International Journal of Engineering
Volume:32 Issue: 10, Oct 2019

Nano-structured surface and its ability to dual release of osteogenic and anti-inflammatory agents have a positive effect on the success of using titanium in orthopedic applications. For this purpose, TiO2 nanotubes (TNTs) were created via anodization method on Ti sheets and loaded by β-glycerophosphate (GP) and dexamethasone (DEX) as osteogenic and anti-inflammatory agents, respectively. They were coated with a polyvinyl alcohol (PVA) layer for controlling their releasing rate. The synthesized dual-release system was characterized by field emission scanning electron microscopy (FE-SEM), Fourier transform infrared spectroscopy (FTIR) analysis, XRD and UV-Vis techniques. The average diameter of TNTs was 84.182 nm. The presence of drugs in the system has been proven in the FTIR analysis. UV-Vis technique’s results show that the coated layer could control the release rate to improve the potential of the structures for supporting mineralization. Releasing of DEX was higher than GP and reached to a constant rate after 9 days. MTT test results confirmed the possibility of the surface designed Ti for bone regeneration purposes.

This paper presents the wet chemical synthesis of WO3/TiO2 nanocomposites using hydrothermally prepared monoclinic WO3 and anatase TiO2 nanoparticles as composite matrices and filler, respectively. The nanocomposites were prepared in different compositions, i.e. WO3:TiO2 ratio (w/w) of (1:1), (1:3), and (3:1). Physicochemical properties of the resultant WO3/TiO2 nanocomposites were evaluated by X-ray diffraction (XRD), scanning electron microscopy (SEM), BET N2 adsorption-desorption isotherms, UV/vis, and Raman spectroscopy. The resultant nanocomposites exhibited a mesoporous structure with specific surface area of up to 11.5 m2 g-1, where TiO2 constituent contributed to higher surface area, especially in (1:3) ratio, and higher number of defect sites. While there was no impurities in the investigated nanocomposites as revealed by XRD analysis and Raman spectra, the WO3:TiO2 (1:3) nanocomposites showed the highest light harvesting ability indicated by higher absorption amplitude in both UV and visible regime. Three different kinetic models including pseudo-first-order, pseudo-second order, and Langmuir-Hinshelwood were applied to experimental data. The pseudo-second-order was found to be the best representing model and the adsorption kinetic studies indicated that chemisorption initially dominated the degradation mechanism. Finally, photocatalytic activity of nanocomposites was compared for photodegradation of methylene blue (MB) aqueous medium and in a good agreement with physicochemical properties, WO3:TiO2 (1:3) nanocomposites yielded the highest MB degradation rate (k ~ 0.162 min-1) and efficiency (96%) within 120 min under UV irradiation.

Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of different transfer functions to redict the coefficients of the Antoine vapor pressure equation. The critical pressure, critical temperature, critical volume, molecular weight, and acentric factor were considered as the input variables and the Antoine equation coefficients showed by the symbols A, B, and C were considered as the output variables. The results of this study indicated that the linear transfer function had a better performance than other transfer functions and the topology of 5-6-3 with Levenberg–Marquardt learning algorithm and linear transfer function had the best performance for prediction of these coefficients.

The main advantage of a fluidized bed is its capability in excellent gas-fuel mixing. However, due to the lacks of gas radial momentum, its lateral mixing of gas-solid is not adequate. Therefore, this research is focused on fluidized bed hydrodynamics enhancement using the modified gas distributor plate design. For getting an optimum fluidized bed hydrodynamics prediction, three different classical ANSYS Fluent drag models, namely Wen-Yu, Syamlal O’Brien, and Gidaspow are examined first. Afterward, a novel distributor plate called swirl distributor plate (SDP) is proposed in order to enhance the gas-fuel mixing in vertical and radial directions. In terms of simulation approach, results were presented and compared with the experimental data. It has been observed that better hydrodynamics prediction is achieved by Syamlal O’Brien drag model. The effect of SDP on gas-solid mixing was then studied numerically and compared with conventional distributor plate (CDP). Compared with CDP, better gas-solid mixing was found while the SDP was used. As a final point, gasification test was conducted in a lab scale system in order to study and compare the composition of produced syngas using both distributor plates. Based on the gasification results, SDP leads to promotion of Hydrogen and Carbon monoxide by 34.85 and 65.92 percent, respectively.

