A structural principle for a class of adaptive systems

A feature common to many adaptive systems for identification and control is the adjustment.of gain parameters in a manner ensuring the stability of the overall system. This paper puts forward a principle which assures such a result for arbitrary systems which are linear and time invariant except for the adjustable parameters. The principle only demands that a transfer function be positive real. This transfer function dependent on the structure of the system with respect to the parameters. Several examples from adaptive identification, control and observer schemes are given as illustrations of the conceptual simplification provided by the structural principle.

Padé approach to potential transients: Part 1. Electron transfer without and with coupling to first-order homogeneous reactions at planar electrodes

Potential transients are obtained by using “Padé approximants” (an accurate approximation procedure valid globally — not just perturbatively) for all amplitudes of concentration polarization and current densities. This is done for several mechanistic schemes under constant current conditions. We invert the non-linear current-potential relationship in the form (using the Lagrange or the Ramanujan method) of power series appropriate to the two extremes, namely near reversible and near irreversible. Transforming both into the Pad́e expressions, we construct the potential-time profile by retaining whichever is the more accurate of the two. The effectiveness of this method is demonstrated through illustrations which include couplings of homogeneous chemical reactions to the electron-transfer step.

Characteristic water contents of a fine-grained soil-water system

This paper critically appraises the limitations of the liquid-limit water content of clayey soils determined conventionally either by percussion cup or by the cone penetration method. It is shown that the conventional liquid limit and plastic limit are arbitrary, strength-based water contents and that they cannot represent the plasticity limits, and that the state of the soil-water system at the conventional liquid limit does not correspond to a stress-free reference state. The present investigation identifies three characteristic limiting water contents for a soil-water system which have well-defined, unique mechanisms controlling them, namely the free swell limit, settling limit and shrinkage limit. Simple procedures for the determination of the free swell limit and settling limit of natural soils are presented. The settling limit is shown to be the 'real liquid limit' of any clayey soil. With a number of experimental illustrations, it is clearly shown that the settling limit represents the maximum water-holding capacity of clayey soils and that it corresponds to the stress-free reference state.

Dynamics of pulsed flow in an elastic tube

Internal haemorrhage, often leading to cardio-vascular arrest happens to be one of the prime sources of high fatality rates in mammals. We propose a simplistic model of fluid flow in our attempt to specify the location of the haemorrhagic spot, which, if located accurately, could possibly be operated leading to an instant cure. The model we employ for the purpose is basically fluid mechanical in origin and consists of a viscous fluid, pumped by a periodic force and flowing through an elastic tube. The analogy is with that of blood, pumped from the heart and flowing through an artery or vein. Our results, aided by graphical illustrations, match reasonably well with experimental observations.

Two-Stage Extended Kalman Filters with Derivative-Free Local Linearizations

This paper proposes a derivative-free two-stage extended Kalman filter (2-EKF) especially suited for state and parameter identification of mechanical oscillators under Gaussian white noise. Two sources of modeling uncertainties are considered: (1) errors in linearization, and (2) an inadequate system model. The state vector is presently composed of the original dynamical/parameter states plus the so-called bias states accounting for the unmodeled dynamics. An extended Kalman estimation concept is applied within a framework predicated on explicit and derivative-free local linearizations (DLL) of nonlinear drift terms in the governing stochastic differential equations (SDEs). The original and bias states are estimated by two separate filters; the bias filter improves the estimates of the original states. Measurements are artificially generated by corrupting the numerical solutions of the SDEs with noise through an implicit form of a higher-order linearization. Numerical illustrations are provided for a few single- and multidegree-of-freedom nonlinear oscillators, demonstrating the remarkable promise that 2-EKF holds over its more conventional EKF-based counterparts. DOI: 10.1061/(ASCE)EM.1943-7889.0000255. (C) 2011 American Society of Civil Engineers.

Monograph on Essentials in Limnology and GIS

Aquatic ecosystems are dynamic and depend on various interdependent and inter-related factors that are vital for their existence and in maintaining the ecological balance. Various anthropogenic activities have impaired ecological conditions in many ecosystems. This monograph gives an account of the essentials in limnology, which helps in understanding the nature and extent of the problems and also provides an insight into the use of Geographic Information System as an effective tool for resource inventorying, monitoring and management. The monograph consists of four chapters, and the first one gives an overall view of the inland aquatic bodies as complex ecological systems. It begins with the formation of lakes, and the various physical, chemical and biological factors that determine these ecosystems. The physical factors covered include morphometry, density, light, etc., and the lake chemistry determined by various anions and cations are discussed in detail. The biological parameters include phytoplankton, zooplankton, waterfowl and fish communities that play an important role in freshwater biodiversity, and are presented with diagrams for easy understanding. The monograph gives an in depth view of the lake zones, productivity, and seasonal changes in the lake community with various energy relationships. The concept of food chain and food web in an aquatic ecosystem is also presented with illustrations. Lastly, the various anthropogenic activities that have deteriorated the quality of water are listed with the restoration strategies.

