Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile radius precision as required as possible. The finite element simulations are accomplished using the commercial code Abaqus/Standard. In order to verify the simulation models, micro deep drawing experiments are carried out using a special set up developed specifically to meet the requirements of the simulations. The results revealed that the proposed technique is feasible to be adopted for producing micro cups with remarkable application capability in miniaturization technology.
Selective recovery of atropine from Datura innoxia seeds was studied. Applying pertraction in a rotating film contactor (RFC) the alkaloid was successfully recovered from native aqueous extracts obtained from the plant seeds. Decane as a liquid membrane and sulfuric acid as a stripping agent were used. Pertraction from native liquid extracts provided also a good atropine refinement, since the most of co-extracted from the plant species remained in the feed or membrane solution. Solid–liquid extraction of atropine from Datura innoxia seeds was coupled with RF-pertraction in order to purify simultaneously the extract obtained from the plant. Applying the integrated process, proposed in this study, a product containing 92.6% atropine was
... Show MoreThe aim of this paper is to present a method for solving third order ordinary differential equations with two point boundary condition , we propose two-point osculatory interpolation to construct polynomial solution. The original problem is concerned using two-points osculatory interpolation with the fit equal numbers of derivatives at the end points of an interval [0 , 1] . Also, many examples are presented to demonstrate the applicability, accuracy and efficiency of the method by compared with conventional method .
The nonlinear refractive index and the nonlinear absorption coefficient of unmodified and functional poly(methyl methacrylate) PMMA films were studied before and after the addition of the filler by the z-scan technique, using a Q-switched Nd:YAG laser at two wavelengths: 532 nm and 1064 nm, and at three input energies (13, 33 and 53) mJ. Both linear and nonlinear refractive indices and absorption coefficients of polymer films were studied by using UV-VIS spectrophotometer. The results show that the creation of functional PMMA from unmodified PMMA will increase the nonlinear optical properties in the functional PMMA/copper matrix more than in the unmodified PMMA/copper matrix. Hence, the functional PMMA appears promising as a useful third
... Show MoreIn this study, the induced splined shaft teeth contact and bending stresses have been investigated numerically using finite element method(Ansys package version 11.0) with changing the most effecting design parameter,(pressure angle, teeth number, fillet radius and normal module), for internal and external splined shaft. Experimental work has been achieved using two dimensional photoelastic techniques to get the contact and bending stresses; the used material is Bakelite sheet type “PSM-4”.
The results of numerical stress analysis indicate that, the increasing of the pressure angle and fillet radius decrease the bending stress and increase the contact stress for both internal and external spline shaft teeth while the increasing of
In this work, electrochemical process was presented to polymerized eugenol on Gr.2 and Gr.5 titanium alloys before and after treated by Micro Arc Oxidation (MAO), where Gr.2 is commercial pure titanium and Gr.5 is Ti-6Al-4V dental alloys. The deposited layers were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The adhesion strength of polymeric thin-film was estimation by using pull-off adhesion test and the result was the adhesion strength of PE was (1.23 MPa) on Gr.2 before MAO and increase to (1.98 MPa) on Gr.2 after MAO treatment. The corrosion behavior of Gr.2 and Gr.5 alloy in artificial saliva environment at
... Show Morea simple accurate and sensitive spectrophotometric method for the determination of promethazine HCI has been developed the method is based on the oxidative coupling reaction of promethazine
Modern emerged technologies impose development and fabrication of miniatur-ized parts and devices in the micro- and nano-scale. Producing micro- and nano-featured structures requires nonconventional machining processes where con-ventional machining processes such as grinding, milling and eroding have failed. New emerging processes, such laser machining processes, are still fraught with almost invincible processes. Micro-/nano-machining are the pro-cesses of producing parts, microsystems or features at a scale of a few microm-eters and less than one hundred nanometers, respectively. Precise cutting and clean material removal accompanied with a negligible heat affected zone (HAZ), which are usually the characteristics of laser ablation, have
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreNatural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are
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