This research presents a mathematical model of feed-interval scallop height, where in a machined surface there are two types of scallop height, the pick(path)-interval scallop and the feed-interval scallop. The pick-interval scallop is generated by the finite pick offset between the successive cutting paths, while the feed-interval scallop is generated by the finite increment between the successive tooth feeds. New model that describes and predicts the geometric generating mechanisms of the feed-interval scallop height have been derived using torus cutter which is commonly used in multi-axis milling machine. The machining parameters (effective tool cutter radius, feed per tooth and the magnitude of tool axis inclination angles) have been considered in theoretical and experimental work to study the effect of these parameters on this type of scallop height. From theoretical and experimental work it was found that at high-speed machining, the feed-interval scallop is more important to the surface roughness than the path-interval scallop, and the feed-interval scallop is very sensitive to the tool-axis inclination angle. The feed-interval scallop height decreased sharply and quickly within a few degrees of the tool-axis inclination to the normal workpiece surface. In general, an inclination angle equal to is good enough for all tool diameters used in the present work, namely (6,8,10 12 mm).
Milling includes a variety of different tasks and tools, ranging from small individual pieces to large, powerful group processes. It is one of the most commonly used techniques for producing custom parts with exact tolerances. Surface roughness of machined parts has a significant impact on the finished item's quality, which may have an impact on its tolerance and performance. This paper studies the prediction of the values of surface roughness of low-carbon steel AISI 1015 in milling operations. Three different machining parameters with nine variable samples are selected to investigate the resultant surface roughness of the AISI 1015 low-carbon steel samples, including different spindle speeds, feed rates, and depths of cut. The results revealed that the feed rate of 100 mm/min at a spindle speed of 930 rpm and a depth of 1.5 mm produced the lowest surface roughness (Ra) value of 1.170 µm, while the feed rate of 300 mm/min at a spindle speed of 1100 rpm produced the greatest surface roughness value of 2.605.
Turning is the most popular machining operation. The quality of the product may be determined using a variety of metrics, such as the surface generation method and the surface roughness of the product. This work uses cutting variables to obtain the best surface quality through a mathematical model. The suggested surface generation in this work results from deriving it using the Bezier technique, with degree (5th) having six chosen control points. One of the critical indicators of the quality of machined components is the surface roughness created during the machining process. Surface roughness improvement via machining process parameter optimization has been extensively researched. The Taguchi Method and actual tests were employed for evaluating the surface quality of complicated forms; regression models with three different variables for the cutting process, such as cutting speed, depth of cut, and feed rate, were also used. According to the experimental findings, the most significant effect of feed rate on the surface roughness is approximately (40.9%), and the more minor effect of depth of cut on the surface roughness is almost (16.23%). In addition, the average percentage error is 4.93%, the maximum error is 0.14 mm, and the minimum error is -0.143 mm for the prediction using the regression equation.
The most common type of abrasive water jet is known as a valuable and advanced non-traditional machining operation due to its no heat-affected zone, best in removing material, very environmentally friendly, and no mechanical stresses. This paper gives an idea about Abrasive water jets in terms of applications, advantages, and limitations. Also illustrates the influence of the parameters on the material removal rate. The effect of feed rate, pressure, and stand-off distance were worked, at three levels for material removal rate (MRR) to machining Aluminium alloy type-5083 by using a tool consisting of a mixture of 70% water and 30% abrasives of red garnet. The distance of the standoff has the most significant impact on the rate of material removal, which is subsequently followed by the feed rate and finally the pressure. The findings demonstrated that the Taguchi model is capable of making accurate predictions regarding the machining reactions, with a rate of material removal of 93.3%.
Nowadays, renewable energy sources are becoming further utilized to produce electricity. Fuel cell (FC) is one of the encouraging renewable and sustainable power resources as a result of its high power density and extremely low release. This paper presents suggestion and implementation of FC power system. So as to design a greatly efficient FC power system, proper DC - DC and DC - AC converters are needed. Among the different types of DC - DC converters, Interleaved Boost Converter (IBC) has been proposed as appropriate interface between FC and the next stage to transform the produced power energy (low voltage high current input into a high voltage low current output of the FC). 11-level Neutral Point Clamped (NPC) Multilevel Converter (MLC) is proposed for converting the DC output of the IBC to AC voltage to feed the load. MLC is chosen because it has many attractive features like high voltage capability, smaller or even no output filter, low voltage stress on load. Simulation of the proposed FC power system has been performed using MATLAB/SIMULINK..
This work presents a compact reconfigurable antenna based on fractal geometry. The investigation discusses the challenges of lower antenna gain and bandwidth, critical for efficient data propagation in 5G systems, particularly for low-profile devices. Its goal is to develop a small, multiband antenna capable of operating in all current and future 5G bands and improve bandwidth and gain for mm-wave and sub-6 GHz applications. The proposed design covers the sub-6 band (2.8, 3.9, 4, 6.2) GHz and the mm-wave band (24.4, 27.1, 28.5, 29.3, 30.6, 33.9, 34.6, 35.2, 38.8, 44.4, 45.1, 59.7, 61.5, 62.3, 65.2, 67.4 and 69.5) GHz with S11 less than -10 dB. A maximum gain of 12.8 dB and a radiation efficiency of 94% are achieved. A partial ground plane with a 50 Ω feed line is used in this design. The antenna is printed on a Roger RT 5880 substrate with a relative dielectric constant 2.2 with a total dimension of 35×32.5×0.8 mm³. The proposed design is simulated using CST software, ensuring accurate calculations and performance evaluation.
The antenna is a Modified Broadband Butterfly Antenna (MBBA). The technical parameters of such systems are heavily influenced by the qualities of the antenna feed devices. The aperture theory of antennas uses the representation of the radiation field of the antenna as a superposition of the fields of elementary sources, characterized by their type and amplitude-phase spatial distribution. The radiation field of an antenna of finite dimensions is a superposition of inhomogeneous spherical waves emitted by the antenna elements. This paper is primarily the study process, Radiation models were calculated using the model of the cavity plates, Simple Green model, and the strict commercial Electromagnetic Simulator. The modified active rectangular patches with the Gann diode were combined into arrays of E and H plane. Calculated and measured results for these two active arrays the beam scanning, the possibilities have been demonstrated for both arrays. The results of an electrodynamics numerical simulation were obtained. Broadband and multiband radio systems have already found widespread practical applications by utilizing basic antenna parameters and characteristics.
The Artificial Neural Network (ANN) and numerical methods are used widely for modeling andpredict the performance of manufacturing technologies. In this paper, the influence of millingparameters (spindle speed (rpm), feed rate (mm/min) and tool diameter (mm)) on material removalrate were studied based on Taguchi design of experiments method using (L16) orthogonalarray with 3 factor and 4 levels and Neural Network technique with two hidden layers and neurons.The experimental data were tested with analysis of variance and artificial neural networkmodel has been proposed to predict the responses. Analysis of variance result shows that tooldiameters were the most significant factors that effect on material removal rate. The predictedresults show a good agreement between experimental and predicted values with mean squarederror equal to (0.000001), (0.00003025), (0.002601) and (0.006889) respectively, which produceflexibility to the manufacturing industries to select the best setting based on applications.