Imre Felde

Computer simulation of steel quenching process using a multi-phase transformation model

A phenomenological kinetic model has been developed for the description of diffusional austenite transformations in low-alloy hypoeutectoid steels during cooling after austenitization. A fundamental property of the model consisting of coupled differential equations is that by taking into account the rate of austenite grain growth, it permits the prediction of the progress of ferrite, pearlite, upper bainite and lower bainite transformations simultaneously. To demonstrate the applicability of the model, experiments have been performed on the DIN 34 Cr 4 steel. Investigations based on computer simulation verified that the coupled multi-phase model can be applicable to predicting the CCT diagrams of low-alloy steels and calculating the microstructure and hardness distribution after quenching.

Simulation of Phase Transformations in Steel Parts Produced by Laser Powder Deposition

Multilayer laser powder deposition is being used for the rapid manufacturing of fully dense near net shape components in a wide variety of materials. In this process parts are built by overlapping consecutive layers of a laser melted material. As a result of this overlapping, the material in each layer will undergo successive thermal cycles as new layers are deposited. Despite their short duration, these thermal cycles can activate solid-state transformations that lead to progressive modification of the microstructure and properties of the material. Since the thermal history of the material in the deposited part will differ from point to point, the part will present a complex and heterogeneous microstructure, and properties that differ from point to point. Given that the microstructure and property distribution in steel parts produced by laser powder deposition can only be predicted by modelling, a three-dimensional thermo-kinetic finite element model of laser powder deposition of tool steels was developed. In the present work this model was applied to the study of the influence of substrate size on the microstructure and properties of a six-layer wall of AISI 420 tool steel. The results show that the temperature field depends significantly on the size of the substrate, leading to distinct microstructures and properties in the final part. Introduction Laser powder deposition (LPD) [1-4] is a very promising technique for the rapid manufacture of fully dense steel components. Although the advantages of this flexible manufacturing process are widely recognised [1-5], there are still some factors restraining its wide acceptance by industry. Controlling and tailoring the material properties of the final part is one such factor. These properties are significantly affected by the solid-state transformations that may occur during deposition, induced by the consecutive thermal cycles created by successive layer overlapping. The lack of detailed understanding of these transformations and of their influence on the final properties of the deposited part may lead to irreproducible results. In order to ensure that the final part possesses an appropriate microstructure, one must know the effect of the processing parameters and part build-up strategy on the thermal cycle and microstructural changes. This knowledge cannot be obtained by trial and error, due to the large number of processing parameters that must be considered. Also, the results of such an approach might not be directly applicable to all cases because the specific geometry of individual parts strongly affects the thermal field in the part and its time evolution. A more satisfactory approach relies on computer aided engineering techniques, such as finite element analysis [6-9]. This approach requires a model describing the time evolution of the thermal field in the part during the deposition process, as well as a detailed knowledge of the solid-state phase transformations that occur in laser processed steels. The latter information is available in the work of several authors [10-15] on laser processed tool steels. In particular, Colaço et. al [11] showed that, due to their fast solidification and cooling rates, laser processed tool steels may contain

A Simplified Semi-Empirical Method to Select the Processing Parameters for Laser Clad Coatings

A semi-empirical method for selecting the processing parameter s of laser cladding is proposed. This phenomenological approach uses simple mathematical formulae, derived from a statistical analysis of measured data, to relate the laser cladding parameters with the geometric features of the clad track. Given the prescribed clad height and avai lable laser beam power, the proposed method allows to calculate values of the scanning speed and powder feed rate which are required to obtain low dilution, pore free coatings, fusion bonded to the substra te. To illustrate the application of this method, variable powder feed rate laser cladding e xperiments were carried out with Stellite 6 powder on mild steel substrates. In this technique t he laser beam power and radius and the processing speed are kept constant, while the powder feed rate is varied along a single track length according to a specified linear function. The expressions derive d from the model allowed to plot the experimental data in a coherent manner, revealing the combine d role of the different processing parameters.

Prediction of as-quenched hardness after rapid austenitization and cooling of surface hardened steels

Abstract A new phenomenological model and computational method is outlined for estimating the as-quenched hardness of steel after rapid austenitization and quenching. The model is based upon the concept of a complex transformation parameter derived from a differential equation characterizing the progress of the “non-isothermal transformations”. A fundamental property of this complex transformation parameter is that it depends not only on the temperature, but also on the rate of temperature change. The applicability of this new approach is demonstrated on the basis of computer simulation and laser hardening experiments with a low alloy hypoeutectoid steel.

