An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Toward A Mechanistic Understanding of Re-Infiltration in Naturally Fractured Reservoirs with Surfactant-Aided Gravity Drainage Process

Surfactant-aided gravity drainage is an improved oil recovery technique for water-invaded zone in fractured carbonate reservoirs, which are mostly oil-wet or mixed-wet rocks. The re-infiltration mechanism in water-invaded zone has a considerable effect on oil vertical movement in gravity drainage processes. In this work, a mechanistic understanding of re-infiltration in surfactant-aided gravity drainage, in comparison to oil–water gravity drainage is presented using an experimentally and numerically validated model. A column model is constructed from three matrix blocks. These blocks are separated from each other by horizontal fractures. A storage tank is considered on top of the model to store depleted oil from matrix blocks. The stacked-blocks model for re-infiltration is validated and verified to simulate water and chemical flooding using a mesh independency study and experimental flooding data in a composite core experiment. Using this model, several analyses are performed to investigate effects of rock and fluid properties, rock saturation functions, wettability alteration, surfactant adsorption, and capillary continuity on re-infiltration.     

Defensive role ofAllium sulfur compounds for leek mothAcrolepiopsis assectella Z. (Lepidoptera) against generalist predators

It has been shown previously that sulfur volatiles produced byAllium plants affect the behavior of their specialist phytophages and of their specialist entomophages. The action of these compounds in protecting the leek mothAcrolepiopsis assectella against generalist entomophages was studied in comparison to the proposed original defensive role of these compounds against generalist herbivorous insects. Two ants species,Formica selysi andF. fusca, were used as generalist predators. Six behavioral criteria of the predatory behavior of the ants were studied in presence of the last-instar caterpillars (C₅). C₅ reared on artificial diets with or without leek components were tested, as well as C₅ soaked in frass of leek-reared caterpillars or disulfide solutions. In addition, the response of the ants to pure chemicals found in leek was studied using honey solutions with or without sulfur compounds. The sulfur allelochemicals ofAllium plants have a negative action on predatory ants. Interestingly, the nonvolatile precursors of sulfur volatiles ofAllium plants seem to have a protective role for their phytophagous insects against generalist entomophages.     

A case study validation of a knowledge-based approach for the selection of requirements engineering techniques

Requirements engineering (RE) is a critical phase in the software engineering process and plays a vital role in ensuring the overall quality of a software product. Recent research has shown that industry increasingly recognizes the importance of good RE practices and the use of appropriate RE techniques. However, due to the large number of RE techniques, requirements engineers find it challenging to select suitable techniques for a particular project. Unfortunately, technique selection based on personal experience has limitations with regards to the scope, effectiveness and suitability of the RE techniques for the project at hand. In this paper, a Knowledge-based Approach for the Selection of Requirements Engineering Techniques (KASRET) is proposed that helps during RE techniques selection. This approach has three major features. First, a library of requirements techniques was developed which includes detailed knowledge about RE techniques. Second, KASRET integrates advantages of different knowledge representation schemata and reasoning mechanisms. Thus, KASRET provides mechanisms for the management of knowledge about requirements techniques and support for RE process development. Third, as a major decision support mechanism, an objective function evaluates the overall ability and cost of RE techniques, which is helpful for the selection of RE techniques. This paper makes not only a contribution to RE but also to research and application of knowledge management and decision support in process development. A case study using an industrial project shows the support of KASRET for RE techniques selection.

Extended Algorithms for Approximating Variable Order Fractional Derivatives with Applications

This paper proposes accurate and robust algorithms for approximating variable order fractional derivatives of arbitrary order. The proposed schemes are based on finite difference approximations. We compare the performance of algorithms by introducing a new formulation of experimental convergence order. Two initial value problems are considered and solved by means of the proposed methods. Numerical results are provided justifying the usefulness of the proposed methods.     

Roll bonding of AA5052 and polypropylene sheets: Bonding mechanisms,microstructure and mechanical properties

Structural, microstructural and mechanical properties in roll bonding of AA5052 and polypropylene sheets have been evaluated in this study. The surface roughness of the AA5052 sheets, rolling temperature and the surface energy of polymer were selected as the bonding variables. The findings indicated that an increase in the surface energy of polypropylene by grafting maleic anhydride would result in higher bonding strength due to chemical interaction between the AA5052 and the maleic anhydride grafted polypropylene (PP-g-MAH). In fact, this reaction caused the formation of an interphase layer at the polymer side of the interface and the diffusion of aluminum into the PP-g-MAH layer. It was also observed that an increase in the rolling temperature increases bonding strength because the polymer penetrates the AA5052 surface irregularities more easily, the PP-g-MAH molecules move more smoothly toward the AA5052 surface, and finally there are more chemical interactions among the layers. An Increase in the bonding strength through increasing the AA5052 surface roughness was attributed to an increase of the van der Waals force and more interaction surface among the layers along with higher mechanical interlocking in the shear tension test.     

