Steady state three-dimensional mathematical model for cupola

A three-dimensional mathematical model has been developed to simulate the gas flow, composition, and temperature profiles inside a cupola. Comparison of the model with the reported experimental data shows the presence of a zone with low combustion rate at the tuyere level. For a 24 in (610 mm) cupola with four rows of tuyeres, the combustion zones from each tuyere overlap each other, forming an overall combustion zone of cylindrical shape of height similar to 0.2 m. Using the model, it is found that the spout temperature initially increases with increasing blast velocity and attains a maximum. Further increase in blast velocity does not change the spout temperature. This suggests that smaller size tuyeres and higher permeability of the bed can give superior cupola performance. (C) 1997 The Institute of Materials.

Model exact low-lying states and spin dynamics in ferric wheels: Fe-6 to Fe-12

Using an efficient numerical scheme that exploits spatial symmetries and spin parity, we have obtained the exact low-lying eigenstates of exchange Hamiltonians for ferric wheels up to Fe-12. The largest calculation involves the Fe-12 ring which spans a Hilbert space dimension of about 145x10(6) for the M-S=0 subspace. Our calculated gaps from the singlet ground state to the excited triplet state agree well with the experimentally measured values. Study of the static structure factor shows that the ground state is spontaneously dimerized for ferric wheels. The spin states of ferric wheels can be viewed as quantized states of a rigid rotor with the gap between the ground and first excited states defining the inverse of the moment of inertia. We have studied the quantum dynamics of Fe-10 as a representative of ferric wheels. We use the low-lying states of Fe-10 to solve exactly the time-dependent Schrodinger equation and find the magnetization of the molecule in the presence of an alternating magnetic field at zero temperature. We observe a nontrivial oscillation of the magnetization which is dependent on the amplitude of the ac field. We have also studied the torque response of Fe-12 as a function of a magnetic field, which clearly shows spin-state crossover.

A numerical model of a liquid-feed solid polymer electrolyte DMFC and its experimental validation

A one-dimensional, biphasic, multicomponent steady-state model based on phenomenological transport equations for the catalyst layer, diffusion layer, and polymeric electrolyte membrane has been developed for a liquid-feed solid polymer electrolyte direct methanol fuel cell (SPE- DMFC). The model employs three important requisites: (i) implementation of analytical treatment of nonlinear terms to obtain a faster numerical solution as also to render the iterative scheme easier to converge, (ii) an appropriate description of two-phase transport phenomena in the diffusive region of the cell to account for flooding and water condensation/evaporation effects, and (iii) treatment of polarization effects due to methanol crossover. An improved numerical solution has been achieved by coupling analytical integration of kinetics and transport equations in the reaction layer, which explicitly include the effect of concentration and pressure gradient on cell polarization within the bulk catalyst layer. In particular, the integrated kinetic treatment explicitly accounts for the nonhomogeneous porous structure of the catalyst layer and the diffusion of reactants within and between the pores in the cathode. At the anode, the analytical integration of electrode kinetics has been obtained within the assumption of macrohomogeneous electrode porous structure, because methanol transport in a liquid-feed SPE- DMFC is essentially a single-phase process because of the high miscibility of methanol with water and its higher concentration in relation to gaseous reactants. A simple empirical model accounts for the effect of capillary forces on liquid-phase saturation in the diffusion layer. Consequently, diffusive and convective flow equations, comprising Nernst-Plank relation for solutes, Darcy law for liquid water, and Stefan-Maxwell equation for gaseous species, have been modified to include the capillary flow contribution to transport. To understand fully the role of model parameters in simulating the performance of the DMCF, we have carried out its parametric study. An experimental validation of model has also been carried out. (C) 2003 The Electrochemical Society.

Mathematical model of COREX melter gasifier: Part II. Dynamic model

A dynamic model of the COREX melter gasifier is developed to study the transient behavior of the furnace. The effect of pulse disturbance and step disturbance on the process performance has been studied. This study shows that the effect of pulse disturbance decays asymptotically. The step change brings the system to a new steady state after a delay of about 5 hours. The dynamic behavior of the melter gasifier with respect to a shutdown/blow-on condition and the effect of tapping are also studied. The results show that the time response of the melter gasifier is much less than that of a blast furnace.

