Hydrodynamics of gas fluidized beds with mixture of group D and B particles

The dynamics of a gas‐solid fluidized bed containing Geldart Group D particles mixed with a small proportion of Geldart Group B particles are investigated using pressure fluctuations data. Time series analysis, using a variety of nonlinear dynamics tools, shows that the slugging present with Group D particles can be suppressed by the addition of a small proportion of Group B particles. The power spectra and the auto‐correlation function are used for a preliminary evaluation of dominant slug frequencies. It is shown that the bed fluidized with the mixture of Group D and B particles behaves in a less periodic manner and is dominated by more random bubble motion. On the other hand, the correlation integral is used to analyze the chaotic behaviour of the flow, through evaluation of the fractal structure of the reconstructed attractors. It is shown that the bed fluidized with Group D particles is characterized by a combination of steady slug motion and irregular particles motion. The behaviour of the fluidized bed of Group D/B particles mixture is characterized by a single correlation dimension for a wide range of fluidization velocities.     

Deep Neural Networks Regularization Using a Combination of Sparsity Inducing Feature Selection Methods

Neural Processing Letters - Deep learning is an important subcategory of machine learning approaches in which there is a hope of replacing man-made features with fully automatic extracted features....     

NN-based Prediction Interval for Nonlinear Processes Controller

Neural networks (NNs) are extensively used in modelling, optimization, and control of nonlinear plants. NN-based inverse type point prediction models are commonly used for nonlinear process control. However, prediction errors (root mean square error (RMSE), mean absolute percentage error (MAPE) etc.) significantly increase in the presence of disturbances and uncertainties. In contrast to point forecast, prediction interval (PI)-based forecast bears extra information such as the prediction accuracy. The PI provides tighter upper and lower bounds with considering uncertainties due to the model mismatch and time dependent or time independent noises for a given confidence level. The use of PIs in the NN controller (NNC) as additional inputs can improve the controller performance. In the present work, the PIs are utilized in control applications, in particular PIs are integrated in the NN internal model-based control framework. A PI-based model that developed using lower upper bound estimation method (LUBE) is used as an online estimator of PIs for the proposed PI-based controller (PIC). PIs along with other inputs for a traditional NN are used to train the PIC to predict the control signal. The proposed controller is tested for two case studies. These include, a chemical reactor, which is a continuous stirred tank reactor (case 1) and a numerical nonlinear plant model (case 2). Simulation results reveal that the tracking performance of the proposed controller is superior to the traditional NNC in terms of setpoint tracking and disturbance rejections. More precisely, 36% and 15% improvements can be achieved using the proposed PIC over the NNC in terms of IAE for case 1 and case 2, respectively for setpoint tracking with step changes.

     

Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

     

Selective harmonic elimination method for wide range of modulation indexes in multilevel inverters using ICA

Selective harmonic elimination（SHE） in multilevel inverters is an intricate optimization problem that involves a set of nonlinear transcendental equations which have multiple local minima. A new advanced objective function with proper weighting is proposed and also its efficiency is compared with the objective function which is more similar to the proposed one. To enhance the ability of the SHE in eliminating high number of selected harmonics, at each level of the output voltage, one slot is created. The SHE problem is solved by imperialist competitive algorithm（ICA）. The conventional SHE methods cannot eliminate the selected harmonics and satisfy the fundamental component in some ranges of modulation indexes. So, to surmount the SHE defect, a DC-DC converter is applied. Theoretical results are substantiated by simulations and experimental results for a 9-level multilevel inverter. The obtained results illustrate that the proposed method successfully minimizes a large number of identified harmonics which consequences very low total harmonic distortion of output voltage.     

Cracks coalescence mechanism and cracks propagation paths in rock-like specimens containing pre-existing random cracks under compression

The mechanism of cracks propagation and cracks coalescence due to compressive loading of the brittle substances containing pre-existing cracks （flaws） was modeled experimentally using specially made rock-like specimens from Portland Pozzolana Cement （PPC）. The breakage process of the specimens was studied by inserting single and double flaws with different inclination angles at the center and applying uniaxial compressive stress at both ends of the specimen. The first crack was oriented at 50＆#176; from the horizontal direction and kept constant throughout the analysis while the orientation of the second crack was changed. It is experimentally observed that the wing cracks are produced at the first stage of loading and start their propagation toward the direction of uniaxial compressive loading. The secondary cracks may also be produced in form of quasi-coplanar and/or oblique cracks in a stable manner. The secondary cracks may eventually continue their propagation in the direction of maximum principle stress. These experimental works were also simulated numerically by a modified higher order displacement discontinuity method and the cracks propagation and cracks coalescence were studied based on Mode I and Mode II stress intensity factors （SIFs）. It is concluded that the wing cracks initiation stresses for the specimens change from 11.3 to 14.1 MPain the case of numerical simulations and from 7.3 to 13.8 MPa in the case of experimental works. It is observed that cracks coalescence stresses change from 21.8 to 25.3 MPa and from 19.5 to 21.8 MPa in the numerical and experimental analyses, respectively. Comparing some of the numerical and experimental results with those recently cited in the literature validates the results obtained by the proposed study. Finally, a numerical simulation was accomplished to study the effect of confining pressure on the crack propagation process, showing that the SIFs increase and the crack initiation angles change in this case.     