In this study, solvent extraction method has been utilized for separation of molybdenum and vanadium from nitrate solution by utilizing coupling of acid and solvating extractants (D2EHPA and TBP extractants). The outcomes demonstrated that synergistic solvent extraction improves stability of formatted complexes for transfer to the organic phase. The main parameters such as pH value, concentration of extractants, NH4OH concentration as the stripping agent and contact time were optimized at 0.4, 15% (v/v) D2EHPA, 10% (v/v) TBP, 2 M and 30 min, respectively. The maximum separation factor of 24.84 was obtained with a new synergistic mixture of D2EHPA and TBP diluted with kerosene. According to McCabe-Thiel diagram, more than 99% of the Mo (VI) was obtained in counter current procedure and three stage numbers using 15% (v/v) D2EHPA and its mixture with 10% (v/v) TBP in kerosene, initial aqueous pH value equal to 0.4 and A/O ratio of 4/1 at room temperature for 30 min. In addition, stripping of Mo (VI) reached 98.75% in three counter current stages using 2 M NH4OH as stripping agent and A/O ratio of 1/4  for 30 min.

This study assesses the adsorption performance of Java plum leaves and guava fruits based adsorbents as natural products widely available in Aceh, Indonesia. These renewable adsorbents were employed to remove free fatty acids (FFAs) that cause the rancid odor in coconut oil. The adsorption tests were carried out at three different doses (50, 75, 100 g) and seven agitating periods (1, 2, 3, 4, 5, 6, 7 h). The adsorbents were characterized by Scanning Electron Microscopy (SEM) to observe their morphologies, and Fourier transform infrared (FTIR) spectroscopy to investigate the functional groups. The adsorption kinetics were also analyzed using the Freundlich and Langmuir isotherm models. The SEM image showed that the particle sizes of the guava fruits based adsorbent were 30-45 µm while those of Java plum leaves based adsorbent were 7-15 µm, both showing attractive range to enhance surface area for adsorption sites. FTIR spectra showed the presence of methylene, aliphatic and phenolic groups for both absorbent, aromatic and alkene groups only for java plum based adsorbent and secondary amine and alcohol groups only for guava fruit based adsorbent. Those groups seem to play important role in enhancing chemical adsorption of FFAs from the coconut oil sample. The results showed that Java plum leaves and guava fruits based adsorbents had a respective maximum adsorption capacity of 144.99 and 133.77 mg/g, with an optimum agitation time of 6 hour. The high absorption capacity could be ascribed from phenolic and flavonoid compounds present in both materials. Kinetics of adsorption of FFAs on both materials obeyed the Freundlich isotherm model indicating a multilayer and heterogeneous surface of adsorbent.

The suspension footbridges are very flexible due to their geometrical structure; hence they may face severe vibration problems induced mainly by natural forces and pedestrians crossing. By exceeding a certain limit, these vibrations can disturb the serviceability of the bridge as well as health and safety of the structure and pedestrians. Therefore, standard design guidelines are sets of recommendations to control the vibrations by applying restrictive design criteria. Because of the complexity of the exact simulation of the human-induced loads, these guidelines provide simplified methods to cover the frequency ranges of the human motion types in order to estimate the response of the structure without modeling the actual motion. As current paper, the simplified loading method proposed by EUR23984 EN code‑as the main footbridge design standard was investigated. Its compliance with pedestrian’s synchronization phenomenon was evaluated using the analysis results of a discontinuous type loading model proposed by authors. It was shown that the response of the footbridge strictly depends on the type and the speed of the pedestrian motion applied to the bridge, which is not included in the design parameters of the code. In this research work, a series of analysis is conducted on a suspension footbridge as a case study under both actual human loads and the simplified loads suggested by the code and the results were compared. It was found out that in the same crowd loading, the actual human loading creates greater vertical accelerations compare to EUR 23984 EN method results.

