Optimization of wastepaper sludge ash (WSA) in robust cementitious systems

Abstract : Wastepaper sludge ash (WSA) is generated by a cogeneration station by burning wastepaper sludge. It mainly consists of amorphous aluminosilicate phase, anhydrite, gehlenite, calcite, lime, C2S, C3A, quartz, anorthite, traces of mayenite. Because of its free lime content (~10%), WSA suspension has a high pH (13). Previous researchers have found that the WSA composition has poor robustness and the variations lead to some unsoundness for Portland cement (PC) blended WSA concrete. This thesis focused on the use of WSA in different types of concrete mixes to avoid the deleterious effect of the expansion due to the WSA hydration. As a result, WSA were used in making alkali-activated materials (AAMs) as a precursor source and as a potential activator in consideration of its amorphous content and the high alkaline nature. Moreover, the autogenous shrinkage behavior of PC concrete at low w/b ratio was used in order to compensate the expansion effect due to WSA. The concrete properties as well as the volume change were investigated for the modified WSA blended concrete. The reaction mechanism and microstructure of newly formed binder were evaluated by X-ray diffraction (XRD), calorimetry, thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). When WSA was used as precursor, the results showed incompatible reaction between WSA and alkaline solution. The mixtures were not workable and provided very low compressive strength no matter what kinds of chemical activators were used. This was due to the metallic aluminum in WSA, which releases abundant hydrogen gas when WSA reacts with strong alkaline solution. Besides, the results of this thesis showed that WSA can activate the glassy phase contained in slag, glass powder (GP) and class F fly ash (FFA) with an optimum blended ratio of 50:50. The WSA/slag (mass ratio of 50:50) mortar (w/b of 0.47) attained 46 MPa at 28 days without heat curing assistance. A significant fast setting was noticed for the WSA-activated binder due to the C3A phase, free lime and metallic aluminum contained in the WSA. Adding 5% of gypsum can delay the fast setting, but this greatly increased the potential risk of intern sulfate attack. The XRD, TGA and calorimetry analyses demonstrated the formation of ettringite, C-S-H, portlandite, hydrogarnet and calcium carboaluminate in the hydrated binder. The mechanical performance of different binder was closely related to the microstructure of corresponding binder which was proved by the SEM observation. The hydrated WSA/slag and WSA/FFA binder formed a C-A-S-H type of gel with lower Ca/Si ratio (0.47~1.6). A hybrid gel (i.e. C-N-A-S-H) was observed for the WSA/GP binder with a very low Ca/Si ratio (0.26) and Na/Si ratio (0.03). The SEM/EDX analyses displayed the formation of expansive gel (ettringite and thaumasite) in the gypsum added WSA/slag concrete. The gradual emission of hydrogen gas due to the reaction of WSA with alkaline environment significantly increased the porosity and degraded the microstructure of hydrated matrix after the setting. In the last phase of this research WSA-PC blended binder was tailored to form a high autogenous shrinkage concrete in order to compensate the initial expansion. Different binders were proportioned with PC, WSA, silica fume or slag. The microstructure and mechanical properties of concrete can be improved by decreasing w/b ratios and by incorporating silica fume or slag. The 28-day compressive strength of WSA-blended concrete was above 22 MPa and reached 45 MPa when silica fume was added. The PC concrete incorporating silica fume or slag tended to develop higher autogenous shrinkage at low w/b ratios, and thus the ternary binder with the addition of WSA inhibited the long term shrinkage due to the initial expansion property to WSA. In the restrained shrinkage test, the concrete ring incorporating the ternary binder (PC/WSA/slag) revealed negligible potential to cracking up to 96 days as a result of the offset effect by WSA expansion. The WSA blended regular concrete could be produced for potential applications with reduced expansion, good mechanical property and lower permeability.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

A structural method for the design of fault tolerant distributed control systems

Distributed digital control systems provide alternatives to conventional, centralised digital control systems. Typically, a modern distributed control system will comprise a multi-processor or network of processors, a communications network, an associated set of sensors and actuators, and the systems and applications software. This thesis addresses the problem of how to design robust decentralised control systems, such as those used to control event-driven, real-time processes in time-critical environments. Emphasis is placed on studying the dynamical behaviour of a system and identifying ways of partitioning the system so that it may be controlled in a distributed manner. A structural partitioning technique is adopted which makes use of natural physical sub-processes in the system, which are then mapped into the software processes to control the system. However, communications are required between the processes because of the disjoint nature of the distributed (i.e. partitioned) state of the physical system. The structural partitioning technique, and recent developments in the theory of potential controllability and observability of a system, are the basis for the design of controllers. In particular, the method is used to derive a decentralised estimate of the state vector for a continuous-time system. The work is also extended to derive a distributed estimate for a discrete-time system. Emphasis is also given to the role of communications in the distributed control of processes and to the partitioning technique necessary to design distributed and decentralised systems with resilient structures. A method is presented for the systematic identification of necessary communications for distributed control. It is also shwon that the structural partitions can be used directly in the design of software fault tolerant concurrent controllers. In particular, the structural partition can be used to identify the boundary of the conversation which can be used to protect a specific part of the system. In addition, for certain classes of system, the partitions can be used to identify processes which may be dynamically reconfigured in the event of a fault. These methods should be of use in the design of robust distributed systems.

