Unimolecular HCl elimination from 1,2-dichloroethane: A single pulse shock tube and ab initio study

Thermal decomposition of 1,2-dichloroethane (1,2-DCE) has been studied in the temperature range of 10501175 K behind reflected shock waves in a single pulse shock tube. The unimolecular elimination of HCl is found to be the major channel through which 1,2-DCE decomposes under these conditions. The rate constant for the unimolecular elimination of HCl from 1,2-dichloroethane is found to be 10(13.98+/-0.80) exp(-57.8+/-2.0/RT) s(-1), where the activation energy is given in kcal mol(-1) and is very close to that value for CH3CH2Cl (EC). Ab initio (HF and MP2) and DFT calculations have been carried out to find the activation barrier and the structure of the transition state for this reaction channel from both EC and 1,2-DCE. The preexponential factors calculated at various levels of theory (BF/6-311++G**, MP2/6-311++G**, and B3LYP/6-311++G**) are (approximate to10(15) s(-1)) significantly larger than the experimental results. If the torsional mode in the ground state is treated as free internal rotation the preexponential factors reduce significantly, giving excellent agreement with experimental values. The DFT results are in excellent (fortuitous?) agreement with the experimental value for activation energy for 1,2-DCE while the MP2 and HF results seem to overestimate the barrier. However, DFT results for EC is 4.5 kcal mol(-1) less than the previously reported experimental values. At all levels, theory predicts an increase in HCI elimination barrier on beta-Cl substitution on EC.

Unsteady mixed convection flow from a rotating vertical cone with a magnetic field

An analysis is developed to study the unsteady mixed convection flow over a vertical cone rotating in an ambient fluid with a time-dependent angular velocity in the presence of a magnetic field. The coupled nonlinear partial differential equations governing the flow have been solved numerically using an implicit finite-difference scheme. The local skin friction coefficients in the tangential and azimuthal directions and the local Nusselt number increase with the time when the angular velocity of the-cone increases, but the reverse trend is observed for decreasing angular velocity. However, these are not mirror reflection of each other. The magnetic field reduces the skin friction coefficient in the tangential direction and also the Nusselt number, but it increases the skin friction coefficient in the azimuthal direction. The skin friction coefficients and the Nusselt number increase with the buoyancy force.

Modeling wrap faced reinforced soil retaining walls subjected to dynamic excitation

This paper describes some of the physical and numerical model tests of reinforced soil retaining walls subjected to dynamic excitation through uni-axial shaking tests. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wrap around technique with dry sand backfill and instrumented with displacement sensors, accelerometers and soil pressure sensors. Numerical modelling of these shaking table tests is carried using FLAC. Numerical model is validated by comparing physical model results. Responses of wrap faced walls with different number of reinforcement layers are discussed from both the physical and numerical model tests. Results showed that the displacements are decreasing with the increase in number of reinforcement layers while acceleration amplifications are not affected significantly.

A Multi-layer Perceptron based Non-linear Mixture Model to estimate class abundance from mixed pixels

Sub-pixel classification is essential for the successful description of many land cover (LC) features with spatial resolution less than the size of the image pixels. A commonly used approach for sub-pixel classification is linear mixture models (LMM). Even though, LMM have shown acceptable results, pragmatically, linear mixtures do not exist. A non-linear mixture model, therefore, may better describe the resultant mixture spectra for endmember (pure pixel) distribution. In this paper, we propose a new methodology for inferring LC fractions by a process called automatic linear-nonlinear mixture model (AL-NLMM). AL-NLMM is a three step process where the endmembers are first derived from an automated algorithm. These endmembers are used by the LMM in the second step that provides abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual proportions are fed to multi-layer perceptron (MLP) architecture as input to train the neurons which further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. AL-NLMM is validated on computer simulated hyperspectral data of 200 bands. Validation of the output showed overall RMSE of 0.0089±0.0022 with LMM and 0.0030±0.0001 with the MLP based AL-NLMM, when compared to actual class proportions indicating that individual class abundances obtained from AL-NLMM are very close to the real observations.