Structural damage can be controlled in performance based seismic design (PBSD) according to the requirement under a certain hazard level. During strong ground motion (GM) such buildings suffer minor to major damages depending on the shaking level of GM. The available damage assessment methods are complex, tedious and time-consuming procedure. In the present study, a simplified empirical model has been proposed that computes the GDI in a single step using the engineering demand parameters (EDPs) namely joint rotation, Inter storey drift (IDR), peak roof displacement. It has been found that the proposed method gives results of GDI near to Park-Ang model. It has been observed that the ground storey suffers maximum damage for all cases. Further, a relationship has been established between ground story DI and global DI. The proposed model effectively berlongferestimates reliable DI and could be used as a powerful tool for estimating seismic damage in buildings, especially for massive structures.

Elevated water tanks supported by the reinforced concrete (RC) Staging are classified as inverted pendulum structures. These are considered as structures of high post-earthquake importance and should remain functional after the seismic events. National codes of various countries recommend Force-Based Design (FBD) procedure for water tank staging, which does not ensure nonlinear performance level for a given hazard. Therefore, it becomes necessary to design these structures with a performance-based design approach like Direct Displacement-Based Design (DDBD). Many design engineers consider that the behavior of frame staging of the elevated water tank is similar to the building's frame and generally adopt the same design principles for both types of structures. However, the seismic behavior of the building frame is significantly different from frame staging due to the absence of diaphragm action at the bracing level and concentrated mass at the top level only. Therefore, it may not be rational to utilize the same DDBD procedure of the building's frame for the design of frame staging of the elevated water tanks. The present study proposes some modification in existing DDBD procedure (used for the design of frame building) based on the nonlinear time history analysis of twenty meters high RC frame staging with four different configurations. The modifications are proposed in terms of inelastic displacement profile, design displacement, effective height, and effective mass calculation. Further, the performance of the same RC frame staging designed using the proposed DDBD procedure has been assessed using nonlinear static and dynamic analyses to verify the suitability of proposed modifications.

Research on increasing the buckling strength of tanks carrying fluid and also cylindrical shells of thin-walled steel in civil engineering and mechanics is important. This is due to the widespread use of these structures in the industry. Due to the low thickness of the body and also due to the pressure forces entering these tanks, these structures are exposed to lateral buckling. In this research, the use of Carbon Fiber Reinforced Polymer (CFRP) rings to enhance and increase the buckling strength of tanks has been investigated. For this study, a tank with dimensions close to the actual tanks has been built and reinforced by a CFRP ring against the buckling. The results of the experiment indicated that the use of CFRP reinforcing ring considerably enhanced the buckling and post-buckling capacity of the tank. Further, comparing the results obtained from the experimental and numerical analysis and the values extracted from the theoretical relationships suggested that the results are in good agreement.

This paper aims to introduce a new modelling approach that represents departure time, destination and travel mode choice under a unified framework. Through it, it is possible to overcome shortages of the traditional 4-step model associated with the lack of introducing actual travellers’ behaviours. This objective can be achieved through adopting discrete 3-level Nested Logit model that represents different potential correlation (cross elasticity) among departure time, destination and travel mode alternatives. The proposed model has been estimated and tested by using discretionary trips’ data from Eskisehir city, Turkey. In the light of the estimation results, individuals tend to jointly decide on discretionary travel dimensions rather than separately as assumed by the traditional 4-step model. Moreover, the proposed approach shows more flexibility in considering attributes of alternatives along with characteristics of decision makers. That results in a more behavioural travel demand modelling, more accurate future forecasting and more trusted policy implications. The proposed model represents a more accurate and reliable alternative for the first 3-steps of the traditional 4-step model in small-scale planning issues. Finally, the proposed approach is a significant milestone toward obtaining a consistent, efficient and integrated full-scale behavioural-model that consists of all travel demand dimensions.

