Theoretical Drawbacks in Fuzzy Ranking Methods and Some Suggestions for a Meaningful Comparison: An Application to Fuzzy Risk Analysis

Comparing fuzzy numbers has become one of the key challenging issues in fuzzy sets. Many researchers have proposed different procedures to rank fuzzy numbers, but the results frequently contradict each other. This work addresses the key weakness of several fuzzy ranking methods which have been introduced in recent articles. In this paper, we reveal that in nearly all ranking methods that the ranking procedure depends on the height of fuzzy numbers the result is unreliable. However, the final aim of this study is to propose some suggestions for a meaningful comparison in new methods. We demonstrate our reasoning with several numerical cases taken from literature.     

Effect of SiC content on the processing, compaction behavior, and properties of Al6061/SiC/Gr hybrid composites

Aluminum matrix composites reinforced with SiC and graphite (Gr) particles are a unique class of advanced engineered materials that have been developed to use in tribological applications. The conventional techniques for producing these composites have some drawbacks. In this study, a new method, namely In situ Powder Metallurgy (IPM), is applied for the preparation of Al6061/SiC/Gr hybrid composites. In this method, the stir casting and the powder metallurgy synthesizing processes are combined into an integrated net shape forming process. 0?C40 vol.% of SiC particles with an average size of 19 ??m, along with 9 vol.% of uncoated Gr particles, were introduced to the molten 6061 aluminum alloy. Then, the slurries were stirred in a specified time?Ctemperature regime resulting in mixtures of the SiC, Gr, and aluminum powder particles. The powder mixtures were cold pressed in six different pressures (between 250 and 750 MPa) and sintered. Finally, the produced composites were heat treated and their hardness and wear properties were investigated. Homogenous distribution of the SiC and Gr particles within the powder mixtures and the hybrid composites is clear from the SEM images. The results also show that the SiC particles decrease the compressibility of the hybrid powders and improve the hardness of composites. The best wear resistance is achieved in the hybrid composite containing 20 vol.% SiC particles.     

Effect of a magnetic field on natural convection in an inclined half-annulus enclosure filled with Cu–water nanofluid using CVFEM

In this paper, the effect of a magnetic field on natural convection in a half-annulus enclosure with one wall under constant heat flux using control volume based finite element method. The fluid in the enclosure is a water-based nanofluid containing Cu nanoparticles. The effective thermal conductivity and viscosity of nanofluid are calculated using the Maxwell–Garnetts (MG) and Brinkman models, respectively. Numerical simulations were performed for different governing parameters namely the Hartmann number, Rayleigh number and inclination angle of enclosure. The results indicate that Hartmann number and the inclination angle of the enclosure can be control parameters at different Rayleigh number. In presence of magnetic field velocity field retarded and hence convection and Nusselt number decreases.     

Dehydration of natural gas and biogas streams using solid desiccants: a review

Natural gas and biogas are two mixtures that consist of methane as their main component. These two gas mixtures are usually saturated with water vapor, which cause many problems, such as damaging the gas processing equipment by increasing the gas’s corrosion potential or clogging the pipelines due to gas hydrate formation. Thus, removing water vapor from these gas streams is mandatory. In this review paper, the main dehydration methods have been overviewed, and scrutiny of the adsorption dehydration has been carried out. Furthermore, the most important solid desiccants and their improvements have been reviewed.     

Application of neural networks to predict the transient performance of a Run-Around Membrane Energy Exchanger for yearly non-stop operation

Application of soft computing methods (i.e. neural networks and genetic algorithms) for modeling and controlling the dynamic and transient behavior of systems has been increasing during the last decade. In this study, a neural network (NN) model is developed to predict the transient heat and moisture transfer performances (i.e., the sensible and latent effectivenesses) of a novel HVAC energy exchanger, called the Run-Around Membrane Energy Exchanger (RAMEE), which is able to transfer both heat and moisture between exhaust and supply air streams. The training data set for the NN model covers a wide range of outdoor conditions and system parameters and is produced using a Transient Numerical Model (TNM) that has been experimentally validated for some transient applications. Two separate NNs (one for sensible and one for latent energy transfer) each with 12 inputs and one output, are selected to represent the RAMEE. The ability of NN models to predict the performance of a given RAMEE design in different climates is numerically validated. The mean absolute difference (MAD) between the results of TNM and NN models for different locations are 0.5 °C for the sensible model and 0.2 g_v/kg_a for the latent model, which indicates satisfactory agreement for energy exchange calculations. These NN models are very fast and easy to use therefore, they might be used for design purposes or estimating the annual energy savings in different buildings with continuous operation and a RAMEE in their HVAC system.     

