International Journal of Engineering
Volume:32 Issue: 9, Sep 2019

The suitability of hemp fibres as green support material for immobilization of Acidithiobacillus ferrooxidans cells in ferrous iron bio-oxidation process was investigated. A series of experiments were carried out in shake flasks and bioreactor for both cell immobilization and iron bio-oxidation. In flask experiments, five successive batch colonization cycles resulted in 6-fold increase in ferrous iron bio-oxidation rate. Evaluation of immobilized cells activity through two approaches as wet and dry storage demonstrated the higher activity of wet stored bacteria than dry ones after a period of two months. The dry stored bacteria lost almost all their activities after eight weeks. Whereas, the activity of wet stored samples was 30% at the same time. In bioreactor experiments, use of a packed-bed bioreactor with hemp fibres, the maximum ferrous iron bio-oxidation rate of 2.46 kg m-3 h-1 was obtained at dilution rate of 3.97 h-1, and retention time of 0.25 h. Our experimental results could pave a new platform for the application of hemp fibre as an inexpensive and environmentally friendly support material in bacterial cell immobilization, especially in ferrous iron bio-oxidation process using acidophilic bacteria.

Underlying fabrics can change the appearance, function and quality of the garment, and also add so much longevity of the garment. Nowadays, with the increasing use of various types of fabrics in the garment industry, their resistance to bagging is of great importance with the aim of determining the effectiveness of textiles under various forces. The current paper investigated the effect of underlying on the bagging behavior of denim fabrics. The experiments carried out on four different denim fabrics as the main components including cotton, polyester and lycra, as well as three types of adhesive interlining and three common lining as the underlying components. The adhesive interlining was added to the fabric by using a fusing machine, and the lining was sewn to the fabric. The bagging behavior was assessed by extraction of the residual bagging height using the image processing method and the bagging fatigue percentage by stress-strain diagram. The results showed that with the addition of adhesive interlining and lining to the fabric, the bagging fatigue percentage increased. The lining sewn to the fabric reduced the residual bagging height. Also, the friction between the face fabric and the lining was an important factor that, the bagging fatigue percentage increased with increasing the friction, regardless of the fabric material.

The sections composed of concrete and steel, which include concrete-encased concrete-filled tubes, generally have defects due to the low tensile strength of concrete. Therefore, an appropriate method was used for the combination of concrete-filled tubes (CFT) and prestressing strands which is encased in concrete. The conventional design guidelines are commonly developed for materials with normal strength thus further investigation is required to be conducted for sections with high-strength materials. In order to develop the design process, high-strength concrete and steel have been utilized in this study to examine the effects of steel and concrete strengths on the core concrete confinement, sectional size and flexural behavior of high-strength prestressed concrete-encased CFST (HS-PCE-CFST) beams. Hence, a total of thirteen HS-PCE-CFST beams were modeled via ABAQUS finite element software. The main variables include the steel tube yield strength, compressive cylinder strength of the core and outer concrete  and the steel tube diameter to section width ratio. Furthermore, experimental results were employed to verify the finite element model. The bending moment, ductility, flexural stiffness and failure mode of beams are also examined. The results confirm that among the compressive strength of the outer and core concrete and the steel tube yield strength, change in the outer concrete compressive strength has a greater effect on the change of flexural parameters, also increasing the ratio of steel tube diameter to section width causes a minor increase in the ultimate bending moment and serviceability level flexural stiffness, but a major escalation in the initial flexural stiffness.

Displacement-based methods are recognized as appropriate approaches to reach the goals of performance-based seismic design method. In the direct displacement-based seismic design method, the seismic yield displacement is applied as one of the important design parameters. In this paper, a new relation is suggested to determine the lateral displacement pattern at first yielding of eccentrically braced frame systems subjected to earthquake ground motions. This relation considers the influence of various structural features of frames. It is developed from the results of several nonlinear dynamic analyses containing 30 eccentrically braced frames under 15 far-field and near-field earthquake ground motions. Then, the results of these analyses are processed by nonlinear regression analysis in order to establish the most effective parameters on the yield displacement pattern of the  frames. As a result, a comparison between the suggested yield displacement pattern and nonlinear dynamic analyses showed the efficiency and advantages of the suggested approach.