Comparing the Performance of Organic Solvent Nanofiltration Membranes in Non-Polar Solvents

Organic solvent nanofiltration (OSN) is gradually expanding from academic research to industrial implementation. The need for membranes with low and sharp molecular weight cutoffs that are able to operate under aggressive OSN conditions is increasing. However, the lack of comparable and uniform performance data frustrates the screening and membrane selection for processes. Here, a collaboration is presented between several academic and industrial partners analyzing the separation performance of 10 different membranes using three model process mixtures. Membrane materials range from classic polymeric and thin film composites (TFCs) to hybrid ceramic types. The model solutions were chosen to mimic cases relevant to today's industrial use: relatively low molar mass solutes (330–550 Da) in n-heptane, toluene, and anisole.     

UV-shielding by a polyurethane/f-Oil fly ash-CeO2 protective coating

A waste material called oil fly ash (OFA) was acid-functionalized, yielding f-OFA-COOH, which was then reacted with cerium oxide (CeO₂) to make CeO₂-functionalized OFA, or f-OFA-CeO₂. Pristine OFA and f-OFA-CeO₂ were used to make waterborne polyurethane (WBPU) dispersions, referred to as WBPU/OFA and WBPU/f-OFA-CeO₂, respectively, with defined OFA and f-OFA-CeO₂ content. All the dispersions were applied to mild steel as organic coatings to evaluate their protective properties, such as their hydrophobicity, adhesive strength and UV-shielding resistance. These protective properties varied based on the OFA and f-OFA-CeO₂ content. The highest water contact angle, minimum water swelling and maximum adhesive strength were found using WBPU/f-OFA-CeO₂-20 coating (using 2.00 wt% f-OFA-CeO₂), which also showed the maximum ultraviolet (UV) absorption via UV–vis spectroscopy analysis. This UV shielding result also matched field test results, as that coating was found to exhibit the lowest UV degradation near a marine atmosphere, as shown by X-ray photoelectron spectroscopy (XPS) analysis. The least affected hydrophobicity was also recorded for the sample with the WBPU/f-OFA-CeO₂-20 coating.     

Fabrication of co-PVDF/modacrylic/SiO2 nanofibrous membrane: Composite separator for safe and high performance lithium-ion batteries

Highly porous free-standing co-poly(vinylidene fluoride)/modacrylic/SiO₂ nanofibrous membrane was developed using electrically-assisted solution blow spinning method. The performance and the potential of the membrane as a lithium-ion battery separator were investigated. The addition of modacrylic enhanced the solution spinnability that resulted in defect-free membranes. Moreover, the presence of modacrylic enhanced the dimensional and thermal stabilities, while the addition of hydrophilic SiO₂ nanoparticle enhanced both mechanical property and ionic conductivity. Combustion test results illustrated that the presence of modacrylic provide flame retarding property over a set of different polymeric-based membranes. Electrochemical performance results showed that the developed membrane can increase the battery capacity compared with the commercial separator.     

Microstructural properties,thermal insulation and thermal degradation behavior of boron-containing monolithic novolac xerogels

Enhancement of thermal stability-insulation performance of hyper porous materials is the premier issue to design of novel porous thermal protection systems. Boron-containing monolithic novolac xerogels (BCNXs) were synthesized using sol–gel networking of novolac resin with hexamethylenetetramine (HMTA) and boric acid at the solvent saturated vapor atmosphere (SSVA). The aim was to elucidate the effect of higher crosslinking density and thermal stable boron containing chemical bonds on the microstructure, thermal conductivity, and thermal oxidation stability of novolac xerogels. The results of FESEM and BET analysis showed that the microstructural characteristics of xerogels are significantly depend on the HMTA and boric acid concentration. The thermogravimetric results were analyzed using characteristic kinetic temperature (CKT)-characteristic kinetic temperature range (CKTR) approximations. The effect of micromorphology of xerogels on the thermal conductivity was investigated. The effective thermal conductivity of samples were in the range of 0.031–0.048 W/m K.