Carlos A. Q. Santos

Determination of transient interfacial heat transfer coefficients in chill mold castings

Abstract The present work focuses on the determination of transient mold–environment and metal–mold heat transfer coefficients during solidification. The method uses the expedient of comparing theoretical and experimental thermal profiles and can be applied both to pure metals and metallic alloys. A solidification model based on the finite difference technique has been used to provide the theoretical results. The experiments were carried out by positioning the thermocouples in both metal and mold. The comparison between experimental and theoretical results is made by an automatic search of the best fitting among theoretical and experimental cooling curves simultaneously in metal and in mold. This has permitted the evaluation of the variation of heat transfer coefficients along the solidification process in unsteady state unidirectional heat flow of Al–Cu and Sn–Pb alloys, as well as the analysis of the effects of the material and the thickness of the mold and melt superheat.

Mathematical modeling and optimization strategies (genetic algorithm and knowledge base) applied to the continuous casting of steel

Abstract The control of quality in continuous casting products cannot be achieved without a knowledge base which incorporates parameters and variables of influence such as: equipment characteristics, steel, each component of the system and operational conditions. This work presents the development of a computational algorithm (software) applied to maximize the quality of steel billets produced by continuous casting. A mathematical model of solidification works integrated with a genetic search algorithm and a knowledge base of operational parameters. The optimization strategy selects a set of cooling conditions (mold and secondary cooling) and metallurgical criteria in order to attain highest product quality, which is related to a homogeneous thermal behavior during solidification. The results of simulations performed using the mathematical model are validated against both experimental and literature results and a good agreement is observed. Using the numerical model linked to a search method and the knowledge base, results can be produced for determining optimum settings of casting conditions, which are conducive to the best strand surface temperature profile and metallurgical length.

Human Paragonimiasis in North America following Ingestion of Raw Crayfish

Paragonimiasis (human infections with the lung fluke Paragonimus westermani) is an important public health problem in parts of Southeast Asia and China. Paragonamiasis has rarely been reported from North America as a zoonosis caused by Paragonimus kellicotti. Paragonimus species have complex life cycles that require 2 intermediate hosts, namely, snails and crustaceans (ie, crabs or crayfish). Humans acquire P. kellicotti when they consume infected raw crayfish. Humans with paragonimiasis usually present with fever and cough, which, together with the presentation of hemoptysis, can be misdiagnosed as tuberculosis. Only 7 autochthonous cases of paragonimiasis have been previously reported from North America. Our study describes 3 patients with proven or probable paragonimiasis with unusual clinical features who were seen at a single medical center during an 18-month period. These patients acquired their infections after consuming raw crayfish from rivers in Missouri. It is likely that other patients with paragonimiasis have been misdiagnosed and improperly treated. Physicians should consider the possibility that patients who present with cough, fever, hemoptysis, and eosinophilia may have paragonimiasis.

The use of artificial intelligence technique for the optimisation of process parameters used in the continuous casting of steel

Abstract The productivity and quality of a continuous caster depend mainly on process parameters, i.e. casting speed, casting temperature, steel composition and cleanliness of the melt, water flow rates in the different cooling zones, etc. This work presents the development of an algorithm, which incorporates heuristic search techniques for direct application in metallurgical industries, particularly those using continuous casting process for the production of steel billets and slabs. This is done to determine the casting objectives of maximum casting rate as a function of casting constraints. These constraints are evaluated with the aid of a heat transfer and solidification model based on the finite difference technique, which has been developed and integrated with a genetic algorithm. The essential parts of continuous casting equipment, which must be subjected to monitoring, as well as a methodology of mathematical model and physical settlements in each cooling region, are presented. The efficiency of the intelligent system is assured by the optimisation of the continuous casting operation by maximum casting rate and defect-free products. This approach is applied to the real dimension of a steel continuous caster, in real conditions of operation, demonstrating that good results can be attained by using heuristic search, such as: smaller temperature gradients between sprays zones, reduction in water consumption and an increase in casting speed.

Modeling of solidification in twin-roll strip casting

Abstract Twin-roll continuous casting combines solidification and hot rolling into a single operation to produce thin strips that are directly coilable. It offers advantages of low capital investment and low operational cost, and the strips produced have a refined solidification microstructure, which has attracted interest of global metal producers. This is evidenced by numerous pilot-scale casters constructed. The successful development of near-net-shape casting depends critically on an understanding of the fundamental knowledge of heat and fluid flow. Despite sophisticated instrumentation technology, information critical to the understanding of the casting region cannot be measured directly, therefore it is necessary to develop efficient numerical tools to control the process. This paper presents a numerical model for the two-dimensional solidification problem in the twin-roll continuous casting system by using a finite difference technique. The thermal analysis results give valuable insight into the thermal characteristics of solidification and processing for the strip casting. Results of subsequent simulations are compared with data from the literature.