The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.3760.10, mean 6 SD) and similar nestedness (NODF = 0.5660.12) than pollination networks. All networks were modular (M=0.32 +/- 0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55 +/- 0.10) and plants (R = 0.68 +/- 0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

Hair coloration by gene regulation: fact or fiction?

The unravelling of hair pigmentation genetics and robust delivery systems to the hair follicle (HF) will allow the development of a new class of colouring products. The challenge will be changing hair colour from inside out by safely regulating the activity of target genes through the specific delivery of synthetic/natural compounds, proteins, genes, or small RNAs.

Uncertainty Propagation in Model-Based Recognition

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

Enfoques para la gestión del riesgo sistémico

En el contexto organizacional actual, que se caracteriza por ser hiper-conectado, cambiante, globalizado y cargado de incertidumbre, la capacidad de las organizaciones para identificar y tratar provechosamente el riesgo se hace necesaria e ineludible. Dicho más claro: gestionar adecuadamente el riesgo se convierte en un aspecto crítico para la perdurabilidad de las organizaciones. Más allá de las comprensiones tradicionales del riesgo, cuyo núcleo es el riesgo financiero, nuevas tendencias –más generales y abarcadoras– se han gestado en las últimas décadas. Una de la más destacada es la gestión del riesgo sistémico. Pese a este reconocimiento, sin embargo, siguen predominando los enfoques analítico-financieros, sobre todo en el ámbito latinoamericano. Este trabajo de grado pretende, por tanto, hacer un análisis sobre la gestión del riesgo sistémico e identificar las diferentes tendencias del riesgo y sus potencialidades de cara al ambiente organizacional actual.

Haptic teleoperation of mobile robots for augmentation of operator perception in environments with low-wireless signal

Wireless teleoperation of field robots for maintenance, inspection and rescue missions is often performed in environments with low wireless connectivity, caused by signal losses from the environment and distance from the wireless transmitters. Various studies from the literature have addressed these problems with time-delay robust control systems and multi-hop wireless relay networks. However, such approaches do not solve the issue of how to present wireless data to the operator to avoid losing control of the robot. Despite the fact that teleoperation for maintenance often already involves haptic devices, no studies look at the possibility of using this existing feedback to aid operators in navigating within areas of variable wireless connectivity. We propose a method to incorporate haptic information into the velocity control of an omnidirectional robot to augment the operators perception of wireless signal strength in the remote environment. In this paper we introduce a mapping between wireless signal strength from multiple receivers to the force feedback of a 6 Degree of Freedom haptic master and evaluate the proposed approach using experimental data and randomly generated wireless maps

On stability in nonsequential MIMO QFT designs

This paper reexamines the stability of uncertain closed-loop systems resulting from the nonsequential (NS) MIMO QFT design methodology. By combining the effect of satisfying both the robust stability and robust performance specifications in a NS MIMO QFT design, a proof for the stability of the uncertain closed-loop system is derived. The stability theorem proves that, subject to the satisfaction of a critical necessary and sufficient condition, the original NS MIMO QFT design methodology will provide a robustly stable closed-loop system. This necessary and sufficient condition provides a useful existence test for a successful NS MIMO QFT design. The results expose the salient features of the NS MIMO QFT design methodology. Two 2 x 2 MIMO design examples are presented to illustrate the key features of the stability, theorem.

Robust state prediction for descriptor systems

This paper deals with the problem of state prediction for descriptor systems subject to bounded uncertainties. The problem is stated in terms of the optimization of an appropriate quadratic functional. This functional is well suited to derive not only the robust predictor for descriptor systems but also that for usual state-space systems. Numerical examples are included in order to demonstrate the performance of this new filter. (C) 2008 Elsevier Ltd. All rights reserved.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Online robust optimization framework for QoS guarantees in distributed soft real-time systems

In distributed soft real-time systems, maximizing the aggregate quality-of-service (QoS) is a typical system-wide goal, and addressing the problem through distributed optimization is challenging. Subtasks are subject to unpredictable failures in many practical environments, and this makes the problem much harder. In this paper, we present a robust optimization framework for maximizing the aggregate QoS in the presence of random failures. We introduce the notion of K-failure to bound the effect of random failures on schedulability. Using this notion we define the concept of K-robustness that quantifies the degree of robustness on QoS guarantee in a probabilistic sense. The parameter K helps to tradeoff achievable QoS versus robustness. The proposed robust framework produces optimal solutions through distributed computations on the basis of Lagrangian duality, and we present some implementation techniques. Our simulation results show that the proposed framework can probabilistically guarantee sub-optimal QoS which remains feasible even in the presence of random failures.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.