Corrosion Versus Mechanical Tests for Indirect Detection of Alpha Prime Phase in UNS S32520 Super Duplex Stainless Steel

Alpha prime formation leads to material embrittlement and deterioration of corrosion resistance. In the present study, the mechanical and corrosion behavior of super duplex stainless steel UNS S32520 aged at 475 degrees C from 0.5 h to 1,032 h was evaluated using microhardness measurements, Charpy impact tests, electrochemical impedance spectroscopy, and cyclic polarization curves. The sensibility of these tests to the effects of alpha prime phase was investigated. The microhardness test showed a gradual increase in hardness with aging time, whereas the impact tests revealed losses of about 80% in the energy absorption capacity for the material aged for 12 h in comparison with the solution-annealed samples. The most responsive analysis was the impact test, which indirectly revealed the presence of this deleterious phase in samples aged for 0.5 h. The electrochemical impedance spectroscopy and polarization tests were not highly sensitive to the alpha prime phase unless these are present in large amounts in the stainless steel.

Quantification of MgO surface excess on the SnO(2) nanoparticles and relationship with nanostability and growth

In this work, we experimentally showed that the spontaneous segregation of MgO as surface excess in MgO doped SnO(2) nanoparticles plays an important role in the system`s energetics and stability. Using Xray fluorescence in specially treated samples, we quantitatively determined the fraction of MgO forming surface excess when doping SnO(2) with several different concentrations and established a relationship between this amount and the surface energy of the nanoparticles using the Gibbs approach. We concluded that the amount of Mg ions on the surface was directly related to the nanoparticles total free energy, in a sense that the dopant will always spontaneously distribute itself to minimize it if enough diffusion is provided. Because we were dealing with nanosized particles, the effect of MgO on the surface was particularly important and has a direct effect on the equilibrium particle size (nanoparticle stability), such that the lower the surface energy is, the smaller the particle sizes are, evidencing and quantifying the thermodynamic basis of using additives to control SnO(2) nanoparticles stability. (C) 2010 Elsevier B.V. All rights reserved.

Influence of the rubbery phase on the crystallinity and thermomechanical properties of poly(3-hydroxybutyrate)/elastomer blends

Poly(3-hydroxybutyrate) (PHB) is a very promising biopolymer. In order to improve its processability and decrease its brittleness, PHB/elastomer blends can be prepared. In the work reported, the effect of the addition of a rubbery phase, i.e. ethylene - propylene-diene terpolymer (EPDM) or poly(vinyl butyral) (PVB), on the properties of PHB was studied. The effects of rubber type and of changing the PHB/elastomer blend processing method on the crystallinity and physical properties of the blends were also investigated. For blends based on PHB, the main role of EPDM is its nucleating effect evidenced by a decrease of crystallization temperature and an increase of crystallinity with increasing EPDM content regardless of the processing route. While EPDM has a weak effect on PHB glass transition temperature, PVB induces a marked decrease of this temperature thank to its plasticizer that swells the PHB amorphous phase. A promising solution to improve the mechanical properties of PHB seems to be the melt-processing of PHB with both plasticizer and EPDM. In fact, the plasticizer is more efficient than the elastomer in decreasing the PHB glass transition temperature and, because of the nucleating effect of EPDM, the decrease of the PHB modulus due to the plasticizer can be counterbalanced. (C) 2010 Society of Chemical Industry

Interface Energy Measurement of MgO and ZnO: Understanding the Thermodynamic Stability of Nanoparticles

Nanomaterials have triggered excitement in both fundamental science and technological applications in several fields However, the same characteristic high interface area that is responsible for their unique properties causes unconventional instability, often leading to local collapsing during application Thermodynamically, this can be attributed to an increased contribution of the interface to the free energy, activating phenomena such as sintering and grain growth The lack of reliable interface energy data has restricted the development of conceptual models to allow the control of nanoparticle stability on a thermodynamic basis. Here we introduce a novel and accessible methodology to measure interface energy of nanoparticles exploiting the heat released during sintering to establish a quantitative relation between the solid solid and solid vapor interface energies. We exploited this method in MgO and ZnO nanoparticles and determined that the ratio between the solid solid and solid vapor interface energy is 11 for MgO and 0.7 for ZnO. We then discuss that this ratio is responsible for a thermodynamic metastable state that may prevent collapsing of nanoparticles and, therefore, may be used as a tool to design long-term stable nanoparticles.

