25 resultados para Car Carrier


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In the framework of the so-called third generation solar cells, three main concepts have been proposed in order to exceed the limiting efficiency of single-gap solar cells: the hot-carrier solar cell, the impact-ionization or multiple-exciton-generation solar cell, and the intermediate-band solar cell. At first sight, the three concepts are different, but in this paper, we illustrate how all these concepts, including the single-gap solar cell, share a common trunk that we call "core photovoltaic material." We demonstrate that each one of these next-generation concepts differentiates in fact from this trunk depending on the hypotheses that are made about the physical principles governing the electron electrochemical potentials. In the process, we also clarify the differences between electron, phonon, and photon chemical potentials (the three fundamental particles involved in the operation of the solar cell). The in-depth discussion of the physics involved about the operation of these cells also provides new insights about the operation of these cells.

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In this paper an on line self-tuned PID controller is proposed for the control of a car whose goal is to follow another one, at distances and speeds typical in urban traffic. The bestknown tuning mechanism is perhaps the MIT rule, due to its ease of implementation. However, as it is well known, this method does not guarantee the stability of the system, providing good results only for constant or slowly varying reference signals and in the absence of noise, which are unrealistic conditions. When the reference input varies with an appreciable rate or in presence of noise, eventually it could result in system instability. In this paper an alternative method is proposed that significantly improves the robustness of the system for varying inputs or in the presence of noise, as demonstrated by simulation.

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Análisis de la atenuación del oleaje por un carguero funcionando como dique flotante y aplicación a dos casos de protección portuaria y costera. The effectiveness of a bulk carrier working as a detached floating breakwater to protect a stretch of coast and form salients or tombolos is assessed in this paper. Experiments were conducted in the Madrid CEDEX facilities in a 30 m long, 3 m wide, 1/150 scale flume. The bulk carrier ship is 205 m long, 29 m wide and 18 m in height with a draught of 13 m, and has been subjected to irregular waves with significant heights from 2 m to 4 m and peak periods from 6 s to 12 s at a depth of 15 m, all prototype dimensions. Three probes were placed between the wave paddle and the ship to record incident and reflected waves and four probes were placed between the ship and the coastline to measure the transmitted waves. Transmission, reflection and dissipation coefficients (Ct, Cr, Cd) were calculated to determine wave attenuation. Results show good shelter in the lee of the ship with values of Ct under 0.5 for peak periods from 6 s to 11 s. In addition, forces on the mooring chains were measured showing maximum values of about 2000 tons at a 10 speak period. Finally, two analytical models were used to determine the shoreline’s response to the ship’s protection and to assess the possible forming of salients or tombolos. According to the results, salients - but not tombolos - are formed in all tests.

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After a criticism on today’s model for electrical noise in resistors, we pass to use a Quantum-compliant model based on the discreteness of electrical charge in a complex Admittance. From this new model we show that carrier drift viewed as charged particle motion in response to an electric field is unlike to occur in bulk regions of Solid-State devices where carriers react as dipoles against this field. The absence of the shot noise that charges drifting in resistors should produce and the evolution of the Phase Noise with the active power existing in the resonators of L-C oscillators, are two effects added in proof for this conduction model without carrier drift where the resistance of any two-terminal device becomes discrete and has a minimum value per carrier that is the Quantum resistance RK/(2pi)

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This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

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The road transportation sector is responsible for around 25% of total man-made CO2 emissions worldwide. Considerable efforts are therefore underway to reduce these emissions using several approaches, including improved vehicle technologies, traffic management and changing driving behaviour. Detailed traffic and emissions models are used extensively to assess the potential effects of these measures. However, if the input and calibration data are not sufficiently detailed there is an inherent risk that the results may be inaccurate. This article presents the use of Floating Car Data to derive useful speed and acceleration values in the process of traffic model calibration as a means of ensuring more accurate results when simulating the effects of particular measures. The data acquired includes instantaneous GPS coordinates to track and select the itineraries, and speed and engine performance extracted directly from the on-board diagnostics system. Once the data is processed, the variations in several calibration parameters can be analyzed by comparing the base case model with the measure application scenarios. Depending on the measure, the results show changes of up to 6.4% in maximum speed values, and reductions of nearly 15% in acceleration and braking levels, especially when eco-driving is applied.

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The inbound logistic for feeding the workstation inside the factory represents a critical issue in the car manufacturing industry. Nowadays, this issue is even more critical than in the past since more types of car are being produced in the assembly lines. Consequently, as workstations have to install many types of components, they also need to have an inventory of different types of the component in a compact space. The replenishment is a critical issue since a lack of inventory could cause line stoppage or reworking. On the other hand, an excess of inventory could increase the holding cost or even block the replenishment paths. The decision of the replenishment routes cannot be made without taking into consideration the inventory needed by each station during the production time which will depend on the production sequence. This problem deals with medium-sized instances and it is solved using online solvers. The contribution of this paper is a MILP for the replenishment and inventory of the components in a car assembly line.

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We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

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El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.