Mechanical properties as a function of thermal parameters and microstructure of Zn–Al castings

Abstract The imposition of a wide range of operational conditions in foundry and casting process generates, as a direct consequence, a diversity of solidification structures. Structural parameters such as grain size and interdendritic spacings are highly influenced by thermal behavior of the metal/mould system during solidification, consequently imposing a close correlation between the described system and the resulting microstructure. The mechanical properties of an alloy depend on the solidification microstructural arrangement. Under this circumstance, grain size, interdendritic spacings, casual porosities, segregated products and other phases will define the mechanical behavior of the alloy, represented by stresses and/or strains. Expressions correlating the mechanical behavior with microstructure parameters are very useful for a previous planning of the solidification conditions in terms of a determined level of mechanical resistance which is intended to be attained, i.e. to settle a way of programming the microstructure and the mechanical properties as well. Particularly, the literature in this field presents relationships between the material yield strength and the grain size, such as the Hall–Petch’s equation. The aim of the present work is to investigate the influence of heat transfer on solidification microstructure of Zn–Al alloys and the correlation with mechanical properties. Experimental results include transient metal/mould heat transfer coefficients, secondary dendrite arm spacings and ultimate and yield strengths as a function of solidification conditions imposed by the metal/mould system.

Evaluation of heat transfer coefficients along the secondary cooling zones in the continuous casting of steel billets

In the present work, heat transfer coefficients (h) along different cooling zones of a continuous caster billet machine were determined during casting of low and medium carbon steels. The effects of casting parameters, such as machine characteristics, the ingot dimension, mold, sprays zones, radiant cooling, melt composition, and casting temperature were investigated and correlated with heat transfer coefficients. By using industrial measured billet surface temperatures, linked with a numerical solution of the solidification problem, ingot/cooling zones heat transfer coefficients were quantified based on the solution of the inverse heat conduction problem (IHCP). The experimental temperatures were compared with simulations furnished by an explicit finite difference numerical model, and an automatic search has selected the best theoretical–experimental fit from a range of values of h. The computer software algorithm has been developed to simulate temperature profiles, solid shell growth, phase transformations, and the point of complete solidification in continuous casting of steel billets and blooms. Industrial experiments were monitored with an optical infrared pyrometer to analyze the evolution of surface temperatures during solidification along the machine. The results permitted the establishment of expressions of h as a function of position along the caster, for different steel compositions, casting parameters and melt superheats.

Application of a Solidification Mathematical Model and a Genetic Algorithm in the Optimization of Strand Thermal Profile Along the Continuous Casting of Steel

ABSTRACT This work presents an optimization method based on a genetic algorithm applied to continuous casting process. A simple genetic algorithm was developed, which works linked to a mathematical model permitting the determination of optimum values for the water flow rates in the secondary cooling zones. First, experimental data (industrial) were compared with simulated results obtained by the solidification mathematical model, to determine the metal/cooling heat transfer coefficients along the machine by the inverse heat conduction problem method. The industrial data concerning surface strand temperature were obtained by using infrared pyrometers along a continuous caster machine during casting of both SAE 1007 and 1025 steels. In a second step, these results were used by a numerical code based on a genetic algorithm for determining optimum settings of water flow rates in the different sprays zones, which are conducive to the best quality of the solidified strand. The simulations were carried out by analyzing the solidification process during continuous casting to attain metallurgical restrictions concerning the reheating of strand surface temperature and metallurgical length.

Metal–mold heat transfer coefficients during horizontal and vertical Unsteady-State solidification of Al–Cu and Sn–Pb Alloys

In this work, metal–mold heat transfer coefficients (h) are determined during unidirectional solidification of Al–Cu and Sn–Pb alloys. The effects of casting assembly (horizontal and vertical), alloy composition, material and thickness of the mold and melt superheat are investigated. By using measured temperatures in both casting and metal, together with numerical solutions of the solidification problem, metal–mold heat transfer coefficients are quantified based on solution of the inverse heat conduction problem. Experimental temperatures are compared with simulations furnished by an explicit finite difference numerical model, and an automatic search selects the best theoretical–experimental fitting from a range of values of metal–mold heat transfer coefficients. Experiments were conducted to analyze the evolution of h during solidification of Al–2, 4.5, 5, 8, 10, 15, 33 wt% Cu alloys and Sn–5, 10, 15, 20, 30, 39 wt% Pb in horizontal and vertical steel chills. The results permitted the establishment of expressions as a power function of time, for different alloy compositions, casting assembly material and thickness of the mold and melt superheat.

A solidification heat transfer model and a neural network based algorithm applied to the continuous casting of steel billets and blooms

This work presents the development of a computational algorithm applied to improve the thermal behaviour in the secondary cooling zone of steel billets and blooms produced by continuous casting. A mathematical solidification heat transfer model works integrated with a neural network based algorithm (NNBA) connected to a knowledge base of boundary conditions of operational parameters and metallurgical constraints. The improved strategy selects a set of cooling conditions (in the secondary cooling zone) and metallurgical criteria established to attain high product quality, which are related to a more homogeneous thermal behaviour during solidification. Initially, the results of simulations performed by using the mathematical model are validated against experimental industrial data, and good agreement is observed, in any case examined, permitting the determination of nominal heat transfer conditions by the inverse heat conduction method. By using the numerical model linked to a NNBA results have been produced determining a set of casting conditions, which has permitted better strand surface temperature profile and metallurgical length to be attained during the continuous casting of SAE 1007 billets and SAE 1025 blooms.