The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).
Abstract\
In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the
... Show MoreSawdust has the ability to adsorb the dyestuff from aqueous solution. It may be useful low cost adsorbent for the treatment of effluents, discharged from textile industries. The effectiveness of sawdust has been tested for the removal of color from the wastewater samples containing two dyes namely Direct Blue (DB) and Vat Yellow (VY). Effect of various parameters such as agitation time, adsorbent dose and initial concentration of each dye has been investigated in the present study. The adsorption of dyes has been tested with various adsorption isotherm models. The Langmuir isotherms model is found to be the most suitable one for the dye adsorption using sawdust and the maximum adsorption capacity is 8.706 mg/g and 6.975 mg/g for DB and V
... Show MoreAtomic Force Microscope is an efficient tool to study the topography of precipitate. A study using Continuous Flow Injection via the use of Ayah 6SX1-T-2D Solar cell CFI Analyser . It was found that Cyproheptadine –HCl form precipitates of different quality using a precipitating agent's potassium hexacyanoferrate (III) and sodium nitroprusside. The formed precipitates are collected as they are formed in the usual sequence of forming the precipitate via the continuous flow .The precipitates are collected and dried under normal atmospheric pressure. The precipitates are subjected to atomic force microscope scanning to study the variation and differences of these precipitates relating them to the kind of response to both precipitates give
... Show MoreOil well drilling fluid rheology, lubricity, swelling, and fluid loss control are all critical factors to take into account before beginning the hole's construction. Drilling fluids can be made smoother, more cost-effective, and more efficient by investigating and evaluating the effects of various nanoparticles including aluminum oxide (Al2O3) and iron oxide (Fe2O3) on their performance. A drilling fluid's performance can be assessed by comparing its baseline characteristics to those of nanoparticle (NPs) enhanced fluids. It was found that the drilling mud contained NPs in concentrations of 0,0.25, 0. 5, 0.75 and 1 g. According to the results, when drilling fluid was used without NPs, the coeff
... Show MoreAn experimental investigation has been carried out for zinc-nickel (Zn-Ni) electro-deposition using the constant applied current technique. Weight difference approach method was used to determine the cathode current efficiency and deposit thickness. Also, the influence effect of current density on the deposition process, solderability, and porosity of the plating layer in microelectronic applications were examined. The bath temperature effect on nickel composition and the form of the contract was studied using Scanning Electron Microscope (SEM). Moreover, elemental nature of the deposition was analyzed by Energy Dispersive X-Ray (EDX).
It has been found that the best bath temperature
... Show MoreBackground Alloys with the addition of zirconium and niobium eliminate the adverse effects of aluminum and vanadium on the nervous system, the possibility of metallosis and the initiation of diseases (including cancers or Alzheimer›s disease). In addition, they have better corrosion resistance, and a Young›s modulus value similar to longitudinal bone tissue. Therefore, only choosing appropriate materials does not guarantee proper functioning of the implants, the surfaces of the implants also have to be suitable to meet the requirements. The laser surface hardening process modifies the surface properties by imparting microstructural changes, whereas surface remelting induces changes in the surface topography, roughness, wettability and w
... Show MoreThe aim of this paper is to introduce the concept of N and Nβ -closed sets in terms of neutrosophic topological spaces. Some of its properties are also discussed.
In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
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