Mayuri Baruah at the Indian Institute of Technology Guwahati for the award of the degree of Doctor of Philosophy was held under my supervision in the Department of Mechanical Engineering, Indian Institute of Technology Guwahati. In my opinion, the thesis has reached a standard that fulfills the conditions for obtaining the degree of Doctor of Philosophy in accordance with the Institute's regulations.
Abstract
A 3D finite element-based thermomechanical model has been developed to study various aspects of plasma and laser microwelding processes. The experimental research on plasma and laser microwelding in terms of mechanical properties, macro- and microstructural features of the welded joint is presented in Chapter 4. The quantitative results of the developed numerical model are mainly presented in Chapter 5.
CONTENTS
No. Title Page No
4.41 (a)Process chart for laser microwelding of Ti6Al4V butt welding configuration as a function of welding energy and speed; (b) Appearance of the weld. 177 5.21 Comparison of deflections along the longitudinal direction at. welding condition of 59.4 J/mm heat input per unit length.
List of Tables
Nomenclature
Introduction
- General Background
- Current Issues
- Research Objectives
- Layout of the thesis
Determination of the effect of welding parameters (current, welding speed, plate thickness) on residual stress and distortion. Critical evaluation of weld joint performance is assessed by micro-tensile, micro-hardness and metallographic analysis. The micro-scale butt joint with micro-welding at optimal parameters is of very high quality, without any internal defects and with a regular fusion zone. .
Literature Review
General Background
Autogenous welding process with highly concentrated energy sources, such as laser beam and electron beam, is therefore gaining increasing interest in applications on a micro scale. However, microplasma welding with a highly constricted and flexible heat source with high energy density is preferred for microwelding applications due to its low equipment costs compared to laser and electron beam welding.
Microwelding
- Laser microwelding
- Micro plasma arc welding
The tensile strength of the weld was almost the same as that of the base metal. 2011] concluded that the microstructure of stainless steel is changed due to the micro plasma arc welding process.
Weldability of Ti6Al4V Alloy
- Laser welding of Ti6Al4V alloy
- Micro plasma welding of Ti6Al4V alloy
2013] reported a study aimed at comparing the properties of the Ti6Al4V titanium alloy joints with a thickness of 0.8 mm between pulsed Nd:YAG laser welding and GTAW. 2014] performed experimental measurements of the temperature and HAZ dimensions in Nd:YAG laser welding of 3 mm thick Ti6Al4V plates.
Structures and Properties of Micro joint
- Micro structural and mechanical characterization of Ti6Al4V joints
Sanchez-Tovar et al.[2011] concluded that the microstructure of the stainless steel was modified as a result of the micro-plasma arc welding procedure. The microstructure formed in the different zones after the welding process is therefore dependent on the cooling rate as a function of the heat input. The welding technique used for the production of the Ti6Al4V makes a significant effect in the microstructure of the weld.
As a result, the fracture toughness of the weld was lower than that of the parent material.
Theoretical Model
- Heat source model
- Conduction heat transfer model
- Convective based weld pool model
- Non-Fourier heat conduction
- Laser transmission welding and gap-conduction
- Experimental investigation
The results show that the temperature profiles and weld deformation vary according to the laser beam heat source equation. A numerical investigation of laser welding of titanium alloy (Ti6Al4V) to model the temperature distribution to predict the heat affected zone (HAZ), depth and width of the staline pool was carried out by Akbari et al., 2014. The aerodynamic drag forces of the plasma jet can also contribute to the convective flow in the weld pool .
A comprehensive fluid flow model has been developed to simulate the geometric profile of laser beam welding of titanium alloys [Du et al., 2004].
Summary
It was realized that a lot of research in the field of microwelding has emerged to find an envelope of the physical parameters for successful welds. The microwelding of the common materials such as stainless steel, copper and aluminum is also tried to be established. The literature indicates that the selection of welding process, amount of heat input, cooling rate, peak temperature reached and welding process parameters have a definite effect on the shape and final structure of the weld and in turn affect the mechanical properties of the weld.
The microstructure of the final weld structure, the presence of surfactant elements in the parent materials in the formation of the weld pool shape, and the effect of fixtures in joining microparts remain to be investigated.
Scope of Present Work
To describe these microscale effects on heat transfer phenomena, the researchers proposed two temperature models and a phase shift model using a damped version of Fourier's heat transfer law. However, the heat transfer and fluid flow mode based on transport phenomena will help improve the understanding of the entire temperature field. Numerical models of heat transfer and fluid flow in fusion welding often do not provide reliable predictions because many of the input variables specifically required for modeling calculations are rarely known with confidence.
It is often necessary to consider the effect of phase shift in the heat transfer mechanism during ultrashort pulse laser processing.
Theoretical Formulation
Introduction
In addition to the process variables, the numerical model requires an additional set of parameters as input, which cannot be specified with certainty based on scientific principles alone. The most appropriate values of some of these significant uncertain input parameters are estimated by integrating the HS (Harmony Search) based global optimization algorithm with the numerical model. The integrated model minimizes the sensitivity of the error in the prediction of the weld pool dimensions obtained from some well-known welding experiments and identifies its appropriate values.
The optimized values of these parameters are then used with greater confidence for heat transfer and fluid flow calculations.
