Multi-criteria end milling parameters optimization of AISI D2 steel using genetic algorithm

This paper focuses on using multi-criteria optimization approach in the end milling machining process of AISI D2 steel. It aims to minimize the cost caused by a poor surface roughness and the electrical energy consumption during machining. A multi-objective cost function was derived based on the energy consumption during machining, and the extra machining needed to improve the surface finish. Three machining parameters have been used to derive the cost function: feed, speed, and depth of cut. Regression analysis was used to model the surface roughness and energy consumption, and the cost function was optimized using a genetic algorithm. The optimal solutions for the feed and speed are found and presented in graphs as functions of extra machining and electrical energy cost. Machine operators can use these graphs to run the milling process under optimal conditions. It is found that the optimal values of the feed and speed decrease as the cost of extra machining increases and the optimal machining condition is achieved at a low value of depth of cut. The multi-criteria optimization approach can be applied to investigate the optimal machining parameters of conventional manufacturing processes such as turning, drilling, grinding, and advanced manufacturing processes such as electrical discharge machining.     

An expert system for unit commitment and power demand prediction using fuzzy logic and neural networks

Abstract: The paper discusses the implementation of a fuzzy logic and artificial neural networks approach to providing a structural framework for the representation, manipulation and utilisation of data and information concerning prediction of power demand and generation commitments. An algorithm has been implemented and trained to predict the power demand at each load point on an hourly basis. The neural network is then implemented to supply the brute force necessary to accommodate the large amount of sensory data to provide the initial evaluation of the generation units to be committed. Results of the fuzzy model show a reasonable correspondence with the actual power demand. A standard deviation error for an hourly based prediction is limited to 4.4. Further refinement of the fuzzy model may produce further improvements.
Implementation of artificial neural networks for scheduling an hourly unit commitment based on load demands is also discussed The backpropagation technique based on the I/O mapping method has been chosen for structuring the neural network. Geographically related load points and generating units are clustered into groups. Grouping has significantly reduced the number of inputs and outputs to the neural network and, hence, reduced the system complexity. As a result, both training requirements and running real time interaction are significantly improved. The expert system would replace and utilise the requirement for skilled dispatchers in scheduling the generators. It is anticipated that this facility is more accurate, dynamic, adaptive and more efficient than a skilled dispatcher. The overall cost of power generation is expected to be less if the new facility is used. Initial results have reflected a satisfactory correlation between predicted and actual results, with a standard deviation error of 1.71% and 1.96% in the base load units of HTPS and ATPS respectively.     

A cost effective approach to design of energy efficient residential buildings

The objective of this study is to identify cost-optimal efficiency packages at several levels of building energy savings. A two-story residential building located in Jordan is selected as a case study. DesignBuilder software is used to predict the annual energy usage of a two-story residence in Irbid, Jordan. Real-time experimental data from a single isolated controlled room was used to verify the proposed model. In addition to energy analysis, the economic, environmental, and social benefits of the proposed design have been investigated. The sequential search optimization approach is used to estimate the minimum cost of the building while considering various design scenarios. In addition, the impact of various energy conservation techniques on residential buildings is assessed, and the payback period for each program is calculated. Ultimately, the optimal combination of design to achieve energy efficiency measures has been identified in several climate regions. The simulations results predict that the annual electricity consumption can be reduced up to 50% if the proper combinations of energy conservation measures are selected at the lowest cost. The payback period is 9.3 years. Finally, energy efficiency measures can lead to a total of 9470 jobs/year job opportunities.The study provide practical framework to link between energy performance criteria and economic goals of building. Linking the energy performance requirements to economic targets provides guidelines for homeowners, contractors, and policymakers for making a suitable decision regarding the retrofitting of existing residential buildings. The study focuses on developing new methodologies that support minimizing costs during a building's lifecycle while maximizing environmental benefits which can not be identified by a series of parametric analyses using individual energy-efficient measures.     

