A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

Modeling, control and experimental validation of a novel actuator based on shape memory alloys

The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.

Development of Control Systems for Safety Instrumented Systems

Safety Instrumented Systems (SIS) are designed to prevent and / or mitigate accidents, avoiding undesirable high potential risk scenarios, assuring protection of people`s health, protecting the environment and saving costs of industrial equipment. The design of these systems require formal methods for ensuring the safety requirements, but according material published in this area, has not identified a consolidated procedure to match the task. This sense, this article introduces a formal method for diagnosis and treatment of critical faults based on Bayesian network (BN) and Petri net (PN). This approach considers diagnosis and treatment for each safety instrumented function (SIF) including hazard and operability (HAZOP) study in the equipment or system under control. It also uses BN and Behavioral Petri net (BPN) for diagnoses and decision-making and the PN for the synthesis, modeling and control to be implemented by Safety Programmable Logic Controller (PLC). An application example considering the diagnosis and treatment of critical faults is presented and illustrates the methodology proposed.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

Effect of nitrogen on the corrosion-erosion synergism in an austenitic stainless steel

High temperature gas nitrided AISI 304L austenitic stainless steel containing 0.55 wt% N in solid solution, was corrosion, erosion and corrosion-erosion tested in a jet-like device, using slurry composed of 3.5% NaCl and quartz particles. Scanning electron microscopy analysis of the damaged surfaces, mass loss measurements and electrochemical test results were used to understand the effect of nitrogen on the degradation mechanisms. Increasing the nitrogen content improved the corrosion, erosion and corrosion-erosion resistance of the AISI 304L austenitic stainless steel. Smoother wear mark contours observed on the nitrided surfaces indicate a positive effect of nitrogen on the reduction of the corrosion-erosion synergism. (C) 2011 Elsevier Ltd. All rights reserved.

Improvement of the cavitation erosion resistance of UNS S31803 stainless steel by duplex treatment

A duplex surface treatment consisting of High Temperature Gas Nitriding (HTGN) followed by Low Temperature Plasma Nitriding (LTPN) was carried out in an UNS S31803 duplex stainless steel. The HTGN treatment was intended to produce a relatively thick and hard fully austenitic layer giving mechanical support to the thinner and much harder expanded austenite layer. HTGN was performed at 1200 degrees C for 3 h, in a 0.1 MPa N(2) atmosphere while LTPN, was carried out in a 75% N(2) + 25% H(2) atmosphere, at 400 degrees C for 12 h, under a 250 Pa pressure, and 450 V. An expanded austenite gamma(N) layer, 2.3 mu m thick, 1500 HVO.025 hard, was formed on top of a 100 mu m thick, 330 HV 0.1 hard, fully austenitic layer, containing 0.9 wt% N. For comparison purposes LTPN was carried out with UNS S30403 stainless steel specimens obtaining a 4.0 mu m thick, 1500 HV 0.025 hard, expanded austenite layer formed on top of a fully austenitic matrix having 190 HV 0.1. The nitrided specimens were tested in a 20 kHz vibratory cavitation-erosion testing equipment. Comparison between the duplex treated UNS S31803 steel and the low temperature plasma nitrided UNS S30403 steel, resulted in incubation times almost 9 times greater. The maximum cavitation wear rate of the LTPN UNS S30403 was 5.5 g/m(2)h, 180 times greater than the one measured for the duplex treated UNS S31803 steel. The greater cavitation wear resistance of the duplex treated UNS S31803 steel, compared to the LTPN treated UNS S30403 steel was explained by the greater mechanical support the fully austenitic, 330 HV 0.1 hard, 100 mu m layer gives to the expanded austenite layer formed on top of the specimen after LTPN. A strong crystallographic textured surface, inherited from the fully austenitic layer formed during HTGN, with the expanded austenite layer showing {101} crystallographic planes//surface contributed also to improve the cavitation resistance of the duplex treated steel. (C) 2010 Elsevier B.V. All rights reserved.

