Variational Foundations and Generalized Unified Theory of RVE-Based Multiscale Models

A unified variational theory is proposed for a general class of multiscale models based on the concept of Representative Volume Element. The entire theory lies on three fundamental principles: (1) kinematical admissibility, whereby the macro- and micro-scale kinematics are defined and linked in a physically meaningful way; (2) duality, through which the natures of the force- and stress-like quantities are uniquely identified as the duals (power-conjugates) of the adopted kinematical variables; and (3) the Principle of Multiscale Virtual Power, a generalization of the well-known Hill-Mandel Principle of Macrohomogeneity, from which equilibrium equations and homogenization relations for the force- and stress-like quantities are unequivocally obtained by straightforward variational arguments. The proposed theory provides a clear, logically-structured framework within which existing formulations can be rationally justified and new, more general multiscale models can be rigorously derived in well-defined steps. Its generality allows the treatment of problems involving phenomena as diverse as dynamics, higher order strain effects, material failure with kinematical discontinuities, fluid mechanics and coupled multi-physics. This is illustrated in a number of examples where a range of models is systematically derived by following the same steps. Due to the variational basis of the theory, the format in which derived models are presented is naturally well suited for discretization by finite element-based or related methods of numerical approximation. Numerical examples illustrate the use of resulting models, including a non-conventional failure-oriented model with discontinuous kinematics, in practical computations.     

Degradation of organic dye using zero-valent iron prepared from by-product of pickling line

In this study, zero-valent iron (ZVI) was produced using iron oxide that is a by-product of a pickling line at a steel works. The reaction activity of the produced ZVI was evaluated through a series of decomposition experiments of Orange II aqueous solution. The size of ZVI particles increased with reduction temperature due to coalescence. Correspondingly, the specific surface area of ZVI decreased with increasing reduction temperature. The decomposition efficiency of synthesized ZVI particles was higher at a lower pH. In particular, no significant decomposition reaction was observed at pH of 4 and higher. The rate of the ZVI-assisted decomposition of Orange II was increased by addition of H2O2 at pH of 3, whereas it was reduced by addition of H2O2 at a higher pH of 6. Nevertheless, simultaneous use of ZVI, UV and H2O2 led to a considerable increase in the decomposition rate even at a high pH condition (pH = 6).     

Context-sensitive dependency pairs

Termination is one of the most interesting problems when dealing with context-sensitive rewrite systems. Although a good number of techniques for proving termination of context-sensitive rewriting (CSR) have been proposed so far, the adaptation to CSR of the dependency pair approach, one of the most powerful techniques for proving termination of rewriting, took some time and was possible only after introducing some new notions like collapsing dependency pairs, which are specific for CSR. In this paper, we develop the notion of context-sensitive dependency pair (CSDP) and show how to use CSDPs in proofs of termination of CSR. The implementation and practical use of the developed techniques yield a novel and powerful framework which improves the current state-of-the-art of methods for automatically proving termination of CSR.     

Autonomous motion planning of a hand-arm robotic system based on captured human-like hand postures

The paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions and trying to mimic real human hand postures. The approach uses the concept of “principal motion directions” to reduce the dimension of the search space in order to obtain results with a compromise between motion optimality and planning complexity (time). Basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a probabilistic roadmap planner. The approach has been implemented for a four finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) assembled on an industrial robot (6 independent degrees of freedom), and experimental examples are included to illustrate its validity.     

Non-invasive organization variation assessment in the onset and termination of paroxysmal atrial fibrillation

Atrial Fibrillation (AF) is the most common supraventricular tachyarrhythmia. Recently, it has been suggested that AF is partially organized on its onset and termination, thus being more suitable for antiarrhythmia and to avoid unnecessary therapy. Although several invasive and non-invasive AF organization estimators have been proposed, the organization time course in the first and last minutes of AF has not been quantified yet. The aim of this work is to study non-invasively the organization variation within the first and last minutes of paroxysmal AF. The organization was evaluated making use of sample entropy, which can robustly estimate electrical atrial activity organization from surface ECG recordings. This work proves an organization decrease in the first minutes of AF onset and an increase within the last minute before spontaneous AF termination. These results are in agreement with the conclusions reported by other authors who made use of invasive recordings.     

Design of interval observers for uncertain dynamical systems

Interval state observers provide an estimate on the set of admissible values of the state vector at each instant of time. Ideally, the size of the evaluated set is proportional to the model uncertainty, thus interval observers generate the state estimates with estimation error bounds, similarly to Kalman filters, but in the deterministic framework. Main tools and techniques for design of interval observers are reviewed in this tutorial for continuous-time, discrete-time and time-delayed systems.     

A note on interval observer design for unknown input estimation

This paper addresses the problem of interval observer design for unknown input estimation in linear time-invariant systems. Although the problem of unknown input estimation has been widely studied in the literature, the design of joint state and unknown input observers has not been considered within a set-membership context. While conventional interval observers could be used to propagate with some additional conservatism, unknown inputs by considering them as disturbances, the proposed approach allows their estimation. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Numerical simulations are presented to show the efficiency of the proposed approach.     

A neuro-genetic-simulated annealing approach to the inverse kinematics solution of robots: a simulation based study

In this study, a hybrid intelligent solution system including neural networks, genetic algorithms and simulated annealing has been proposed for the inverse kinematics solution of robotic manipulators. The main purpose of the proposed system is to decrease the end effector error of a neural network based inverse kinematics solution. In the designed hybrid intelligent system, simulated annealing algorithm has been used as a genetic operator to decrease the process time of the genetic algorithm to find the optimum solution. Obtained best solution from the neural network has been included in the initial solution of genetic algorithm with randomly produced solutions. The end effector error has been reduced micrometer levels after the implementation of the hybrid intelligent solution system.     

Environmental Fatigue and Static Behavior of RC Beams Strengthened with Carbon-Fiber-Reinforced Polymer

Many countries around the world have tremendous needs to repair and strengthen their transportation infrastructure. Almost everywhere, traffic loads have reached levels largely exceeding design expectations. Northern countries also experience severe winter conditions that are combined with an extensive use of deicing salts and accelerate structural deterioration. In Canada, the extent of deterioration has prompted many authorities, including the federal and provincial governments, to investigate the potential use of fiber-reinforced polymer products to extend the life of their existing structures. However, it is widely recognized that the large-scale implementation of these products is often impaired by the lack of data on their durability. This paper presents an experimental project undertaken in order to assess the durability of reinforced concrete beams externally strengthened with two types of carbon-fiber-reinforced polymer (CFRP). The beams were first exposed to either wet-dry cycles or continuous immersion in water and then were loaded in fatigue. Finally, they were tested quasi-statically under four-point bending up to failure. The test results presented here provide some insights on the potential long-term performance of CFRP-strengthened beams exposed to severe environmental conditions.     

Advanced and Intelligent Control Techniques Applied to the Drive Control and Path Tracking Systems on a Robotic Wheelchair

This paper presents the theoretical support and experimental results of the application of advanced and intelligent control techniques to the drive control and trajectory tracking systems on a robotic wheelchair. The adaptive optimal control of the differential drive helps to improve the automatic guidance system's safety and comfort taking into consideration operating conditions such as load and distribution changes or motion actuator limitations. Furthermore, the incorporation of an optimal controller to minimize location errors and a fuzzy controller to adapt the linear velocity to the characteristics of the trajectory, provide the vehicle with a high degree of intelligence and autonomy, even when faced with obstacles. The global control solution implemented increases the features of the wheelchair for handicapped people, especially for those with a high degree of disability.