Analysis of chill-cast NiAl intermetallic compound with copper additions

This study carried out a characterization of chill-cast NiAl alloys with copper additions, which were added to NiAl, such that the resulting alloy composition occurred in the β-field of the ternary NiAlCu phase diagram. The alloys were vacuum induction melted and casted in copper chill molds to produce ingots 0.002 m thick, 0.020 m wide, and 0.050 m long. X-ray diffractometry (XRD) and transmission electron microscopy (TEM) performed in chill-cast ingots identified mainly the presence of the β-(Ni,Cu)Al phase. As-cast ingots showed essentially no ductility at room temperature except for the Ni₅₀Al₄₀Cu₁₀ alloy, which showed 1.79% of elongation at room temperature. Ingots with this alloy composition were then heat treated under a high-purity argon atmosphere at 550 °C (24 h) and cooled either in the furnace or in air, until room temperature was reached. β-(Ni,Cu)Al and γ′(Ni,Cu)₃Al were present in specimens cooled in the furnace and β-(Ni,Cu)Al, γ′(Ni,Cu)₃Al plus martensite-(Ni,Cu)Al were present in specimens cooled in air. Thermogravimetric analysis indicated that martensite transformation was the result of a solid-state reaction with M _s ∼ 470 and M _f ∼ 430 °C. Tensile tests performed on bulk heat-treated ingots showed room-temperature ductility between 3 and 6%, depending on the cooling media.     

Margarines: A rheological study

Time-dependent flow properties of both commercial and pilot plant-made margarines were characterized under steady shear. Flow curves were fitted to the kinetic expression τ = τ _i +a e ^−k1t +b e ^−k2t . A first-order kinetic model did not describe the observed destruction process of the margarine structure in an adequate manner. In the proposed model, two structures with different destruction rates are postulated. Each structure contributes to a part of the shear stress necessary to deform the margarine sample. The parameters τ _i a andb are temperature-dependent. Decreasing temperatures produce an exponential increase of τ _i , a linear increase ofb and an increase ofa up to a point beyond which it remains constant. A physical interpretation of the model is proposed. The role of the aqueous phase was also studied. Greater hardness was detected at higher water content. Parameter τ _i increased, at any selected temperature, with increasing aqueous phase content of the sample. Parametera increased with decreasing temperatures and higher water content. On the other hand, parameterb was not affected by the amount of aqueous phase. This kinetic model could be employed to perform studies on the influence of different parameters of margarine formulation on its rheologic behavior.     

<Emphasis Type="Italic">In situ</Emphasis> monitoring of solid fat content by means of pulsed nuclear magnetic resonance spectrometry and ultrasonics

An ultrasonic technique was developed to study the crystallization process of edible fats on-line. A chirp wave was used instead of the conventional pulser signal, thus achieving a higher signal-to-noise ratio. This enabled measurements to be made in concentrated systems [≈20% solid fat content (SFC)] through a 8.11-cm thick sample without significant signal loss. Fat samples were crystallized at 20, 25, and 30°C at a constant agitation rate of 400 rpm for 90 min. The crystallization process was followed by ultrasonic spectroscopy and a low-resolution pulsed nuclear magnetic resonance spectrometer. Specific relationships were found between ultrasonic parameters [integrated response, time of flight (TF), and full width half maximum] and SFC. TF, which is an indirect measurement of the ultrasonic velocity (v), was highly correlated to SFC (r ²>0.9) in a linear fashion (v=2.601 SFC+1433.0).     

Off-line optimization and control for real time integration of a three-phase hydrogenation catalytic reactor

In order to develop and test the integration procedure, in this paper a real time process integration involving the optimization and control of the process is presented, in this case, with the two-layer approach. The used optimization algorithms were Levenberg–Marquardt and SQP that solve a non-linear least square problem subject to bounds on the variables. The two-layer approach is a hierarchical control structure where an optimization layer calculates the set points and manipulated variables to the advanced controller, which is based on the dynamic matrix control with constraints (QDMC). The non-isothermal dynamic model of the three-phase slurry catalytic reactor with appropriate solution procedure was utilized in this work (Vasco de Toledo, E. C., Santana, P. L., Maciel, M. R. W., & Maciel Filho, R. (2001). Dynamic modeling of a three-phase catalytic slurry reactor. Chemical Engineering Science, 56, 6055–6061). The model consists on mass and heat balance equations for the catalyst particles as well as for the bulk phases of gas and liquid. The model was used to describe the dynamic behavior of hydrogenation reaction of o-cresol to obtain 2-methil-cyclohexanol, in the presence of a catalyst Ni/SiO₂.     

