Linked Simulation-Optimization based Dedicated Monitoring Network Design for Unknown Pollutant Source Identification using Dynamic Time Warping Distance

Implementation of monitoring strategy for increasing the efficiency of groundwater pollutant source characterization is often necessary, especially when only inadequate and arbitrary concentration measurement data are initially available. Two main parameters that need to be estimated for efficient and accurate characterization of groundwater pollution sources are: location of the source and the time when the source became active. Complexities involved with the explicit estimation of the time of start and source activity have not been addressed so far in previous studies. The main complexity arises due to the fact that the spatial location and time of activity are inter-related. Therefore, specifying one and solving for the other simplifies the source characterization problem. Hence, in this study, both the source location and time of initiation are treated as unknowns. The developed methodology uses dynamic time warping distance in the linked simulation-optimization model to address some complex issues in designing a monitoring network to efficiently estimate source characteristics including the time of first activity of unknown groundwater source. Performance of the developed methodology is evaluated on illustrative contaminated aquifer. These evaluation results demonstrate the potential use of the developed methodology.     

Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources

The identification of unknown pollution sources is a prerequisite for designing of a remediation strategy. In most of the real world situations, it is difficult to identify the pollution sources without a scientifically designed efficient monitoring network. The locations of the contaminant concentration measurement sites would determine the efficiency of the unknown source identification process to a large extent. Therefore coupled and iterative sequential source identification and dynamic monitoring network design framework is developed. The coupled approach provides a framework for necessary sequential exchange of information between monitoring network and source identification methodology. The preliminary identification of unknown sources, based on limited concentration data from existing arbitrarily located wells provides the initial rough estimate of the source fluxes. These identified source fluxes are then utilized for designing an optimal monitoring network for the first stage. Both the monitoring network and source identification process is repeated by sequential identification of sources and design of monitoring network which provides the feedback information. In the optimal source identification model, the Jacobian matrix which is the determinant for the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. For the optimal monitoring network design, the integer programming based optimal design model requires as input, simulated sets of concentration data. In the proposed methodology, the concentration measurement data from the designed and implemented monitoring network are used as feedback information for sequential identification of unknown pollution sources. The potential applicability of the developed methodology is demonstrated for an illustrative study area.     

Simplified Impedance Model for Adhesively Bonded Piezo-Impedance Transducers

The electromechanical impedance technique employs surface-bonded lead zirconate titanate piezoelectric ceramic patches as impedance transducers for structural health monitoring and nondestructive evaluation. The patches are bonded to the monitored structures using finitely thick adhesive bond layer, which introduces shear lag effect, thus invariably influencing the electromechanical admittance signatures. This paper presents a new simplified impedance model to incorporate shear lag effect into electromechanical admittance formulations, both one-dimensional and two-dimensional. This provides a closed-form analytical solution of the inverse problem, i.e. to derive the true structural impedance from the measured conductance and susceptance signatures, thus an improvement over the existing models. The influence of various parameters (associated with the bond layer) on admittance signatures is investigated using the proposed model and the results compared with existing models. The results show that the new model, which is far simpler than the existing models, models the shear lag phenomenon reasonably well besides providing direct solution of a complex inverse problem.     

Modelling of a downdraft biomass gasifier with finite rate kinetics in the reduction zone

A model of a downdraft gasifier has been developed based on chemical equilibrium in the pyro‐oxidation zone and finite rate kinetic‐controlled chemical reactions in the reduction zone. The char reactivity factor (C_RF) in the reduction zone, representing the number of active sites on the char and its degree of burn out, has been optimized by comparing the model predictions against the experimental results from the literature. The model predictions agree well with the temperature distribution and exit gas composition obtained from the experiments at C_RF=100. A detailed parametric study has been performed at different equivalence ratios (between 2 and 3.4) and moisture content (in the range of 0–40%) in the fuel to obtain the composition of the producer gas as well as its heating value. It is observed that the heating value of the producer gas increases with the increase in the equivalence ratio and decrease in the biomass moisture content. The effect of divergence angle of the reduction zone geometry (in the range of 30–150°) on the temperature and species concentration distributions in the gasifier has been studied. An optimum divergence angle, giving the best quality of the producer gas, has been identified for a particular height of the reduction zone. Copyright © 2009 John Wiley & Sons, Ltd.     

