850 resultados para Optimal speed


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The purpose of this study was to test the hypothesis that the potentiation of dynamic function was dependent upon both length change speed and direction. Mouse EDL was cycled in vitro (250 C) about optimal length (Lo) with constant peak strain (± 2.5% Lo) at 1.5,3.3 and 6.9 Hz before and after a conditioning stimulus. A single pulse was applied during shortening or lengthening and peak dynamic (concentric or eccentric) forces were assessed at Lo. Stimulation increased peak concentric force at all frequencies (range: 19±1 to 30 ± 2%) but this increase was proportional to shortening speed, as were the related changes to concentric work/power (range: -15 ± 1 to 39 ± 1 %). In contrast, stimulation did not increase eccentric force, work or power at any frequency. Thus, results reveal a unique hysteresis like effect for the potentiation of dynamic output wherein concentric and eccentric forces increase and decrease, respectively, with work cycle frequency.

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One of the primary goals of the Center for Integrated Space Weather Modeling (CISM) effort is to assess and improve prediction of the solar wind conditions in near‐Earth space, arising from both quasi‐steady and transient structures. We compare 8 years of L1 in situ observations to predictions of the solar wind speed made by the Wang‐Sheeley‐Arge (WSA) empirical model. The mean‐square error (MSE) between the observed and model predictions is used to reach a number of useful conclusions: there is no systematic lag in the WSA predictions, the MSE is found to be highest at solar minimum and lowest during the rise to solar maximum, and the optimal lead time for 1 AU solar wind speed predictions is found to be 3 days. However, MSE is shown to frequently be an inadequate “figure of merit” for assessing solar wind speed predictions. A complementary, event‐based analysis technique is developed in which high‐speed enhancements (HSEs) are systematically selected and associated from observed and model time series. WSA model is validated using comparisons of the number of hit, missed, and false HSEs, along with the timing and speed magnitude errors between the forecasted and observed events. Morphological differences between the different HSE populations are investigated to aid interpretation of the results and improvements to the model. Finally, by defining discrete events in the time series, model predictions from above and below the ecliptic plane can be used to estimate an uncertainty in the predicted HSE arrival times.

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This paper considers the motion planning problem for oriented vehicles travelling at unit speed in a 3-D space. A Lie group formulation arises naturally and the vehicles are modeled as kinematic control systems with drift defined on the orthonormal frame bundles of particular Riemannian manifolds, specifically, the 3-D space forms Euclidean space E-3, the sphere S-3, and the hyperboloid H'. The corresponding frame bundles are equal to the Euclidean group of motions SE(3), the rotation group SO(4), and the Lorentz group SO (1, 3). The maximum principle of optimal control shifts the emphasis for these systems to the associated Hamiltonian formalism. For an integrable case, the extremal curves are explicitly expressed in terms of elliptic functions. In this paper, a study at the singularities of the extremal curves are given, which correspond to critical points of these elliptic functions. The extremal curves are characterized as the intersections of invariant surfaces and are illustrated graphically at the singular points. It. is then shown that the projections, of the extremals onto the base space, called elastica, at these singular points, are curves of constant curvature and torsion, which in turn implies that the oriented vehicles trace helices.

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Planning of autonomous vehicles in the absence of speed lanes is a less-researched problem. However, it is an important step toward extending the possibility of autonomous vehicles to countries where speed lanes are not followed. The advantages of having nonlane-oriented traffic include larger traffic bandwidth and more overtaking, which are features that are highlighted when vehicles vary in terms of speed and size. In the most general case, the road would be filled with a complex grid of static obstacles and vehicles of varying speeds. The optimal travel plan consists of a set of maneuvers that enables a vehicle to avoid obstacles and to overtake vehicles in an optimal manner and, in turn, enable other vehicles to overtake. The desired characteristics of this planning scenario include near completeness and near optimality in real time with an unstructured environment, with vehicles essentially displaying a high degree of cooperation and enabling every possible(safe) overtaking procedure to be completed as soon as possible. Challenges addressed in this paper include a (fast) method for initial path generation using an elastic strip, (re-)defining the notion of completeness specific to the problem, and inducing the notion of cooperation in the elastic strip. Using this approach, vehicular behaviors of overtaking, cooperation, vehicle following,obstacle avoidance, etc., are demonstrated.

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The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.

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Inverse methods are widely used in various fields of atmospheric science. However, such methods are not commonly used within the boundary-layer community, where robust observations of surface fluxes are a particular concern. We present a new technique for deriving surface sensible heat fluxes from boundary-layer turbulence observations using an inverse method. Doppler lidar observations of vertical velocity variance are combined with two well-known mixed-layer scaling forward models for a convective boundary layer (CBL). The inverse method is validated using large-eddy simulations of a CBL with increasing wind speed. The majority of the estimated heat fluxes agree within error with the proscribed heat flux, across all wind speeds tested. The method is then applied to Doppler lidar data from the Chilbolton Observatory, UK. Heat fluxes are compared with those from a mast-mounted sonic anemometer. Errors in estimated heat fluxes are on average 18 %, an improvement on previous techniques. However, a significant negative bias is observed (on average −63%) that is more pronounced in the morning. Results are improved for the fully-developed CBL later in the day, which suggests that the bias is largely related to the choice of forward model, which is kept deliberately simple for this study. Overall, the inverse method provided reasonable flux estimates for the simple case of a CBL. Results shown here demonstrate that this method has promise in utilizing ground-based remote sensing to derive surface fluxes. Extension of the method is relatively straight-forward, and could include more complex forward models, or other measurements.

