Multiscale modelling of dendrite growth during vacuum arc remelting

Vacuum Arc Remelting (VAR) is the accepted method for producing homogeneous, fine microstructures that are free of inclusions required for rotating grade applications. However, as ingot sizes are increasing INCONEL 718 becomes increasingly susceptible to defects such as freckles, tree rings, and white spots increases for large diameter billets. Therefore, predictive models of these defects are required to allow optimization of process parameters. In this paper, a multiscale and multi-physics model is presented to predict the development of microstructures in the VAR ingot during solidification. At the microscale, a combined stochastic nucleation approach and finite difference solution of the solute diffusion is applied in the semi-solid zone of the VAR ingot. The micromodel is coupled with a solution of the macroscale heat transfer, fluid flow and electromagnetism in the VAR process through the temperature, pressure and fluid flow fields. The main objective of this study is to achieve a better understanding of the formation of the defects in VAR by quantifying the influence of VAR processing parameters on grain nucleation and dendrite growth. In particular, the effect of different ingot growth velocities on the microstructure formation was investigated. It was found that reducing the velocity produces significantly more coarse grains.

Vibrational spectroscopy and DFT calculations of di-amino acid cyclic peptides. Part I: cyclo(Gly-Gly), cyclo(L-Ala-L-Ala) and cyclo(L-Ala-Gly) in the solid state and in aqueous solution

Investigations of the vibrational spectra of cyclo(Gly-Gly), cyclo(L-Ala-L-Ala) and cyclo(t-Ala-Gly) are reported. Raman scattering and Fourier transform infrared (FTIR) spectra of solid-state and aqueous protonated samples, as well as their corresponding N-deuterated isotopomers, have been examined. In addition, density functional theory (DFT) (B3-LYP/cc-pVDZ) calculations of molecular structures and their associated vibrational modes were carried out. In each case, the calculated structures of lowest energy for the isolated gas-phase molecules have boat conformations. Assignments have been made for the observed Raman and FTIR vibrational bands of the cyclic di-amino acid peptides (CDAPs) examined. Raman polarization studies of aqueous phase samples are consistent with C-2 and C-1 symmetries for the six-membered rings of cyclo(L-Ala-L-Ala) and cydo(L-Ala-Gly), respectively. There is a good correlation between experimental and calculated vibrational bands for the three CDAPs. These data are in keeping with boat conformations for cydo(L-Ala-L-Ala) and cyclo(L-Ala-Gly) molecules, predicted by the ab initio calculations, in both the solid and aqueous solution states. However, Raman spectroscopic results might infer that cyclo(L-AlaGly) deviates only slightly from planarity in the solid state. The potential energy distributions of the amide I and II modes of a cis-peptide linkage are shown to be significantly different from those of the trans-peptides. For example, deuterium shifts have shown that the cis-amide I vibrations found in cyclo(Gly-Gly), cyclo(L-Ala-L-Ala), and cyclo(L-Ala-Gly) have larger N-H contributions compared to their trans-amide counterparts. Compared to trans-amide II vibrations, cis-amide II vibrations show a considerable decrease in N-H character.

Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging

This paper studies the possibility of distinguishing between benign and malignant masses by exploiting the morphology-dependent temporal and spectral characteristics of their microwave backscatter response in ultra-wideband breast cancer detection. The spiculated border profiles of 2-D breast masses are generated by modifying the baseline elliptical rings based upon the irregularity of their peripheries. Furthermore, the single- and multilayer lesion models are used to characterize a distinct mass region followed by a sharp transition to background, and a blurred mass border exhibiting a gradual transition to background, respectively. Subsequently, the complex natural resonances (CNRs) of the backscatter microwave signature can be derived from the late-time target response and reveal diagnostically useful information. The fractional sequence CLEAN algorithm is proposed to estimate the lesions' delay intervals and identify the late-time responses. Finally, it is shown through numerical examples that the locations of dominant CNRs are dependent on the lesion morphologies, where 2-D computational breast phantoms with single and multiple lesions are investigated. The analysis is of potential use for discrimination between benign and malignant lesions, where the former usually possesses a better-defined, more compact shape as opposed to the latter.