Poly(vinylidene fluoride) with zinc oxide and carbon nanotubes applied to pressure sheath layers in oil and gas pipelines

In this work, PVDF composites containing 0.2% (m/m) of carbon nanotubes (MWCNTs), PVDF with 5.0% (m/m) of zinc oxide (ZnO), and composites containing both particles in the same contents in the matrix were melt processed in a mini-extruder machine with double screws, using the counter-rotation mode. Composites were characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (XRD), dynamic-mechanical analysis (DMA), and contact angle tests (CA). The samples presented the predominance of the α phase, with an increased degree of crystallinity as well as an increase in dimensional stability by incorporating both fillers, showing a synergistic effect between these particles, as shown on FTIR, DSC, and XRD results. SEM images showed a good dispersion of high aspect ratio particles. In general, DMA and TGA analysis showed that composites had not decreased their thermal and mechanical performance when compared to neat PVDF. Results of CA analysis showed an increase in the hydrophobicity of the sample containing MWCNTs. Permeability tests were also performed using a differential pressure system, combining high temperature and pressure, obtaining permeability measures and time lag. This work presents an alternative of composite materials, suggesting its application in the internal pressure sheath layers of oil and gas flexible pipes.     

Rheological,thermal and morphological properties of polyethylene terephthalate/polyamide 6/rice husk ash composites

This work deals with the rheological, morphological, and thermal properties of composites having poly(ethylene terephthalate) (PET), polyamide-6 (PA6), and their blends as matrices, and rice husk ash (RHA) as a filler. The study determines the effect of composition on the change in viscosity and rate of degradation during processing in a torque rheometer. Our data indicates that thermal stability and degradation during processing depend on matrix composition and filler concentration. SEM micrographs show both partial adhesion of the filler to the matrices and filler pullout. Optical microscopy shows particle agglomeration and that agglomerate size increased with filler content. FTIR investigates the shifting of absorption bands of PET/PA6 composite after the addition of RHA and attributes the selective dispersion of RHA to the formation of hydrogen bonds. Our data supports the idea that filler employed here is an option to develop polymer composites with improved properties.     

Effect of different surface treatments on polypropylene composites reinforced with yerba mate fibers: Physical,mechanical, chemical,and morphological properties

This study presents the preparation of post-consumer polypropylene (r-PP) composites filled with 30 wt% yerba mate (YM) stick particles. To improve the fiber–matrix adhesion, three surface treatments were performed: alkaline treatment with sodium hydroxide (NaOH) and use of 3-aminopropyltriethoxysilane (APTS) and maleic anhydride graft polypropylene copolymer (PP-g-MA) as coupling agents. Mechanical properties including tensile, flexural, and impact resistance were determined, and chemical (Fourier transform infrared spectroscopy [FTIR]), physical (water absorption), and morphological analyses were performed. The main findings show that the treatments were efficient in improving the mechanical properties of the composites, with emphasis on the r-PP/YM30/APTS and r-PP/YM30/PP-g-MA composites, which proved to be superior in tensile, flexion and impact strength and absorption of water compared to the untreated composite. The morphological analysis showed a better interaction between the fiber and the polymeric matrix for the composites with YM/APTS and YM/PP-g-MA, which corroborates the results of tensile and flexural strength, as well as with the spectra of FTIR in which the chemical modification of the fibers is observed. However, the results show that these treatments are promising in obtaining composites with recycled matrix with better properties.     

The effect of adding devulcanized rubber on the thermomechanical properties of recycled polypropylene

This work aims to investigate the effect of adding vulcanized or partially devulcanized rubbers on recycled polypropylene (PPr), considering thermomechanical and morphological properties. The study proposes to better understand how structural changes underwent by rubber (after the devulcanization) contributed to improving the mechanical properties of the PPr. The PPr/rubber blends were prepared by a co-rotating twin-screw extruder and then were injected. The blends composed of the most devulcanized rubbers by microwaves with refined microstructure showed higher values of elongation at break and toughness. Data showed that the devulcanization process applied to the rubber interfered positively in its adhesion to the PPr. Data from dynamic mechanical analysis and atomic force microscopy indicated that the most devulcanized rubbers presented an interface more connected to PPr. These chemical interactions possibly impacted the mechanical properties of the PPr. Moreover, dilatation processes favored the fracture mechanisms of the PPr when rubber was added to it.     

Graded plasma spraying of premixed metalceramic powders on metallic substrates

The mismatch between the thermal expansion coefficients of ceramics and metals and the differential stresses it causes at the interface create problems in metal to ceramic joining. Research has been con-ducted to solve this problem in thermal barrier coating technology. Previous studies have considered met-al-ceramic multilayers or graded-coatings, which include a metallic bond coat. In this study, a graded plasma-sprayed metal-ceramic coating is developed using the deposition of premixed metal and ceramic powders without the conventional metallic bond coat. Influences of thickness variations, number, and composition of the layers are investigated. Coatings are prepared by atmospheric plasma-spraying on In-conel 718 superalloy substrates. Ni-Cr-Al and ZrO₂ -8 % Y₂O₃ powders are used for plasma spraying. Ad-hesive and cohesive strength of the coatings are determined. The concentration profile of the elements is determined by x-ray energy-dispersive analysis. The microstructure and morphology of the coatings are investigated by optical and scanning electron microscopy (SEM). Results show that the mixed metal-ce-ramic coating obtained with the deposition of premixed powders is homogeneous. The morphology and microstructure of the coatings are considered satisfactory.     

