The effects of machining process variables and tooling characterisation on the surface generation: modelling, simulation and application promise

The paper presents a novel approach for modelling and simulation of the surface generation in the machining process. The approach, by integrating dynamic cutting force model, regenerative vibration model, machining system response model and tool profile model, models the complex surface generation process. Matlab Simulink is used to interactively perform the simulation in a user-friendly, effective and efficient manner. The effects of machining variables and tooling characteristics on the surface generation are investigated through simulations. CNC turning trials have been carried out to evaluate and validate the approach and simulations presented. The proposed approach contributes to comprehensive and better understanding of the machining system, and is promising for industrial applications with particular reference to the optimisation of the machining process based on the product/component surface functionality requirements

Electrospray ionization mass spectrometric observation of ligand exchange of zinc pyrithione with amino acids

ArticleRAPID COMMUNICATIONS IN MASS SPECTROMETRY. 23(14):2161-2166 (2009)journal articl

Stability conditions and positivity of invariants of fibrations

We study three methods that prove the positivity of a natural numerical invariant associated to $1-$parameter families of polarized varieties. All these methods involve different stability conditions. In dimension 2 we prove that there is a natural connection between them, related to a yet another stability condition, the linear stability. Finally we make some speculations and prove new results in higher dimension.Comment: Final version, to appear in the Springer volume dedicated to Klaus Hulek on the occasion of his 60-th birthda

Lead Isotopes in Olivine-Phyric Shergottite Tissint: Implications for the Geochemical Evolution of the Shergottite Source Mantle

Geochemically-depleted shergottites are basaltic rocks derived from a martian mantle source reservoir. Geochemical evolution of the martian mantle has been investigated mainly based on the Rb-Sr, Sm-Nd, and Lu-Hf isotope systematics of the shergottites [1]. Although potentially informative, U-Th- Pb isotope systematics have been limited because of difficulties in interpreting the analyses of depleted meteorite samples that are more susceptible to the effects of near-surface processes and terrestrial contamination. This study conducts a 5-step sequential acid leaching experiment of the first witnessed fall of the geochemically-depleted olivinephyric shergottite Tissint to minimize the effect of low temperature distrubence. Trace element analyses of the Tissint acid residue (mostly pyroxene) indicate that Pb isotope compositions of the residue do not contain either a martian surface or terrestrial component, but represent the Tissint magma source [2]. The residue has relatively unradiogenic initial Pb isotopic compositions (e.g., 206Pb/204Pb = 10.8136) that fall within the Pb isotope space of other geochemically-depleted shergottites. An initial -value (238U/204Pb = 1.5) of Tissint at the time of crystallization (472 Ma [3]) is similar to a time-integrated mu- value (1.72 at 472 Ma) of the Tissint source mantle calculated based on the two-stage mantle evolution model [1]. On the other hand, the other geochemically-depleted shergottites (e.g., QUE 94201 [4]) have initial -values of their parental magmas distinctly lower than those of their modeled source mantle. These results suggest that only Tissint potentially reflects the geochemical signature of the shergottite mantle source that originated from cumulates of the martian magma ocea

Lead Isotope Compositions of Acid Residues from Olivine-Phyric Shergottite Tissint: Implications for Heterogeneous Shergottite Source Reservoirs

Geochemical studies of shergottites suggest that their parental magmas reflect mixtures between at least two distinct geochemical source reservoirs, producing correlations between radiogenic isotope compositions and trace element abundances. These correlations have been interpreted as indicating the presence of a reduced, incompatible element- depleted reservoir and an oxidized, incompatible- element-enriched reservoir. The former is clearly a depleted mantle source, but there is ongoing debate regarding the origin of the enriched reservoir. Two contrasting models have been proposed regarding the location and mixing process of the two geochemical source reservoirs: (1) assimilation of oxidized crust by mantle derived, reduced magmas, or (2) mixing of two distinct mantle reservoirs during melting. The former requires the ancient Martian crust to be the enriched source (crustal assimilation), whereas the latter requires isolation of a long-lived enriched mantle domain that probably originated from residual melts formed during solidification of a magma ocean (heterogeneous mantle model). This study conducts Pb isotope and trace element concentration analyses of sequential acid-leaching fractions (leachates and the final residues) from the geochemically depleted olivine-phyric shergottite Tissint. The results suggest that the Tissint magma is not isotopically uniform and sampled at least two geochemical source reservoirs, implying that either crustal assimilation or magma mixing would have played a role in the Tissint petrogenesis

3D-Spatiotemporal Forecasting the Expansion of Supernova Shells Using Deep Learning toward High-Resolution Galaxy Simulations

Supernova (SN) plays an important role in galaxy formation and evolution. In high-resolution galaxy simulations using massively parallel computing, short integration timesteps for SNe are serious bottlenecks. This is an urgent issue that needs to be resolved for future higher-resolution galaxy simulations. One possible solution would be to use the Hamiltonian splitting method, in which regions requiring short timesteps are integrated separately from the entire system. To apply this method to the particles affected by SNe in a smoothed-particle hydrodynamics simulation, we need to detect the shape of the shell on and within which such SN-affected particles reside during the subsequent global step in advance. In this paper, we develop a deep learning model, 3D-MIM, to predict a shell expansion after a SN explosion. Trained on turbulent cloud simulations with particle mass $m_{\rm gas}=1$M$_\odot$, the model accurately reproduces the anisotropic shell shape, where densities decrease by over 10 per cent by the explosion. We also demonstrate that the model properly predicts the shell radius in the uniform medium beyond the training dataset of inhomogeneous turbulent clouds. We conclude that our model enables the forecast of the shell and its interior where SN-affected particles will be present.Comment: 14 pages, 14 figures, 3 tables, accepted for MNRA