Membrane-based deformable mirror: intrinsic aberrations and alignment issues

A deformable mirror (DM) is an important component of an adaptive optics system. It is known that an on-axis spherical/parabolic optical component, placed at an angle to the incident beam introduces defocus as well as astigmatism in the image plane. Although the former can be compensated by changing the focal plane position, the latter cannot be removed by mere optical realignment. Since the DM is to be used to compensate a turbulence-induced curvature term in addition to other aberrations, it is necessary to determine the aberrations induced by such (curved DM surface) an optical element when placed at an angle (other than 0 deg) of incidence in the optical path. To this effect, we estimate to a first order the aberrations introduced by a DM as a function of the incidence angle and deformation of the DM surface. We record images using a simple setup in which the incident beam is reflected by a 37 channel micro-machined membrane deformable mirror for various angles of incidence. It is observed that astigmatism is a dominant aberration, which was determined by measuring the difference between the tangential and sagittal focal planes. We justify our results on the basis of theoretical simulations and discuss the feasibility of using such a system for adaptive optics considering a trade-off between wavefront correction and astigmatism due to deformation. (C) 2015 Optical Society of America

THREE-LAYER FLUID FLOW OVER A SMALL OBSTRUCTION ON THE BOTTOM OF A CHANNEL

Many boundary value problems occur in a natural way while studying fluid flow problems in a channel. The solutions of two such boundary value problems are obtained and analysed in the context of flow problems involving three layers of fluids of different constant densities in a channel, associated with an impermeable bottom that has a small undulation. The top surface of the channel is either bounded by a rigid lid or free to the atmosphere. The fluid in each layer is assumed to be inviscid and incompressible, and the flow is irrotational and two-dimensional. Only waves that are stationary with respect to the bottom profile are considered in this paper. The effect of surface tension is neglected. In the process of obtaining solutions for both the problems, regular perturbation analysis along with a Fourier transform technique is employed to derive the first-order corrections of some important physical quantities. Two types of bottom topography, such as concave and convex, are considered to derive the profiles of the interfaces. We observe that the profiles are oscillatory in nature, representing waves of variable amplitude with distinct wave numbers propagating downstream and with no wave upstream. The observations are presented in tabular and graphical forms.

Reliability Assessment of a Storm Water Drain Network

Most of the cities in India are undergoing rapid development in recent decades, and many rural localities are undergoing transformation to urban hotspots. These developments have associated land use/land cover (LULC) change that effects runoff response from catchments, which is often evident in the form of increase in runoff peaks, volume and velocity in drain network. Often most of the existing storm water drains are in dilapidated stage owing to improper maintenance or inadequate design. The drains are conventionally designed using procedures that are based on some anticipated future conditions. Further, values of parameters/variables associated with design of the network are traditionally considered to be deterministic. However, in reality, the parameters/variables have uncertainty due to natural and/or inherent randomness. There is a need to consider the uncertainties for designing a storm water drain network that can effectively convey the discharge. The present study evaluates performance of an existing storm water drain network in Bangalore, India, through reliability analysis by Advance First Order Second Moment (AFOSM) method. In the reliability analysis, parameters that are considered to be random variables are roughness coefficient, slope and conduit dimensions. Performance of the existing network is evaluated considering three failure modes. The first failure mode occurs when runoff exceeds capacity of the storm water drain network, while the second failure mode occurs when the actual flow velocity in the storm water drain network exceeds the maximum allowable velocity for erosion control, whereas the third failure mode occurs when the minimum flow velocity is less than the minimum allowable velocity for deposition control. In the analysis, runoff generated from subcatchments of the study area and flow velocity in storm water drains are estimated using Storm Water Management Model (SWMM). Results from the study are presented and discussed. The reliability values are low under the three failure modes, indicating a need to redesign several of the conduits to improve their reliability. This study finds use in devising plans for expansion of the Bangalore storm water drain system. (C) 2015 The Authors. Published by Elsevier B.V.

CROSS-SECTIONAL ANALYSIS OF PRE-TWISTED THICK BEAMS USING VARIATIONAL ASYMPTOTIC METHOD

An asymptotically-exact methodology is presented for obtaining the cross-sectional stiffness matrix of a pre-twisted moderately-thick beam having rectangular cross sections and made of transversely isotropic materials. The anisotropic beam is modeled 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 of the beam is computed making use of the constitutive law and the kinematical relations derived with the inclusion of geometrical nonlinearities and initial twist. Large displacements and rotations are allowed, but small strain is assumed. The Variational Asymptotic Method is used to minimize the energy functional, thereby reducing the cross section to a point on the reference line with appropriate properties, yielding a 1-D constitutive law. In this method as applied herein, the 2-D 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 as orders of the small parameters. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that renders the 1-D strain measures well-defined. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

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.