36 research outputs found
Investigating the bioenergy potential of invasive Reed Canary (Phalaris arundinacea) through thermal and kinetic analyses
No full textThe thermal conversion of biomass plays an important role in the development of energy reaping technologies and fire engineering. The study investigates the bioenergy potential of Reed Canary (Phalaris arundinacea) through investigating the combustion kinetics and thermal behavior. Reed Canary samples were collected from various rural areas of Ontario, Canada. Four heating rates (10, 20, 30, and 40 °C min^−1) were utilized to perform the thermal degradation analysis using a thermogravimetric analyzer. Three different stages were identified ranging from 25 °C to 800 °C in which major degradation stage had two regions from 210 °C to 530 °C where most of the biomass changed into products. Furthermore, iso-conversional models including Kissenger-Akahira-Sunose (KSA), Starink and Flynn–Wall–Ozawa (FWO) were used to evaluate the reaction kinetics such as the activation energy and the pre-exponential factor. The reported kinetics parameters demonstrate the promising potential of Reed Canary for bioenergy production. Moreover, the low cost and the abundance of Reed Canary facilitate the possibility of introducing the biomass as a cost efficient and environmentally friendly natural resource for renewable bioenergy production
Graphene and Glass Flake Nanocomposites Coatings for Corrosion Mitigation in Chloride Rich Environments
No full textInspired by the needs for the preparation of protective coatings with enhanced protection properties especially corrosion resistance in the oil and gas industry, the research focuses on the synthesis and the evaluation of various polymer composites on different metals substrates as protective coatings in Chloride rich environment. In various areas of application including oil and gas industry, metals substrates are continuously exposed to various deterioration factors including corrosion, impact, thermal and UV degradation. In addition, the rates of deterioration based on those factors can be further accelerated in certain environment. For example, the rate of metal deterioration due to corrosion can be accelerated in a Chloride rich environment causing significant reduction in the life span of metal substrates in different fields including oil and gas industry. For instance, in off shore oil and gas operation, drilling rigs are continently exposed to the Chloride rich ocean’s wave, which may accelerates the corrosion process on various metals based items of the rigs. Therefore, various corrosion mitigation techniques including the use of protective coatings are utilized to attenuate the corrosion rate and extend the life span of metal substrates. In particular areas, protective coatings can be exposed to various degradation factors including UV, Thermal degradations as well as deterioration due to impact. Therefore, it was important to evaluate other protection properties of the prepared protective coatings in addition to corrosion resistance. The studies focused on the incorporation of pristine Graphene and Glass Flake in different polymer resin such as Epoxy and Polyetherimide and evaluates the composites as protective coating on different metals substrates such as Copper, Stainless Steel 304 and Cold Rolled Steel. Furthermore, the studies investigated the possibility of enhancing the protective properties of the prepared protective composites coating by surface modification and functionalization of the filler in order to enhance the level of interaction between the polymer resin and the fillers. The synthesized composites are characterized using X-Ray diffraction (XRD) and Fourier transfer infrared (FTIR) techniques, while the dispersion of the fillers in polymeric matrices are examined using Transition electron microscopy (TEM) and Scanning electron microscopy (SEM). The corrosion protection properties of the prepared protective composites coatings are examined using Electrochemical impedance spectroscopy (EIS) and Cyclic voltammetry (CV) or potentiodynamic techniques. Furthermore, the interface adhesion between metal substrates and the protective coatings is examined and evaluated according to the ASTM-D3359 standard, while the impact resistance and the UV degradation properties are examined and evaluated according to the ASTM -D2794 and ASTM-D4587 standards, respectively. Moreover, the thermal degradation properties of the prepared protective coatings are evaluated by examining the rate of degradation or weight loss of the composites using Thermal Gravimetric Analysis (TGA) techniques and examining the influences of the incorporation of the various fillers in the glass transition temperature of the composites using Differential Scanning Calorimetry (DSC) technique. The studies reveal that the incorporation of the different types of fillers will enhance the corrosion resistance properties of the polymer resin in addition to other properties such as impact resistance, thermal stability and UV degradation. Furthermore, the studies conclude that the level of enhancement in corrosion protection as well as other protection properties can be further excelled by increasing the load of fillers in the composites. Moreover, it was interesting to observe that increasing the load of filler in the composites may negatively impact imperative properties such as interface adhesion, where increasing the load of fillers may attenuate the interface adhesion between the protective coatings and the coated metal substrates. A number of contributions have been reported in this research project including the preparation and the examination of nanocomposites materials as protective coatings on different metals substrates after the incorporation of different pristine nano-fillers such as Graphene and Glass Flake. The contributions also include the reporting for the first time of new and unique recipes that demonstrate simple steps for the surface fuctionalization of Graphene Oxide and Glass Flake before utilizing the functionalized fillers in the preparation of nanocomposites coatings with enhanced protective properties including corrosion resistance and thermal stabilit
An Accurate Model of the Corrosion Current Density of Coatings Using an Adaptive Network-Based Fuzzy Inference System
