Ahmed Z. Al-Garni

Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time-series analysis

Univariate Box-Jenkins time-series analysis has been used for modeling and forecasting monthly domestic electric energy consumption in the Eastern Province of Saudi Arabia. Autoregressive integrated moving average (ARIMA) models were developed using data for 5 yr and evaluated on forecasting new data for the sixth year. The optimum model derived is a multiplicative combination of seasonal and nonseasonal autoregressive parts, each being of the first order, following first differencing at both the seasonal and nonseasonal levels. Compared to regression and abductive network machine-learning models previously developed on the same data, ARIMA models require less data, have fewer coefficients, and are more accurate. The optimum ARIMA model forecasts monthly data for the evaluation year with an average percentage error of 3.8% compared to 8.1% and 5.6% for the best multiple-series regression and abductory induction mechanism (AIM) models, respectively; the mean-square forecasting error is reduced with the ARIMA model by factors of 3.2 and 1.6, respectively.

Plasma nitriding of Ti6Al4V alloy to improve some tribological properties

The present study was conducted to investigate the tribological and mechanical properties of plasma-nitrided Ti6Al4V alloy. Specimens were nitrided in an H2N2 (1:8 ratio) plasma. The nitrogen concentration along the nitrided zone was obtained using the nuclear reaction analysis technique. The workpiece temperature was varied from 450 to 520 °C during the nitriding process. Pin-on-disc wear tests were carried out to evaluate the wear properties of the resultant samples and a ball-on-disc experiment was conducted to measure the friction coefficient. Microhardness tests, Scanning electron microscopy and X-ray diffraction were carried out to investigate the phases developed in the nitrided zone. It was found that the wear resistance improved considerably after the nitriding process. Three distinct layers were identified: (i) an inner layer where δ-TiN + e-Ti2N phases formed, (ii) an intermediate layer where α-(TiN) with or without e phase developed and (iii) an outer layer where precipitations were dominant.

Friction welding of StAl and AlCu materials

Abstract The present study investigates the mechanical and metallurgical properties of friction-welded steel-aluminum and aluminium-copper bars, a friction welder having been designed and built for this purpose. The effects of the three main parameters: speed of rotation; friction load; and duration of welding; on the metallurgical and mechanical properties of the weld such as the yield, tensile and breaking strengths, are studied experimentally and statistically. The metallurgical properties of the weld are examined using electron and optical microscopy.

Optimal control of overhead cranes

Abstract A nonlinear dynamic model of an overhead crane which represents simultaneous travel, traverse, and hoisting/lowering motions is considered. Nonlinear feedback forms of control are studied, and numerical results are obtained in such a way that specified boundary conditions and the functional constraints for the states and controls are satisfied while minimizing the sway and final time. The results show that the crane can be transferred to a desired position in the shortest possible time while minimizing the sway of the load not only during transfer but also at final time using the suggested control scheme. Several numerical results of the controls, objectives, and of the states are presented which indicate that the proposed method works well.

Modelling and forecasting monthly electric energy consumption in eastern Saudi Arabia using abductive networks

Abductive network machine learning is proposed as an alternative to the conventional multiple regression analysis method for modelling and forecasting monthly electric energy consumption. The AIM (abductory induction mechanism) is used to model the domestic consumption in the eastern province of Saudi Arabia in terms of key weather parameters and demographic and economy indicators. Models are synthesized by training on data for 5 years and forecasting new data for the sixth year. Compared to regression models previously developed for the same data, AIM models require fewer input parameters, are more accurate and are easier and faster to develop. An AIM model that uses only the mean relative humidity and air temperature gives an average forecasting error of about 5.6% over the year. Our study demonstrates the advantage of using actual values for monthly average weather data rather than means of such averages over a few years.

Finite Element Modeling of Thermopiezomagnetic Smart Structures

Linearconstitutiveequationsofa thermopiezomagneticmedium involving mechanical, electrical, magnetic, and thermal e elds are presented with the aid of a thermodynamic potential. A thermopiezomagnetic medium can be formed by bonding together a piezoelectric and magnetostrictive composite. Two energy functionals are dee ned. It is shown via Hamilton’ s principle that these functionals yield the equations of motion for the mechanical e eld, Maxwell’ s equilibrium equations for the electrical and magnetic e elds, and the generalized heat equation for the thermal e eld. Finite element equations for the thermopiezomagnetic media are obtained by using the linear constitutive equations in Hamilton’ s principle together with the e nite element approximations. The e nite element equations are utilized on an example two-layer smartstructure, which consistsof a piezoceramic (barium titanate ) layer at the bottom and a magnetoceramic (cobalt ferrite ) layer at the top. An electrostatic e eld applied to the piezoceramic layer causes strain in the structure. This strain then produces magnetic e eld in the magnetoceramic layer.

A regression model for electric-energy-consumption forecasting in eastern Saudi Arabia

Electrical energy consumption in Eastern Saudi Arabia is modeled as a function of weather data, global solar radiation and population. Five years of data have been used to develop the energy-consumption model. Variable selection in the regression model is carried out by using general, stepping-regression techniques. The problem of colinearity between the regressors is investigated by using standard statistical procedures. Model adequacy is determined from a residual analysis technique. The final model involves the parameters air temperature, relative humidity, solar radiation, and population. However, the model coefficients are functions only of solar radiation and relative humidity or constant.

The optimal dimensions of circular fins with variable profile and temperature-dependent thermal conductivity

Abstract The optimal dimensions of circular fins with variable profile, and temperature-dependent thermal conductivity are obtained. A profile of the form y = ( w 2 )[1 + ( r 0 r ) n ] is studied, while the thermal conductivity considered is of the form k = k0[1 + e (T−T∞)/T0. The results have been expressed in terms of suitable dimensionless parameters. A correlation for the optimal dimensions of a constant and variable profile fins is presented in terms of reduced heat-transfer rate. It is found that a parabolic circular fin with n = 2 gives an optimum performance. For example, an increase in heat-transfer rate (as compared to constant thickness fin) by about 20% for the optimal fin profile is observed. The effect of thermal conductivity on the optimal dimensions is negligible for the variable profile fin. It is also observed that in general, the optimal fin length is greater for the optimal fin profile.

SOLAR-POWERED AIR CONDITIONING SYSTEM

The development of renewable energy is on the rise worldwide because of the growing demand on energy, high oil prices, and concerns of environmental impacts. In recent years, progress on solar-powered air conditioning has increased as nowadays, air conditioning system is almost a must in every building if we want to have a good indoor comfort inside the building. Therefore, this paper focuses in the design and construction of a direct current (DC) air conditioning system integrated with photovoltaic (PV) system which consists of PV panels, solar charger, inverter and batteries. The air conditioning system can be operated on solar and can be used in non-electrified areas. As we all known, solar energy is cost effective, renewable and environmentally friendly.

Effect of fouling on operational cost in pipe flow due to entropy generation

The effect of fouling on thermodynamic performance can be evaluated by studying the increase of entropy generation rate due to fouling as compared to that for clean surface tubes. In this study, an attempt has been made to correlate the effect of fouling with entropy generation and related operational cost. In the model developed, fouling thickness and tube surface temperature are considered to be the main parameters. Numerical results of entropy generation and related operational cost due to both heat transfer and viscous friction under fouling conditions are presented and discussed.