Mathematical model of COREX melter gasifier: Part I. Steady-state model

The COREX melter gasifier is a countercurrent reactor to produce liquid iron. Directly reduced iron (DRI), noncoking coal, and other additives are charged to the melter gasifier at their respective temperatures, and O-2 is blown through the tuyeres. Functionally, a melter gasifier is divided into three zones: a moving bed, fluidized bed, and free board. A model has been developed for the moving bed, where the tuyere region is two-dimensional (2-D) and the rest is one-dimensional (1-D). It is based on multiphase conservation of mass, momentum, and heat. The fluidized bed has been treated as 1-D. Partial equilibrium is calculated for the free board. The calculated temperature of the hot metal, the top gas, and the chemistry of the top gas agree with the reported plant data. The model has been used to study the effects of bed height, injection of impure O-2, coal chemistry, and reactivity on the process performance.

An Empirical Model of the Process of Synthesis of Multiple State Mechanical Devices

Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. The research work presented here is based on the processes of synthesizing multiple state mechanical devices carried out individually by ten engineering designers. The designers are asked to think aloud, while carrying out the synthesis. The ten design synthesis processes are video recorded, and the records are transcribed and coded for identifying activities occurring in the synthesis processes, as well as for identifying the inputs to and outputs from the activities. A mathematical representation for specifying multi-state design task is proposed. Further, a descriptive model capturing all the ten synthesis processes is developed and presented in this paper. This will be used to identify the outstanding issues to be resolved before a system for supporting design synthesis of multiple state mechanical devices that is capable of creating a comprehensive variety of solution alternatives could be developed.

Nonlinear cyclic load analysis for lateral response of batter piles in soft clay with a rigorous degradation model

Nonlinear analysis of batter piles in soft clay is performed using the finite element technique. As the batter piles are not only governed by lateral load but also axial load, the effect of P- Delta moment and geometric stiffness matrix is included in the analysis. For implementing the nonlinear soil behavior, reduction in soil strength (degradation), and formation of gap with number of load cycles, a numerical model is developed where a hyperbolic relation is adopted for the soil in static condition and hyperbolic relation considering degradation and gap for cyclic load condition. The numerical model is validated with published experimental results for cyclic lateral loading and the hysteresis loops are developed to predict the load-deflection behavior and soil resistance behavior during consecutive cycles of loading. This paper highlights the importance of a rigorous degradation model for subsequent cycles of loading on the pile-soil system by a hysteretic representation.

Non-linear electrical response of chalcogenide glasses: Memory state phenomena

Investigations on the switching behaviour of arsenic-tellurium glasses with Ge or Al additives, yield interesting information about the dependence of switching on network rigidity, co-ordination of the constituents, glass transition & ambient temperature and glass forming ability.

Bose-Hubbard model in a strong effective magnetic field: Emergence of a chiral Mott insulator ground state

Motivated by experiments on Josephson junction arrays, and cold atoms in an optical lattice in a synthetic magnetic field, we study the ``fully frustrated'' Bose-Hubbard model with half a magnetic flux quantum per plaquette. We obtain the phase diagram of this model on a two-leg ladder at integer filling via the density matrix renormalization group approach, complemented by Monte Carlo simulations on an effective classical XY model. The ground state at intermediate correlations is consistently shown to be a chiral Mott insulator (CMI) with a gap to all excitations and staggered loop currents which spontaneously break time-reversal symmetry. We characterize the CMI state as a vortex supersolid or an indirect exciton condensate, and discuss various experimental implications.