Modeling managerial behavior in real options valuation for project-based environments

Project valuation, as a decision-making tool for initiating investments in projects, should be able to value project flexibilities and incorporate reasonable risk preferences of relevant decision makers. Real options valuation methods are the available approaches for valuing project flexibilities, whereas they have shortcomings in considering managers’ reasonable risk preferences in project decisions. Therefore, researchers have suggested approximating the perspective on risk of real options methods and practitioners in project management. This study proposes a fair real options valuation for project-based environments by a behavioral economic approach, which adopts binomial lattice method, Monte-Carlo simulation, and cumulative prospect theory. The results show that behavioral factors such as ‘risk attitude’ and ‘loss aversion’ should be accepted in project investment decisions while limited to an acceptable amount depending on the project conditions (e.g. uniqueness of decision-making scenarios). This research contributes to the project management domain by enhancing project investment decisions that include project flexibilities.     

Comparison and evaluation of dust detection algorithms using MODIS Aqua/Terra Level 1B data and MODIS/OMI dust products in the Middle East

Dust storms have a major impact on air quality, economic loss, and human health over large regions of the Middle East. Because of the broad extent of dust storms and also political–security issues in this region, satellite data are an important source of dust detection and mapping. The aim of this study was to compare and evaluate the performance of five main dust detection algorithms, including Ackerman, Miller, normalized difference dust index (NDDI), Roskovensky and Liou, and thermal-infrared dust index (TDI), using MODIS Level 1B and also MODIS Deep Blue AOD and OMI AI products in two dust events originating from Iraq and Saudi Arabia. Overall, results showed that the performance of the algorithms varied from event to event and it was not possible to use the published dust/no-dust thresholds for the algorithms tested in the study area. The MODIS AOD and OMI AI products were very effective for initial dust detection and the AOD and AI images correlated highly with the dust images at provincial scale (p-value <0.001), but the application of these products was limited at local scale due to their poor spatial resolution. Results also indicated that algorithms based on MODIS thermal infrared (TIR) bands or a combination of TIR and reflectance bands were better indicators of dust than reflectance-based ones. Among the TIR- based algorithms, TDI performed the best over water surfaces and dust sources, and accounted for approximately 93% and 90% of variations in the AOD and OMI AI data.     

Immobilization of Metalloporphyrin on Functionalized MCM-48 Nanoporous Silica as a Catalyst in Oxidation of Cyclohexene: The Effects of Nanoporous Structure of MCM-48 on Its Catalytic Efficiency

MCM-48 nanoporous silica were prepared by the sol–gel method and functionalized by pyridine using a silane agent. With the aid of pyridines on the surface, the nanoporous material was used as a support for immobilization of metalloporphyrin. The formation of this material was confirmed by infrared spectroscopy, X-ray powder diffraction, transmission electron microscopy, inductively coupled plasma atomic emission spectroscopy analysis and specific surface area measurement. The application of this metalloporphyrin-immobilized MCM-48 was investigated as a heterogeneous catalyst in cyclohexene oxidation. Various parameters such as solvent and time were optimized. Also the effect of nanoporous structure on the efficiency of the catalyst was investigated by comparing the results with the same composite using nonporous silica (SiO₂). The result showed that the MCM-48 immobilized metalloporphyrin is a better catalyst for cyclohexene oxidation, which can be attributed to its nanoporous structure. The nanoporous structure increases the surface area of MCM-48 and leads to more metalloporphyrin immobilization.     

Seismic performance evaluation of steel moment resisting frames through incremental dynamic analysis

Earthquake hazards effect significant damage to structures and cause widespread failure throughout buildings. Moment resisting frames are widely used as lateral resisting systems when sufficient ductility is to be met. Generally three types of moment resisting frames are designed in practice namely Special, Intermediate and Ordinary Moment Frames, each of which has certain level of ductility. Comparative studies on the seismic performance of these three different types of structure are performed in this study. Analytical models of connections are employed including panel zone and beam to column joint model. Incremental dynamic analysis is then utilized to assess the structural dynamic behavior of the frames and to generate required data for performance based evaluations. Maximum annual probability of exceeding different limit states may reveal the superiority of a ductile structure in which a greater behavior factor is employed. Special moment resisting frames are expected to perform better once a certain level of ductility is to be met but the amount of superiority may be the subject of investigation especially from a performance based design standpoint.