A Comparative Study of Deterministic and Stochastic Models of Microstructure Evolution during Multi-Step Hot Deformation of Steels.

Modern construction materials, including steels, have to combine strength with good formability. In metallic materials, these features are obtained for heterogeneous multiphase microstructures. Design of such microstructures requires advanced numerical models. It has been shown in our earlier works that models based on stochastic internal variables meet this requirement. The focus of the present paper is on deterministic and stochastic approaches to modelling hot deformation of multiphase steels. The main aim was to survey recent advances in describing the evolution of dislocations and grain size accounting for the stochastic character of the recrystallization. To present a path leading to this objective, we reviewed several papers dedicated to the application of internal variables and statistical approaches to modelling recrystallization. Following this, the idea of the model with dislocation density and grain size being the stochastic internal variables is described. Experiments composed of hot compression of cylindrical samples are also included for better presentation of the utility of this approach. Firstly, an empirical data describing the loads as a function of time during compression and data needed to create histograms of the austenite grain size after the tests were collected. Using the measured data, identification and validation of the models were performed. To present possible applications of the model, it was used to produce a simulation imitating industrial hot-forming processes. Finally, calculations of the dislocation density and the grain size distribution were utilized as inputs in simulations of phase transformations during cooling. Distributions of the ferrite volume fraction and the ferrite grain size after cooling recapitulate the paper. This should give readers good overview on the application of collected equations in practice.

Physical and Numerical Simulations for Predicting Distribution of Microstructural Features during Thermomechanical Processing of Steels.

The design of modern construction materials with heterogeneous microstructures requires a numerical model that can predict the distribution of microstructural features instead of average values. The accuracy and reliability of such models depend on the proper identification of the coefficients for a particular material. This work was motivated by the need for advanced experimental data to identify stochastic material models. Extensive experiments were performed to supply data to identify a model of austenite microstructure evolution in steels during hot deformation and during the interpass times between deformations. Two sets of tests were performed. The first set involved hot compressions with a nominal strain of 1. The second set involved hot compressions with lower nominal strains, followed by holding at the deformation temperature for different times. Histograms of austenite grain size after each test were measured and used in the identification procedure. The stochastic model, which was developed elsewhere, was identified. Inverse analysis with the objective function based on the distance between the measured and calculated histograms was applied. Validation of the model was performed for the experiments, which were not used in the identification. The distance between the measured and calculated histograms was determined for each test using the Bhattacharyya metric and very low values were obtained. As a case study, the model with the optimal coefficients was applied to the simulation of the selected industrial hot-forming process.

Numerical Modeling of Phase Transformations in Dual-Phase Steels Using Level Set and SSRVE Approaches.

Development of a reliable model of phase transformations in steels presents significant challenges, not only metallurgical but also connected to numerical solutions and implementation. The model proposed in this paper is dedicated to austenitic transformation during heating and ferritic transformation during cooling. The goal was to find a solution which allows for the decreasing of computing time without noticeable decreasing the accuracy and reliability of the model. Proceedings to achieve this goal were twofold. Statistically Similar Representative Volume Element was used as a representation of the microstructure. It allowed for the reducing of the complexity of the computational domain. For the purpose of the model, carbon diffusion was assumed to be the main driving force for both transformations. A coupled finite element-level set method was used to describe growth of a new phase. The model was verified and validated by comparing the results with the experimental data. Numerical tests of the model were performed for the industrial intercritical annealing process.

Physical and Numerical Simulations of Closed Die Hot Forging and Heat Treatment of Forged Parts.

The paper describes physical and numerical simulations of a manufacturing process composed of hot forging and controlled cooling, which replace the conventional heat treatment technology. The objective was to investigate possibilities and limitations of the heat treatment with the use of the heat of forging. Three steels used to manufacture automotive parts were investigated. Experiments were composed of two sets of tests. The first were isothermal (TTT) and constant cooling rate (CCT) dilatometric tests, which supplied data for the identification of the numerical phase transformation model. The second was a physical simulation of the sequence forging-cooling on Gleeble 3800, which supplied data for the validation of the models. In the numerical part, a finite element (FE) thermal-mechanical code was combined with metallurgical models describing recrystallization and grain growth during forging and phase transformations during cooling. The FE model predicted distributions of the temperature and the austenite grain size in the forging, which were input data for further simulations of phase transformations during cooling. A modified JMAK equation was used to calculate the kinetics of transformation and volume fraction of microstructural constituents after cooling. Since the dilatometric tests were performed for various austenitization temperatures before cooling, it was possible to include austenite grain size as a variable in the model. An inverse algorithm developed by the authors was applied in the identification procedure. The model with optimal material parameters was used for simulations of hot forging and controlled cooling in one of the forging shops in Poland. Distributions of microstructural constituents in the forging after cooling were calculated. As a consequence, various cooling sequences during heat treatment could be analyzed and compared.

[Drug sensitivity of Enterococcus sp. strains isolated from clinical material or from healthy persons]. / Lekowrazliwosc szczepów Enterococcus sp. izolowanych z materialu klinicznego oraz od osób zdrowych.

The aim of this study was to evaluate the drug susceptibility of Enterococcus sp. strains isolated in 2000-2001, from patients of five Warsaw's hospitals (154 strains) and from fecal samples of healthy persons (33 strains). On biochemical reaction profiles species of clinical enterococci were identified as: E. faecalis--66.2%, E. faecium--29.2%, E. hirae--1.9%, E. gallinarum--1.3%, E. casseliflavus--0.6% and E. avium--0.6%. The species of enterococci from stool's samples were identified as: E. faecalis--28 strains, E. durans--2 strains and single strains: E. faecium, E. gallinarum and E. casseliflavus. Susceptibility to 20 antibiotics was tested by disc diffusion method. None of these 187 enterococcal strains was vancomycin resistant; 3 strains of E. gallinarum and 1--E. casseliflavus demonstrated intermediately susceptibility to vancomycin, but they were susceptible to teicoplanin--phenotype Van C. Among clinical strains were resistant to penicillin--33.3% of E. faecalis and 100% of E. faecium, to ampicillin--over 80% of E. faecium and 1 strain of E. faecalis. None of these strains produced beta-lactamase. High-level resistance to aminoglicoside was expressed by 48 strains (47.1%) E. faecalis and 36 (80%) E. faecium isolated from clinical specimens. Both--HLR to streptomycin and gentamycin were found in 28.3% of E. faecalis and 68.9% of E. faecium. Among 33 strains isolated from fecal samples of healthy persons--3 of E. faecalis were resistant to streptomycin and one was resistant to both gentamicin and streptomycin. In general, enterococcal strains isolated from samples of healthy persons were susceptible to the most of used antibiotics. But to rifampicin none of these strains were susceptible. There were about 40% of E. faecalis strains isolated from healthy persons, resistant to tetracyline.