Continuous hydrogenation of vegetable oils in reactors equipped with static mixers

Continuous hydrogenation of industrially refined soybean oil with Harshaw Ni catalyst was achieved in a slurry column equipped with Sulzer SMV motionless mixers. The influence of the operating parameters (temperature, pressure, catalyst concentration and gas velocity) was investigated. The presumption that, in this equipment, the liquid-solid mass transfer limits the rate of the process is in good agreement with the experimental data.     

InSAR validation based on GNSS measurements in Bucharest

This research aims to complex validate radar displacement products over Bucharest based on Global Navigation Satellite System or GNSS. Validation was represented by the comparison of the recent TerraSAR-X (TSX) displacement results with field GNSS data. For this purpose, 24 and 27 high-resolution images acquired from the TSX satellite between 2011 and 2014 were processed by Permanent Scatterer Inteferometry (PSI) and Small BASeline Subset (SBAS) – interferometric techniques using synthetic aperture radar (SAR) images. The images were selected from a larger pool of SAR images, after consulting weather databases, which helped eliminate the images acquired under adverse weather conditions. GNSS locations were cross-checked on high-resolution optical images and 21 ground points (including three permanent stations) were selected. All these points were (1) characterized by high coherence on radar images; (2) were on the ground; (3) were situated in large vacant spaces; and (4) far away from radar obstacles such as trees. A major challenge in achieving the research goal was to overcome the lack of permanent stations at the ground level within the area of Bucharest. Instead of permanent stations, our team designed and installed forced centring systems that remained stable over time, eliminating the instalment errors of GNSS receivers. The line-of-site (LOS) components derived from GNSS data have been compared with those of the SAR scatterers closest to the GNSS markers (never coinciding). For each location, the vertical reading was projected in the LOS of the SAR sensor. These readings were compared with the displacement values determined at the locations of permanent scatterers (PSs) within 100 m from the GNSS nodes, by eliminating all scatterers on buildings. The comparison has shown a good agreement.     

The effect of chelating/combustion agent on catalytic activity and magnetic properties of Dy doped Ni–Zn ferrite

The spinel ferrite Ni_0.8Zn_0.2Fe_1.98Dy_0.02O₄ was prepared by sol–gel low temperature autocombustion method using four different chelating/combustion agents: citric acid, tartaric acid, urea and cellulose. Infrared spectroscopy (IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET) specific surface area measurement, the catalytic H₂O₂ decomposition and the magnetic behavior were employed to investigate the influence of the combustion agents on structural characteristics, catalytic activity and magnetic properties. Spinel-type phase in the nano-scale domain was accomplished during sol–gel synthesis and was confirmed by XRD and IR. The best catalytic activity is belonging to the sample obtained using urea, which shows the smallest grain size (SEM), the highest specific surface area (BET measurements) and DyFeO₃ phase (XRD), while ferrimagnetic behavior prevails for all the samples independently of fuel agent.     

Exact and efficient computation of moments of free-form surface and trivariate based geometry

Two schemes for computing moments of free-form objects are developed and analyzed. In the first scheme, we assume that the boundary of the analyzed object is represented using parametric surfaces. In the second scheme, we represent the boundary of the object as a constant set of a trivariate function. These schemes rely on a pre-computation step which allows fast re-evaluation of the moments when the analyzed object is modified. Both schemes take advantage of a representation that is based on the B-spline blending functions.     

Scan Test Strategy for Asynchronous-Synchronous Interfaces

In the coming years, the well-known synchronous design style will not be able to keep pace with the increase speed and capabilities of integration of advanced processes. New design paradigms, like core reuse of the already designed synchronous modules and asynchronous designs, are considered in order to cope with the ever increasing complexity. The future SoCs will contain multiple synchronous and asynchronous cores. Asynchronous design will become more and more common among digital designers, while synchronous-asynchronous interactions will emerge as a key issue in the future SoC designs.This paper will present test strategies for 2-phase asynchronous-synchronous interfaces and vice versa. It will be shown how test vectors can be automatically generated using commercially available ATPG tools. The generated ATPG vectors will be able to test all stuck-at-faults within the asynchronous-synchronous interfaces.     

Multibeam Optical System and Neural Processing for Turbidity Measurement

This paper presents a turbidity measuring system based on a modulated four infrared (IR) light beam architecture with advanced data processing. The turbidity sensing component consists of a pair of IR light-emitting diodes (LEDs) connected to a current drive controlled through the pulsewidth modulated (PWM) outputs of a multifunction input/output board. The scattered and transmitted IR light in the media under test is detected by a two-channel IR photodiode module that includes a set of transimpedance and programmable gain amplifier. The voltages proportional to the detectors' output currents, are acquired using a 12-bit ADC included in a microcontroller and RS232 transmitted to a laptop personal computer (PC) that works as an advanced control and processing unit. Using optimal neural network processing architectures, an accurate extraction of the turbidity information is performed. A practical approach concerning the neural network architectures [multilayer perceptron single-input-single-output (SISO), multiple-input-single-output (MISO)] including neural network training and testing is discussed in the paper. The multi-input architectures prove to be a robust and general solution for the proposed application. Results from a turbidity measuring system that was designed for automated standalone remote operation with sensing channel autocalibration capabilities are presented