961 resultados para predictive performance


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The effect of Pigment Volume Content (PVC) on fungal growth on acrylic paint formulations with and without biocide, exposed to weathering in three different climatic regions in Brazil for four years, was studied Latex paints. with PVC of 30%, 35% and 50%, were applied to autoclaved aerated concrete blocks pre-covered with acrylic sealer and acrylic plaster They were exposed to equatorial, tropical and temperate climates in north, south-east, and south Brazil Cladosporium was the most abundant fungal genus detected in the biofilm on the surfaces of all paint formulations at all sites after four years Heaviest fungal colonization occurred in the tropical south-east and lightest in the temperate south of the country, but more phototrophs, principally cyanobacteria, were detected in the equatorial region PVC and presence of biocides were shown to be of less importance than environmental conditions (irradiance, humidity and temperature) for biofilm formation and consequent discolouration These results have important implications for testing of paint formulations (C) 2010 Elsevier B V All rights reserved

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The purpose of this study is to investigate the thermal performance of cool colored acrylic paints containing infrared reflective pigments in comparison to conventional colored acrylic paints of similar colors (white, brown and yellow) applied on sheets of corrugated fiber cement roofing. Evaluated properties are: color according to ASTM D 2244-89, the UV/VIS/NIR reflectance according to ASTM E 90396, and thermal performance by exposure to infrared radiation emitted from a lamp with the measurement of surface temperatures of the specimens with thermocouples connected to a data logging system. Results demonstrated that the cool colored paint formulations produced significantly higher NIR reflectance than conventional paints of similar colors, and that the surface temperatures were more than 10 degrees C lower than those of conventional paints when exposed to infrared radiation. The study shows that cool paints enhance thermal comfort inside buildings, which can reduce air conditioning costs. (C) 2009 Elsevier B.V. All rights reserved.

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The single phase induction motors needs two stator windings to produce rotating magnetic field : one main winding and the other auxiliary winding. The aim of the auxiliary winding is to create the rotating electromagnetic field when the machine is started-up and is afterwards turned off, generally through the centrifugal switch coupled together with the shaft of the machine rotor. The main purpose of this document is to evaluate the influence that the two windings have on the external characteristics of the single phase induction motor. For this purpose, two different kinds of windings were carried out and simulated, with the proposal to obtain some benefits. The main winding and the auxiliary winding were prepared and mounted on a prototype. The simulation was done via software based FEM, to make the extraction and results analysis possible. This results are shown at the end this document.

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This article presents a tool for the allocation analysis of complex systems of water resources, called AcquaNetXL, developed in the form of spreadsheet in which a model of linear optimization and another nonlinear were incorporated. The AcquaNetXL keeps the concepts and attributes of a decision support system. In other words, it straightens out the communication between the user and the computer, facilitates the understanding and the formulation of the problem, the interpretation of the results and it also gives a support in the process of decision making, turning it into a clear and organized process. The performance of the algorithms used for solving the problems of water allocation was satisfactory especially for the linear model.

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The properties of recycled aggregate produced from mixed (masonry and concrete) construction and demolition (C&D) waste are highly variable, and this restricts the use of such aggregate in structural concrete production. The development of classification techniques capable of reducing this variability is instrumental for quality control purposes and the production of high quality C&D aggregate. This paper investigates how the classification of C&D mixed coarse aggregate according to porosity influences the mechanical performance of concrete. Concretes using a variety of C&D aggregate porosity classes and different water/cement ratios were produced and the mechanical properties measured. For concretes produced with constant volume fractions of water, cement, natural sand and coarse aggregate from recycled mixed C&D waste, the compressive strength and Young modulus are direct exponential functions of the aggregate porosity. Sink and float technique is a simple laboratory density separation tool that facilitates the separation of cement particles with lower porosity, a difficult task when done only by visual sorting. For this experiment, separation using a 2.2 kg/dmA(3) suspension produced recycled aggregate (porosity less than 17%) which yielded good performance in concrete production. Industrial gravity separators may lead to the production of high quality recycled aggregate from mixed C&D waste for structural concrete applications.

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The therapeutic ultrasound (US) is one of the resources mostly used by physiotherapists; however the use of uncalibrated equipments results in inefficient or even harmful therapies to the patient. In this direction, the objective of this study was to evaluate the performance and the procedures of utilization and maintenance of US in use in clinics and Physical-therapy offices. A questionnaire with questions related to the procedures applied in service during the use of therapeutic ultrasound was applied to physiotherapists. The performance of 31 equipments of 6 different brands and 13 different models was evaluated according to the IEC 61689 norm. The parameters measured were: acoustic power; effective radiating area (AER); non-uniformity ratio of the beam (RBN); maximum effective intensity; acoustic frequency of operation, modulation factor and wave form on pulsate mode. As for the questionnaires, it was evident that the professionals are not concerned about the calibration of the equipment. The results demonstrated that only 32.3% of the equipments were in accordance with the norms for the variables power and effective radiation area. The frequency analysis indicated that 20% of the 3 MHz transducers and 12.5% of the 1 MHz contemplated the norms. In the pulsate mode, 12.7% presented relation rest/duration inside allowed limits. A great variation of the ultrasonic field was observed on the obtained images, which presented beams not centered, sometimes with bifurcation of its apex. The results allow concluding that, although used in therapeutic sessions with the population, none of the equipments presents all the analyzed variables inside technical norms. (C) 2010 Elsevier B. V. All rights reserved.

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High-density polyethylene resins have increasingly been used in the production of pipes for water- and gas-pressurized distribution systems and are expected to remain in service for several years, but they eventually fail prematurely by creep fracture. Usual standard methods used to rank resins in terms of their resistance to fracture are expensive and non-practical for quality control purposes, justifying the search for alternative methods. Essential work of fracture (EWF) method provides a relatively simple procedure to characterize the fracture behavior of ductile polymers, such as polyethylene resins. In the present work, six resins were analyzed using the EWF methodology. The results show that the plastic work dissipation factor, beta w(p), is the most reliable parameter to evaluate the performance. Attention must be given to specimen preparation that might result in excessive dispersion in the results, especially for the essential work of fracture w(e).

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The 475 degrees C embrittlement in stainless steels is a well-known phenomenon associated to alpha prime (alpha`) formed by precipitation or spinodal decomposition. Many doubts still remain on the mechanism of alpha` formation and its consequence on deformation and fracture mechanisms and corrosion resistance. In this investigation, the fracture behavior and corrosion resistance of two high performance ferritic stainless steels were investigated: a superferritic DIN 1.4575 and MA 956 superalloy were evaluated. Samples of both stainless steels (SS) were aged at 475 degrees C for periods varying from 1 to 1,080 h. Their fracture surfaces were observed using scanning electron microscopy (SEM) and the cleavage planes were determined by electron backscattering diffraction (EBSD). Some samples were tested for corrosion resistance using electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization. Brittle and ductile fractures were observed in both ferritic stainless steels after aging at 475 degrees C. For aging periods longer than 500 h, the ductile fracture regions completely disappeared. The cleavage plane in the DIN 1.4575 samples aged at 475 degrees C for 1,080 h was mainly {110}, however the {102}, {314}, and {131} families of planes were also detected. The pitting corrosion resistance decreased with aging at 475 degrees C. The effect of alpha prime on the corrosion resistance was more significant in the DIN 1.4575 SS comparatively to the Incoloy MA 956.

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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.

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This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

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A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

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This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables - possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

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In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.

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Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.