Modelling and comparative study of viscoelastic laminated composite beam – an operator based finite element approach

Mechanics of Time-Dependent Materials - Finite element formulation of damped laminated composite beam considering both Euler-Bernoulli and Timoshenko beam theory is proposed based on Equivalent...     

Nonlinear control of a multicomponent distillation process coupled with a binary distillation model as an EKF predictor

The work is devoted to design the globally linearizing control (GLC) strategy for a multicomponent distillation process. The control system is comprised with a nonlinear transformer, a nonlinear closed-loop state estimator [extended Kalman filter (EKF)], and a linear external controller [conventional proportional integral (PI) controller]. The model of a binary distillation column has been used as a state predictor to avoid huge design complexity of the EKF estimator. The binary components are the light key and the heavy key of the multicomponent system. The proposed GLC-EKF (GLC in conjunction with EKF) control algorithm has been compared with the GLC-ROOLE [GLC coupled with reduced-order open-loop estimator (ROOLE)] and the dual-loop PI controller based on set point tracking and disturbance rejection performance. Despite huge process/predictor mismatch, the superiority of the GLC-EKF has been inspected over the GLC-ROOLE control structure.     

Effect of thermomechanical treatment on structure and mechanical properties of Mo-bearing dual phase steel

The effects of hot rolling of a dual phase steel in the (α + γ) range on microstructure and mechanical properties was investigated by using two thermomechanical (TMT) routes. The first consisted of heating A_c3, soaking, cooling to deformation temperature in the (α + γ) range. The second comprises heating to deformation temperature in the (α + γ) range, followed by rolling and quenching. Parameters varied were temperature (with the first route) and extent of deformation (with the second). The microstructures were characterised by optical and transmission electron microscopy. The results indicate a distinct difference in the final structure and properties due to the two different TMT routes. The first TMT route resulted in a greater amount of ferrite, finer lath width of martensite, finer ferrite grain size and increased density of dislocations. The strength properties decreased, the YS/UTS ratio decreased and ductility increased with the increase in the extent and temperature of deformation. However, TMT route 2 resulted in an increase in the amount of martensite, finer ferrite grain size, decrease in the martensite lath width and increased dislocation density. The strength properties increased, YS/UTS ratio increased and ductility decreased with increase in the extent and temperature of deformation.     

Synthesis and characterization of an electro-deposited polyaniline-bismuth telluride nanocomposite — A novel thermoelectric material

The present work consists of synthesis and characterization of a novel thermoelectric material polyaniline (PANI)-bismuth telluride (Bi₂Te₃) nanocomposite using simultaneous electrochemical reactions and deposition method. The inorganic bismuth nitrate has been used as a dopant for polyaniline to achieve high electrical conductivity. A semi-batch mode of operation has been employed to control the rate of deposition of an individual component and thus the molecular architecture of the composite. The electro-deposited composite film on ITO coated glass substrate has been characterized by X-ray diffraction analysis (XRD), FTIR analysis, scanning electron microscope (SEM), and transmission electron microscope (TEM). The microscopic analysis reveals the formation of rod-like nanostructures of diameter less than 100 nm. It has been found that smaller molecules of Bi₂Te₃ are dispersed in the macromolecules of PANI. The nanocomposite has been characterized by thermoelectric power.     

A simulation-based generalized framework to model vulnerability of interdependent critical infrastructure systems under incomplete information

This paper proposes a novel simulation-based hybrid approach coupled with time-dependent Bayesian network analysis to model multi-infrastructure vulnerability over time under physical, spatial, and informational uncertainties while considering cascading failures within and across infrastructure networks. Unlike existing studies that unrealistically assume that infrastructure managers have full knowledge of all the infrastructure systems, the proposed approach considers a realistic scenario where complete information about the infrastructure network topology or the supply–demand flow characteristics is not available while estimating multi-infrastructure vulnerability. A novel heuristic algorithm is proposed to construct a dynamic fault tree to abstract the network topology of any infrastructure. In addition, to account for the unavailability of exact supply–demand flow characteristics, the proposed approach constructs the interdependence links across infrastructure network systems using different simulated parameters considering the physical, logical, and geographical dependencies. Finally, using parameters for geographical proximity, infrastructure managers' risk perception, and the relative importance of one infrastructure on another, the multi-infrastructure vulnerability over time is estimated. Results from the numerical experiment show that for an opportunistic risk perception, the interdependencies attribute to redundancies, and with an increase in redundancy, the vulnerability decreases. On the other hand, from a conservative risk perspective, the interdependencies attribute to deficiencies/liabilities, and the vulnerability increases with an increase in the number of such interdependencies.