In order to understand the seismic performance and mechanism of bottom frame seismic wall masonry structure (BFSWMS) and its vulnerability in empirical seismic damage, based on the statistical and numerical analysis of the field seismic damage observation data of 2178 Dujiangyan structures in the Wenchuan great earthquake urban of China on May 12, 2008, a non-linear function model between the seismic grade and the number of field damage samples is established, and the regression curve is given. The empirical seismic vulnerability matrices in multiple intensity regions are established, and the regression model functions of each intensity region and the vulnerability curves based on seismic damage grade and exceeding probability are obtained, respectively. A vulnerability matrix model with mean damage index (MDI) as its parameter is proposed, and the empirical vulnerability matrix is embedded in it. The vulnerability matrix based on this parameter and the regression curve of MDI in Dujiangyan city are derived. The above research results can provide the necessary practical reference for the vulnerability study of BFSWMS and the seismic code of China.

In this study, the energy consumption of Nasirabad Industrial Park (NIP) treatment plant was evaluated. A combination of up-flow anaerobic baffled reactor (UABR) and aerobic integrated fixed-bed activated sludge (IFAS) processes were employed in NIP. To find out the average electrical energy use per m3 influent wastewater, the rate of energy usage of the plant was calculated by data derived from the monthly utility bills in 2013 and 2014.  The energy consumption was estimated to be 10.4 and 10.7 kWh.day-1.m-3 in 2013 and 2014, respectively. In addition, the electrical energy consumption of different electromechanical equipment of the plant was separately assessed. The average daily electrical energy consumed by treatment processes (effective energy) in both 2013 and 2014 was estimated at 7.2 kWh.day-1.m-3, while the average energy consumption by other parts of the treatment plant (ineffective energy) was 3.2 and 3.5 kWh.day-1.m-3 in 2013and 2014, respectively. The rate of electrical energy usage per kg COD removal was found to be 4.9 and 5.1 kWh.day-1 in 2013 and 2014, respectively. Finally, it was inferred that energy use in NIP was not being managed in a suitable manor. Given the significance of energy, price risings, and the decline of resources by which energy is generated, it is imperative to take effective managerial actions to reduce electrical energy consumption in wastewater treatment plants. Also, the designers of water and wastewater treatment plants should consider less energy-intensive processes to improve their energy efficiency.

Underlying fabrics can change the appearance, function and quality of the garment, and also add so much longevity of the garment. Nowadays, with the increasing use of various types of fabrics in the garment industry, their resistance to bagging is of great importance with the aim of determining the effectiveness of textiles under various forces. The current paper investigated the effect of underlying on the bagging behavior of denim fabrics. The experiments carried out on four different denim fabrics as the main components including cotton, polyester and lycra, as well as three types of adhesive interlining and three common lining as the underlying components. The adhesive interlining was added to the fabric by using a fusing machine, and the lining was sewn to the fabric. The bagging behavior was assessed by extraction of the residual bagging height using the image processing method and the bagging fatigue percentage by stress-strain diagram. The results showed that with the addition of adhesive interlining and lining to the fabric, the bagging fatigue percentage increased. The lining sewn to the fabric reduced the residual bagging height. Also, the friction between the face fabric and the lining was an important factor that, the bagging fatigue percentage increased with increasing the friction, regardless of the fabric material.

Recently, a large set of electroencephalography (EEG) data is being generated by several high-quality labs worldwide and is free to be used by all researchers in the world. On the other hand, many neuroscience researchers need these data to study different neural disorders for better diagnosis and evaluating the treatment. However, some format adaptation and pre-processing are necessary before using these available data. In this paper, we introduce the SecondBrain as a new lightweight and simplified module that can easily apply various major analysis on EEG data with common data formats. The characteristics of the SecondBrain shows that it is suitable for everyday usage with medium analyzing power. It is easy to learn and accept many data formats. The SecondBrain module has been developed with Python and has the power to windowing data, whitening transform, independent component analysis (ICA), downloading the public datasets, computing common spatial patterns (CSP) and other useful analysis. The SecondBrain, also, employs a common spatial pattern (CSP) to extract features and classifying the EEG MI-based data through support vector machine (SVM). We achieved a satisfactory result in terms of speed and performance.

Security and privacy are very important challenges for outsourced private data over cloud storages. By taking Attribute-Based Encryption (ABE) for Access Control (AC) purpose we use fine-grained AC over cloud storage. In this paper, we extend previous Ciphertext Policy ABE (CP-ABE) schemes especially for mobile and resource-constrained devices in a cloud computing environment in two aspects, a novel authentication mechanism and a new revocation approach. To wide-spread adoptions of ABE for a resource-constrained device, a very light-weight authentication mechanism is required to authentication ciphertext before starting cost expensive ABE techniques to thwart Denial-of-Service (DoS) attacks which are used to power depletion and network downing purposes by attackers. We introduce and address the problem to more robustness of whole networks when DoS attacks are present. Moreover, we propose an efficient revocation mechanism which is a very important challenge in the context. Finally with a discussion on different aspects of the proposal and extensive experimental results we show its profitability.