Causality analysis of groundwater dynamics based on a Vector Autoregressive model in the semi-arid basin of Gundal (South India)

Causal relationships existing between observed levels of groundwater in a semi-arid sub-basin of the Kabini River basin (Karnataka state, India) are investigated in this study. A Vector Auto Regressive model is used for this purpose. Its structure is built on an upstream/downstream interaction network based on observed hydro-physical properties. Exogenous climatic forcing is used as an input based on cumulated rainfall departure. Optimal models are obtained thanks to a trial approach and are used as a proxy of the dynamics to derive causal networks. It appears to be an interesting tool for analysing the causal relationships existing inside the basin. The causal network reveals 3 main regions: the Northeastern part of the Gundal basin is closely coupled to the outlet dynamics. The Northwestern part is mainly controlled by the climatic forcing and only marginally linked to the outlet dynamic. Finally, the upper part of the basin plays as a forcing rather than a coupling with the lower part of the basin allowing for a separate analysis of this local behaviour. The analysis also reveals differential time scales at work inside the basin when comparing upstream oriented with downstream oriented causalities. In the upper part of the basin, time delays are close to 2 months in the upward direction and lower than 1 month in the downward direction. These time scales are likely to be good indicators of the hydraulic response time of the basin which is a parameter usually difficult to estimate practically. This suggests that, at the sub-basin scale, intra-annual time scales would be more relevant scales for analysing or modelling tropical basin dynamics in hard rock (granitic and gneissic) aquifers ubiquitous in south India. (c) 2012 Elsevier B.V. All rights reserved.

Nonlinear dynamic state estimation in instrumented structures with conditionally linear Gaussian substructures

Many problems of state estimation in structural dynamics permit a partitioning of system states into nonlinear and conditionally linear substructures. This enables a part of the problem to be solved exactly, using the Kalman filter, and the remainder using Monte Carlo simulations. The present study develops an algorithm that combines sequential importance sampling based particle filtering with Kalman filtering to a fairly general form of process equations and demonstrates the application of a substructuring scheme to problems of hidden state estimation in structures with local nonlinearities, response sensitivity model updating in nonlinear systems, and characterization of residual displacements in instrumented inelastic structures. The paper also theoretically demonstrates that the sampling variance associated with the substructuring scheme used does not exceed the sampling variance corresponding to the Monte Carlo filtering without substructuring. (C) 2012 Elsevier Ltd. All rights reserved.

Sharp raman anomalies and broken adiabaticity at a pressure induced transition from band to topological insulator in Sb2Se3

The nontrivial electronic topology of a topological insulator is thus far known to display signatures in a robust metallic state at the surface. Here, we establish vibrational anomalies in Raman spectra of the bulk that signify changes in electronic topology: an E-g(2) phonon softens unusually and its linewidth exhibits an asymmetric peak at the pressure induced electronic topological transition (ETT) in Sb2Se3 crystal. Our first-principles calculations confirm the electronic transition from band to topological insulating state with reversal of parity of electronic bands passing through a metallic state at the ETT, but do not capture the phonon anomalies which involve breakdown of adiabatic approximation due to strongly coupled dynamics of phonons and electrons. Treating this within a four-band model of topological insulators, we elucidate how nonadiabatic renormalization of phonons constitutes readily measurable bulk signatures of an ETT, which will facilitate efforts to develop topological insulators by modifying a band insulator. DOI: 10.1103/PhysRevLett.110.107401

Time variant reliability model updating in instrumented dynamical systems based on Girsanov's transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

Modeling the dynamic response of wrap-faced reinforced soil retaining walls

This paper describes the development of a numerical model for simulating the shaking table tests on wrap-faced reinforced soil retaining walls. Some of the physical model tests carried out on reinforced soil retaining walls subjected to dynamic excitation through uniaxial shaking tests are briefly discussed. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wraparound technique with dry sand backfill and instrumented with displacement sensors, accelerometers, and soil pressure sensors. Results showed that the displacements decrease with the increase in number of reinforcement layers, whereas acceleration amplifications were not affected significantly. Numerical modeling of these shaking table tests is carried out using the Fast Lagrangian Analysis of Continua program. The numerical model is validated by comparing the results with experiments on physical models. Responses of wrap-faced walls with varying numbers of reinforcement layers are compared. Sensitivity analysis performed on the numerical models showed that the friction and dilation angle of backfill material and stiffness properties of the geotextile-soil interface are the most affecting parameters for the model response.

State estimation in power systems using linear model infinity norm-based trust region approach

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.