Precipitation of Laves phase in a 28%Cr-4%Ni-2%Mo-Nb superferritic stainless steel

The main objective of the present work was to study the precipitation of the Laves phase in the X1 CrNiMoNb 28 4 2 (Werkstoff-Nr. DIN 1.4575) superferritic stainless steel employing several complementary techniques of microstructural analysis. The phase that precipitated in largest quantity in the DIN 1.4575 steel was the sigma (sigma) phase. However, along grain boundaries, after aging at 850 degrees C, a Laves phase of the MgZn2 type, with a hexagonal C14 crystal structure and chemical composition (Fe,Cr,Ni)(2)(Nb,Mo,Si), was also identified. Growth of the Laves phase is curtailed by exhaustion of niobium of the matrix and by the presence of the sigma phase, which also precipitates in the vicinity of the grain boundaries, however in larger amounts. No chi (chi) or austenite phases were detected in the temperature range studied. (C) 2007 Elsevier Inc. All rights reserved.

Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Solid-liquid phase equilibrium modeling of triacylglycerol mixtures is essential for lipids design. Considering the alpha polymorphism and liquid phase as ideal, the Margules 2-suffix excess Gibbs energy model with predictive binary parameter correlations describes the non ideal beta and beta` solid polymorphs. Solving by direct optimization of the Gibbs free energy enables one to predict from a bulk mixture composition the phases composition at a given temperature and thus the SFC curve, the melting profile and the Differential Scanning Calorimetry (DSC) curve that are related to end-user lipid properties. Phase diagram, SFC and DSC curve experimental data are qualitatively and quantitatively well predicted for the binary mixture 1,3-dipalmitoyl-2-oleoyl-sn-glycerol (POP) and 1,2,3-tripalmitoyl-sn-glycerol (PPP), the ternary mixture 1,3-dimyristoyl-2-palmitoyl-sn-glycerol (MPM), 1,2-distearoyl-3-oleoyl-sn-glycerol (SSO) and 1,2,3-trioleoyl-sn-glycerol (OOO), for palm oil and cocoa butter. Then, addition to palm oil of Medium-Long-Medium type structured lipids is evaluated, using caprylic acid as medium chain and long chain fatty acids (EPA-eicosapentaenoic acid, DHA-docosahexaenoic acid, gamma-linolenic-octadecatrienoic acid and AA-arachidonic acid), as sn-2 substitutes. EPA, DHA and AA increase the melting range on both the fusion and crystallization side. gamma-linolenic shifts the melting range upwards. This predictive tool is useful for the pre-screening of lipids matching desired properties set a priori.

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.

Phase equilibria of lysozyme precipitation with the volatile salt ammonium carbamate

Lysozyme precipitation induced by the addition of the volatile salt ammonium carbamate was studied through cloud-point measurements and precipitation assays. Phase equilibrium experiments were carried out at 5.0, 15.0 and 25.0 degrees C and the compositions of the coexisting phases were determined. A complete separation of the coexisting liquid and solid phases could not be achieved. Nevertheless it was possible to determine the composition of the solid precipitate through the extensions of experimental tie lines. The same precipitate was found at all temperatures. Lysozyme enzymatic activities of the supernatant and precipitate phases were also determined. The activity balance suggests that ammonium carbamate preserves lysozyme activity after the salting-out precipitation. (C) 2010 Elsevier B.V. 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.

Phase equilibria for salt-induced lysozyme precipitation: Effect of salt type and temperature

The salt-induced precipitation of lysozyme from aqueous solutions was studied through precipitation assays in which the equilibrium compositions of the coexisting phases were determined. Lysozyme precipitation experiments were carried out at 5, 15 and 25 degrees C and pH 7.0 with ammonium sulfate, sodium sulfate and sodium chloride as precipitating agents. In these experiments a complete separation of the coexisting phases (liquid and solid) could not be achieved. Nevertheless it was possible to determine the composition of the precipitate. The enzymatic activity of lysozyme in the supernatant phase as well as in the precipitate phase was also determined. The activity balance suggests that there is a relationship between the composition of the true precipitate and the total activity recovery. (C) 2009 Elsevier B.V. All rights reserved.

Liquid-Liquid Equilibrium of Aqueous Two-Phase Systems Containing Some Synthetic Polyelectrolytes and Polyethylene Glycol

Experimental results are presented for the liquid-liquid equilibrium of aqueous two-phase systems containing a synthetic polyelectrolyte (polysodium acrylate, polysodium methacrylate, and polysodium ethylene sulfonate) and polyethylene glycol at (298.2 and 323.2) K. A total of 40 phase diagrams were obtained, comprising data both of the binodal curve (obtained through cloud-point measurements) and of equilibrium compositions. The influences of temperature, the nature of the polyelectrolyte monomer unit, and the chain length of both types of polymers are analyzed and discussed.

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.

A stable MPC with zone control

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.