NEW APPROACH TO THE DESIGN OF ADVANCED WELDING MATERIALS
V. Mazurovsky1, M. Zinigrad1, L. Leontev2, and V. Lisin2
1Materials Research Center, College of Judea and Samaria, Ariel, Israel
2Institute of Metallurgy, Ural Division of the Russian Academy of Sciences, Ekaterinburg, Russia
ABSTRACT. A new approach to the design of welding and hardfacing materials is developed. The new approach is shown to be based on modeling of the physicochemical processes that occur in all stages of the formation of a welded joint and its interaction with the environment. A concise description of the development of a computer-aided design system for welding materials is given. An example of the practical implementation of the new method for designing hardfacing flux-cored wires is presented.
Introduction
Researchers have been engaged in the development of welding materials for more than 100 years, and during this entire period, questions concerning the fusion of welding materials and the formation of the weld metal have been subjected to thorough study. It was found that the physicochemical processes taking place during fusion welding determine the course of an industrial welding process and thus its result, i.e., the composition, structure, and properties of the weld deposit. Fusion welding is a complex process primarily because of the complexity of the formation of the weld pool, which is a multicomponent, multiphase system with a nonuniform temperature field and complex mass- and heat-transfer processes. The mass-transfer processes that occur on the metal–slag and metal–gas boundaries determine the chemical composition of the weld metal, and, consequently, they largely determine its mechanical properties. However, the properties of a weld, especially of a welded joint, are shaped not only by the chemical composition of the metal, but also by the crystallization processes that occur in it. The thermodynamic and kinetic characteristics of the most important chemical reactions in the liquid melt have been thoroughly investigated in numerous studies [1-5], and kinetic analysis [5, 6] has been used successfully to predict the chemical composition of the weld deposit. However, the processes that occur during the subsequent cooling and crystallization have been studied to a far smaller extent due to the complexity of their course. The needs of practical metallurgy were satisfied by the black-box approach, i.e., determination of the known state at the entrance (in the molten metal) and the result at the exit (in the solid alloy), which was attained by the tedious and costly trial-and-error method. However, as production was intensified and automated, it became necessary to develop and employ predictive methods for evaluating the physicochemical processes in the final stage of the formation of the cast metal. This was promoted to a significant degree by the use of modern computer technology. Modeling of the solid-phase transformations in a weld deposit as it crystallizes and employment of the results for predicting its composition, structure, and properties and for designing advanced welding materials were previously considered in [7-9]. These subjects are developed further below.
Designing welding and hardfacing materials
The main function of welding materials is to ensure that the weld metal has the necessary strength characteristics and service properties. They perform this function by participating in the welding process, which includes numerous different complex physicochemical processes that generally occur simultaneously. It is impossible to describe the structure, shape, composition, function, and properties of welding materials (Fig. 1) without taking into account these processes, which provide for transformation of the welding and base materials into the weld deposit. The problem of creating welding materials, which includes developing the formula of the material and the technology for manufacturing it, must be structuralized on the basis of a systematic approach. This requires an analysis of the processes that occur when the welding material and the metal being welded melt and when the weld bead and weld pool form, an analysis of the crystallization of the molten metal in the weld pool, an analysis of the interaction of the weld deposit with the environment, and an analysis of the service properties of the weld deposit and the welding material itself. The result of applying a systematic approach and structural analysis to the development of welding materials was the formulation of the main points of the new approach. This approach can be described as a logical sequence of interrelated steps for designing new welding materials:
§ analysis of the environment, the workpiece, and the loading of the workpiece;
§ establishment of the nature of the environment–workpiece interaction;
§ determination of the required structure of the weld metal;
§ calculation of the primary structure and chemical composition of the weld metal;
§ determination of the electrode formula of a special welding (hardfacing) material.
A detailed analysis of these aspects of the proposed approach [9] calls for constructing corresponding models of the principal physicochemical processes that occur in all stages of the formation of a welded joint [3, 4] and its interaction with the environment. It was shown that an effective method for developing a new welding material involves solving the inverse problem of finding the formula of the material as a function of the service characteristics of the weld metal. The most important problems for the new methodology in the area of determining the electrode formula of a new welding material include devising a model of the required structure of the weld metal under service conditions and calculating the primary structure and chemical composition of the weld deposit. The chemical composition of the weld metal is determined by the initial chemical composition of the welding material and the base metal and by the nature of the physiochemical processes accompanying the interaction between the molten metal and slag.
Prediction of the chemical composition of a weld deposit is based on a kinetic analysis of the simultaneous diffusion-controlled reactions that occur between the molten metal and slag [5]. The mutual influence of the reactions and the diffusion of all the reactants in the metal and slag are also taken into account. As a result, in accordance with [6], for the current and final composition of the molten metal we have:
(1)
where Ap is the interfacial area, Vcryst is the rate of crystallization of the weld pool, is the molar mass of the i-th element, Vd and Vbm are the rates of supply of the electrode and base metals to the weld pool, and [Ei]d and [Ei]bm are the concentrations of the i-th element in the electrode and base metals (wt. %).
Fig, 1. Flow chart of a flux-cored wire.
