Aeronautical Engineering: A special bibliography, supplement 60

This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1975

Integrated computational intelligent paradigm for nonlinear electric circuit models using neural networks, genetic algorithms and sequential quadratic programming

© 2019, Springer-Verlag London Ltd., part of Springer Nature. In this paper, a novel application of biologically inspired computing paradigm is presented for solving initial value problem (IVP) of electric circuits based on nonlinear RL model by exploiting the competency of accurate modeling with feed forward artificial neural network (FF-ANN), global search efficacy of genetic algorithms (GA) and rapid local search with sequential quadratic programming (SQP). The fitness function for IVP of associated nonlinear RL circuit is developed by exploiting the approximation theory in mean squared error sense using an approximate FF-ANN model. Training of the networks is conducted by integrated computational heuristic based on GA-aided with SQP, i.e., GA-SQP. The designed methodology is evaluated to variants of nonlinear RL systems based on both AC and DC excitations for number of scenarios with different voltages, resistances and inductance parameters. The comparative studies of the proposed results with Adam’s numerical solutions in terms of various performance measures verify the accuracy of the scheme. Results of statistics based on Monte-Carlo simulations validate the accuracy, convergence, stability and robustness of the designed scheme for solving problem in nonlinear circuit theory

Nonlinear Model Predictive Control for Gas Antisolvent Recrystallization Process

학위논문(석사)--서울대학교 대학원 :공과대학 화학생물공학부,2013. 2. 이종민.Crystallization techniques have been played an important role for several decades in producing various chemical products such as polymers, dyes, pharmaceuticals, and explosives. It is also essentially used in separation and purification stages of petrochemical and fine-chemical industries. Conventional crystallization processes, however, have practical problems in that toxic waste solvent streams are inevitably produced in the process and some substances are contaminated with the solvent, deteriorating the purity. In this reason, novel crystallization processes using supercritical fluids have recently attracted much attention. They are environmentally acceptable due to the use of benign solution such as CO2, applicable to various solutes, and operated at mild conditions, 25℃ and 5-100 bar. These include rapid expansion of supercritical solution (RESS), gas antisolvent (GAS) process, and particles from gas-saturated solutions (PGSS). It is well known that GAS crystallization process attains a very rapid, essentially uniform and very high supersaturation upon reduction of the solid solubility in its solution with dissolution of antisolvent CO2. This owes to the two way mass transfer of CO2 and solvent, for dissolution of CO2 and evaporation of solvent, respectively. This facilitates uniform nucleation and almost instantaneous crystallization, which make the antisolvent crystallization a unique process resulting in the formation of ultra-fine particles with a narrow particle size distribution and controlled morphology. In this work, a dynamic model for GAS process is presented and control approach to obtain a desired particle size distribution (PSD) is proposed. At first, a mathematical model from a population balance model (PBM) is developed to describe PSD of GAS process. The developed GAS model consists of a partial differential equation (PDE), a set of ordinary differential equations (ODE), and algebraic equations associated with it. Thus, it requires a numerical discretization method to solve the PDE. A high resolution (HR) scheme is presented since it is rather simple to implement and more accurate than other discretization methods. Simulation results show the effect of CO2 addition rate on the final particle size distribution in the process. Control issues in GAS processes are quite challenging since the system is highly nonlinear and includes complex crystallization kinetics, nucleation and growth. Researchers have investigated the control of liquid antisolvent crystallization process to find optimal input profile, but the control for gas antisolvnet process has not been much tried yet. It is generally more difficult to control GAS process than liquid antisolvent process since the liquid-vapor phase equilibrium should be considered in the system model. A nonlinear model predictive control (MPC) strategy is proposed to control the particle size distribution of GAS process. Linear MPC, successive linearized MPC are applied to the system and the control results are compared.Abstract i 1. Introduction 1 1.1 Crystallization process in industry 1 1.2 Crystallization mechanism 2 1.3 Crystallization techniques using supercritical fluids 5 1.3.1 Rapid expansion of supercritical solutions (RESS) 5 1.3.2 Gas antisolvent process (GAS) 7 1.3.3 Particles from gas-saturated solutions (PGSS) 9 1.4 Control issues for crystallization process 10 1.5 Outline of the thesis 13 2. Experiment 14 2.1 Materials and equipments 15 2.2 Experimental results 18 3. Modeling and Simulation for GAS process 24 3.1 Population balance model 24 3.2 Mathematical model for GAS process 27 3.3 High resolution method for solving PDE 32 3.4 Simulation results 37 4. Nonlinear Model Predictive Control for GAS Process 42 4.1 Model predictive control algorithm 44 4.2 MPC results of GAS process 49 5. Concluding Remarks 54 Bibliography 56Maste

Nonlinear Systems

The editors of this book have incorporated contributions from a diverse group of leading researchers in the field of nonlinear systems. To enrich the scope of the content, this book contains a valuable selection of works on fractional differential equations.The book aims to provide an overview of the current knowledge on nonlinear systems and some aspects of fractional calculus. The main subject areas are divided into two theoretical and applied sections. Nonlinear systems are useful for researchers in mathematics, applied mathematics, and physics, as well as graduate students who are studying these systems with reference to their theory and application. This book is also an ideal complement to the specific literature on engineering, biology, health science, and other applied science areas. The opportunity given by IntechOpen to offer this book under the open access system contributes to disseminating the field of nonlinear systems to a wide range of researchers

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

The positivity of the fractional order model of a two-dimensional temperature field

The paper presents analysis of the positivity for a two-dimensional temperature field. The process under consideration is described by the linear, infinite-dimensional, noninteger order state equation. It is derived from a two-dimensional parabolic equation with homogenous Neumann boundary conditions along all borders and homogenous initial condition. The form of control and observation operators is determined by the construction of a real system. The internal and external positivity of the model are associated to the localization of heater and measurement. It has been proven that the internal positivity of the considered system can be achieved by the proper selection of attachment of a heater and place of a measurement as well as the dimension of the finite-dimensional approximation of the considered model. Conditions of the internal positivity associated with construction of real experimental system are proposed. The postivity is analysed separately for control and output of the system. This allows one to analyse the positivity of thermal systems without explicit control. Theoretical considerations are numerically verified with the use of experimental data. The proposed results can be applied i.e. to point suitable places for measuring of a temperature using a thermal imaging camera

Proceedings of FORM 2022. Construction The Formation of Living Environment

This study examines the integration of building information modelling (BIM) technologies in operation & maintenance stage in the system of managing real estate that helps to reduce transaction costs. The approach and method are based on Digital Twin technology and Model Based System Engineering (MBSE) approach. The results of the development of a service for digital facility management and digital expertise are presented. The connection between physical and digital objects is conceptualized

An order verification method for truncated asymptotic expansion solutions to initial value problems

The focus of this paper is to obtain explicit solutions to initial value problems, where numerical methods cannot provide one, and to verify the accuracy orders of the explicit solutions. One of available methods to obtain an explicit solution is the asymptotic (formal) expansion method. However, we must be sure with the accuracy order of the explicit solution. In this paper, an order verification method is proposed for truncated asymptotic formal expansion solutions to initial value problems. A least-squares fit of error data is used in the existing order verification method. The method that we propose does not involve any application of least-squares fit of error data, so is simpler, yet produces accurate expected accuracy orders of solutions of explicit truncated asymptotic formal expansions. With our proposed method, we are successful in verifying the accuracy orders of solutions of truncated asymptotic formal expansions to the linear and nonlinear initial value problems accurately