CFD modeling of solid-liquid fluidized beds of mono and binary particle mixtures

CFD simulation of bed expansion of mono size solid-liquid fluidized beds has been performed in creeping, transition and turbulent flow regimes, where Reynolds number (Re_∞=d_pV_S∞ρ_L/μ_L) has been varied from 0.138 to 1718. It has been observed that the predicted values of bed voidage using the drag law of Joshi [1983. Solid-liquid fluidized beds: some design aspects. Chemical Engineering Research and Design 61, 143-161] and Pandit and Joshi [1998. Pressure drop in packed, expanded and fluidized beds, packed columns and static mixers—a unified approach. Reviews in Chemical Engineering 14, 321-371] (which has been derived from the first principals), exhibited an excellent agreement with the Richardson and Zaki equation. CFD simulations have also been performed for the prediction of segregation and/or intermixing of binary particle systems having the ratio of terminal settling velocity over a range from 3.2 to 1.06. The Reynolds number has also been varied over the range of 0.33 to 2080. It has been observed that the present CFD model explains all the qualitative and quantitative observations reported in the published literature (complete segregation, partial segregation, complete intermixing, etc) and these predictions are in good agreement with the experimental results. The present CFD model also predicts successfully the layer inversion phenomena which occur in the binary particle mixtures of different size as well as density. Further, the critical velocity at which the complete mixing of the two particle species occurs has also been predicted.     

Dispersion,migration, and ‘network‐like’ structure formation of multiwall carbon nanotubes in co‐continuous,binary immiscible blends of polyamide 6 and acrylonitrile–butadiene–styrene copolymer during simultaneous melt‐mixing

Multiwall carbon nanotubes (MWNTs) were melt‐mixed in polyamide 6 (PA6) and acrylonitrile–butadiene–styrene (ABS) copolymer blends using a simultaneous mixing protocol in order to investigate the state of dispersion of MWNTs in PA6/ABS blends. The blend composition was varied from 40/60 (wt/wt) to 60/40 (wt/wt) in PA6/ABS blends, which showed ‘co‐continuous’ morphology in the presence of MWNTs. State of dispersion of MWNTs in these blends was assessed through bulk electrical conductivity measurements, morphological analysis, solution experiments, and UV‐vis spectroscopic analysis. MWNTs were subsequently modified with a novel organic modifier, sodium salt of 6‐aminohexanoic acid (Na‐AHA), to improve the state of dispersion of MWNTs. Blends with unmodified MWNTs exhibited the DC electrical conductivity in the range ～10^?11 to ～10^?5 S/cm, whereas blends with Na‐AHA‐modified MWNTs exhibited DC electrical conductivity in the range ～10^?7 to ～10^?5 S/cm. The reduction in MWNTs ‘agglomerate’ size (～73.7 μm for 40/60 blend with unmodified MWNTs to ～59.9 μm in the corresponding blend with Na‐AHA‐modified MWNTs) was observed through morphological analysis. The rheological studies showed increased complex viscosity and storage moduli in lower frequency region in case of blends with Na‐AHA‐modified MWNTs confirming a refined ‘network‐like’ structure of MWNTs. POLYM. ENG. SCI., 55:443–456, 2015. © 2014 Society of Plastics Engineers     

Hot wire chemical vapor deposited multiphase silicon carbide (SiC) thin films at various filament temperatures

Influence of filament temperature (T_Fil) on the structural, morphology, optical and electrical properties of silicon carbide (SiC) films deposited by using hot wire chemical vapor deposition technique has been investigated. Characterization of these films by low angle XRD, Raman scattering, XPS and TEM revealed the multiphase structure SiC films consisting of 3C–SiC and graphide oxide embedded in amorphous matrix. FTIR spectroscopy analysis show an increase in Si–C, Si–H, and C–H bond densities and decrease in hydrogen content with increase in T_Fil. The C–H bond density was found higher than the of Si–H and Si–C bond densities suggesting that H preferably get attached to C than Si. AFM investigations show decrease in rms surface roughness and grain size with increase in T_Fil. SEM studies show that films deposited at low T_Fil has spherulites-like morphology while at high T_Fil has cauliflower-like structure. Band gap values E_Tauc and E₀₄ increases from 1.76 to 2.10 eV and from 1.80 to 2.21 eV respectively, when T_Fil was increased from 1500 to 2000 °C. These result show increase in band tail width (E₀₄–E_Tauc) of multiphase SiC films. Electrical properties revealed that σ_Dark increases from ~7.87 × 10^?10 to 1.54 × 10^?5 S/cm and E_act decreases from 0.67 to 0.41 eV, which implies possible increase in unintentional doping of oxygen or nitrogen due to improved crystallinity and Si–C bond density with increase in T_Fil. The deposition rate for the films was found moderately high (21 < r_dep < 30 Å/s) over the entire range of T_Fil studied.     

UHT Milk Processing and Effect of Plasmin Activity on Shelf Life: A Review

Abstract: The demand for ultra‐high‐temperature (UHT) processed and aseptically packaged milk is increasing worldwide. A rise of 47% from 187 billion in 2008 to 265 billon in 2013 in pack numbers is expected. Selection of UHT and aseptic packaging systems reflect customer preferences and the processes are designed to ensure commercial sterility and acceptable sensory attributes throughout shelf life. Advantages of UHT processing include extended shelf life, lower energy costs, and the elimination of required refrigeration during storage and distribution. Desirable changes taking place during UHT processing of milk such as destruction of microorganisms and inactivation of enzymes occur, while undesirable effects such as browning, loss of nutrients, sedimentation, fat separation, cooked flavor also take place. Gelation of UHT milk during storage (age gelation) is a major factor limiting its shelf life. Significant factors that influence the onset of gelation include the nature of the heat treatment, proteolysis during storage, milk composition and quality, seasonal milk production factors, and storage temperature. This review is focused on the types of age gelation and the effect of plasmin activity on enzymatic gelation in UHT milk during a prolonged storage period. Measuring enzyme activity is a major concern to commercial producers, and many techniques, such as enzyme‐linked immunosorbent assay, spectrophotometery, high‐performance liquid chromatography, and so on, are available. Extension of shelf life of UHT milk can be achieved by deactivation of enzymes, by deploying low‐temperature inactivation at 55 °C for 60 min, innovative steam injection heating, membrane processing, and high‐pressure treatments.     