No full textCorrosion resistance coating is fabricated using epoxy/glass flake (E/GF) composites and is utilized to prolong the lifespan of cold-rolled steel (CRS) metal substrates. An in situ synthesis approach was adopted to prepare the composite coating at different levels of synthesis parameters, including a load of filler and coating thickness. In addition, this work shows the effects of the chemical functionalization of the filler on the corrosion protection property of the epoxy/functional glass flake (E/FGF) composite coatings. The effects of the modification of the filler, as well as the other synthesis parameters, on the corrosion resistance property are evaluated using a potentiodynamic polarization technique. Here, the corrosion resistance property is evaluated based on the observed current density. The primary goal of this work is to present an accurate model of corrosion current density (CCD). By using measured data, a precise model, which simulates the corrosion resistance properties of the coatings, has been created by an adaptive network-based fuzzy inference system (ANFIS) in terms of glass flake loading, chemical functionalization, and coating thickness. The obtained results revealed good agreement between ANFIS-based modelling and the measured dataset. The root mean square errors of the prediction model were 8.1391 × 10−8 and 0.0104 for training and testing, respectively. The coefficient of determination (R2) values of the ANFIS output were found to be 1.0 and 0.9997 for training and testing, respectively. To prove the superiority of the ANFIS-based model of CCD, the achieved results were compared with an analysis of variance (ANOVA). ANOVA utilizes a linear regression approach to get the model. Thanks to ANFIS, compared with ANOVA, the values of R2 are increased by 10% and 18.6% for the training and testing phases, respectively. Finally, the accuracy of the ANFIS model of corrosion current density is validated experimentally
Learning Smooth Representation for Unsupervised Domain Adaptation
No full textTypical adversarial-training-based unsupervised domain adaptation (UDA) methods are vulnerable when the source and target datasets are highly complex or exhibit a large discrepancy between their data distributions. Recently, several Lipschitz-constraint-based methods have been explored. The satisfaction of Lipschitz continuity guarantees a remarkable performance on a target domain. However, they lack a mathematical analysis of why a Lipschitz constraint is beneficial to UDA and usually perform poorly on large-scale datasets. In this article, we take the principle of utilizing a Lipschitz constraint further by discussing how it affects the error bound of UDA. A connection between them is built, and an illustration of how Lipschitzness reduces the error bound is presented. A local smooth discrepancy is defined to measure the Lipschitzness of a target distribution in a pointwise way. When constructing a deep end-to-end model, to ensure the effectiveness and stability of UDA, three critical factors are considered in our proposed optimization strategy, i.e., the sample amount of a target domain, dimension, and batchsize of samples. Experimental results demonstrate that our model performs well on several standard benchmarks. Our ablation study shows that the sample amount of a target domain, the dimension, and batchsize of samples, indeed, greatly impact Lipschitz-constraint-based methods\u27 ability to handle large-scale datasets
Preparation and Characterization of Electroactive Polymer Composites in the Presence of Graphene Nanoplatelets
No full textIncreasing Output Power of a Microfluidic Fuel Cell Using Fuzzy Modeling and Jellyfish Search Optimization
No full textAn efficient electrochemical energy conversion system with little to no environmental impact is the fuel cell (FC). FCs have demonstrated encouraging results in various applications and can even run on biofuel, such as bio-glycerol, a by-product of biodiesel. The most effective ways to operate FCs can significantly enhance their effectiveness. Incorporating fuzzy modeling and metaheuristic methods, this work used artificial intelligence to determine the ideal operating parameters for a microfluidic fuel cell (MFC). The concentrations of the following four variables were considered: bio-glycerol concentration, anode electrocatalyst loading, anode electrolyte concentration, and cathode electrolyte concentration. The output power density of the MFC was used to assess its performance. The output power density of the MFC was modeled using fuzzy logic, taking into account the aforementioned operational parameters. A jellyfish search optimizer (JSO) was then used to find the ideal operating conditions. The results were contrasted with response surface methodology (RSM) and experimental datasets to demonstrate the superiority of the proposed integration between fuzzy modeling and the JSO. In comparison with the measured and RSM approaches, the suggested strategy boosted the power density of the MFC by 9.38% and 8.6%, respectively
CORROSION PROTECTION OF STAINLESS STEEL TYPE 304 USING GRAPHENE COMPOSITES
No full textPolyetherimide-Graphene (PEI/G) composites were prepared using in situ polymerization approach and thermally cured under vacuum on Stainless Steel 304 (SS304) substrates in order to be evaluated as corrosion protection coatings. Several steps curing were performed to ensure complete imidization of PEI/G composites. Dispersion of the graphene fillers in the PEI matrices was captured using Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM). The study examines PEI/G composites as corrosion protection coatings using electrochemical techniques such as Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS). Furthermore, the influences of the load of graphene on the electrochemical behavior as well as the interface adhesion of the PEI/G composites are illustrated. Adhesion tests were conducted and evaluated according to ASTM D3359 standard and the long term performances of the prepared PEI/G coatings were confirmed by conducting the adhesion tests after 30 days of exposure to the corrosive medium. The study revealed that PEI may slow down the corrosion process on SS304 substrates and this protection property of PEI can be excelled by the incorporation of graphene in the PEI matrix.
Corrosion inhibition of copper in sodium chloride solution using polyetherimide/graphene composites
No full textRadiation and Multiple Slip Effects on Magnetohydrodynamic Bioconvection Flow of Micropolar Based Nanofluid over a Stretching Surface
No full textOur aim in this article is to study the radiation and multiple slip effects on magnetohydrodynamic bioconvection flow of micropolar based nanofluid over a stretching surface. In addition, a steering mechanism of making improvements to the Brownian motion and thermophoresis motion of nanoparticles is integrated. The numerical solution of 2-dimensional laminar bioconvective boundary layer flow of micropolar based nanofluids is presented. The basic formulation as partial differential equations is transmuted into ordinary differential equations with the help of suitable similarity transformations. Which are then solved by using the Runge–Kutta method of fourth-order with shooting technique. Some important and relevant characteristics of physical quantities are evaluated via inclusive numerical computations. The influence of vital parameters such as buoyancy parameter λ, bioconvection Rayleigh number Rb, the material parameter K are examined. This investigation showed that with the increment in material parameter, micro rotation and velocity profile increases. In addition, the temperature rises due to the enhancement in Nb (Brownian motion) and Nt (thermophoresis parameter)
