Optimal design of stepped spillways using the HBMO algorithm

Studies on stepped spillways as flood energy dissipators have been conducted to understand the hydraulics on the stepped face of roller-compacted concrete dams as well as overlays of embankment dams. Significant energy losses occur along the stepped chute so that the energy dissipation structure becomes smaller and more economic. In addition, considering the design discharge, downstream face slope, height of spillway, different combinations of spillway width and number of spillway steps may lead to different head losses. In each feasible combination, the remaining head after the steps should be dissipated by downstream energy dissipators. Design and construction of spillways and energy disspators are very cost-consuming and build up a major part of the dam's construction expenses. Thus, the cost of a financially viable stepped spillway project that consists of the steps’ cost and downstream dissipator's cost should be minimised. In this paper, the honey-bee mating optimisation (HBMO) algorithm is used to determine the best combination of design variables so as to minimise the total cost of both spillway chute and stilling basin. Results are compared with those previously obtained by genetic algorithm (GA) and show the promising potential of the HBMO algorithm in this field of application.     

Electric load forecasting by using dynamic neural network

Electrical energy is fundamental for the wellbeing and for the economic development of any country. However, all countries must ensure access to essential resources and ensure the continuity of its supply. Due to the non-storable nature of electrical energy, the amount of consumed active power should always be equal the produced active power just to avoid power system frequency deviation problem. In order to keep the relationship production–consumption relation in compliance with different standards and to secure profitable operations of power system, electric load consumption must be predicted and controlled instantaneously. Several statistical and classical techniques are proposed in the literature but unfortunately all these methods are not accurate in a satisfactory manner. In this paper, a dynamic neural network is used for the prediction of daily power consumption. The suitability and the performance of the proposed approach is illustrated and verified with simulations on load data collected from French Transmission System Operator (RTE) website. The obtained results show that the accuracy and the efficiency are improved comparatively to conventional methods widely used in this field of research.     

Modeling hydrogen storage on Mg–H2 and LiNH2 under variable temperature using multiple regression analysis with respect to ANOVA

The world is facing a major problem due to the depletion of conventional energy sources. Hydrogen is considered one of the most promising sources of energy. Recently, one of the problems facing utilization of hydrogen energy is the storage. Therefore, finding materials to store hydrogen based on the adsorption/desorption methodology (i.e. metal hydrides) is considered extremely vital issue. During this work two candidate materials (i.e. Mg–H₂ and LiNH₂) were investigated at different temperatures (25–45 °C). The results revealed that both candidate materials possessed long cycle life and cyclibility which opens the wide door to use these materials in vehicular applications. On the other hand the generated mathematical models based on the multiple regression analysis with respect to ANOVA showed that increasing temperature will increase the weight of hydrogen adsorption for both candidate materials.     

Considerations for the development of radiation resistant devices and VLSI circuits

The impact of radiation on Very Large Scale Integration (VLSI) silicon technology is discussed with a focus on Complimentary Metal-Oxide Semiconductor (CMOS). Effects of total dose, transient radiation, single event phenomena, and neutron fluence on devices and circuits are presented. General approaches to mitigating radiation effects are put forth. With proper considerations, VLSI CMOS can be enhanced to achieve several orders-of-magnitude increase in radiation tolerance.     

Intraoperative arthrography and the Ilizarov technique. Role in the correction of paediatric deformity and leg lengthening

We performed intraoperative arthrography of the knee in 12 children with congenital short femur, Blount's disease or Ollier's disease in whom the Ilizarov technique was used for correction of deformity, leg lengthening or both. In each case, arthrography revealed a joint surface considerably different from that assumed from plain radiographs, and resulted in a change in the placement of our reference wires before application of the frame. This gave significant improvement in the mechanical axis obtained at the time of removal of the frame. The technique is safe, cheap and easy to perform. It is a useful adjunct to the application of the Ilizarov frame when used for complex lengthening and correction of deformity in the leg.     

Adaptive control for non‐negative and compartmental dynamical systems with applications to general anesthesia

Non‐negative and compartmental dynamical system models are composed of homogeneous interconnected subsystems or compartments which exchange variable non‐negative quantities of material with conservation laws describing transfer, accumulation, and elimination between the compartments and the environment. These models are widespread in biological and physiological sciences and play a key role in understanding these processes. In this paper, we develop a direct adaptive control framework for linear uncertain non‐negative and compartmental systems. The proposed framework is Lyapunov‐based and guarantees partial asymptotic set‐point regulation; that is, asymptotic set‐point stability with respect to part of the closed‐loop system states associated with the plant. In addition, the adaptive controller guarantees that the physical system states remain in the non‐negative orthant of the state space. Finally, a numerical example involving the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for non‐cardiac surgery is provided to demonstrate the efficacy of the proposed approach. Copyright © 2003 John Wiley & Sons, Ltd.     

Effect of processing on the quality of edible argan oil

Sensory quality of edible oil is essential to get the consumer acceptance. Modifications during processing can alter edible oil sensory quality. The storage stability and sensory quality of argan oil prepared from (1) mechanically pressed unroasted kernels, (2) mechanically pressed roasted kernels, (3) hand-pressed roasted kernels, and (4) hand-pressed roasted kernels coming from goat-digested fruits was studied at room temperature and under accelerated conditions (60 °C). The roasting process had a positive effect on storage stability of the resulting oils, while argan oil prepared from mechanically pressed roasted kernels provides the optimum storage stability. Oil from hand-pressed roasted kernels originating from goat-digested fruits was not suitable for human consumption because of the unpleasant taste and odoûr. Only oil from mechanically pressed roasted kernels did not produce negative sensory attributes like fusty or Roquefort cheese.     

The measurement of minimotors and micromotors torque-characteristic using miniaturized cable brake

 A miniaturized torque sensor based on cable brake principle for the measurement of torque-characteristic of minimotors and micromotors has been developed. The first generation torque sensor enables the measurement of torque of minimotors in the range of μNm. Design principles and the production process are described. Experimental results show fair conformity with technical data for minimotors. Received: 30 October 1996 / Accepted: 14 November 1996     

Book reviews

Book reviewed in this article:
The Information Economy and American Cities. Matthew P. Drennan.
Transportation Networks and the Optimal Location of Human Activities: A Numerical Geography Approach. (Transport Economics, Management and Policy Series.)
Travel Behaviour: Spatial Patterns, Congestion and Modelling. E. Stern, I. Salomon, P.H.I. Bovy (eds).
Input-Output Analysis: Frontiers and Extensions. Michael L. Lahr and Erik Dietzenbacher (eds).