Thus, the proposed method can be used to find the chemical composition of the molten metal in the weld pool, i.e., of the metal in a welded joint. This chemical composition is the starting point for determining the quantitative and qualitative composition of the phases of the weld deposit. The subsequent transformations of the molten metal are associated with the primary and secondary crystallization processes, i.e., the phase transformations in the multicomponent alloy. Let us use the chemical composition of the liquid molten metal in the weld pool as a starting point for examining the primary crystallization process. As we know from the theory of welding processes [10], crystallization of the weld pool proceeds under conditions that are extremely far from equilibrium in the absence of convective stirring of the metal in the “tail” of the weld pool, i.e., at the crystallization front. Therefore, the process of distributing the components between the liquid and solid phases is controlled only by diffusion. Another important factor that determines the distribution of the components is the concentration buildup occurring at the crystallization front. These factors produce crystallization-induced supercooling, which, together, with thermal supercooling, is responsible for the cyclic character of weld pool crystallization and the chemical nonuniformity of the crystallized weld metal [10-12]. At any moment during crystallization of the weld pool, the amount of the i-th component that has passed from the liquid phase into the solid phase can be defined as [10, 12]:
, (2)
where Ei(s) is the concentration of the i-th component in the solid phase at the crystallization time t, Ei0 is the initial mean concentration of the i-th component in the molten phase, Keff is the effective distribution coefficient, Lt is the distance from the crystallization starting point (the length of the crystallite at the crystallization time t), Vcryst is the crystallization rate, and is the diffusion coefficient of the i-th component in the molten phase.
After determining the concentration of the i-th component in the solid phase at the crystallization time t, we still cannot determine its distribution between the austenite and the strengthening phases that have formed at the crystallization time. In most cases, we have a single solid solution in the crystallized weld metal, that is, the austenite phase, and several phases of primary carbides. We need to know the distribution of the i-th component between the solid solution and these phases. The factors that influence carbide formation can be divided into two groups: physicochemical factors, which directly determine the nature of the carbide-formation process, and technological factors, which indirectly influence the carbide-formation process by altering the physicochemical factors parameters. In [7, 8], the principles governing carbide formation in an alloyed iron-carbon weld deposit were formulated on the basis of a detailed physicochemical analysis of the formation of primary carbides as compounds of carbon with d metals with consideration of the quantum-chemical theories of the electronic structure of d metals and primary carbides. According to these principles, the amount of carbon that is used to form the carbide of the i-th metal is proportional to the atomic radius of the metal (Ri) and is inversely proportional to the number of electrons in the d sublevel of the metal (di). We introduce the concept of the absolute carbide-forming tendency of the i-th d metal () as the ratio
. (3)
It follows from an analysis of (3) that the carbide-forming tendency increases along the series consisting of Fe, Mn, Cr, Mo, W, Nb, V, Ta, Ti, Zr, and Hf, in good agreement with the results in [13-16]. The distribution of the alloying elements and carbon between the liquid and solid phases is given by (2). Diffusionless decomposition of the supersaturated solid solution to austenite and carbide phases occurs during crystallization. The amount of carbon bound by any carbide-forming element is determined by the stoichiometry of the compound (MexCy) and can be found from the following expression:
, (4)
where x and y are stoichiometric coefficients, AC and Ai are the atomic weights of carbon and the carbide-forming element, respectively, and is the concentration of the carbide-forming element in the carbide phase. It is logical to assume that only the portion of the alloying elements and carbon that cannot be dissolved in austenite at the respective temperature is used for carbide formation:
(5)
where is the concentration of carbon that is not dissolved in austenite, is the carbon concentration given by (4) at the crystallization time, and is the solubility limit of carbon in austenite at the respective crystallization temperature at the time tk. The distribution of carbon between the carbide phases and the alloy will be proportional to the relative carbide-forming tendency of the respective transition element and its concentration in the alloy ai. It is now clear that the proportionality factor for the i-th carbide-forming element is
. (6)
Then the concentration of the i-th carbide-forming element bound in the corresponding carbide phase at the time tkt can be defined as (wt. %)
, (7)
Therefore, the concentration of the i-th carbide-forming element dissolved in austenite at the time tk equals (wt. %):
. (8)
The concentration of carbides formed at the time tk (wt. %) is the sum of the carbon concentration and the total concentration of the carbide-forming elements that have participated in carbide formation:
. (9)
In the next time interval (tk+1), the compositions of the austenite and carbide phases will be different. The calculation is repeated z times (z = trc/tkt, where trc is the cooling time, which is determined by the parameters of the thermal-straining cycle during welding and depends on the process scheme used [3, 4]). The total carbide concentration (wt. %) at the end of primary crystallization (trc) is defined as
. (10)
Then the austenite content (wt. %) is
. (11)
The mean concentrations (wt. %) of carbon and the alloying elements in the austenite phase can be found, respectively, as
; (12)
Thus, at the end of primary crystallization, we know the mean chemical composition of the austenite phase, as well as the quantitative and qualitative composition of the carbide phases in different zones of the welded joint. Secondary crystallization is accompanied by diffusion-controlled evening of the composition of the weld metal to the composition specified by expression (12) and partial coagulation of the primary carbides along their grain boundaries during cooling. When the temperature for the limiting solubility of carbon and the alloying elements in austenite is reached, the spinodal decomposition of austenite occurs, and the distribution of carbon between the carbide phases is proportional to the carbide-forming tendency of the respective transition element. In analogy to (7), we can write
. (13)
Here wj is the fraction of carbon in the j-th carbide phase relative to the total amount of carbon used to form carbides of the i-th alloying element, is the concentration of carbon in the austenite decomposition products [15], and hi is the coefficient defined by (6). Then the concentrations (wt. %) of the carbide-forming element and of the carbon dissolved in the matrix are given by the expressions
, (14)
. (15)