Solving one-dimensional IHCP with particle swarm optimization using graphics accelerators

There are several implicit and explicit formulations to solve the Inverse Heat Conduction Problem. One of the most promising methods is the Particle Swarm Optimization; however, it needs a long time to find solutions for large scale problems (large swarm populations). This paper presents the implementation and the evaluation of a parallel approach using graphics accelerators. This GPU implementation is about three times faster than the original CPU based method.

Estimation of temporospatial boundary conditions using a particle swarm optimisation technique

In this paper, we present an inverse solver for the estimation of the temporospatial heat transfer coefficients (HTCs) without using prior information of the thermal boundary conditions. The particle swarm optimisation (PSO) method has been introduced to recover the unknown HTC function obtained during immersion quenching. The HTC obtained on the surfaces of a cylindrical work piece is aimed to estimate by using cooling curves recorded internal thermocouples. The fitness function to be minimised by the PSO approach is defined by the deviation of the measured and the calculated cooling curves. The PSO algorithm has been parallelised and implemented on the graphics processing unit (GPU) architecture. The method is tested and evaluated by using hypothetical HTC function on a 2D axis symmetrical heat transfer model. The proposed approach provide significant acceleration of computation and accurate estimation.

Cost function-free optimization in inverse kinematics of open kinematic chains

The traditional ways of solving various tasks “optimally” in control technology and robotics normally are based on the minimization of some cost function (or functional). On the basis of function minimization various “generalized inverse matrices” can be introduced that have special significance in the inverse kinematic tasks of redundant manipulators, where the possible solutions are ambiguous—therefore various choices are available. The solution suggested here tackles the question of optimality by the geometric interpretation of the simple and computationally efficient Gram-Schmidt algorithm. The method is presented via simulations using a redundant arm structure.

Determination of Thermal Boundary Conditions During Immersion Quenching by Optimization Algorithms

The estimation of thermal boundary conditions occurring during heat treatment processes is an essential requirement for characterization of heat transfer phenomena. In this work, the performance of four optimization techniques is studied. These models are the conjugate gradient method, the Levenberg-Marquardt method, the simplex method, and the non-dominated sorting genetic algorithm (NSGA II) algorithm. The models are used to estimate the heat transfer coefficient in 1D and 2D axis symmetrical cases during transient heat transfer. The performance of the optimization methods is demonstrated using numerical experiments.

A Complete System for Testing and Evaluation of Quenchants and Quenching Systems

The quenching operation is a very critical part of the heat treatment process. Improper quenching parameters and drifting of the cooling characteristics during the working life of the quenchant will influence the quenching results. Sophisticated computer-based tools have made it possible to monitor, evaluate, and perform a continuous quality control of the quenchants’ and the quenching systems’ performance. The increasing and ever more sophisticated use of FEM simulation in order to optimize products and processes means that there is also a growing need for accurate input data. In quenching simulations, the boundary conditions expressed as heat transfer coefficients based on measured cooling curves are of great importance in order to obtain accurate calculations. One system that offers these features is the ivf SmartQuench® system (SQ). This system encompasses data acquisition and a software module for analyzing the cooling curves. With the new, extended software module that was introduced in 2007, SQintegra (SQi), it is now possible for the user to calculate heat transfer coefficients (e.g., for the ISO 9950 probe), as well as hardness and microstructure in a cross section of steel samples. Heat transfer calculations are made on the basis of an inverse analysis of the recorded cooling curve. The result is used as input for the calculation of microstructural constituents and the hardness profile of cylindrical samples of arbitrary diameter. Calculations can be made for several different steel grades. The system can be used for quality control of quenchants, troubleshooting, process follow-up, calculation of heat transfer coefficients, hardness calculations compared to verifying tests, and sensitivity analyses of quenchants. The system has also been used to evaluate the cooling performance in showers used for quenching after induction heating. The process window for a specific quenching shower was established for a polymer quenchant. Factors considered were flow rate, concentration and temperature of the quenchant.

Heat transfer simulation using GPUs

Several real-world applications involve simulation of the heat transfer within a given workpiece when placed into an environment with a different temperature. This requires calculation of the temperature in a particular location and at a given moment in time according to the available input parameters (shape and thermal characteristics of the given object and the environment). There are several computer-assisted numerical methods available for solving this type of problem, but these usually have a high computational demand. This paper presents a way to re-design an already known method as a data-parallel one, which makes it possible to use graphics accelerators to speed up the simulation process. According to the test results, the CUDA implementation of the parallel algorithm offers the same accuracy, but 4-5x lower runtime, as the original sequential method.