"Aluminum alloy cleanliness has been in the limelight during the last three decades and still remains as one of the top concerns in the aluminum casting industry. In general, cleaning an aluminum alloy refers to minimizing the following contaminants: 1) dissolved gases, especially hydrogen, 2) alkaline elements, such as sodium, lithium, and calcium, and 3) unwanted solid particles, such as oxides, carbides, and a variety of intermetallic compounds. Extensive research has resulted in significant improvements in our understanding of the various aspects of these contaminants, and in many foundries, melt-cleansing practices have been established and are routinely used. However, with the ever-increasing demands for improved casting properties, requirements for molten metal cleanliness has become extremely stringent. Rotary degassing is one of the most efficient ways of cleansing molten metals, thus removal of unwanted particles and dissolved hydrogen from molten aluminum alloys by rotary degassing has become a widely used foundry practice. Rotary degassing involves purging a gas into the molten alloy through holes in a rotating impeller. Monatomic dissolved hydrogen either diffuses into these gas bubbles or it forms diatomic hydrogen gas at the bubbles’ surface; in any case, it is removed from the melt with the rising bubbles. Simultaneously, solid particles in the melt collide with one another due to turbulence created by the impeller and form aggregates. These aggregates either settle to the furnace floor, or are captured by the rising gas bubbles and are also removed from the melt. The objective of this work is to understand the physical mechanisms underlying the removal of dissolved hydrogen and unwanted solid particles from molten aluminum alloys by the rotating impeller degasser, and to develop a methodology for the effective use of the degassing process by providing mathematical models and computer simulations of the process. The models and simulations can be used to optimize the process, design new equipment and determine the cause of specific operational problems."

"Semi-solid metal (SSM) processing has emerged as a preferred manufacturing method due to the superior quality associated with semi-solid castings. In recent years, the driving force to reduce process cost has led to the development of a few rheocasting (also termed slurry-on-demand) processes. These include UBE’s New Rheocasting (NRC) process [1], Idra Prince’s Semi-Solid Rheocasting (SSR) process [2], and THT’s Sub-Liquidus Casting (SLC®) process [3]. A novel slurry-making SSM process developed at ACRC/MPI, termed the “Continuous Rheoconversion Process” (CRP), is a passive liquid mixing technique in which the nucleation and growth of the primary phase are controlled using a specially designed “reactor”. The reactor provides heat extraction, copious nucleation and forced convection during the initial stage of solidification, leading to the formation of thixotropic structures. In these studies, the critical issues/challenges to optimize the CRP for industrial applications have been addressed through validation experiments and pre-industrial trials."

In this thesis structural optimization of castings and thermomechanical analysis of castings are studied. In paper I an optimization algorithm is created by using Matlab. The algorithm is linked to the commercial FE solver Abaqus by using Python script. The optimization algorithm uses the successive response surfaces methodology (SRSM) to create global response surfaces. It is shown that including residual stresses in structural optimization of castings yields an optimal shape that differs significantly from the one obtained when residual stresses are excluded. In paper II the optimization algorithm is expanded to using neural networks. It is tested on some typical bench mark problems and shows very promising results. Combining paper I and II the response surfaces can be either analytical functions, both linear and non-linear, or neural networks. The optimization is then performed by using sequential linear programming or by using a zero-order method called Complex. This is all gathered in a package called StuG-OPT. In paper III and IV focus is on the thermomechanical problem when residual stresses are calculated. In paper III a literature review is performed and some numerical simulations are performed to see where numerical simulations can be used in the industry today. In paper IV simulations are compared to real tests. Several stress lattices are casted and the residual stresses are measured. Simulations are performed by using Magmasoft and Abaqus. In Magmasoft a J2-plasticity model is used and in Abaqus two simulations are performed using either J2-plasticity or the ”Cast Iron Plasticity” available in Abaqus that takes into account the different behavior in tension and compression for grey cast iron. / <p>Report code: LIU-TEK-LIC-2007:34.</p>

<p>In this thesis structural optimization of castings and thermomechanical analysis of castings are studied.</p><p>In paper I an optimization algorithm is created by using Matlab. The algorithm is linked to the commercial FE solver Abaqus by using Python script. The optimization algorithm uses the successive response surfaces methodology (SRSM) to create global response surfaces. It is shown that including residual stresses in structural optimization of castings yields an optimal shape that differs significantly from the one obtained when residual stresses are excluded.</p><p>In paper II the optimization algorithm is expanded to using neural networks. It is tested on some typical bench mark problems and shows very promising results. Combining paper I and II the response surfaces can be either analytical functions, both linear and non-linear, or neural networks. The optimization is then performed by using sequential linear programming or by using a zero-order method called Complex. This is all gathered in a package called StuG-OPT.</p><p>In paper III and IV focus is on the thermomechanical problem when residual stresses are calculated. In paper III a literature review is performed and some numerical simulations are performed to see where numerical simulations can be used in the industry today. In paper IV simulations are compared to real tests. Several stress lattices are casted and the residual stresses are measured. Simulations are performed by using Magmasoft and Abaqus. In Magmasoft a J2-plasticity model is used and in Abaqus two simulations are performed using either J2-plasticity or the ”Cast Iron Plasticity” available in Abaqus that takes into account the different behavior in tension and compression for grey cast iron.</p> / Report code: LIU-TEK-LIC-2007:34.

Thesis (Ph.D.)--Mississippi State University. Department of Mechanical Engineering. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D)--University of Alabama at Birmingham, 2009. / Title from PDF t.p. (viewed June 30, 2010). Additional advisors: Viola L. Acoff, Krishan K. Chawla, Raymond J. Donahue, Gregg M. Janowski, Harry E. Littleton (ad hoc). Includes bibliographical references (p. 143-138).

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The diploma thesis deals with the production of spacious thin-walled castings of aluminum alloys with a good surface quality. During the casting process, different types of molding sands and aluminum alloys are used. The target of the diploma thesis is to evaluate the casting surface quality, to analyse the defects and to evaluate the results.

The aim of this thesis was to determine the impact of the used chemical composure during metallurgical treatment and foundry technology on the inner and surface quality of experimental casting under operational conditions at Třinec foundry. A minor part of this thesis is focused on the determination of the effect of filtration on mechanical properties of steel.

Indiana University-Purdue University Indianapolis (IUPUI) / Aluminum extrusion is a metal forming process used for the production of a large variety of solid, semi-solid and complex hollow products. During extrusion, the hot aluminum billet goes under severe plastic deformation as it is forced to flow through a smaller die cavity that defines the final shape of the extruding product. Surface finish and dimensional accuracy are the two most important criteria that specify the productivity and feasibility of the extrusion process which is highly influenced by the flow of aluminum through the deforming die. Therefore, die design is considered as one of the most important characteristics of the extrusion process that influences aluminum flow, quality of the extruding product and its dimensional accuracy. Currently, development of extrusion dies is primarily based upon the empirical knowledge of the die designer gained through trial and error, which inevitability is an expensive, time consuming and ineffective method. However, owing to the technological advancements of this century in the field of finite element modeling, this decade old trial and error method can now be replaced by numerical simulations that not only save time and money but also, can accurately predict the flow of aluminum through a die as well as predict die deformation occurring during the extrusion process The motivation of this research project came from a private extrusion die manufactures need for improving their pioneered modular die based on good analytical and scientific understanding of the dies performance during the extrusion process. In this thesis, a commercial simulation package Deform 3D is used to simulate the thermo-mechanical interactions of aluminum flow through the deforming modular die for the production of Micro Multi-Port (MMP) tubes.