Investigation of the rheological behavior of titanium dioxide pigmented acrylonitrile–butadiene–styrene polymer

Titanium dioxide (TiO₂) pigments may be surface‐modified by hydrous oxides, such as alumina (e.g., Cristal 134) or by organic compounds, such as organophosphate (e.g., Tiona 188). In this investigation, the effects of these pigments on the rheological properties of acrylonitrile–butadiene–styrene (ABS) polymer were investigated. With the oscillatory rheometry method in the linear viscoelastic region, the storage and loss moduli versus frequency graph of ABS in the molten state showed two crossover points (COPs) when the surface of the ABS components, that is, poly(styrene‐stat‐acrylonitrile) and poly[(styrene‐stat‐acrylonitrile)‐graft‐polybutadiene] or g‐ABS, had good interaction. The first COPs increased when the TiO₂ content rose to 0.5 and 1.5% in Tiona 188 and Cristal 134 pigmented ABS samples, respectively. With the addition of TiO₂ up to these contents, the polymer–pigment interaction becomes stronger so that the dispersion of the pigments was good. With increasing TiO₂, the first COPs dramatically decreased because of agglomeration of the pigments. The shifting of the first COP may be applied as a criterion to specify the dispersion of TiO₂ particles in the ABS matrix. Scanning electron micrographs showed that the pigments had no effect on the size of the polybutadiene particles. Also, transmission electron micrographs proved that agglomerates of Tiona 188 and Cristal 134 particles were formed above 0.5 and 1.5% TiO₂ contents, respectively. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

A comparative study on viscoelastic properties of polymeric composites measured by a longitudinal free vibration non-destructive test and dynamic mechanical thermal analysis

In this study, viscoelastic properties of polymeric composites were investigated through a non-destructive test (NDT) method based on longitudinal free vibration. First, three different polyester composites reinforced separately with carbon, glass, and hemp fibers, as well as, one polyester composite sample reinforced with poplar wood powder were manufactured via pultrusion and hand lay-up methods, respectively. In the proposed resonant free vibration non-destructive method, each rod-shaped test specimen was hit by a hammer at one end of specimen and immediately the acoustic response of the specimen was recorded by a microphone at the other end of the sample. Subsequently, the recorded sounds were analysed using fast Fourier transform technique. Then, frequency of the first mode of vibration for each composite specimen was utilised to calculate modulus of elasticity. Further, decrement in vibration energy as a function of time was examined to obtain loss parameter (tan ??) of the provided composites. Moreover, parameters (i.e., elastic modulus and tan ??) were also compared with those determined by dynamic mechanical thermal analysis (DMTA). It is found that the results obtained from the examined non-destructive test method are in consistent with those measured by DMTA approach, providing reliable, accurate and quick responses.     

Effect of oxygenates blending with gasoline to improve fuel properties

The purpose of this paper is to study the effect of oxygenate additives into gasoline for the improvement of physicochemical properties of blends.Methyl Tertiary Butyl Ether(MTBE),Methanol,Tertiary butyl alcohol(TBA),and Tertiary amyl alcohol(TAA) blend into unleaded gasoline with various blended rates of 2.5%,5%,7.5%,10%,15%,and 20%.Physicochemical properties of blends are analyzed by the standard American Society of Testing and Materials(ASTM) methods.Methanol,TBA,and TAA increase density of the mixtures,but MTBE decreases density.The addition of oxygenates lead to a distortion of the base gasoline’s distillation curves.The Reid vapor pressure(RVP) of gasoline is found to increase with the addition of the oxygenated compounds.All oxygenates improve both motor and research octane numbers.Among these four additives,TBA shows the best fuel properties.     

Optimization of parallel manipulator trajectory for obstacle and singularity avoidances based on neural network

This paper presents a novel method for singularity-free path planning and obstacle avoidance of parallel manipulators. A modified 3-4-5 interpolating polynomial is used to plan a trajectory for a planar 3-DOF parallel manipulator. The polynomial function which is smooth and continuous in displacement, velocity, and acceleration is used to find a smooth path avoiding the obstacles and singularities. An artificial neural network is implemented to solve forward kinematics of the manipulator to estimate the distance between gripper and singularity or obstacle. The simulating results demonstrate the efficiency of the proposed algorithm.