Electro-chemical chloride extraction: Influence of C3A of the cement on treatment efficiency

The aim of this study was to clarify whether the C₃A content of cement had a significant effect on electrochemical chloride extraction (ECE) treatment efficiency. It is known that a higher C₃A content in a cement gives it superior chloride complexing ability resulting in the formation of an “insoluble” calcium chloro aluminate compound.ECE was applied using cylindrical specimens made from concrete containing two levels of C₃A (4.3% and 9.05%). Specimens were 5 cm in diameter and 10 cm in height. Steel was placed in the axial direction with an embedded length of 7 cm. These specimens were immersed in an NaCl solution and dried in a stream of air at 40 °C for 10 months. The corrosion was monitored by half-cell potential and polarization resistance measurements. After steel depassivation, ECE was applied for 20, 30, 40 and 50 days using a constant current density of 1 A/m² of steel. At the end of the treatment, the specimens were maintained at 20 °C and 70% RH in order to observe the evolution of the steel (electrochemical measurements).The results show that, after 30 days of treatment, the chloride content remained constant in the specimen. This was probably due to OH⁻ ion formation on the steel. The OH⁻ ions “contribute” to the current transport, decreasing the ECE efficiency. Concerning the C₃A content, ECE efficiency was slightly affected by C₃A because only a part of the bound chloride ions was released. From the point of view of corrosion, half-cell potential showed a shift in the positive direction, indicating little corrosion activity at 20 °C and 70% RH. However, polarization resistance measurements showed that 2 months post treatment corrosion rates were significant, although the corrosion rate decreased from 6 μA/cm² to 2.5 μA/cm².     

Synthesis of nanodispersed oxides of vanadium, titanium, molybdenum, and tungsten on mesoporous silica using atomic layer deposition

The advantages of the atomic layer deposition (ALD) method for preparation of tungsten, vanadium, titanium, and molybdenum oxide catalyst supported on mesoporous silica are discussed, with emphasis on the importance of synthesis conditions on dispersion, structure and activity of the resulting materials. A suite of complementary techniques such as DRS-UV/Vis, BET, ¹H-NMR, XRD, and TEM were used to study the structural properties of the supported metal oxides, and probe reactions such as 2-butanol dehydration and ethanol partial oxidation were used to demonstrate the potential advantages of the ALD-prepared catalysts. Specifically, highly dispersed oxides of titanium, molybdenum, and tungsten oxide on mesoporous silica were synthesized using the ALD method. It is also demonstrated that attainment of high dispersions of vanadium oxide on mesoporous silica requires the presence of at least a single layer of titanium oxide due to the well-known poor interaction between vanadia and silica. The highly dispersed catalysts prepared here by ALD methods exhibited superior catalytic performance relative to those prepared using conventional incipient wetness impregnation.     

Modeling the Direct Synthesis of Dimethyl Ether using Artificial Neural Networks

Artificial neural networks (ANNs) are designed and implemented to model the direct synthesis of dimethyl ether (DME) from syngas over a commercial catalyst system. The predictive power of the ANNs is assessed by comparison with the predictions of a lumped model parameterized to fit the same data used for ANN training. The ANN training converges much faster than the parameter estimation of the lumped model, and the predictions show a higher degree of accuracy under all conditions. Furthermore, the simulations show that the ANN predictions are also accurate even at some conditions beyond the validity range.     

Improving data fusion in personal positioning systems for outdoor environments

A fault detection and correction methodology for personal positioning systems for outdoor environments is presented. We demonstrate its successful use in a system consisting of a global positioning system receiver and an inertial measurement unit. Localization is based on the dead reckoning algorithm. In order to obtain more reliable information from data fusion, which is carried out with Kalman filtering, the proposed methodology involves: (1) evaluation of the information provided by the sensors and (2) adaptability of the filtering. By carefully analyzing these factors we accomplish fault detection in different sources of information and in filtering. This allows us to apply corrections whenever the system requires it. Hence, our methodology consists of two stages. In the first stage, the evaluation is conducted. We apply the principles of causal diagnosis using possibility theory by defining states for normal behavior and for fault states. When a fault occurs, corrective measures are applied according to empirical knowledge. In the second stage, the consistency test of the filtering is performed. If this is inconsistent, principles of adaptive Kalman filtering are applied, which means the process and measurement noise matrices are tuned. Our results indicate a reasonable improvement of the trajectory obtained. At the same time, we can achieve consistent filtering, to obtain a more robust system and reliable information.