Investigation of Fluid Flow and Heat Transfer in 3D Dual-Beam Laser Keyhole Welding

Dual-beam laser welding has become an emerging joining technique. Studies have demonstrated that it can provide benefits over conventional single-beam laser welding, such as increasing keyhole stability, slowing down cooling rate and delaying the humping onset to a higher welding speed. It is also reported to be able to improve weld quality significantly. However, due to its complexity the development of this promising technique has been limited to the trial-and-error procedure. In this study, mathematical models are developed to investigate the heat transfer, melt flow, and solidification process in three-dimensional dual-beam laser keyhole welding. Effects of key parameters, such as laser-beam configuration on melt flow, weld shape, and keyhole dynamics are studied. Some experimentally observed phenomena, such as the changes of the weld pool shape from oval to circle and from circle to oval during the welding process are analyzed in current study.

Identification for Control of Low Pressure Die Casting

Controlling and eliminating defects, such as macro-porosity, in die casting processes is an on-going challenge for manufacturers. Current strategies for eliminating defects focus on the execution of a pre-set casting cycle, die structure design or the combination of both. To respond to process variability and mitigate its negative effects, advanced process control methodologies may be employed to dynamically adjust the operational parameters of the process. In this work, a finite element heat transfer model, validated by comparison with experimental data, has been developed to predict the evolution of temperatures and the volume of liquid encapsulation in an experimental casting process. A virtual process, made up of the heat transfer model and a wrapper script for communication, has been employed to simulate the continuous operation of the real process. A stochastic state-space model, based on data from measurements and the virtual process, has been developed to provide a reliable representation of this virtual process. The parameters of the deterministic portion result from system identification of the virtual process, whereas the parameters of the stochastic portion arise from the analysis and comparison of measurement data with virtual process data. The resulting state-space model, which can be extended to a multi-input multi-output model, will facilitate the design of a model-based controller for this process.

Three-Dimensional Simulation of Cross-Flow Microfilter Fouling in Tortuous Pore Profiles With Semi-Synthetic Metalworking Fluids

Fluid flow and fouling mechanisms are examined with a three-dimensional simulation of the tortuous, verisimilar geometry of an α-alumina microfilter. Reconstruction of the three-dimensional geometry was accomplished from two-dimensional cross-sectional cuts, obtained from a focused ion beam. A wall collision model and a particle trapping model are developed for the investigation of fouling mechanisms. The reconstructed geometry and the two models were used in computational fluid dynamics to simulate metalworking colloidal particles travelling through and trapping in the tortuous pore paths of a microfilter. Results reveal sharp flux decline initiating from partial pore blocking and subdued flux decline finalizing in cake layer development with steady-state flow. This flow behavior is in agreement with experimental data from earlier studies. The inclusion of the wall collision model and particle trapping model enabled the revelation of cake layer development as a fouling mechanism.

Fabrication of Al6061-CNT Composite by Mechanical Alloying Followed by Semi-Solid Powder Processing

Carbon nanotubes (CNTs) have been widely investigated as a reinforcement material to improve the mechanical, electrical and thermal properties of composite materials. Various routes have been employed to fabricate aluminum-carbon nanotube (Al-CNT) composites in the past few years. However, uniform distribution of CNTs in the metal matrix is still challenging. In this paper, a novel semi-solid powder processing (SPP) was used to incorporate CNT uniformly into the Al6061-CNT composite. Al6061-CNT powders mechanically alloyed for different durations were also examined to understand how the CNTs were dispersed in the Al6061 powders. As-received CNT cluster balls were crushed into dense thin CNT layers during mechanical alloying. As mechanical alloying time increased, CNTs were dispersed in the Al6061 particles. Well-densified microstructures with severely deformed grains were observed in the Al6061-CNT composite.

Characterization and Prediction of Texture in Laser Annealed NiTi Shape Memory Thin Films

Thin film shape memory alloys are a promising material for use in micro-scale devices for actuation and sensing due to their strong actuating force, substantial displacements, and large surface to volume ratios. NiTi, in particular, has been of great interest due to its biocompatibility and corrosion resistance. Effort has been directed toward adjusting the microstructure of as-deposited films in order to modify their shape memory properties for specific applications. The anisotropy of the shape memory and superelastic effects suggests that inducing preferred orientations could allow for optimization of shape memory properties. Limited work, however, has been performed on adjusting the crystallographic texture of these films. In this study, thin film NiTi samples are processed using excimer laser crystallization and the effect on the overall preferred orientation is analyzed through the use of electron backscatter diffraction and x-ray diffraction. A 3-dimensional Monte Carlo grain growth model is developed to characterize textures formed through surface energy induced abnormal grain growth during solidification. Furthermore, a scaling factor between Monte Carlo steps and real time is determined to aid in the prediction of texture changes during laser crystallization in the partial melting regime.

