Girsanov Transformation-Based Reliability Modeling and Testing of Actively Controlled Structures

The problem of estimation of the time-variant reliability of actively controlled structural dynamical systems under stochastic excitations is considered. Monte Carlo simulations, reinforced with Girsanov transformation-based sampling variance reduction, are used to tackle the problem. In this approach, the external excitations are biased by an additional artificial control force. The conflicting objectives of the two control forces-one designed to reduce structural responses and the other to promote limit-state violations (but to reduce sampling variance)-are noted. The control for variance reduction is fashioned after design-point oscillations based on a first-order reliability method. It is shown that for structures that are amenable to laboratory testing, the reliability can be estimated experimentally with reduced testing times by devising a procedure based on the ideas of the Girsanov transformation. Illustrative examples include studies on a building frame with a magnetorheologic damper-based isolation system subject to nonstationary random earthquake excitations. (C) 2014 American Society of Civil Engineers.

Markov chain splitting methods in structural reliability integral estimation

Monte Carlo simulation methods involving splitting of Markov chains have been used in evaluation of multi-fold integrals in different application areas. We examine in this paper the performance of these methods in the context of evaluation of reliability integrals from the point of view of characterizing the sampling fluctuations. The methods discussed include the Au-Beck subset simulation, Holmes-Diaconis-Ross method, and generalized splitting algorithm. A few improvisations based on first order reliability method are suggested to select algorithmic parameters of the latter two methods. The bias and sampling variance of the alternative estimators are discussed. Also, an approximation to the sampling distribution of some of these estimators is obtained. Illustrative examples involving component and series system reliability analyses are presented with a view to bring out the relative merits of alternative methods. (C) 2015 Elsevier Ltd. All rights reserved.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.

Phase diagram of the half-filled ionic Hubbard model

We study the phase diagram of the ionic Hubbard model (IHM) at half filling on a Bethe lattice of infinite connectivity using dynamical mean-field theory (DMFT), with two impurity solvers, namely, iterated perturbation theory (IPT) and continuous time quantum Monte Carlo (CTQMC). The physics of the IHM is governed by the competition between the staggered ionic potential Delta and the on-site Hubbard U. We find that for a finite Delta and at zero temperature, long-range antiferromagnetic (AFM) order sets in beyond a threshold U = U-AF via a first-order phase transition. For U smaller than U-AF the system is a correlated band insulator. Both methods show a clear evidence for a quantum transition to a half-metal (HM) phase just after the AFM order is turned on, followed by the formation of an AFM insulator on further increasing U. We show that the results obtained within both methods have good qualitative and quantitative consistency in the intermediate-to-strong-coupling regime at zero temperature as well as at finite temperature. On increasing the temperature, the AFM order is lost via a first-order phase transition at a transition temperature T-AF(U,Delta) or, equivalently, on decreasing U below U-AF(T,Delta)], within both methods, for weak to intermediate values of U/t. In the strongly correlated regime, where the effective low-energy Hamiltonian is the Heisenberg model, IPT is unable to capture the thermal (Neel) transition from the AFM phase to the paramagnetic phase, but the CTQMC does. At a finite temperature T, DMFT + CTQMC shows a second phase transition (not seen within DMFT + IPT) on increasing U beyond U-AF. At U-N > U-AF, when the Neel temperature T-N for the effective Heisenberg model becomes lower than T, the AFM order is lost via a second-order transition. For U >> Delta, T-N similar to t(2)/U(1 - x(2)), where x = 2 Delta/U and thus T-N increases with increase in Delta/U. In the three-dimensional parameter space of (U/t, T/t, and Delta/t), as T increases, the surface of first-order transition at U-AF(T,Delta) and that of the second-order transition at U-N(T,Delta) approach each other, shrinking the range over which the AFM order is stable. There is a line of tricritical points that separates the surfaces of first- and second-order phase transitions.

Analysis of Transverse Shear Strains in Pre-Twisted Thick Beams using Variational Asymptotic Method

The cross-sectional stiffness matrix is derived for a pre-twisted, moderately thick beam made of transversely isotropic materials and having rectangular cross sections. An asymptotically-exact methodology is used to model the anisotropic beam from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy is computed making use of the beam constitutive law and kinematical relations derived with the inclusion of geometrical nonlinearities and an initial twist. The energy functional is minimized making use of the Variational Asymptotic Method (VAM), thereby reducing the cross section to a point on the beam reference line with appropriate properties, forming a 1-D constitutive law. VAM is a mathematical technique employed in the current problem to rigorously split the 3-D analysis of beams into two: a 2-D analysis over the beam cross-sectional domain, which provides a compact semi-analytical form of the properties of the cross sections, and a nonlinear 1-D analysis of the beam reference curve. In this method, as applied herein, the cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged in orders of the small parameters. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that render the 1-D strain measures well-defined. The zeroth-order 3-D warping field thus yielded is then used to integrate the 3-D strain energy density over the cross section, resulting in the 1-D strain energy density, which in turn helps identify the corresponding cross-sectional stiffness matrix. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

