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This research enhances the previous control method by utilizing an embedded controller (EC) to create a fuzzy logic controller (FLC) to reduce the power consumption of a notebook or netbook and to lengthen the battery life. Our control methods are all written in assembly language, so that there is no need to rely on any high-level application program for the FLC. Thus our design has greater efficiency and accelerates the pace of operations. We add a CPU throttle function in connection with the FLC to control the clock frequency of the CPU. This design reduces power consumption and lengthens battery life. The low-power embedded controller in a notebook is a device to assist the onboard power management system which consists of the cooling fan, the keyboard, the LCD backlight brightness and the battery recharging functions. By using the fuzzy control rule as a replacement of the default method, the fan speed becomes variable so as to maintain a certain range of temperature of the mobile computer. The LCD backlight brightness is adjusted and based on the keystroke frequency or the touchpad controlled by the FLC of our design.

AbstractWe devise a methodology to predict failures in wind turbine drive‐train components and quantify its utility. The methodology consists of two main steps. The first step is the set up of a predictive model for shutdown events, which is able to raise an alarm in advance of the fault‐induced shutdown. The model is trained on data for shutdown events retrieved from the alarm log of an offshore wind farm. Here, it is assumed that the timely prediction of low‐severity events, typically caused by abnormal component operation, allows for an intervention that can prevent premature component failures. The prediction models are based on statistical classification using only supervisory control and data acquisition (SCADA) data. In the second step, the shutdown prediction model is combined with a cost model to provide an estimate of the benefits associated with implementing the predictive maintenance system. This is achieved by computing the maximum net utility attainable as a function of the model performance and efficiency of intervention carried out by the user. Results show that the system can be expected to be cost‐effective under specific conditions. A discussion about potential improvements of the approach is provided, along with suggestions for further research in this area.

As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

Abstract AP1000® Generation III+ reactor bases its safety concept on passive systems, differently from the previous Generation II reactors. This fact has led the approximations and methodologies previously used for modeling active safety systems to be reviewed and adapted to simulate the physics of passive systems. Diverse studies about the AP1000 containment have demonstrated the difficulty to correctly model the occurring phenomenology. In this paper, an integral AP1000 3D containment GOTHIC model is presented, including the Passive Containment Cooling System (PCCS). The model includes the compartments inside and outside the metallic containment liner that influence the thermal–hydraulic behavior. The model is tested against a Large Break Loss of Coolant Accident (LBLOCA) to assess its thermal–hydraulic performance, assuming a PCS tank malfunction, what is a conservative hypothesis. The pressure and temperature evolution predicted by the 3D containment model is analyzed and compared with a single node Lumped Parameters model, allowing to evaluate some preliminary benefits of 3D modeling for containment safety analysis. The 3D containment model allows to predict the thermal evolution in each containment compartment capturing the heterogeneity of this phenomenon, with higher resolution than the lumped parameters models traditionally used in this kind of analyses. It allows to observe the thermohydraulic conditions locally at any time during the transient.

Electric power planners in developing countries have the opportunity to anticipate air conditioning-induced demand peaks, rather than merely react to them, as has happened in the United States. Demand-side management activities targeting future air conditioning installations therefore may be warranted, based on economic efficiency considerations, the U.S. experience, and worldwide trends in air conditioning usage. The feasibility of such anticipatory efforts is likely to hinge on local parameters, including domestic energy supplies, foreign exchange and capital constraints, rates of load growth, evidence of impacts on load profiles, and familiarity with demand-side planning concepts.

A mathematical model of the LiAl/LiCl, KCl/FeS cell has been used to study the behavior of the system during relaxation and charging. The effects of state of charge, cell temperature, and current density are presented, and the influence of a period of relaxation on the subsequent charging operation is investigated. In addition, factors that can have a significant impact on the charging characteristics are identified.

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

[EN]A systematic approach is developed for the conceptual optimal design of biomethane production via carbon capture. A hybrid heuristic-mathematical procedure is proposed to determine the optimal technology and operating conditions. The heuristic step consists of a literature-based screening of the available technologies. After the prescreening stage, the technologies selected are amine absorption, pressure swing adsorption (PSA), and membrane separation. The mathematical stage is composed of two steps. First, different alternatives for each technology are modeled based on first principles and rules of thumb. These models are used to select the optimal configuration for each process considered. Second, a superstructure model for biomethane production is developed integrating the pre-selected upgrading technologies to select the optimal process, as well as to determine the optimal operating conditions. Four waste sources are analyzed: cattle manure, swine manure, municipal food waste, and sludge. The results suggest that the best amine is diethanolamine (DEA), the best membrane material is the polyimide, and the suggested zeolite is 13X among the ones studied. Finally, among the three technologies, the overall results show that carbon capture using a PSA system using zeolite 13X results in lower production and investment costs, but very close to the use of membranes. The results indicate that food waste shows the lowest production cost for biomethane 0.36 €/Nm3, due to the largest organic matter content, whereas the investment costs are 67 M€, considering a biogas production rate of 0.035 kg of biomethane per kg of waste and the processing of 311 kt/yr of food waste. Credits or incentives are still needed for biomethane to be competitive with fossil natural gas. Junta de Castilla y León y USAL

In order to exploit renewable energies from tidal stream, tandem propellers of a unique counter-rotating type horizontal-axis tidal turbine was firstly designed based on the blade element momentum (BEM) theory. And then a multi-objective numerical optimization method coupled the response surface method (RSM) with the genetic algorithm (GA) was employed to obtain desirable blade profiles. The front blade pitch angle distribution was taken as optimization variable in this paper, as it plays an important role in affecting the inlet conditions of the rear blade. The numerical results show that both optimization objectives of power coefficient and thrust coefficient can be significantly improved. It was verified that the performance of the power unit with the optimized blades increases obviously by optimizing the pitch angle.

As the US biofuels market struggles in the wake of a drought crisis, conditions in Europe have improved. Major barriers to growth remain though, says Toby Cohen.