Double-disk rotating viscous micro-pump with slip flow

In this paper numerical solution was provided for the 2D, axisymmetric Navier-Stokes equations coupled with energy equation for gaseous slip flow between two micro rotating disks pump. A first-order slip boundary condition was applied to all internal solid walls. The objective is to study the effect of Knudsen number, rotational Reynolds number and gap height on pump head, flow rate, coefficient of moments and overall micro-pump efficiency. Pump head, flow rate, coefficient of moments and pump efficiency were calculated for various pump operating conditions when the mass flow rate is applied at the pump inlet port. Detailed investigations were performed for rotational Reynolds number equals to 10. Effect of gap height between the two disks was studied. Effect of rotational Reynolds number on maximum flow rate and maximum pressure rise was simulated. The present numerical results for no-slip were compared with previously published experimental and theoretical data and found to be in a very good agreement. Knudsen number Kn values were found to be major parameters that affect the performance of pump. Pump performance decreases with increasing Kn. Optimal pump performance occurs around middle point of pump operating range. Pump operating range decreases with increasing Kn numbers. Pump performance is found to experience a steep degradation for Kn approaching 0.1. Maximum flow rate increases with rotational speed almost linearly. Maximum pressure rise also increases with rotational speed. Reducing gap height results in increasing maximum pressure rise, while increasing gap height results in larger maximum flow rate.     

Assessment of aggression, sexual behavior and fertility in adult male rat following long-term ingestion of four industrial metals salts

1. The effect of long-term ingestion of the industrial metals salts, manganese sulfate, aluminum chloride, lead acetate and copper chloride was investigated on aggression, sexual behavior and fertility in male rat. Adult male rats ingested solutions of these salts along with drinking water at a concentration of 1000 p.p.m. for 12 weeks. 2. Male rat sexual behavior was suppressed after the ingestion of manganese sulfate, aluminum chloride, lead acetate and copper chloride. The ingestion of solutions of these salts markedly prolonged the intromission and ejaculation latencies. Aluminum chloride and copper chloride reduced the copulatory efficiency. 3. Male rat aggression was also abolished after the ingestion of manganese sulfate, aluminum chloride, lead acetate and copper chloride. The ingestion of solutions of these salts markedly suppressed lateralizations, boxing bouts, fight with stud male and ventral presenting postures. 4. Fertility was reduced in male rats ingested with lead acetate. The total number of resorptions was increased in female rats impregnated by males ingested with manganese sulfate and lead acetate. 5. Body, absolute or relative testes, seminal vesicles weights were dropped in adult male rats ingested with manganese sulfate, aluminum chloride, lead acetate and copper chloride. However, the absolute or relative preputial gland weights were not affected. Collectively, these results suggest that the long-term ingestion of manganese sulfate, aluminum chloride, lead acetate and copper chloride would have adverse effects on sexual behavior, territorial aggression, fertility and the reproductive system of the adult male rat.     

Approximate analytical solutions of systems of PDEs by homotopy analysis method

In this paper, the homotopy analysis method (HAM) is applied to obtain series solutions to linear and nonlinear systems of first- and second-order partial differential equations (PDEs). The HAM solutions contain an auxiliary parameter which provides a convenient way of controlling the convergence region of series solutions. It is shown in particular that the solutions obtained by the variational iteration method (VIM) are only special cases of the HAM solutions.     

