Collision Computation Of Moving Bodies

In this paper, an explicit mathematical representation of n-dimensional bodies moving in translation along general trajectories is derived. This representation is used to find out if two moving bodies are going to collide. An optimization problem is developed for finding the time and location of collision. We consider the special cases of linear and piecewise linear trajectories. The collision in this case can be obtained by solving a linear program or a sequence of linear programs, respectively. The problem of finding the collision time and location of several moving bodies is cast as an integer programming problem. A comprehensive simulation study shows that this approach requires much lesser computation time when compared with the current approach of finding the collision between all pairs of bodies

Collision Computation Of Moving Bodies

In this paper, an explicit mathematical representation of n-dimensional bodies moving in translation along general trajectories is derived. This representation is used to find out if two moving bodies are going to collide. An optimization problem is developed for finding the time and location of collision. We consider the special cases of linear and piecewise linear trajectories. The collision in this case can be obtained by solving a linear program or a sequence of linear programs, respectively. The problem of finding the collision time and location of several moving bodies is cast as an integer programming problem. A comprehensive simulation study shows that this approach requires much lesser computation time when compared with the current approach of finding the collision between all pairs of bodies

An Algorithm For Computing The Distance Between Two Circular Disks

This paper presents an algorithm for computing the distance between two circular disks in three-dimensional space. A Kurush-Kuhn-Tucker (KKT) approach is used to solve the problem. We show that when the optimal points are not both at the borders of disks, the solutions of the KKT equations can be obtained in closed-form. For the case where the points are at the circumferences, the problem has no analytical solutions [IBM J. Res. Develop. 34 (5) (1990)]. Instead, we propose for the latter case an iterative algorithm based on computing the distance between a fixed point and a circle. We also show that the point-circle distance problem is solvable in closed-form, and the convergence of the numerical algorithm is linear

An Algorithm For Computing The Distance Between Two Circular Disks

This paper presents an algorithm for computing the distance between two circular disks in three-dimensional space. A Kurush-Kuhn-Tucker (KKT) approach is used to solve the problem. We show that when the optimal points are not both at the borders of disks, the solutions of the KKT equations can be obtained in closed-form. For the case where the points are at the circumferences, the problem has no analytical solutions [IBM J. Res. Develop. 34 (5) (1990)]. Instead, we propose for the latter case an iterative algorithm based on computing the distance between a fixed point and a circle. We also show that the point-circle distance problem is solvable in closed-form, and the convergence of the numerical algorithm is linear

Theoretical and Experimental Sets of Choice Anode/Cathode Architectonics for High-Performance Full-Scale LIB Built-up Models

To control the power hierarchy design of lithium-ion battery (LIB) built-up sets for electric vehicles (EVs), we offer intensive theoretical and experimental sets of choice anode/cathode architectonics that can be modulated in full-scale LIB built-up models. As primary structural tectonics, heterogeneous composite superstructures of full-cell-LIB (anode//cathode) electrodes were designed in closely packed flower agave rosettes TiO2@C (FRTO@C anode) and vertical-star-tower LiFePO4@C (VST@C cathode) building blocks to regulate the electron/ion movement in the three-dimensional axes and orientation pathways. The superpower hierarchy surfaces and multi-directional orientation components may create isosurface potential electrodes with mobile electron movements, in-to-out interplay electron dominances, and electron/charge cloud distributions. This study is the first to evaluate the hotkeys of choice anode/cathode architectonics to assemble different LIB–electrode platforms with high-mobility electron/ion flows and high-performance capacity functionalities. Density functional theory calculation revealed that the FRTO@C anode and VST-(i)@C cathode architectonics are a superior choice for the configuration of full-scale LIB built-up models. The integrated FRTO@C//VST-(i)@C full-scale LIB retains a huge discharge capacity (~ 94.2%), an average Coulombic efficiency of 99.85% after 2000 cycles at 1 C, and a high energy density of 127 Wh kg−1, thereby satisfying scale-up commercial EV requirements

Modification of bacterial cell membrane to accelerate decolorization of textile wastewater effluent using microbial fuel cells: role of gamma radiation, salinity and endogenous biosurfactant induction

A combined approach was investigated to accelerate Microbial Fuel Cell (MFC) performance and textile wastewater decolorization through modifying bacterial membrane. The aim was to increase both bacterial adhesion on anode and electron mediator release. Ten Gram-positive exoelectrogenic bacteria were isolated from the anodic biofilm after decolorization of real textile waste water in mediator-less MFC. The isolates were identified and characterized, to understand the nature of the bacteria involved. According to the battery of tests performed, three factors gamma radiation, salinity and induction of endogenous biosurfactant were involved membrane modification. Dielectric measurement, a non-invasive technique, was used to measure the cell membrane permeability and cell surface charge. Plackett-Burman experimental design was carried out to determine the key contributor among the three studied factors. Exposing the cells to 1 KGy gamma radiation led to 7.84- and 1.71- fold increase in total surface-charge and cell-permeability, respectively. Scanning Electron Microscope (SEM) images and surface-bound protein concentrations for the samples indicated that biofilm formation increased under the same conditions. These results have been reflected on the power density profiles and decolorization of textile wastewater. Modification of bacterial membrane prior to MFC operation can be considered highly effective as a pre-treatment tool that accelerates MFC performance

A mean-field kinetic lattice gas model of electrochemical cells

We develop Electrochemical Mean-Field Kinetic Equations (EMFKE) to simulate electrochemical cells. We start from a microscopic lattice-gas model with charged particles, and build mean-field kinetic equations following the lines of earlier work for neutral particles. We include the Poisson equation to account for the influence of the electric field on ion migration, and oxido-reduction processes on the electrode surfaces to allow for growth and dissolution. We confirm the viability of our approach by simulating (i) the electrochemical equilibrium at flat electrodes, which displays the correct charged double-layer, (ii) the growth kinetics of one-dimensional electrochemical cells during growth and dissolution, and (iii) electrochemical dendrites in two dimensions.Comment: 14 pages twocolumn, 17 figure

Identifying important individual‐ and country‐level predictors of conspiracy theorizing: a machine learning analysis

Psychological research on the predictors of conspiracy theorizing—explaining important social and political events or circumstances as secret plots by malevolent groups—has flourished in recent years. However, research has typically examined only a small number of predictors in one, or a small number of, national contexts. Such approaches make it difficult to examine the relative importance of predictors, and risk overlooking some potentially relevant variables altogether. To overcome this limitation, the present study used machine learning to rank-order the importance of 115 individual- and country-level variables in predicting conspiracy theorizing. Data were collected from 56,072 respondents across 28 countries during the early weeks of the COVID-19 pandemic. Echoing previous findings, important predictors at the individual level included societal discontent, paranoia, and personal struggle. Contrary to prior research, important country-level predictors included indicators of political stability and effective government COVID response, which suggests that conspiracy theorizing may thrive in relatively well-functioning democracies