Updating reliability models of statically loaded instrumented structures

The study extends the first order reliability method (FORM) and inverse FORM to update reliability models for existing, statically loaded structures based on measured responses. Solutions based on Bayes' theorem, Markov chain Monte Carlo simulations, and inverse reliability analysis are developed. The case of linear systems with Gaussian uncertainties and linear performance functions is shown to be exactly solvable. FORM and inverse reliability based methods are subsequently developed to deal with more general problems. The proposed procedures are implemented by combining Matlab based reliability modules with finite element models residing on the Abaqus software. Numerical illustrations on linear and nonlinear frames are presented. (c) 2012 Elsevier Ltd. All rights reserved.

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.

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.

Measurement Based Impromptu Deployment of a Multi-Hop Wireless Relay Network

We study the problem of optimal sequential (''as-you-go'') deployment of wireless relay nodes, as a person walks along a line of random length (with a known distribution). The objective is to create an impromptu multihop wireless network for connecting a packet source to be placed at the end of the line with a sink node located at the starting point, to operate in the light traffic regime. In walking from the sink towards the source, at every step, measurements yield the transmit powers required to establish links to one or more previously placed nodes. Based on these measurements, at every step, a decision is made to place a relay node, the overall system objective being to minimize a linear combination of the expected sum power (or the expected maximum power) required to deliver a packet from the source to the sink node and the expected number of relay nodes deployed. For each of these two objectives, two different relay selection strategies are considered: (i) each relay communicates with the sink via its immediate previous relay, (ii) the communication path can skip some of the deployed relays. With appropriate modeling assumptions, we formulate each of these problems as a Markov decision process (MDP). We provide the optimal policy structures for all these cases, and provide illustrations of the policies and their performance, via numerical results, for some typical parameters.

Appraisal of observational method for consolidation analysis

Two of the aims of laboratory one-dimensional consolidation tests are prediction of the end of primary settlement, and determination of the coefficient of consolidation of soils required for the time rate of consolidation analysis from time-compression data. Of the many methods documented in the literature to achieve these aims, Asaoka's method is a simple and useful tool, and yet the most neglected one since its inception in the geotechnical engineering literature more than three decades ago. This paper appraises Asaoka's method, originally proposed for the field prediction of ultimate settlement, from the perspective of laboratory consolidation analysis along with recent developments. It is shown through experimental illustrations that Asaoka's method is simpler than the conventional and popular methods, and makes a satisfactory prediction of both the end of primary compression and the coefficient of consolidation from laboratory one-dimensional consolidation test data.

Regional hydrological impacts of climate change: implications for water management in India

Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

Global response sensitivity analysis of uncertain structures

The problem of characterizing global sensitivity indices of structural response when system uncertainties are represented using probabilistic and (or) non-probabilistic modeling frameworks (which include intervals, convex functions, and fuzzy variables) is considered. These indices are characterized in terms of distance measures between a fiducial model in which uncertainties in all the pertinent variables are taken into account and a family of hypothetical models in which uncertainty in one or more selected variables are suppressed. The distance measures considered include various probability distance measures (Hellinger,l(2), and the Kantorovich metrics, and the Kullback-Leibler divergence) and Hausdorff distance measure as applied to intervals and fuzzy variables. Illustrations include studies on an uncertainly parametered building frame carrying uncertain loads. (C) 2015 Elsevier Ltd. All rights reserved.

Boron clusters in luminescent materials

In recent times, luminescent materials with tunable emission properties have found applications in almost all aspects of modern material sciences. Any discussion on the recent developments in luminescent materials would be incomplete if one does not account for the versatile photophysical features of boron containing compounds. Apart from triarylboranes and tetra-coordinate borate dyes, luminescent materials consisting of boron clusters have also found immense interest in recent times. Recent studies have unveiled the opportunities hidden within boranes, carboranes and metalloboranes, etc. as active constituents of luminescent materials. From simple illustrations of luminescence, to advanced applications in LASERs, OLEDs and bioimaging, etc., the unique features of such compounds and their promising versatility have already been established. In this review, recent revelations about the excellent photophysical properties of such materials are discussed.

Global Response Sensitivity Analysis of Randomly Excited Dynamic Structures

The response of structural dynamical systems excited by multiple random excitations is considered. Two new procedures for evaluating global response sensitivity measures with respect to the excitation components are proposed. The first procedure is valid for stationary response of linear systems under stationary random excitations and is based on the notion of Hellinger's metric of distance between two power spectral density functions. The second procedure is more generally valid and is based on the l2 norm based distance measure between two probability density functions. Specific cases which admit exact solutions are presented, and solution procedures based on Monte Carlo simulations for more general class of problems are outlined. Illustrations include studies on a parametrically excited linear system and a nonlinear random vibration problem involving moving oscillator-beam system that considers excitations attributable to random support motions and guide-way unevenness. (C) 2015 American Society of Civil Engineers.