Zincated Nanoclay Polymer Composites (ZNCPCs): Synthesis,Characterization, Biodegradation and Controlled Release Behaviour in Soil

Novel zincated nanoclay polymer composites (ZNCPCs) with variable percentage of commercial bentonite and nanobentonite (8%, 10% and 12% of monomer for each case) were synthesized. Polyacrylic acid-Polyacrylamide copolymer was synthesized using N, N-Methylene bisacrylamide as crosslinker and ammonium persulfate as initiator. Clays as well as ZNCPCs were characterized by XRD, SEM, TEM and FTIR. 12% nanoclay containing formulation showed slowest release rate. ZNCPCs containing 8% clay recorded highest Zn content as well as highest equilibrium water absorbency. Biodegradation study revealed that Aspergillus spp was more effective as compared with Trichoderma spp in degradation of ZNCPCs.     

Robust and minimum norm partial quadratic eigenvalue assignment in vibrating systems: A new optimization approach

The partial quadratic eigenvalue assignment problem (PQEVAP) concerns reassigning a few undesired eigenvalues of a quadratic matrix pencil to suitably chosen locations and keeping the other large number of eigenvalues and eigenvectors unchanged (no spill-over). The problem naturally arises in controlling dangerous vibrations in structures by means of active feedback control design. For practical viability, the design must be robust, which requires that the norms of the feedback matrices and the condition number of the closed-loop eigenvectors are as small as possible. The problem of computing feedback matrices that satisfy the above two practical requirements is known as the Robust Partial Quadratic Eigenvalue Assignment Problem (RPQEVAP). In this paper, we formulate the RPQEVAP as an unconstrained minimization problem with the cost function involving the condition number of the closed-loop eigenvector matrix and two feedback norms. Since only a small number of eigenvalues of the open-loop quadratic pencil are computable using the state-of-the-art matrix computational techniques and/or measurable in a vibration laboratory, it is imperative that the problem is solved using these small number of eigenvalues and the corresponding eigenvectors. To this end, a class of the feedback matrices are obtained in parametric form, parameterized by a single parametric matrix, and the cost function and the required gradient formulas for the optimization problem are developed in terms of the small number of eigenvalues that are reassigned and their corresponding eigenvectors. The problem is solved directly in quadratic setting without transforming it to a standard first-order control problem and most importantly, the significant “no spill-over property” of the closed-loop eigenvalues and eigenvectors is established by means of a mathematical result. These features make the proposed method practically applicable even for very large structures. Results on numerical experiments show that the proposed method considerably reduces both feedback norms and the sensitivity of the closed-loop eigenvalues. A study on robustness of the system responses of the method under small perturbations show that the responses of the perturbed closed-loop system are compatible with perturbations.     

A study on dynamic rheological characterisation of electron beam crosslinked high vinyl styrene butadiene styrene block copolymer

Crosslinking of elastomers using electron beam radiation has several advantages over conventional method. It is accomplished much faster, in a more environmental friendly approach and in a much simpler manner. When fast moving electrons that are generated from electron accelerators are targeted on a polymer matrix, they primarily crosslink the polymer. However, in the process, some chain scission may also occur. In this work, a high vinyl (~50%) styrene–butadiene–styrene (S–B–S) block copolymer was used as the base polymer. Radiation doses were varied from 25 to 300 kGy. A detailed investigation was made to understand the effect of electron beam radiation on the rheological properties such as storage modulus, loss modulus, storage viscosity and complex viscosity of the block copolymer under strain and frequency sweeps performed in a Rubber Process Analyzer (RPA). Recyclability of the crosslinked S–B–S polymer was also explored by RPA and mechanical studies.     

Microfabrication and characterization of metal-embedded thin-film thermomechanical microsensors for applications in hostile manufacturing environments

Effective monitoring and diagnosis of manufacturing processes is of critical importance. If critical manufacturing process conditions are continuously monitored, problems can be detected and solved during the processing cycle. However, current technology still evidently lags behind practical needs. Microfabricated thin-film thermocouples and strain gauges are attractive for their small size and fast response. It is challenging to fabricate and embed these sensors into metallic components that are widely used in manufacturing. This paper investigates the fabrication, embedding, and characterization of metal embedded thin-film thermocouples and strain gauges. The materials (dielectric and metallic) constituting a complete microsensor were characterized and optimized. The results obtained from characterization and optimization of materials are presented and discussed. Thin-film thermocouples on stainless steel substrates (before and after embedding) were calibrated to elevated temperatures. The behavior of thin-film strain gauges was also studied. The metal embedded sensors demonstrated good accuracy, sensitivity, and linearity that matched the performance of commercial thermocouples and strain gauges well. The metal embedded microsensors are promising for in situ monitoring in hostile manufacturing environments.