An improved detection of blind image forgery using hybrid deep belief network and adaptive fuzzy clustering

Blind image forgery prediction in the field of image forgery is difficult. Hence, it is the major attention for the investigators recently. This work introduces an innovative methodology for blind image forgery detection. The steps are described as: initially, input images are pre-processed using hybrid homomorphic filtering to enhance the images. After pre-processing images, features such as Hybrid Speeded up Robust features and scale-invariant feature transform (hybrid SURF-SIFT) and hybrid wavelet features are extracted. According to the extracted features hybrid deep belief neural network (HDBN) framework performs the block matching to examine the forgery region in images. Here, modified atom search optimization is utilized for weights optimization in HDBN framework and improving the performance of matching process. The HDBN framework detects non matching regions, and finally, the forgery region is accurately localized with the presented Adaptive fuzzy clustering based improved sun flower optimization (AFCSO) approach. The implementation platform used in work is PYTHON. The presented technique is tested with three datasets: CG-1050, SMIFD, and Coverage. Moreover, the experimental results of the presented approach is examined with the existing techniques in regard to accuracy, precision, recall, F-measure, True positive rate, False positive rate, True negative rate, and False-negative rate. The performance measures of forgery detection with CG-1050 dataset is F-measure (98.98%), Accuracy (99%), recall (98%), precision (99.9%), True positive rate (99.5%), False positive rate (0.4%), True negative rate (99.7%), False negative rate (2%). The performance measures of forgery detection with SMIFD dataset is F-measure (99.15%), True positive rate (99.57%), Accuracy (98.67%), precision (99.57%), false-positive rate (1.56%), True negative rate (98.43%), and false-negative rate (1.25%). The performance measures of forgery detection with COVERAGE dataset is F-measure (98%), True positive rate (98%), False positive rate (2%), Accuracy (98.3%), precision (97.1%), True negative rate (98%), False negative rate (2%). This proved that the presented approach outperforms the compared existing approaches.

     

Small-Strain Shear Moduli of Chemically Stabilized Sulfate-Bearing Cohesive Soils

An experimental study was conducted to measure small-strain shear moduli of chemically treated sulfate-bearing expansive soils using the bender element test. The bender element test was chosen because it provides reliable and repeatable small strain shear modulus measurements and allows for the periodical monitoring of stiffness property responses of soil specimens under varying curing conditions. Bender element tests were conducted on cement and lime treated soils and the results were then analyzed to study the variations in stiffness properties of soil specimens at different sulfate levels and curing conditions. Both cement and lime treated natural and artificial clays with low sulfate level of 1,000?ppm showed considerable enhancements in small strain shear moduli, whereas the same treated soils at high sulfate level of 10,000?ppm showed less enhancements in shear moduli due to sulfate heaving. Also, enhancements in shear moduli were lower for soil specimens continuously soaked under water compared to those cured in the humidity room. Rates of stiffness enhancements due to stabilizer type, compaction moisture content, type of curing, and sulfate levels are quantified and summarized.     

Assessment of the development and implementation of tools in contract cleaning

This paper illustrates and discusses problems with the implementation and use of ergonomic tools and techniques in the process of cleaning. Cleaning is an occupation with a high risk of developing work-related disorders. One high-strain task where recommended tools and techniques are difficult to apply is cleaning staircases. This study evaluated the muscular activity of cleaners while mopping staircases using two different mop handles and found that an easily adjustable mop handle can decrease a cleaner's physical load. The results also show that the implementation and contextualization of the mop are of great importance for how a mop is used. A more holistic approach is needed to improve the benefits of good tools and techniques in cleaning work. More research is needed on how workplace organization can be improved to support the implementation of strategies to increase the health of professional cleaners.     

Bounded Unpopularity Matchings

We investigate the following problem: given a set of jobs and a set of people with preferences over the jobs, what is the optimal way of matching people to jobs? Here we consider the notion of popularity. A matching M is popular if there is no matching M′ such that more people prefer M′ to M than the other way around. Determining whether a given instance admits a popular matching and, if so, finding one, was studied by Abraham et al. (SIAM J. Comput. 37(4):1030–1045, 2007). If there is no popular matching, a reasonable substitute is a matching whose unpopularity is bounded. We consider two measures of unpopularity—unpopularity factor denoted by u(M) and unpopularity margin denoted by g(M). McCutchen recently showed that computing a matching M with the minimum value of u(M) or g(M) is NP-hard, and that if G does not admit a popular matching, then we have u(M)≥2 for all matchings M in G.Here we show that a matching M that achieves u(M)=2 can be computed in \(O(m\sqrt{n})\) time (where m is the number of edges in G and n is the number of nodes) provided a certain graph H admits a matching that matches all people. We also describe a sequence of graphs: H=H ₂,H ₃,…,H _k such that if H _k admits a matching that matches all people, then we can compute in \(O(km\sqrt{n})\) time a matching M such that u(M)≤k?1 and \(g(M)\le n(1-\frac{2}{k})\). Simulation results suggest that our algorithm finds a matching with low unpopularity in random instances.     

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and ‘Omics’ Tools

Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based ‘dietary protein’ biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.