The lowering of the groundwater table causes the area above the water table to become unsaturated and capillary phenomena to appear in this zone. This means that the bearing capacity of shallow footings will be influenced by capillary stress or matric suction. In this research, the effect of groundwater table lowering on the bearing capacity of a shallow square model footing on dense sand has been investigated by conducting plate load tests under different groundwater table conditions. Numerical simulations of the experiments also were performed using the finite element software Optum G2. The results of the experiments showed that lowering of the water table increased the matric suction. At a suction 0.5 to 4.5 kPa, the ultimate bearing capacity in the soil increased non-linearly from 2.5 to 4-times the bearing capacity of the saturated state. Numerical simulation of the experiments by assuming cohesion due to matric suction for the upper part of the groundwater table predicted the same behavior. Very good agreement was obtained between the predicted bearing capacity and the measured values.

The proposed paper presents the DC/AC microgrid modeling using the Energy storage units and photovoltaic (PV) panels. The modal consists of a two stage power conversion. The power is supplied to the both DC and AC loads by this PV solar panels. The suitable way to explore the PV generation model is by using manufacturer datasheet. A bidirectional converter is connected to the battery storage system and dc bus. To keep the bus voltage stable, the storage system absorbs the excess power whenever generation is more and delivers power to the load when generation is less.  This system eliminates hazards of islanding by supply the local loads continuously incase of grid discontinuity. This paper emphasizes on control and stability of dc bus voltage and energy management scheme. Matlab/Simulink is used for integration of system modeling and efficiency of the system is verified by simulation.

The supply chain network design (SCND) implicates decision-making at a strategic level and makes it possible to create an effective and helpful context for managing. The aim of the network is to minimize the total cost so that customer's demands should be met. Preventive maintenance is pre-determined work performed to a schedule with the aim of preventing the wear and tear or sudden failure of equipment components. Unfortunately, there is very little work on the issues of preventive maintenance in the SCND. At first, a mixed integer nonlinear programming model (MINLP) is formulated that maximaize the profit of the network. Since the SCND is an NP-hard problem, we use three meta-heuristic algorithms, namely tabu search, harmony search and genetic algorithm to solve the given problem. Taguchi method is also used to adjust the significant parameters of the forgoing meta-heuristics and select the optimal levels of the influential factors for the better algorithm performance. The results of different numerical experiments endorse the effectiveness of the HS algorithm.

Faced with the dynamic demands of a changing market, companies are facing fierce competition, which forces them to consider more and more new approaches to improve quality, reduce costs, produce on time, control their risks and remain successful in the face of any disruption. It is clear that the choice of appropriate suppliers is one of the key factors in increasing the competitiveness of companies. Thus, suppliers selection has a very important impact on the control of risks throughout the supply chain and on increase of its performance. Therefore, it is important for managers to realize the long-term impact of their supplier selection strategies on the benefits and effective functioning of the organization. To minimize supply and demand risks, this work presents a generic supplier selection model based on artificial neural networks (ANNs) to help manufacturers to choose the most efficient suppliers and monitor their performance. The results showed that ANNs are very well adapted to our problem since they have provided a very considerable efficiency in terms of the results obtained. Indeed, the application of the ANN will avoid the difficulty of desiging an algorithm to solve our problem, it is through the expertise of the managers in the purchasing department that our ANN will learn to be efficient and serve as a tool to help a decision makers to choose the best suppliers.

In this research, an integrated approach is presented to simultaneously solve quay crane scheduling and yard truck scheduling problems. A mathematical model was proposed considering the main real-world assumptions such as quay crane non-crossing, precedence constraints and variable berthing times for vessels with the aim of minimizing vessels completion time. Based on the numerical results, this proposed mathematical model has suitable efficiency for solving small instances. Two versions of imperialist competitive algorithm (ICA) are presented to heuristically solve the problem. The grouping version of  algorithm (G-ICA) is used to solve the large-sized instances based on considering the allocation of trucks as a grouping problem. Effectiveness of the proposed metaheuristics on small-sized problems is compared with the optimal results of the mathematical model. In order to compare the efficiency of the proposed algorithms for large-sized instances, several instances were generated and solved, and the performance of algorithms has been compared with each other. Moreover, a simulated annealing (SA) algorithm is developed to solve the problem and evaluate the performance of the proposed ICA algorithms. Based on the experimental results, the G-ICA has a better performance compared to the ICA and SA. Also an instance of a container terminal in Iran has been investigated which shows that the proposed model and solution methods are applicable in real-world problems.