Combining the main advantages of the permanent magnet synchronous motors and pure synchronous reluctance motors (SynRM), permanent magnet assisted synchronous reluctance motor (PMaSynRM) has been considered as a promising alternative to the conventional induction motors. In this paper, utilizing a macroscopic design parameter, called insulation ratio along the q-axis, and based on the magnetic reluctance concept, a simple and fast design procedure of synchronous reluctance motor is introduced. Then, the performance improvement of the machine by inserting the permanent magnets into the rotor body is investigated. After calculating the width of the magnetic flux barriers two dimensions Finite Element Method (FEM) analysis simulation of the designed motor is presented. Additionally, the performance characteristics of the designed motor such as torque producing capability and torque ripple are discussed. Furthermore, thermal analysis is conducted to determine the temperature distribution in the designed motor. Consequently, the prototype motor is fabricated and the experimental results are compared to the simulation results which validate the usefulness of the design method.

The optimization of investment portfolios is the most important topic in financial decision making, and many relevant models can be found in the literature.  According to importance of portfolio optimization in this paper, deals with novel solution approaches to solve new developed portfolio optimization model. Contrary to previous work, the uncertainty of future returns of a given portfolio is modeled using LR-FUZZY numbers while the function of its return are evaluated using possibility theory. We used a novel Lp-metric method to solve the model. The efficacy of the proposed model is tested on criterion problems of portfolio optimization  on LINGO provides a framework to optimize objectives when creating the loan portfoliso, in a search for a dynamic markets decision. In addition to, the performance of the proposed efficiently encoded multi-objective portfolio optimization solver is assessed in comparison with two well-known MOEAs, namely NSGAII and ICA. To the best of our knowledge, there is no research that considered NSGAΠ, ICA fuzzy simultaneously. Due to improve the performance of algorithm, the performance of this approach more study is probed by using a dataset of assets from the Iran’s stock market for three years historical data and PRE method. The results are analyzed through novel performance parameters RPD method. Thus, the potential of our comparison led to improve different portfolios in different generations.

Today, workforce scheduling programs are being implemented in many production and service centers. These sectors can provide better quality products and/or services to their customers, taking into account employees’ desires and preferences in order to increase sector productivity. In this study, an employee shift scheduling problem in the service sector is discussed. In the problem, the aim is to minimize the total amount of workloads of the employees and to provide the preferences of the employees. Under this multi-objective structure, by taking into account the needs of employees, a multi-objective decision model has been developed. After then, a multi-criteria decision-making model has been developed to obtain the weights/priorities of the objective functions. By the help of these obtained weights, the problem is scalarized by the Weighted Sum Scalarization (WSS) and Conic Scalarization (CS) methods. When Pareto solutions are compared, it is seen that more Pareto solutions are obtained with CS method. Additionally, better schedules have been obtained in a very short time in terms of the quality of the solution according to the manually prepared schedule.

The current work investigates the exergy analysis of a new system to generate power, heat, and refrigeration. In the proposed system, the heat loss of a gas turbine (GT) is first recovered by a Heat Recovery Steam Generator (HRSD), then by an Organic Rankine Cycle (ORC) to generate warm water and additional power, respectively. In the ORC, reheating is used to increase the output power, the required heat of which is provided by a geothermal resource. Moreover, there is an absorption refrigeration cycle in the system that operates with the remaining geothermal heat. The exergy efficiency of the system were 50.65%; while the coefficient of performance of the refrigeration system was calculated to be 0.5. In this regard in the entire system, the combustion chamber accounted for the major exergy destruction, making the GT/HRSG system have the highest portion of 87.71%. The greatest exergy efficiency was 96%, which was obtained for the gas turbine.

Nowadays, the major challenge of diesel engines development is simultaneous nitrogen oxides and soot emissions reduction without the thermal efficiency drop. Hence, different combustion concepts should be investigated to reach optimum emission and performance conditions in diesel engines without expensive aftertreatment systems. This paper presents the results of a study on a dual fuel (DF) engine including natural gas and diesel fuel in view of combustion and emissions parameters. The current investigation also supports by 3D-CFD simulation coupled with the chemical kinetics mechanism for detailed investigation. Based on the results, increasing the premixed ratio of natural gas from 50% to 90% causes the combustion shifts toward the expansion stroke. Therefore, the in-cylinder pressure and combustion efficiency decreases. In 90% premixed ratio of natural gas, the non-combustion condition can be observed. This phenomena leads to extremely increase in HC and CO emissions.