A preliminary assessment of machinability of titanium alloy Ti 6Al 4V during thin wall machining using trochoidal milling

Titanium alloys are of great demand in the aerospace and biomedical industries. Most the titanium products are either cast or sintered to required shape and finish machined to get the appropriate surface texture to meet the design requirements. Ti-6Al-4V is often referred as work horse among the titanium alloys due to its heavy use in the aerospace industry. This paper is an attempt to investigate and improve the machining performance of Ti-6Al-4V. Thin wall machining is an advance machining technique especially used in machining turbine blades which can be done both in a conventional way and using a special technique known as trochoidal milling. The experimental design consists of conducting trials using combination of cutting parameters such as cutting speed (vc), 90 and 120 m/min; feed/tooth (fz) of 0.25 and 0.35 mm/min; step over (ae) 0.3 and 0.2; at constant depth of cut (ap) 20mm and using coolant. A preliminary assessment of machinability of Ti-6Al-4V during thin wall machining using trochoidal milling is done. A correlation established using cutting force, surface texture and dimensional accuracy.

A microstructure based analytical model for tensile twinning in a rod textured Mg alloy

Abstract A model for tensile twinning during the compression of rod textured magnesium is developed based on the idea that these twins nucleate at grain boundaries and that when the twin number density per grain is low these twins readily give rise to the formation of other 'interaction' twins in adjacent grains. Experimental observations of twin aspect ratios measured at a single grain size and twin number densities measured over four grain sizes were used to determine model material parameters. Using these, the model provides reasonable predictions for the observed magnitudes and trends for the following observations:Effect of grain size and stress on twin volume fraction, fractional twin length and the fraction of twin contact.Effect of grain size on the yield stress.Effect of grain size on the general shape of the stress-strain curve at low strains. A parametric study shows the model to be quite robust but that it is particularly sensitive to the value of the exponent assumed for the twin nucleation rate law. It is seen that preventing the formation of interaction twins provides an important avenue for hardening and that the flow stress is also particularly sensitive to the relaxation of the twin back stresses. The model shows the importance of taking microstructure into account when modelling twinning.

DeepCare: a deep dynamic memory model for predictive medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.

Constitutive modelling of high strength titanium alloy Ti-6Al-4 V for sheet forming applications at room temperature

To enable the design and optimisation of forming processes at room temperature the material behaviour of Ti-6Al-4 V needs to be accurately represented in numerical analysis and this requires an advanced material model. In particular, an accurate representation of the shape and size of the yield locus as well as its evolution during forming is important. In this study a rigorous set of experiments on the quasi-static deformation behaviour of a Ti-6Al-4 V alloy sheet sample at room temperature was conducted for various loading conditions and a constitutive material model developed. To quantify the anisotropy and asymmetry properties, tensile and compression tests were carried out for different specimen orientations. To examine the Bauschinger effect and the transient hardening behaviour in - plane tensile - compression and compression - tensile tests were performed. Balanced biaxial and plane strain tension tests were conducted to construct and validate the yield surface of the Ti-6Al-4 V alloy sheet sample at room temperature. A recently proposed anisotropic elastic-plastic constitutive material model, so-called HAH, was employed to describe the behaviour, in particular for load reversals. The HAH yield surface is composed of a stable component, which includes plastic anisotropy and is distorted by a fluctuating component. The key of the formulation is the use of a suitable yield function that reproduces the experimental observations well for the stable component. Meanwhile, the rapid evolution of the material structure must be captured at the macro - scale level by the fluctuating component embedded in the HAH model. Compared to conventional hardening equations, the proposed model leads to higher accuracy in predicting the Bauschinger effect and the transient hardening behaviour for the Ti-6Al-4 V sheet sample tested at room temperature.

A Mg-Al-Nd alloy produced via a powder metallurgical route

A Mg-5 wt.%Al-2 wt.%Nd alloy has been prepared by a powder metallurgical route using a blend of two dissimilar alloy powders. The initial consolidation of the powders was achieved through a single equal channel angular extrusion pass at 150 °C. After heat treatment at temperatures between 420 °C and 530 °C, it was possible to produce a microstructure that consisted of a uniform distribution of Al3Nd and Al11Nd3 precipitates in a magnesium matrix. These precipitates displayed distinct orientation relationships with the matrix. The size and shape of the precipitates depended on the heat treatment temperature and time. © 2009 Elsevier B.V. All rights reserved.

Imaging identity: media, memory and portraiture in the digital age

Imaging Identity presents potent reflections on the human condition through the prism of portraiture. Taking digital imaging technologies and the dynamic and precarious dimensions of contemporary identity as critical reference points, these essays consider why portraits continue to have such galvanising appeal and perform fundamental work across so many social settings. This multidisciplinary enquiry brings together artists, art historians, art theorists and anthropologists working with a variety of media. Authors look beyond conventional ideas of the portrait to the wider cultural contexts, governmental practices and intimate experiences that shape relationships between persons and pictures. Their shared purpose centres on a commitment to understanding the power of images to draw people into their worlds. Imaging Identity tracks a fundamental symbiosis — to grapple with the workings of images is to understand something vital of what it is to be human.