both single- and multi-GPU are discussed. A benchmark test that is a flow past fixed periodic circles is simulated to investigate the accuracy and speed of the algorithm. Comparable precision with uniformly fine simulation is achieved by APS, whereas computational demand is reduced considerably. Satisfactory speedup and acceptable scalability are obtained, demonstrating that GPU-accelerated APS is a promising tool to speed up large-scale particle-based simulations. (C) 2013 Elsevier B.V. All rights reserved

MHD enhanced nanofluid mediated heat transfer in porous metal for CPU cooling

In this study, impingement cooling of a porous metal CPU cooler saturated with nanofluid under the effects of magnetic field was modeled analytically. Darcy-Brinkman-Forchheimer model and viscous dissipation effect were considered to simulate fluid flow of nanofluid through the porous media under magnetic field. Proper similarity variables were proposed and the original partial differential governing equations were converted to nonlinear ordinary differential equations (ODEs), and the resulted ODEs were solved numerically. A system of water-alumina nanofluid flowing through a rectangular porous metal foam with top impinging jet (fan) and hot bottom wall (CPU surface) was modeled. The analytical solver was first validated against CFD and experimental data. Next, effects of different critical parameters including Darcy number (), Reynolds number (), aspect ratio (), Eckert number (), Hartmann number (), porosity (), and dimensionless distance from the axis of symmetry plane (), on fluid flow and heat transfer behaviors were investigated. Results indicate that the increase of can enhance heat transfer performance, while opposite trends are found for aspect ratio and Eckert number. However, the behavior of is more complex. At a low porosity, Nusselt number slightly decreases as increases, while an opposite behavior is observed at a high porosity. Overall, the use of a stronger magnetic field is beneficial to enhance the impingement cooling heat transfer with highly porous metal foam