Coordinate ascent for maximizing nondifferentiable concave functions

Cover title.Includes bibliographical references.Partially supported by the U.S. Army Research Office (Center for Intelligent Control Systems) DAAL03-86-K-0171 Partially supported by the National Science Foundation. NSF-ECS-8519058by Paul Tseng

Applications of a splitting algorithm to decomposition in convex programming and variational inequalities

Cover title.Includes bibliographical references.Partially supported by the U.S. Army Research Office (Center for Intelligent Control Systems) DAAL03-86-K-0171 Partially supported by the National Science Foundation. NSF-ECS-8519058by Paul Tseng

Design, simulation and optimization of conformal cooling channels in injection molds: a review

The manufacturing of conformal cooling channels (CCC’s) is now easier and more affordable, owing to the recent developments in the field of additive manufacturing. The use of CCC’s allows better cooling performances than the conventional (straight-drilled) channels, in the injection molding process. The main reason is that CCC’s can follow the pathways of the molded geometry, while the conventional channels, manufactured by traditional machining techniques, are not able to do so. Some of the parameters that can be significantly improved by the use of CCC are cooling time, total injection time, uniform temperature distribution, thermal stress, warpage thickness. However, the design process for CCC is more complex than for conventional channels. Computer-aided engineering (CAE) simulations are important for achieving effective and affordable design. This review article focuses the main aspects related to the use of CCC’s in injection molding, as follows: Sect. 1 presents an introduction, which focuses on the most important facts about the topic of this paper. Section 2 presents a comparison between straight cooling channels and conformal cooling channels. In Sect. 3, the theoretical background of injection molding is presented. In Sects. 3 to 7, the manufacturing, design, simulation and optimization of CCC’s are presented, respectively. Section 7 is about coupled approaches, in which several systems, methods or techniques are used together for better efficiency.This research was supported by the Research Grant number POCI-01-0247-FEDER-024516, co-funded by the European Regional Development Fund,by the Operational Program "Competitiveness and Internationalization”, inthe scope of “Portugal 2020

A path-following algorithm for linear programming using quadratic and logarithmic penalty functions

Cover title.Includes bibliographical references (p. 29-32).Research partially supported by the U.S. Army Research Office (Center for Intelligent Control Systems) DAAL03-86-K-0171by Paul Tseng

Research on an augmented Lagrangian penalty function algorithm for nonlinear programming

The augmented Lagrangian (ALAG) Penalty Function Algorithm for optimizing nonlinear mathematical models is discussed. The mathematical models of interest are deterministic in nature and finite dimensional optimization is assumed. A detailed review of penalty function techniques in general and the ALAG technique in particular is presented. Numerical experiments are conducted utilizing a number of nonlinear optimization problems to identify an efficient ALAG Penalty Function Technique for computer implementation

Transformation methods in nonlinear programming

Many of the results described in this thesis have been established during or as the result of collaboration and discussion with M.R. Osborne and have subsequently been published in the following joint papers Kowalik, Osborne and Ryan (1969) and Osborne and Ryan (1970a, 1970b). When discussing these results in this thesis the text of the relevant papers has been closely followed

A Framework for the Automatic Identification of Optimized Yield Surface Parameters

Advanced engineering materials are designed to display tensile-compressive asymmetry (TCA) and anisotropy to provide unique attributes to critical components necessary in the hot section of turbines. The never-ending chase for higher efficiencies, and with them, higher temperature gradients, intrinsically leads to more and more of these complex materials, like single crystal turbine blades, embedded within the turbine environment. Mathematical models, known as yield criteria, allow engineers to visualize the mechanical behavior of these materials in various orientations under complex loading. Yield criteria are dependent on three key items in determination of their governing parameters: material test data, mathematical constraints, and knowledge about the examined materials microstructure in order to predict the materials attributes (Anisotropy, Tensile-Compressive Asymmetry). The optimization of the modeling parameters governing constitutive modeling of TCA and anisotropic material has been a semi- active area of research in the last decade. As such, there is a deficit of repeatable, robust, and more efficient techniques present within the literature surrounding determination of the yield criteria parameters surrounding nickel-base superalloys. Research is proposed to derive a novel way to identify yield surface parameters. Meshing proven algorithms with a vast material database, identifying the overall best modeling parameters, and reducing the required physical testing will be of fundamental concern. The inherent reduction of lab time, and accompanied cost of experimentation, will allow the user to make use of the test data more efficiently. Implementing the constant determination approach will be facilitated by developed MATLAB code, providing an easy and centralized environment for identifying and parameterizing a repeatable yield surface representing the user uploaded anisotropic and TCA material