Experimental study of back‐scattering spectrum of textile structures

The back‐scattered light by textile surfaces mainly depends on their surface state, which is often periodic and directional. The analysis of the reflectance spectra in back‐scattering conditions of two types of structures (yarn, plain and twill weaves) shows the influence of the orientation of these surfaces as well as the back‐scattered angle. In fact, the declination of the yarn orientation in relation to the incidence plane involves an increase of the reflectance factor to reach a maximum value when the yarns are perpendicular to this plane. For woven fabrics, the back‐scattering of surface according to a given orientation primarily depends on its geometrical characteristic in this direction and consequently the used yarn densities. The computation of the ratio of mean quadratic surface roughness h to correlation length l for various used orientations shows the close link between this parameter and the evolution of back‐scattering. The effect of the variation of back‐scattered angle on the back‐scattered light varies with the value of h/l . The comparison between these experimental results and a theoretical study based on Gaussian and isotropic surfaces shows a satisfactory correlation between these two elements with the presence of some cases of discrepancy due to the different natures of the two types of surfaces. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 122–132, 2006     

Influence of surface roughness on the diffuse to near‐normal viewing reflectance factor of coatings and its consequences on color measurements

In this work, we discuss the effect of surface roughness on the measurement of the diffuse to near‐normal viewing reflectance factor of coatings and evaluate its impact on the corresponding color coordinates. We compare specular component included (SCI) and excluded measurements. We introduce a gloss‐factor to account for surface roughness in specular component excluded measurements. We present experimental results on samples with different degrees of surface roughness. Samples in this study were chosen to expose the contribution of the surface in the reflectance factor. For slightly rough surfaces, the influence on the measured reflectance factor depends on whether the specular‐component is included or excluded. As the surface roughness increases, the specular‐excluded reflectance factor increases approaching its value with the SCI further roughness lead to similar measurement results in both configurations. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 177–187, 2013.     

Droplet velocity,size, and local holdup measurements in an extraction column by tri‐sensor optical probe

The tri‐sensor optical probe was applied to study the hydrodynamic characteristic in a pulsed sieve plate extraction column. Two immiscible liquids consisting of the dispersed phase (kerosene) and continuous phase (water) were introduced in countercurrent operation. Local parameters such as droplet velocity, drop size, and holdup of the dispersed phase were obtained. It was found that the tri‐sensor optical probe could be used as an efficient and convenient technique for measuring local hydrodynamic parameters inside the pulsed sieve plate extraction column. Furthermore, the results indicated that pulsation intensity imposed more influence on these hydrodynamic parameters than two‐phase superficial flow rates in the investigated ranges. Experimental results were found to be in good agreement with the empirical correlations reported in literature. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3958–3963, 2015     

Diffuse reflectance‐factor measurements of rose petals

The diffuse reflectance factor for different colored rose petals is measured as a function of wavelength using a high resolution optical spectrometer. The tristimulus values, the CIE chromaticity coordinates, the dominant wavelength and purity, the CIE whiteness index, the tint index, the CIE 1976 LAB coordinates, as well as CIELAB hue‐angle and chroma are reported. The data on diffuse reflectance factor are presented in the 390?800 nm range at intervals of 10 nm. Using the data, one can generate the perceived color of the roses and the color coordinates in different illuminating light sources and environments. The present data will be useful for the color characterization of flowers, realistic rendering of flowers in computer graphics, color photography, and in the development of filters for color photography. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Healthier lipid combination oil‐in‐water emulsions prepared with various protein systems: an approach for development of functional meat products