Friction stir welding (FSW) can be defined as a green technology, because the consumption of energy during this process is less than other welding methods. In addition, during the process there is no gas, filler material or other consumables. It should be noted that, complex curved shapes are now commonly used in different industries in a bid to have lightweight structures. According to the above-mentioned descriptions, several investigations into the potential benefits of adopting Friction Stir Welding (FSW) in the production and joining different materials are being undertaken. The work presented in this paper is focused on thermal behavior of the curved FSW and its benefits for the green technology. Due to the robust nature of FSW process aluminum 6061-T6 alloy has been selected as the welding material. The results of the study showed that, the total peak temperature value of 300°C happened at time, t = 3 s at the plunge stage (outside of the welding seam). Meanwhile, at the dwell stage (between t = 3 s to t = 5 s), there is a stable situation in the amount of the generated heat from the plastic deformation as well as the contact shear stress at the tool-workpiece contact interfaces, thus the interfacial temperature is found to be stable. By the end of the dwelling step, the total generated heat is stable to the maximum value of 300°C. At the step time of t = 12.8 s, the temperature is distributed asymmetrically across the workpiece until the time step of 19.6 s which at this point the asymmetric contour expanded in the stir zone.

Erosion caused by sand transportation in flow changing devices is a serious concern in the hydrocarbon and mineral processing industry, which entail to failure and malfunction of flow devices. In this study, computational fluid dynamics (CFD) with discrete phase models (DPM) were employed for analysis of carbon steel long radius 90-Degree elbow erosion due to the sand concentration of 2, 5 and 10% transported in the liquid phase. The simulation is completed with the Reynolds Stress Model (RSM) and Oka erosion model. The simulation result from the RSM model was validated by comparison with the erosion distribution results in the literature. The largest erosion zones have been identified at or near the outlet of the 90-Degree elbows outer wall surface with a maximum erosion rate appeared for 10% sand concentration. Furthermore, the relationships of turbulence intensity on erosion, particle trajectory, and particle mass concentration in the elbow pipe were discussed.

From a regression analysis perspective, this paper focused on literature about TiO2 nano particles. The particles on focus entailed those that had been suspended in ethylene glycol and water – at a ratio of 60:40. Indeed, regression analysis has gained application in contexts such as the turbulent Reynolds number, especially with the aim of establishing the impact of the ratio of the base fluid on heat transfer coefficients, as well as the target materials’ thermal properties. From the findings, this study infers that when the water-ethylene glycol mixture is used at a ratio of 60:40, the rate of heat transfer is higher than that which is obtained when water is used solely. Additional findings established from the examination of the impact of material concentration and temperature on the rate of nanofluids’ heat transfer suggested that as temperature increases, the rate of heat transfer decreases. However, it was noted that an increase in concentration exhibits a positive correlation with the nanofluids’ rate of heat transfer whereby an increase in the former parameter (concentration) leads to an increase in the latter (rate of nanofluids heat transfer).

Due to great effect of mining operation on environment and dependent sides, paying attention to the aspects of sustainable development (SD) is important. A conjugation of Grey theory and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is able to find out cause and effect relations among the triple mining SD components and their effective factors. Grey–DEMATEL approach has been used in order to effectively quantify indicators of sustainable development of a copper mine located in south east Iran. This systematic approach transformed the quantitative and qualitative information into a analogous scale and measured the interrelationships among the SD components and their factors. Hierarchical Grey-based DEMATEL compensated the incomplete and uncertain environmental and socio-economic information. The obtained results indicated that social component with an R value of 10 is relatively strong direct influencer on the other components and the economic component is the least direct influencer with R= 8.49. Among the social impacting factors, employment of local work forces is the most important factor that needs to be consider with sustainable development objectives.