Sharif Digital Repository

We propose and analyse a nonmonotone quasi-Newton algorithm for unconstrained strongly convex multiobjective optimization. In our method, we allow for the decrease of a convex combination of recent function values. We establish the global convergence and local superlinear rate of convergence under reasonable assumptions. We implement our scheme in the context of BFGS quasi-Newton method for solving unconstrained multiobjective optimization problems. Our numerical results show that the nonmonotone quasi-Newton algorithm uses fewer function evaluations than the monotone quasi-Newton algorithm. © 2020 Informa UK Limited, trading as Taylor & Francis Group  

The purpose of this paper is to design and develop an advanced co-flow fluidic nozzle, based on the Coanda effect concept, for multi-directional thrust vectoring of small jet engines. Recent progress on finding an optimal geometry with a fixed momentum ratio to achieve maximum thrust deflection angle is discussed here. The efficiency of the system is found to be a weakly nonlinear function of the secondary to primary flow momentum as well as three geometric parameters. A useful empirical formulation is derived for thrust vectoring angle, based on a series of tests carried out on different nozzles. An accurate computational fluid dynamics model is also developed and evaluated against the... 

A non-equilibrium simplex simulated annealing algorithm is applied as a global optimization method to parameter optimization for an equation of state based on the generalized statistical associating fluid theory incorporating potentials of variable range. The parameters are determined by optimizing the calculated phase behaviour of a number of pure solvents, such as water and alcohols, and aqueous electrolyte solutions. The optimized parameters obtained via the simulated annealing algorithm are compared to those obtained using the simplex method and, for the electrolyte solutions, a gradient-based quasi-Newton method. In the case of the pure solvents, the lowest values of the objective... 

In this work, an optimum multilayer perceptron neural network is developed to model the correlation between hot working parameters (temperature, strain rate and strain) and flow stress of IN625 alloy. Three variations of standard back propagation algorithm (Broyden, Fletcher, Goldfarb and Shanno quasi-Newton, Levenberg-Marquardt and Bayesian) are applied to train the model. The results show that, in this case, the best performance, minimum error and shortest converging time are achieved by the Levenberg-Marquardt training algorithm. Comparing the predicted values and the experimental values reveals that a well trained network is capable of accurately calculating the flow stress of the alloy... 

ABS methods are a large class of algorithms for solving continuous and integer linear algebraic equations, and nonlinear continuous algebraic equations, with applications to optimization. Recent work by Chinese researchers led by Zunquan Xia has extended these methods also to stochastic, fuzzy and infinite systems, extensions not considered here. The work on ABS methods began almost thirty years. It involved an international collaboration of mathematicians especially from Hungary, England, China and Iran, coordinated by the university of Bergamo. The ABS method are based on the rank reducing matrix update due to Egerváry and can be considered as the most fruitful extension of such technique.... 

Mathematical formulation and modeling of combustion processes is an important tool in the understanding of this phenomenon. Determination of equilibrium temperature and composition is often the first stage in calculation of combustion characteristics. There are number of different techniques for simulation of combustion process. In this study a basic model has been developed based on the minimization of Gibb's free energy to simulate the combustion processes. A nonlinear mathematical optimization has been developed based on Lagrange multipliers and solved using Quasi-Newton method written in MathCAD environment. The effect of various parameters such as initial temperature, pressure, and... 

The performance of Co-flow fluidic thrust vectoring is a function of secondary flow characteristics and the fluidic nozzle geometry. In terms of nozzle geometry, wall shape and the secondary slot aspect ratio are the main parameters that control the vector angle. The present study aims to find a high quality wall shape to achieve the best thrust vectoring performance, which is characterized by the maximum thrust deflection angle with respect to the injected secondary air. A 3D computational fluid dynamics (CFD) model is employed to investigate the flow characteristics in thrust vectoring system. This model is validated using experimental data collected from the deflection of exhaust gases of...