Five protein‐stabilized oil‐in‐water emulsions were prepared using sodium caseinate (O/SC), soy protein isolate (O/SPI), sodium caseinate and microbial transglutaminase (O/SC + MTG), sodium caseinate, microbial transglutaminase and meat slurry (O/SC + MTG + MS) and SPI, sodium caseinate and microbial transglutaminase (O/IPS + SC + MTG); their composition (proximate analysis and fatty acid profile) and physicochemical characteristics were examined. The lipid phase was a combination of healthy fatty acids from olive, linseed and fish oils, containing low proportions (15%) of saturated fatty acids (SFA) and high proportions of monounsaturated fatty acids (MUFA, 47%) and polyunsaturated fatty acids (PUFA, 36%), with a PUFA/SFA ratio >2, and a n‐6/n‐3 PUFA ratio of 0.4. All the oil‐in‐water emulsions showed high thermal and creamy stability. Results of penetration test and dynamic rheological properties showed la existencia de different types of oil‐in‐water emulsion structures according to stabilizing system of emulsion. Those structures ranged from concentrate solution‐like (stabilized only with SC) (gel strength 0.06 mJ) to gel‐like (samples containing MTG) behaviours (gel strength ranged between 3.4 and 6.2 mJ). Morphological differences in the organization of the network structure were observed (by scanning electron microscopy) as functions of the protein system used to stabilize the oil‐in‐water emulsions.     

Bubble size and velocity measurement in gas—liquid systems: Application of fiber optic technique to pilot plant scale

A new fiber optic probe was developed for the detection and measurement of bubble sizes and velocities in a gas-liquid column. The probe is made of a single 1 mm plastic fiber with a sharp wedge tip. The calibration was carried out on a laboratory scale unit using a cine-photographic technique to verify the measurements. Bubble velocities were calculated using two identical parallel fibers and the cross-correlation technique. With the velocities and the passage time determined, it was then possible to determine the bubble diameter. Bubble diameters were within 10% of the measurements obtained with the cine-photographic technique. After calibration, measurements were carried out on a pilot scale unit.     

Water content of light n‐alkanes: New measurements and cubic‐plus‐association equation of state modeling

Light hydrocarbon gases such as methane, ethane, propane, and butane or other so called gaseous solvents have been suggested as steam additives to improve bitumen recovery and energy efficiency. The water content of these gases is one of the key requirements in the simulation and design of solvent‐aided thermal heavy oil recovery processes. In this work, we present new experimental data for the water content of these gases at high temperatures (up to 493.15 K) and moderate pressures (P < 6 MPa). The experimental data was regenerated using the cubic‐plus‐association equation of state. The Soave–Redlich–Kwong equation of state is used to treat the physical interactions. The association interactions are captured using Wertheim's first‐order thermodynamic perturbation theory. A set of binary interaction parameters is proposed to calculate the water content of methane, ethane, propane, and n‐butane at the operating conditions of the thermal heavy oil and bitumen recovery processes. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1384–1389, 2017     

Thermal behaviour of polyethylene‐block‐poly(methyl methacrylate) block copolymer: effect of multiple heating and cooling rates versus mathematical artefact

The melting and crystallization behaviours of a polyethylene‐block‐poly(methyl methacrylate) (PE‐b‐PMMA) diblock copolymer and a PE homopolymer were investigated using multiple heating and cooling rate differential scanning calorimetry (DSC) experiments, and modelling of the crystallization kinetics and lamellar thickness distribution. This new model was first validated applying literature and experimental data. The model‐predicted morphology (n = 3.2) closely matched the spherulitic morphology (n = 3), which was determined using polarized optical microscopy. For each experimental cooling rate, the model predicted diblock copolymer crystallinity that well matched the entire DSC crystallinity curve, notably for an Avrami–Erofeev index of n = 2; and apparent crystallization activation energy that hardly varied with the cooling rates used, relative crystallinity (α), and crystallization temperature or time. This disfavours the concept of variable activation energy. The use of the right crystallization model and parameter estimation algorithm is important for addressing the mathematical artefact. Under non‐isothermal cooling, the PE‐b‐PMMA diblock copolymer, as per the model prediction, crystallized without confinement (n ≠ 1), preserving the cylindrical structure. From the characteristic shapes of the crystallization function f(α(T)) versus 1/T and crystallization rate versus α plots, the resulting T_cmax and narrow α_max range can guide the search for an appropriate crystallization model. The overall treatment illustrated in this study is not restricted to a PE homopolymer and a PE‐b‐isotactic PMMA block copolymer. It can be generally applied to crystalline homopolymers and copolymers (alternating, random and block), as well as their blends. The block copolymers and blends can be crystalline–amorphous as well as crystalline–crystalline. © 2014 Society of Chemical Industry