Volume conservation issues in incompressible smoothed particle hydrodynamics

A divergence-free velocity field is usually sought in numerical simulations of incompressible fluids. We show that the particle methods that compute a divergence-free velocity field to achieve incompressibility suffer from a volume conservation issue when a finite time-step position update scheme is used. Further, we propose a deformation gradient based approach to arrive at a velocity field that reduces the volume conservation issues in free surface flows and maintains density uniformity in internal flows while retaining the simplicity of first order time updates. (C) 2015 Elsevier Inc. All rights reserved.

Multiobjective Optimization of Piezoelectric Bimorph Actuator with Rigid Extension

Production of high tip deflection in a piezoelectric bimorph laminar actuator by applying high voltage is limited by many physical constraints. Therefore, piezoelectric bimorph actuator with a rigid extension of non-piezoelectric material at its tip is used to increase the tip deflection of such an actuator. Research on this type of piezoelectric bending actuator is either limited to first order constitutive relations, which do not include non-linear behavior of piezoelectric element at high electric field, or limited to curve fitting techniques. Therefore, this paper considers high electric field, and analytically models tapered piezoelectric bimorph actuator with a rigid extension of non-piezoelectric material at its tip. The stiffness, capacitance, effective tip deflection, block force, output strain energy, output energy density, input electrical energy and energy efficiency of the actuator are calculated analytically. The paper also discusses the multi-objective optimization of this type of actuator subjected to the mechanical and electrical constraints.

Exchange spring behaviour in SrFe12O19-CoFe2O4 nanocomposites

Nanocomposites of hard (SrFe12O19) and soft ferrite (CoFe2O4) are prepared by mixing individual ferrite components at appropriate weight ratio and subsequent heat treatment. The magnetization of the composites showed hysteresis loop that is characteristic of the exchange spring system. The variation of J(r)/J(r)(infinity) vs. J(d)/J(r)(infinity) for these nanocomposites are investigated to understand the presence of both the interacting field and the disorder in the system. This is further corroborated with the First Order Reversal Curve analysis (FORC) on the nanocomposites of 1:4 (Cobalt Ferrite: Strontium Ferrite) and 1:16 (Cobalt Ferrite: Strontium Ferrite). The FORC distribution reveals that the pinning mechanism is stronger in the nanocomposite of 1:4 compared to 1:16. However, the nanocomposite of 1:16 exhibit superior exchange coupling strength in contrast to 1:4. The asymmetric nature of the FORC distribution at H-c = 0 Oe for both the nanocomposites validates the intercoupling between the reversible and irreversible magnetization. (C) 2015 Author(s).

Effective Degradation of Aqueous Nitrobenzene Using the SrFeO3-delta Photocatalyst under UV Illumination and Its Kinetics and Mechanistic Studies

In this article, the SrFeO3-delta photocatalyst was synthesized by a solution combustion method and applied for the photocatalytic degradation of aqueous nitrobenzene in the presence and absence of H2O2. The SrFeO3-delta photocatalyst was characterized by XRD, FT-IR, FE-SEM, TEM, TG-DTG, XPS, and UV visible spectroscopy. The band gap energy of SrFeO3-delta was found to be 3.75 eV which lies in the UV region. The XPS results indicate that the oxidation state of Sr and Fe in SrFeO3-delta was 2+ and 3+, respectively, and the surface atomic ratio of Sr and Fe is 0.995. The photocatalytic activity reveals that the degradation of nitrobenzene over the SrFeO3-delta catalyst itself (UV/SFO) is superior compared to SrFeO3-delta in the presence of H2O2 (UV/SFO/H2O2) with a degradation efficiency of 99-96%. The degradation of nitrobenzene obeys first-order kinetics in both UV/SFO and UV/SFO/H2O2 processes. The decrease in degradation efficiency with UV/SFO/H2O2 was attributed due to the formation of strontium carbonate on the photocatalyst surface.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Combination of Cyanine Behaviour and Giant Hyperpolarisability in Novel Merocyanine Dyes: Beyond the Bond Length Alternation (BLA) Paradigm

Merocyanine dyes that exhibit antithetic cyaninelike behaviour and giant first-order hyperpolarisability (beta) values have been designed. These cyanine-type dyes open up an intriguing route towards molecular-based electrooptic materials as well as new second-harmonic generation dyes for imaging.