Conduction Mode Heat Transfer Analysis
- Fourier heat conduction
- Distortion and residual stress model
- Computational methods
- Non-Fourier heat conduction
- Contact conduction
The discretized form of the heat conduction equation is written as: where [H] is the heat conduction matrix, {T} is the temperature vector, [C] is the heat capacity matrix, and {P} is the heat flow vector. In contrast, Fourier's law assumes that the heat flux and temperature gradient are established instantaneously (i.e. the relaxation time is zero). The DPL model in three-dimensional form is written as. where δ is the thermal diffusivity and T represents the temperature variable.
Heat transfer between contacting interfaces in ABAQUS is defined as:. where q is the heat transfer between the respective nodes 1 and 2, h is the gap conductivity.
Three Dimensional Heat Transfer and Fluid Flow Analysis
Considering Boussnesq approximation [McLay and Carey, 1989], the body force vector in Z direction (i = 3) is expressed as. where β is the coefficient of thermal expansion, g is the gravitational acceleration and To is the reference temperature. In the frame of state mode laser welding, the heat source model is defined by. where Q refers to laser power, ref is effective radius of laser beam on the workpiece surface, d is the power density distribution factor of heat source, p is the welding depth and t is the thickness of plate. To avoid non-linearity due to the presence of the velocity components in the convective term (first term of Eq. 3.54) during solution. the momentum equations, the convective velocities are made independent of the nodal velocity variables.
The velocity and temperature can be approximated in an 8-knot element as:. where i = 1, 2, 3 and N is the interpolation function or shape function.
Optimization of Uncertain Model Parameters
The HS algorithm, which was developed to solve optimization problems, uses just as musical harmony improves each time, the solution vector improves iteration by iteration. HS contains algorithm parameters including Harmonic Memory Consideration Rate (HMCR), Pitch Adaptation Rate (PAR), Maximum Improvisation (MI) and Fret Width (FW). A new harmony vector is then generated based on three mechanisms such as memory selection. , Harmonic Memory Consideration Rate (HMCR) and Pitch Adaptation Rate (PAR). If the new harmony is better than the existing worst harmony vector, it is included in the HM and the worst harmony vector is excluded.
All sets of unknown parameters are used to calculate the weld dimensions with the help of the numerical model. Then, the numerical value of the objective function is evaluated together with the initial HM. The HM is then improvised for the randomly selected individual.
Summary
Introduction
Materials
The color of the welded sample gives an indication of the effectiveness of the inert gases to protect the solidified pool from atmospheric gases. MPAW of SS304 and low carbon steel was performed and the analysis was performed comparatively. The phase composition of the sample is evaluated by XRD by filtered CuKα radiation in the scan mode where the 2θ angle range varies from 20° to 90° with a scan step size of 0.033 s.
The standard chart is used in qualitative phase analysis using integral intensity values of diffraction lines (Fig. 4.2b).
Micro plasma arc welding
- MPAW of Titanium alloy
- MPAW of steels
This is due to the fact that the low heat input (~ 45-90 J/mm) of the plasma arc is not enough to make the lock. This is because there is a high temperature gradient in the narrow ZTV due to the low process heat input (48.7 J/mm). The ultimate tensile strength of the welded specimen was found to be comparable to the base metal (1090 MPa).
The ultimate tensile strength of the material first increases and then decreases with increased heat input.
Laser microwelding
- Macro/microstructural characteristics
- Characteristics of mechanical properties
- Distortion of laser welded structure
The shape of the pulse is rectangular (Fig.1b). The average power ( ) and peak power ( ) during welding are estimated at. 4.41 (a) Process chart for laser microwelding of Ti6Al4V butt welding configuration as a function of welding energy and speed; (b) Appearance of the weld surface. The average hardness is found to be highest in the melting zone, regardless of pulse energy and welding speed.
With further increase in heat input, the size of the weld pool increases and becomes stable with further increase in heat input.
Comparative study between microplasma and laser microwelding of Ti6Al4V alloy
Distortion analysis of welds with both processes also showed that the pattern is different. The results show that the out-of-plane deformation of the thin plate joint is much smaller in laser welding than in micro-plasma welding. However, the oxygen concentration in the final weld is much lower in the case of laser welding, as shown by EDX analysis.
Summary
The influence of laser scanning speed and pulse energy is analyzed to produce a defect-free joint. High peak power is actually damped by pulsation of laser crater to use in micro welding process. It is therefore clear that the microstructure of titanium alloy greatly affects the mechanical properties of the weld.
Experimental results show that the heat input per unit length is an important parameter for the microwelding process.
Results and Discussions
- Introduction
- Model Geometry and Material Properties
- Material Properties
- Calibration of Numerical Model
- Selection of mesh size
- Selection of time step
- Non-dimensional heat input index
- Micro plasma welding of Ti6Al4V alloy
Thermal effects due to solidification of the weld pool are modeled by including the latent heat of fusion. The thermal conductivity value decreases almost linearly up to 1073 K and then becomes almost constant. It is very important to consider the type of element, the size and thus the number of elements.
The software (ABAQUS) limits the time steps to ensure that this value is not exceeded at any node (except nodes with boundary conditions) during an increment of the analysis.
