Time–cost optimization: using GA and fuzzy sets theory for uncertainties in cost

Uncertainties should be considered in any time–cost trade‐off problems when minimizing project cost and duration, which leads to the so‐called stochastic time–cost trade‐off problem. A new approach to investigate stochastic time–cost trade‐off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop a solution to the multi‐objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non‐dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision‐making process by selecting specified risk levels and employing the associated Pareto front.     

Cement take estimation using neural networks and statistical analysis in Bakhtiari and Karun 4 dam sites,in south west of Iran

Bulletin of Engineering Geology and the Environment - Water seepage from dam foundations causes reservoir water loss and raises the risk of dam instability. One method of remediation for...     

A novel stimuli-responsive magnetic hydrogel based on nature-inspired tragacanth gum for chemo/hyperthermia treatment of cancerous cells

Journal of Polymer Research - Derivatives of formyl pyrazole were synthesized by the reaction of acetophenone, 4-methyl acetophenone, 3-acetyl furan, 3-acetyl thiophen and phenyl hydrazine...     

Zinc Oxide/Graphene Oxide as a Robust Active Catalyst for Direct Oxidative Synthesis of Nitriles from Alcohols in Water

Catalysis Letters - In this work, without using any linker or chemical modification of graphene oxide, a zinc oxide immobilized graphene oxide-based catalyst was used for the direct aerobic...     

Ternary gas permeation through synthesized pdms membranes: Experimental and CFD simulation basedon sorption‐dependent system using neural network model

In this study, a predictive model for the separation of gases via a polydimethylsiloxane (PDMS) membrane has been developed. This model takes into account the effects of gas composition and pressure at the membrane surfaces on the gas sorption and diffusion coefficients in the membrane. Computational fluid dynamics (CFD) modeling has been employed in order to predict the behavior of a gas mixture containing C₃H₈, CH₄, and H₂ at various operating conditions and three zones (upstream, downstream, and membrane body). Artificial neural network (ANN) modeling has been applied to predict sorption and diffusion coefficients of each component of the gas mixture in the membrane. A procedure of calculation has been applied to combine the CFD modeling and the ANN modeling in order to predict sorption, diffusion, and composition of each component at various sites of the membrane. The results determined using the developed prediction model have been found to be in agreement with those determined using experimental investigations with an average error of 10.21%. POLYM. ENG. SCI., 54:215–226, 2014. © 2013 Society of Plastics Engineers     

Synthesis and characteristics of fly ash and bottom ash based geopolymers–A comparative study

The research was carried out to develop geopolymers mortars and concrete from fly ash and bottom ash and compare the characteristics deriving from either of these products. The mortars were produced by mixing the ashes with sodium silicate and sodium hydroxide as activator solution. After curing and drying, the bulk density, apparent density and porosity, of geopolymer samples were evaluated. The microstructure, phase composition and thermal behavior of geopolymer samples were characterized by scanning electron microscopy, XRD and TGA-DTA analysis respectively. FTIR analysis revealed higher degree of reaction in bottom ash based geopolymer. Mechanical characterization shows, geopolymer processed from fly ash having a compressive strength 61.4 MPa and Young's modulus of 2.9 GPa, whereas bottom ash geopolymer shows a compressive strength up to 55.2 MPa and Young's modulus of 2.8 GPa. The mechanical characterization depicts that bottom ash geopolymers are almost equally viable as fly ash geopolymer. Thermal conductivity analysis reveals that fly ash geopolymer shows lower thermal conductivity of 0.58 W/mK compared to bottom ash geopolymer 0.85 W/mK.     

Evaluation of alumina reinforced oil fly ash composites prepared by spark plasma sintering

The thermomechanical behavior of micro/nano-alumina (Al₂O₃) ceramics reinforced with 1-5 wt.% of acid-treated oil fly ash (OFA) was investigated. Composites were sintered using spark plasma sintering (SPS) technique at a temperature of 1400°C by applying a constant uniaxial pressure of 50 MPa. It was evaluated that the fracture toughness of micro- and nanosized composites improved in contrast with the monolithic alumina. Highest fracture toughness value of 4.85 MPam^1/2 was measured for the nanosized composite reinforced with 5 wt.% OFA. The thermal conductivity of the composites (nano-/microsized) decreased with the increase in temperature. However, the addition of OFA (1-5 wt.%) in nanosized alumina enhanced the thermal conductivity at an evaluated temperature. Furthermore, a minimum thermal expansion value of 6.17 ppm*K⁻¹ was measured for nanosized Al₂O₃/5 wt.% OFA composite. Microstructural characterization of Al₂O₃-OFA composites was done by x-ray diffraction and Raman spectroscopy. Oil fly ash particles were seen to be well dispersed within the alumina matrix. Moreover, the comparative analysis of the nano-/microsized Al₂O₃/OFA composites shows that the mechanical and thermal properties were improved in nanosized alumina composites.     

Synthesis of modified catalyst and stabilization of CuO/NH4‐ZSM‐5 for conversion of methanol to gasoline

In this article, the catalytic conversion of methanol to gasoline range hydrocarbons has been studied over CuO/ NH₄‐ZSM‐5(3,5,7,9%) catalysts prepared via sono‐chemistry methods. In order to improve, copper oxide can be used as a booster on NH₄‐ZSM‐5 this catalyst property. Accordingly, the conversion process of Methanol to Gasoline (MTG) was conducted under a pressure of 1 atm and temperature of 400°C by a fixed‐bed reactor on copper oxide catalysts which were prepared based on synthetic NH₄‐ZSM‐5. The synthetic catalyst was investigated by such analyses as BET, XRD, FT‐IR, and SEM. Formation of copper oxide phase and proper distribution of copper oxide were proven on the basic level of using XRD analysis. BET analysis showed the reduction in catalyst level and SEM images depicted the proper distribution of particles. The present investigation is to study the effect of CuO loading on NH4‐ZSM‐5 support for conversion of methanol to gasoline range hydrocarbons. A series of CuO/ NH4‐ZSM‐5 catalysts were prepared, characterized, and experimented for their performance on methanol conversion and hydrocarbon yield.     

Additive Manufacturing of Graphene–Hydroxyapatite Nanocomposite Structures

In this article, a powder‐bed class of additive manufacturing (AM) is incorporated into the manufacturing of graphene nanocomposite 3D structures. For AM of graphene‐based 3D structures, graphene oxide (GO)/hydroxyapatite (Hap) nanocomposite (GHN) was synthesized at different GO to Hap percentage (wt.%), including 0.2% and 0.4% to develop a printable powder. The synthesized powder was utilized in a powder‐bed AM system to fabricate 3D porous structures of GHN powder. It was shown that at layer thickness of 125 μm and core binder saturation level of 400%, the compressive mechanical strength of the samples with higher content of graphene was improved significantly.