Estimating east Mediterranean forest parameters using Landsat ETM

The conservation of Jordan's Mediterranean forest requires the use of remote sensing. Among the most important parameters needed are the crown-cover percentage (C) and above-ground biomass (A). This study aims to: (1) identify the best predictor(s) of C using Landsat Enhanced Thematic Mapper (ETM) bands and the derived transformed normalized difference vegetation index (TNDVI); (2) determine if C is a good predictor of A, volume (V), Shannon diversity index (S) and basal area (B); and (3) generate maps of all these parameters. A Landsat ETM image, aerial photographs and ground surveys are used to model C using multiple regression. C is then modelled to A, V, S and B using linear regression. The relationship between C and Landsat ETM bands (1 and 7) plus the TNDVI is significantly high (coefficient of determination R ² = 0.8) and is used to produce the C map. The generated C map is used to predict A (R ² = 0.56), V (R ² = 0.58), S (R ² = 0.50) and B (R ² = 0.43). Cross validation for the predicted C map (cross-validation error = 5.3%) and for the predicted forest-parameter maps (cross-validation error = 13.7%–19.9%) shows acceptable error levels. Results indicate that Jordan's east Mediterranean forest parameters can be mapped and monitored for biomass accumulation and carbon dioxide (CO₂) flux using Landsat ETM images.     

Adaptive binarization method for degraded document images based on surface contrast variation

Document binarization is an important technique in document image analysis and recognition. Generally, binarization methods are ineffective for degraded images. Several binarization methods have been proposed; however, none of them are effective for historical and degraded document images. In this paper, a new binarization method is proposed for degraded document images. The proposed method based on the variance between pixel contrast, it consists of four stages: pre-processing, geometrical feature extraction, feature selection, and post-processing. The proposed method was evaluated based on several visual and statistical experiments. The experiments were conducted using five International Document Image Binarization Contest benchmark datasets specialized for binarization testing. The results compared with five adaptive binarization methods: Niblack, Sauvola thresholding, Sauvola compound algorithm, NICK, and Bataineh. The results show that the proposed method performs better than other methods in all binarization cases.     

Assessment of renewable energy potential,at Aqaba in Jordan

The present paper is aimed to assess the potential of renewable energy resources, namely wind and solar, at Aqaba city located in the southern region of Jordan. Long-term measured data of wind speed and solar irradiation at the site are utilized in this study. Skew-Normal (SN) distribution is used to describe wind speeds and irradiance levels. The main feature of SN distribution over, the well known, Weibull distribution is the possibility of applying it to a data set having zero values. The goodness-of-fit of SN-model is demonstrated graphically, via Chi-Square (CS) distribution and through Kolmogorov–Smirnov (KS) statistical test. To show the effect of turbine hub's height, wind speed characteristics and wind power potential are estimated at different heights. The recorded solar irradiation levels are separated into three clusters and SN distribution is used to fit the data of each cluster. Solar insolation characteristics; mean and most occurrence insolations, and irradiance power potential are computed and presented in this paper. The results obtained show that Aqaba has a great potential of utilizing stand-alone, grid-connected or hybrid renewable energy systems.     

Combined convection heat transfer in a lid driven cavity filled with nanofluids

A simulation study is performed of laminar steady combined convection heat transfer in a lid-driven cavity containing various types of nanofluid (CuO–water nanofluid and Al₂O₃–water nanofluid) at various boundary conditions. The influence of two different types of temperature distributions applied to the cavity's bottom wall is investigated. There are two types of temperature distributions: constant temperature (T_h) and a sinusoidal temperature distribution applied to the bottom wall, which has a higher temperature than the top moving wall (T_c). In both circumstances, the sidewalls are kept adiabatic. The finite element method is utilized for the current issue. The influence of the Richardson number, which ranges from 0.01 to 10, and the volume fraction of nanoparticles, which ranges from 0 to 0.1, on the heat transfer rate has been explored. The influence of the sinusoidal temperature distribution's amplitude and phase angle is also examined. The isotherm and streamline patterns within the cavity are diverse with distinct nanoparticle volume fractions, and the Richardson numbers are presented and analyzed. The numerical findings showed that lowering the Richardson number raises the average Nusselt number. Also, the existence of nanoparticles in pure water increases heat transmission. Additionally, raising the sinusoidal temperature's amplitude increases the average Nusselt number. The results show that the increase of average Nusselt number at (φ = 0, Gr = 10⁴, Pr = 1, Ɣ = 3π/2) for amplitude 0.25, 0.5, 0.75, and 1 is 0.53, 0.9, 1.3, and 1.87, respectively.