Elastic modulus measurements via laser-ultrasonic and knoop indentation techniques in thermally sprayed coatings

Nondestructive techniques for evaluating and characterizing coatings were extensively demanded by the thermal spray community; nonetheless, few results have been produced in practice due to difficulties in analyzing the complex structure of thermal spray coatings. Of particular interest is knowledge of the elastic modulus values and Poisson’s ratios, which are very important when seeking to understand and/or model the mechanical behavior or to develop life prediction models of thermal spray coatings used in various applications (e.g., wear, fatigue, and high temperatures). In the current study, two techniques, laser-ultrasonics and Knoop indentation, were used to determine the elastic modulus of thermal spray coatings. Laser-ultrasonics is a noncontact and nondestructive evaluation method that uses lasers to generate and detect ultrasound. Ultrasonic velocities in a material are directly related to its elastic modulus value. The Knoop indentation technique, which has been widely used as a method for determining elastic modulus values, was used to compare and validate the measurements of the laser-ultrasonic technique. The determination of elastic modulus values via the Knoop indentation technique is based on the measurement of elastic recovery of the dimensions of the Knoop indentation impression. The approach used in the current study was to focus on evaluating the elastic modulus of very uniform, dense, and near-isotropic titania and WC-Co thermal spray coatings using these two techniques. Four different coatings were evaluated: two titania coatings produced by air plasma spray (APS) and high-velocity oxyfuel (HVOF) and two types of WC-Co coatings, conventional and multimodal (nanostructured and microsized particles), deposited by HVOF. The original version of this article was published as part of the ASM Proceedings, Thermal Spray 2003: Advancing the Science and Applying the Technology, International Thermal Spray Conference (Orlando, FL), 5–8 May, 2003, Basil R. Marple and Christian Moreau, Eds., ASM International, 2003.     

Real-time lane tracking using Rao-Blackwellized particle filter

A novel approach to real-time lane modeling using a single camera is proposed. The proposed method is based on an efficient design and implementation of a particle filter which applies the concepts of the Rao-Blackwellized particle filter (RBPF) by separating the state into linear and non-linear parts. As a result the dimensionality of the problem is reduced, which allows the system to perform in real-time in embedded systems. The method is used to determine the position of the vehicle inside its own lane and the curvature of the road ahead to enhance the performance of advanced driver assistance systems. The effectiveness of the method has been demonstrated implementing a prototype and testing its performance empirically on road sequences with different illumination conditions (day and nightime), pavement types, traffic density, etc. Results show that our proposal is capable of accurately determining if the vehicle is approaching the lane markings (Lane Departure Warning), and the curvature of the road ahead, achieving processing times below 2 ms per frame for laptop CPUs, and 12 ms for embedded CPUs.     

Spectroscopic Multicomponent Analysis Using Multi-objective Optimization for Variable Selection

The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.     

QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: Implications for control and land use management

In the Galapagos Islands of Ecuador, one of the greatest threats to the terrestrial ecosystem is the increasing number and areal extent of invasive species. Increased human presence on the islands has hastened the introduction of plant and animal species that threaten the native and endemic flora and fauna. Considerable research on invasive species in the Galapagos Islands has been conducted by the Charles Darwin Foundation. We complement that work through a spatially- and spectrally-explicit satellite assessment of an important invasive plant species (Psidium guajava — guava) on Isabela Island that integrates diverse remote sensing systems, data types, spatial and spectral resolutions, and analytical and image processing approaches. QuickBird and Hyperion satellite data are processed to characterize the areal extent and spatial structure of guava through the following approaches: (1) QuickBird data are classified through a traditional pixel-based approach (i.e., an unsupervised classification approach using the ISODATA algorithm), as well as an Object-Based Image Analysis (OBIA) approach; (2) multiple approaches for spectral “unmixing” of the Hyperion hyper-spectral data are assessed to construct spectral end-members from QuickBird data using linear and non-linear mixture modeling approaches; and (3) landscape pattern metrics are calculated and compared for the pixel-based, object-based, and spectral unmixing approaches. The spectral–spatial characteristics of guava are interpreted relative to management strategies for the control of guava and the restoration of natural ecosystems in the Galapagos National Park.     

Algorithm based on simulated annealing for land-use allocation

This article describes the use of simulated annealing for allocation of land units to a set of possible uses on, the basis of their suitability for those uses, and the compactness of the total areas allotted to the same use or kind of use, which are fixed a priori. The results obtained for the Terra Chá district of Galicia (N.W. Spain) using different objective weighting schemes are compared with each other and with those obtained for this district under the same area constraints, using hierarchical optimization, ideal point analysis, and multi-objective land allocation (MOLA) to maximize average use suitability. Inclusion of compactness in the simulated annealing objective function avoids the highly disperse allocations typical of optimizations that ignore this sub-objective.