Assessment of the cavitation erosion resistance in high nitrogen austenitic stainless steels: study of the wear mechanisms

Specimens of a UNS S31803 steel were submitted to high temperature gas nitriding and then to vibratory pitting wear tests. Nitrided samples displayed fully austenitic microstructures and 0.9 wt. % nitrogen contents. Prior to pitting tests, sample texture was characterized by electron backscattering diffraction, EBSD. Later on, the samples were tested in a vibratory pit testing equipment using distilled water Pitting tests were periodically interrupted to evaluate mass loss and to characterize the surface wear by SEM observations. At earlier pit erosion, stages intense and highly heterogeneous plastic deformation inside individual grains was observed. Later on, after the incubation period, mass loss by debris detachment was observed. Initial debris micro fracturing was addressed to low cycle fatigue. Damage started at both sites, inside the grains and grain boundaries. The twin boundaries were the most prone to mass-loss incubation. Grains with (101) planes oriented near parallel to the sample surface displayed higher wear resistance than grains with other textures. This was attributed to lower resolved stresses for plastic deformation inside the grains with (101)

Erosion-fatigue of steam turbine blades

The premature failure of steam turbine rotor blades, manufactured in forged 12% Cr-NiMoV martensitic stainless steel, was investigated using visual inspection non-destructive testing, macro and microfractography, microstructural characterization, EDS microanalysis, chemical analysis, micro hardness and tensile testing. The blades belonged to the last stage of a thermoelectric plant steam turbine generator (140 MV A). The results indicated that the failure of the blades was promoted by foreign-particle erosion, which attacked preferentially the low-pressure side of the lower trailing edge of the blades. The resulting wear grooves acted as stress raisers and promoted the nucleation of fatigue cracks, which probably grew during the transition events of the steam turbine operation. Finally, water drop erosion was observed on the blade upper leading edge (low-pressure side). (C) 2009 Elsevier Ltd. All rights reserved.

EROSION-CORROSION SYNERGISM OF AN AISI 410 MARTENSITIC STAINLESS STEEL

In this work, the behavior of an AISI 410 martensitic stainless steel under corrosion-erosion conditions is evaluated. Quenched and tempered samples were used for the wear test, using a low velocity jet-like device connected to a potentiostat. Potentiodynamic polarization curves were obtained with the electrolyte in static state, with flow conditions and under corrosion-erosion, adding quartz particles to the electrolyte. In addition, mass loss measurements under erosion and corrosion-erosion conditions were carried out. The topography of the surfaces was examined after the wear tests, using optical and scanning electron microscopy. This information, together with the results of mass losses and the electrochemical tests were used to establish the degradation mechanisms of the stainless steels under different testing conditions. The results showed that synergism is a significant part of the degradation process of this steel (66.5%) and that the mass removal process of steel was controlled by corrosion assisted by erosion.

Mesoscale plasticity anisotropy at the earliest stages of cavitation-erosion damage of a high nitrogen austenitic stainless steel

A high nitrogen austenitic stainless steel (0.9wt% N) and an ordinary 304 austenitic stainless steel were submitted to cavitation-erosion tests in a vibratory apparatus operating at a frequency of 20 kHz. The high nitrogen stainless steel was obtained by high temperature gas nitriding a 1-mm thick strip of an UNS 31803 duplex stainless steel. The 304 austenitic stainless steel was used for comparison purposes. The specimens were characterized by scanning electron microscopy and Electron Back Scatter Diffraction. The surface of the cavitation damaged specimens was analyzed trying to find out the regions where cavitation damage occurred preferentially. The distribution of sites where cavitation inception occurred was extremely heterogeneous, concentrating basically at (i) slip lines inside some grains and (ii) Sigma-3 coincidence site lattice (CSL) boundaries (twin boundaries). Furthermore, it was observed that the CE damage spread faster inside those grains which were more susceptible to damage incubation. The damage heterogeneity was addressed to plasticity anisotropy. Grains in which the crystallographic orientation leads to high resolved shear stress show intense damage at slip lines. Grain boundaries between grains with large differences in resolved shear stress where also intensely damaged. The relationship between crystallite orientation distributions, plasticity anisotropy and CE damage mechanisms are discussed. (C) 2009 Elsevier B.V. All rights reserved.

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.

Real time optimization (RTO) with model predictive control (MPC)

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.

Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 Elsevier Ltd. All rights reserved.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

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.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.