Laser Coating of HAp/Ti Nanoparticles on Metal Implants: Interfacial Bonding Strength, Chemical Analysis and Biocompatibility

In this paper, laser coating of hydroxyapatite (HAp) and Ti nanoparticles on Ti-6Al-4V implants was developed. An Nd:YAG laser was used to coat multilayers of HAp and Ti nanoparticles on implants. This coating process has the following advantages: (1) low temperature coating of nanoscale HAp is realized due to good sinterability of titanium nanoparticles; (2) high interfacial strength between layer and substrate because of the functional multilayer coating; (3) HAp nanoparticles provide better biocompability than micro-particles; (4) biphasic calcium phosphate (BCP) could be introduced, which has been reported to have excellent biocompatibility. In order to achieve these goals, careful selection of laser processing parameters is required. A multiphysics model is built and validated with experiments. This model is employed to determine the appropriate laser processing conditions. After laser processing, the features of the coated samples were characterized, including microstructures, chemical compositions, surface roughness, structure porosity and interfacial bonding strength. Qualitative cell culture studies with osteoblast-like UMR-105 cells were carried out to reveal the biocompatibility of so-coated implants. It is found that multilayer laser coated nanoHAp/Ti implants has beneficial biocompatibility, surface roughness, maintained chemical composition, porous microstructure and strong coating/substrate interfacial strength.

Effects of Container Geometry on Energy Consumption During Hardening in Ice Cream Manufacturing

Energy consumption by the dairy food industry in the United States constitutes 10% of all energy consumed by the U.S. food industry. Reducing energy consumption in cooling and refrigeration of foods plays an important role in meeting the challenge of the energy crisis. Hardening is an important and energy-intensive step in ice cream manufacturing. This work presents Finite Element Method (FEM) investigation of the ice cream hardening process, aiming to provide insight and guidance for energy savings in ice cream manufacturing. Effects of container shape and dimensions, container layers, and heat transfer boundary conditions on energy consumption for hardening of ice cream were investigated.

A Dislocation Dynamics Based Constitutive Model and Experimental Validations by 3D Microscale Laser Dynamic Forming of Metallic Thin Films

Microscale Laser Dynamic Forming (μLDF) shows great potential in fabricating the robust and high-aspect-ratio metallic microcomponents by the high speed plasma shockwave. Experiments revealed that strain rate and sample size play important roles in determining the final results of μLDF. To further understand the deformation behavior, we develop a constitutive model integrating size effects and ultrahigh strain rate effects to predict the ultimate plastic deformations. To derive this model, 3-D Discrete Dislocation Dynamics (DDD) simulations are first set up to investigate the dislocation evolutions and the dynamic responses during shockwave propagation. It is observed that there exist three dynamic stages during deformation process, and the initial strain hardening rate in Stage II increases with strain rate. The simulation also reveals that stain softening occurs only for the smaller cell size due to two competing mechanisms. In addition, the simulation predicts that the flow stress and yield strength increase with the strain rate and decrease with cell size. The modified mechanical threshold stress (MTS) model integrating these effects is implemented in Abaqus/Explicit and predicts the deformation depth and thickness variations in good agreement with the experimental results.

Formability of Open-Cell Aluminum Foams by Laser

A new forming method for open-cell aluminum (Al) foams by laser was introduced. Laser forming is generally applied to sheet metals but a good formability was observed also for Al alloy cellular structures. In this study, laser bending tests were performed on rectangular samples made of open-cell Al alloy foams by means of a diode laser. Laser scan velocity and power were changed in the experimentation so as to identify the best process conditions for three different Al foams. A finite element model was implemented to simulate the laser-material interaction during forming in dependence of the foam structure. At fixed values of laser velocity and power, higher bending angles were obtained for foams with smaller pores but, changing the process parameters, a better formability was observed for the foams with bigger pores.

Smart Machining Simulation Based on High-Level Data

The main objective of any machining simulation system is to produce a model that can reveal or mimic the real machining process as accurately as possible. Current simulation systems often use G-code or CL data as input that has inherent drawbacks such as vendor-specific nature, incomplete data, irreversible data conversions and lack of accuracy. These limitations hinder the development of a ‘trustworthy’ simulation system. Hence, there is a need for higher-level input data that can assist with accurate simulation for machining processes. There is also a need to take into account of true behaviour and real-time data of a machine tool. The paper presents a ‘near-real simulation’ solution for more accurate results. STEP-NC is used as the input data as it provides a more complete data model for machining simulations. Data from the machine tool is captured by means of sensors to provide true values for machining simulation purposes. The outcome of the research provides a smart and better informed simulation environment. The paper reviewed some of the current simulation approaches, discussed input data sources for smart simulation system and proposed near-real simulation system architecture.