Modelling and FE Simulation of HVC Using Multi Objective Response Surface Optimization Techniques

The purpose of an automotive chassis is to maintain the shape of the vehicle and bear the various loads that are applied to the vehicle. The structure typically accounts for a large portion of the development and production costs of the new vehicle program, and the designer has many different structural concepts available. Choosing the best is important to ensure acceptable structural performance under other design constraints, such as cost, volume and method of production, product application, and more. The material selection for chassis depends upon various factors like lightness, economy, safety, recyclability, and circulation of life. The current study aims to perform optimization of the design of a heavy vehicle chassis using central composite design & optimal space fill design scheme (s) with the material tested is Al6092/SiC/17.5p MMC. Different design points are generated using design of experiments. The equivalent stress, deformation and mass are evaluated for each design points. The CAD modelling and FE simulation of heavy motor vehicle chassis is conducted using ANSYS software. From the optimization conducted on chassis design, response surface plots of equivalent stress, deformation and mass are generated which enabled to determine the range of dimensions for which these parameters are maximum or minimum. The use of Discontinuously Reinforced Aluminium-Matrix Composites Al6092/SiC/17.5p MMC aided to reduce weight of chassis by 66.25% and 66.68% by using CCD and Optimal space fill design scheme respectively, without much reduction in strength of chassis.

Numerical Modelling and Multi Objective Optimization Analysis of Heavy Vehicle Chassis

The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a heavy motor vehicle chassis using numerical and experimental methods. The CAD design and FE analysis is conducted using the ANSYS software. The design of the chassis is then optimized using Taguchi design of Experiments (DOE); the optimization techniques used are the central composite design (CCD) scheme and optimal space filling (OSF) design. Thereafter, sensitivity plots and response surface plots are generated. These plots allow us to determine the critical range of optimized chassis geometry values. The optimization results obtained from the CCD design scheme show that cross member 1 has a higher effect on the equivalent stresses as compared to cross members 2 and 3. The chassis mass reduction obtained from the CCD scheme is approximately 5.3%. The optimization results obtained from the OSF scheme shows that cross member 2 has a higher effect on equivalent stress as compared to cross members 1 and 3. The chassis mass reduction obtained from optimal space filling design scheme is approximately 4.35%.

IMPLEMENTASI DUA MODEL CROSSOVER PADA ALGORITMA GENETIKA UNTUK OPTIMASI PENGGUNAAN RUANG PERKULIAHAN

The lecture mapping process is often hampered by the number and capacity of rooms, this condition often occurs because of the many obstacles that must be fulfilled. For example, there are courses offered in one semester that cannot be slots in space and time and the lecturer can teach at the same time for different courses. This is experienced by the Informatics Engineering Study Program of the Faculty of Mathematics and Natural Sciences, Udayana University, which offers a fairly large subject in each semester, causing optimization of the lecture space to often experience problems. The Genetic Algorithm (GA) is a model in the optimization of lecture space based on the natural selection mechanism through; coding problem, generate initial population, calculate fitness value, selection, crossover, mutation and optimal population. In this research, the optimization process implements two crossover models in the genetic algorithm, namely the n-point crossover and the cycle crossover. Based on the research that has been carried out, two crossover models provide optimal space usage mapping. From testing the n-point crossover model system gives the best fitness 1 in the 361 generation with a computation time of 11.08 while the cycle crossover model produces the best fitness 1 in the 361 generation with a computation time of 15.08.

A study on stochastic maximal regularity for rough time-dependent problems

We unify and extend the semigroup and the PDE approaches to stochastic maximal regularity of time-dependent semilinear parabolic problems with noise given by a cylindrical Brownian motion. We treat random coefficients that are only progressively measurable in the time variable. For 2m-th order systems with VMO regularity in space, we obtain Lp(Lq) estimates for all p > 2 and q ≥ 2, leading to optimal space-time regularity results. For second order systems with continuous coefficients in space, we also include a first order linear term, under a stochastic parabolicity condition, and obtain Lp(Lp) estimates together with optimal space-time regularity. For linear second order equations in divergence form with random coefficients that are merely measurable in both space and time, we obtain estimates in the tent spaces Tp,2 of Coifman-Meyer-Stein. This is done in the deterministic case under no extra assumption, and in the stochastic case under the assumption that the coefficients are divergence free.

Optimal Space Trajectories with Multiple Coast Arcs Using Modified Equinoctial Elements

The detection of optimal trajectories with multiple coast arcs represents a significant and challenging problem of practical relevance in space mission analysis. Two such types of optimal paths are analyzed in this study: (a) minimum-time low-thrust trajectories with eclipse intervals and (b) minimum-fuel finite-thrust paths. Modified equinoctial elements are used to describe the orbit dynamics. Problem (a) is formulated as a multiple-arc optimization problem, and additional, specific multipoint necessary conditions for optimality are derived. These yield the jump conditions for the costate variables at the transitions from light to shadow (and vice versa). A sequential solution methodology capable of enforcing all the multipoint conditions is proposed and successfully applied in an illustrative numerical example. Unlike several preceding researches, no regularization or averaging is required to make tractable and solve the problem. Moreover, this work revisits problem (b), formulated as a single-arc optimization problem, while emphasizing the substantial analytical differences between minimum-fuel paths and problem (a). This study also proves the existence and provides the derivation of the closed-form expressions for the costate variables (associated with equinoctial elements) along optimal coast arcs.

Discovery of a weak topological insulating state and van Hove singularity in triclinic RhBi2

Time reversal symmetric (TRS) invariant topological insulators (TIs) fullfil a paradigmatic role in the field of topological materials, standing at the origin of its development. Apart from TRS protected strong TIs, it was realized early on that more confounding weak topological insulators (WTI) exist. WTIs depend on translational symmetry and exhibit topological surface states only in certain directions making it significantly more difficult to match the experimental success of strong TIs. We here report on the discovery of a WTI state in RhBi2 that belongs to the optimal space group P$$\bar{1}$$ 1 ¯ , which is the only space group where symmetry indicated eigenvalues enumerate all possible invariants due to absence of additional constraining crystalline symmetries. Our ARPES, DFT calculations, and effective model reveal topological surface states with saddle points that are located in the vicinity of a Dirac point resulting in a van Hove singularity (VHS) along the (100) direction close to the Fermi energy (EF). Due to the combination of exotic features, this material offers great potential as a material platform for novel quantum effects.