Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were divided randomly into three subsets for training, validation, and testing the developed hybrid intelligent model. ANOVA results revealed that feed rate is highly affected by the surface roughness followed by the depth of cut. One-way ANOVA, including a Post-Hoc test, was used to evaluate the performance of three developed models. The hybrid model of Artificial Neural Network-Gravitational Search Algorithm (ANN-GSA) has outperformed Artificial Neural Network (ANN) and Artificial Neural Network-Genetic Algorithm (ANN-GA) models. ANN-GSA achieved minimum testing mean square error of 7.41 × 10−13 and a maximum R-value of 1. Further, its convergence speed was faster than ANN-GA. GSA proved its ability to improve the performance of BPNN, which suffers from local minima problems.
In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.
loge(DI)=a1+0.0123(2loge T
... Show MoreThe shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial
... Show MoreAn application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter
Research in consumer science has proven that grocery shopping is a complex and distressing process. Further, the task of generating the grocery lists for the grocery shopping is always undervalued as the effort and time took to create and manage the grocery lists are unseen and unrecognized. Even though grocery lists represent consumers’ purchase intention, research pertaining the grocery lists does not get much attention from researchers; therefore, limited studies about the topic are found in the literature. Hence, this study aims at bridging the gap by designing and developing a mobile app (application) for creating and managing grocery lists using modern smartphones. Smartphones are pervasive and become a necessity for everyone tod
... Show MorePredicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
... Show MoreAbstract\
preparation process of performance evaluation in organizations is of extreme importance, and under development in organizations and the opening of markets and technological developments in the industry and heightened competition among industrial organizations imposed systems are built for performance give a clear picture about performance and competition, And centered research problem in answering the following questions: Is performance evaluation system is available in Wasit State Company for Textile Industries(Research sample ), This research aims to assess the performance of policies and programs in the company, according to guide performance evaluation of programs and policies prepared by the Dutch Cou
... Show MorePhotovoltaic devices (PVs) were fabricated by spray-coating an ink of copper indium diselenide CuInSeR 2 R(CIS) nanocrystals as the light-absorbing layer. Without high-temperature post-deposition annealing, PVs were made on glass substrates with power conversion efficiencies of up to 1.5% and 0.9%, for Au and Mo coated respectively, under AM 1.5 illumination. UV–Vis spectrophotometer in the wavelength range 350–1500 nm. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CuInSeR 2 R have the chalcopyrite structure as the major phase and no secondary phase with a preferred orientation along (112) direction and The atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2.
In this modern Internet era and the transition to IPv6, routing protocols must adjust to assist this transformation. RIPng, EIGRPv6 and OSPFv3 are the dominant IPv6 IGRP (Interior Gateway Routing Protocols). Selecting the best routing protocol among the available is a critical task, which depends upon the network requirement and performance parameters of different real time applications. The primary motivation of this paper is to estimate the performance of these protocols in real time applications. The evaluation is based on a number of criteria including: network convergence duration, Http Page Response Time, DB Query Response Time, IPv6 traffic dropped, video packet delay variation and video packet end to end de
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