Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.

3D FEM simulation of helical milling hole process for titanium alloy Ti-6Al-4V

As an emerging hole-machining methodology, helical milling process has become increasingly popular in aeromaterials manufacturing research, especially in areas of aircraft structural parts, dies, and molds manufacturing. Helical milling process is highly demanding due to its complex tool geometry and the progressive material failure on the workpiece. This paper outlines the development of a 3D finite element model for helical milling hole of titanium alloy Ti-6Al-4V using commercial FE code ABAQUS/Explicit. The proposed model simulates the helical milling hole process by taking into account the damage initiation and evolution in the workpiece material. A contact model at the interface between end-mill bit and workpiece has been established and the process parameters specified. Furthermore, a simulation procedure is proposed to simulate different cutting processes with the same failure parameters. With this finite element model, a series of FEAs for machined titanium alloy have been carried out and results compared with laboratory experimental data. The effects of machining parameters on helical milling have been elucidated, and the capability and advantage of FE simulation on helical milling process have been well presented.

Enhancement of Wear and Corrosion Resistance of Beta Titanium Alloy by Laser Gas Alloying with Nitrogen

The relatively high elastic modulus coupled with the presence of toxic vanadium (V) in Ti6Al4 V alloy has long been a concern in orthopaedic applications. To solve the problem, a variety of non-toxic and low modulus beta-titanium (beta-Ti) alloys have been developed. Among the beta-Ti alloy family, the quaternary Ti-Nb-Zr-Ta (TNZT) alloys have received the highest attention as a promising replacement for Ti6Al4 V due to their lower elastic modulus and outstanding long term stability against corrosion in biological environments. However, the inferior wear resistance of TNZT is still a problem that must be resolved before commercialising in the orthopaedic market. In this work, a newly-developed laser surface treatment technique was employed to improve the surface properties of Ti-35.3Nb-7.3Zr-5.7Ta alloy. The surface structure and composition of the laser-treated TNZT surface were examined by grazing incidence x-ray diffraction (GI-XRD) and x-ray photoelectron spectroscopy (XPS). The wear and corrosion resistance were evaluated by pin-on-plate sliding test and anodic polarisation test in Hanks’ solution. The experimental results were compared with the untreated (or base) TNZT material. The research findings showed that the laser surface treatment technique reported in this work can effectively improve the wear and corrosion resistance of TNZT.

The use of Log-file analysis within VMAT audits

OBJECTIVE: This work investigates the delivery accuracy of different Varian linear accelerator models using log-file derived MLC RMS values.

METHODS: Seven centres independently created a plan on the same virtual phantom using their own planning system and the log files were analysed following delivery of the plan in each centre to assess MLC positioning accuracy. A single standard plan was also delivered by seven centres to remove variations in complexity and the log files were analysed for Varian TrueBeams and Clinacs (2300IX or 2100CD models).

RESULTS: Varian TrueBeam accelerators had better MLC positioning accuracy (<1.0mm) than the 2300IX (<2.5mm) following delivery of the plans created by each centre and also the standard plan. In one case log files provided evidence that reduced delivery accuracy was not associated with the linear accelerator model but was due to planning issues.

CONCLUSIONS: Log files are useful in identifying differences between linear accelerator models, and isolate errors during end-to-end testing in VMAT audits. Log file analysis can rapidly eliminate the machine delivery from the process and divert attention with confidence to other aspects. Advances in Knowledge: Log file evaluation was shown to be an effective method to rapidly verify satisfactory treatment delivery when a dosimetric evaluation fails during end-to-end dosimetry audits. MLC RMS values for Varian TrueBeams were shown to be much smaller than Varian Clinacs for VMAT deliveries.