Role of upward leaders in modifying the induced currents in solitary down-conductors during a nearby lightning strike to ground

Electromagnetic field produced by a lightning strike to ground causes significant induction to tall objects in the vicinity. The frequency of occurrence of such nearby ground strikes can be higher than the number of direct strikes. Therefore, a complete knowledge on these induced currents is of practical relevance. However, limited efforts towards the characterisation of such induced currents in tall down-conductors could be seen in the literature. Due to the intensification of the background field caused by the descending stepped leader, tall towers/down-conductors can launch upward leaders of significant length. The nonlinearity in the conductance of upward leader and the surrounding corona sheath can alter the characteristics of the induced currents. Preliminary aspects of this phenomenon have been studied by the author previously and the present work aims to perform a detailed investigation on the role of upward leaders in modifying the characteristics of the induced currents. A consistent model for the upward leader, which covers all the essential electrical aspects of the phenomena, is employed. A first order arc model for representing the conductance of upward leader and a field dependant quadratic conductivity model for the corona sheath is employed. The initial gradient in the upward leader and the field produced by the return stroke forms the excitation. The dynamic electromagnetic response is determined by solving the wave equation using thin-wire time-domain formulation. Simulations are carried out initially to ascertain the role of individual parameters, including the length of the upward leader. Based on the simulation results, it is shown that the upward leader enhances the induced current, and when significant in length, can alter the waveshape of induced current from bipolar oscillatory to unipolar. The duration of the induced current is governed by the length of upward leader, which in turn is dependant on the return stroke current and the effective length of the down-conductor. If the current during the upward leader developmental phase is considered along with that after the stroke termination to ground, it would present a bipolar current pulse. (C) 2015 Elsevier Ltd. All rights reserved.

Study of H/D exchange rates to derive the strength of intramolecular hydrogen bonds in halo substituted organic building blocks: An NMR spectroscopic investigation

Rates of hydrogen/deuterium (H/D) exchange determined by H-1 NMR spectroscopy are utilized to derive the strength of hydrogen bonds and to monitor the electronic effects in the site-specific halogen substituted benzamides and anilines. The theoretical fitting of the time dependent variation of the integral areas of H-1 NMR resonances to the first order decay function permitted the determination of HID exchange rate constants (k) and their precise half-lives (t(1/2)) with high degree of reproducibility. The comparative study also permitted the unambiguous determination of relative strength of hydrogen bonds and the contribution from electronic effects on the HID exchange rate. (C) 2015 Elsevier B.V. All rights reserved.

Hetero-atom Doped Carbon Nanotubes for Dye Degradation and Oxygen Reduction Reaction

We report the synthesis of nitrogen doped vertically aligned multi-walled (MWNCNTs) carbon nanotubes by pyrolysis and its catalytic performance for degradation of methylene blue (MB) dye & oxygen reduction reaction (ORR). The degradation of MB was monitored spectrophotometrically with time. Kinetic studies show the degradation of MB follows a first order kinetic with rate constant k=0.0178 min(-1). The present rate constant is better than that reported for various supported/non-supported semiconducting nanomaterials. Further ORR performance in alkaline media makes MWNCNTs a promising cost-effective, fuel crossover tolerance, metal-free, eco-friendly cathode catalyst for direct alcohol fuel cell.

Length scales in glass-forming liquids and related systems: a review

The central problem in the study of glass-forming liquids and other glassy systems is the understanding of the complex structural relaxation and rapid growth of relaxation times seen on approaching the glass transition. A central conceptual question is whether one can identify one or more growing length scale(s) associated with this behavior. Given the diversity of molecular glass-formers and a vast body of experimental, computational and theoretical work addressing glassy behavior, a number of ideas and observations pertaining to growing length scales have been presented over the past few decades, but there is as yet no consensus view on this question. In this review, we will summarize the salient results and the state of our understanding of length scales associated with dynamical slow down. After a review of slow dynamics and the glass transition, pertinent theories of the glass transition will be summarized and a survey of ideas relating to length scales in glassy systems will be presented. A number of studies have focused on the emergence of preferred packing arrangements and discussed their role in glassy dynamics. More recently, a central object of attention has been the study of spatially correlated, heterogeneous dynamics and the associated length scale, studied in computer simulations and theoretical analysis such as inhomogeneous mode coupling theory. A number of static length scales have been proposed and studied recently, such as the mosaic length scale discussed in the random first-order transition theory and the related point-to-set correlation length. We will discuss these, elaborating on key results, along with a critical appraisal of the state of the art. Finally we will discuss length scales in driven soft matter, granular fluids and amorphous solids, and give a brief description of length scales in aging systems. Possible relations of these length scales with those in glass-forming liquids will be discussed.