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The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal oxygen uptake (V. O2max) as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on the body-mass exponent for V. O2max among elite male skiers. Twenty-four elite male skiers (age: 21.4±3.3 years [mean ± standard deviation]) completed an incremental treadmill roller-skiing test to determine their V. O2max. Performance data were collected from a 15 km classicaltechnique cross-country skiing competition performed on a 5 km course. Power-function modeling (ie, an allometric scaling approach) was used to establish the optimal body-mass exponent for V . O2max to predict the skiing performance. The optimal power-function models were found to be race speed = 8.83⋅(V . O2max m-0.53) 0.66 and lap speed = 5.89⋅(V . O2max m-(0.49+0.018lap)) 0.43e0.010age, which explained 69% and 81% of the variance in skiing speed, respectively. All the variables contributed to the models. Based on the validation results, it may be recommended that V. O2max divided by the square root of body mass (mL⋅min−1 ⋅kg−0.5) should be used when elite male skiers’ performance capability in 15 km classical-technique races is evaluated. Moreover, the body-mass exponent for V . O2max was demonstrated to be influenced by the distance covered, indicating that heavier skiers have a more pronounced positive pacing profile (ie, race speed gradually decreasing throughout the race) compared to that of lighter skiers.

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Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper presents for the first time how to easily incorporate facts devices in an optimal active power flow model such that an efficient interior-point method may be applied. The optimal active power flow model is based on a network flow approach instead of the traditional nodal formulation that allows the use of an efficiently predictor-corrector interior point method speed up by sparsity exploitation. The mathematical equivalence between the network flow and the nodal models is addressed, as well as the computational advantages of the former considering the solution by interior point methods. The adequacy of the network flow model for representing facts devices is presented and illustrated on a small 5-bus system. The model was implemented using Matlab and its performance was evaluated with the 3,397-bus and 4,075-branch Brazilian power system which show the robustness and efficiency of the formulation proposed. The numerical results also indicate an efficient tool for optimal active power flow that is suitable for incorporating facts devices.

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A new approach called the Modified Barrier Lagrangian Function (MBLF) to solve the Optimal Reactive Power Flow problem is presented. In this approach, the inequality constraints are treated by the Modified Barrier Function (MBF) method, which has a finite convergence property: i.e. the optimal solution in the MBF method can actually be in the bound of the feasible set. Hence, the inequality constraints can be precisely equal to zero. Another property of the MBF method is that the barrier parameter does not need to be driven to zero to attain the solution. Therefore, the conditioning of the involved Hessian matrix is greatly enhanced. In order to show this, a comparative analysis of the numeric conditioning of the Hessian matrix of the MBLF approach, by the decomposition in singular values, is carried out. The feasibility of the proposed approach is also demonstrated with comparative tests to Interior Point Method (IPM) using various IEEE test systems and two networks derived from Brazilian generation/transmission system. The results show that the MBLF method is computationally more attractive than the IPM in terms of speed, number of iterations and numerical conditioning. (C) 2011 Elsevier B.V. All rights reserved.

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Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

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An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.

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This paper reports the studies carried out to develop and calibrate the optimal models for the objectives of this work. In particular, quarter bogie model for vehicle, rail-wheel contact with Lagrangian multiplier method, 2D spatial discretization were selected as the optimal decisions. Furthermore, the 3D model of coupled vehicle-track also has been developed to contrast the results obtained in the 2D model. The calculations were carried out in the time domain and envelopes of relevant results were obtained for several track profiles and speed ranges. Distributed elevation irregularities were generated based on power spectral density (PSD) distributions. The results obtained include the wheel-rail contact forces, forces transmitted to the bogie by primary suspension. The latter loads are relevant for the purpose of evaluating the performance of the infrastructure

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La termografía infrarroja (TI) es una técnica no invasiva y de bajo coste que permite, con el simple acto de tomar una fotografía, el registro sin contacto de la energía que irradia el cuerpo humano (Akimov & Son’kin, 2011, Merla et al., 2005, Ng et al., 2009, Costello et al., 2012, Hildebrandt et al., 2010). Esta técnica comenzó a utilizarse en el ámbito médico en los años 60, pero debido a los malos resultados como herramienta diagnóstica y la falta de protocolos estandarizados (Head & Elliot, 2002), ésta se dejó de utilizar en detrimento de otras técnicas más precisas a nivel diagnóstico. No obstante, las mejoras tecnológicas de la TI en los últimos años han hecho posible un resurgimiento de la misma (Jiang et al., 2005, Vainer et al., 2005, Cheng et al., 2009, Spalding et al., 2011, Skala et al., 2012), abriendo el camino a nuevas aplicaciones no sólo centradas en el uso diagnóstico. Entre las nuevas aplicaciones, destacamos las que se desarrollan en el ámbito de la actividad física y el deporte, donde recientemente se ha demostrado que los nuevos avances con imágenes de alta resolución pueden proporcionar información muy interesante sobre el complejo sistema de termorregulación humana (Hildebrandt et al., 2010). Entre las nuevas aplicaciones destacan: la cuantificación de la asimilación de la carga de trabajo físico (Čoh & Širok, 2007), la valoración de la condición física (Chudecka et al., 2010, 2012, Akimov et al., 2009, 2011, Merla et al., 2010), la prevención y seguimiento de lesiones (Hildebrandt et al., 2010, 2012, Badža et al., 2012, Gómez Carmona, 2012) e incluso la detección de agujetas (Al-Nakhli et al., 2012). Bajo estas circunstancias, se acusa cada vez más la necesidad de ampliar el conocimiento sobre los factores que influyen en la aplicación de la TI en los seres humanos, así como la descripción de la respuesta de la temperatura de la piel (TP) en condiciones normales, y bajo la influencia de los diferentes tipos de ejercicio. Por consiguiente, este estudio presenta en una primera parte una revisión bibliográfica sobre los factores que afectan al uso de la TI en los seres humanos y una propuesta de clasificación de los mismos. Hemos analizado la fiabilidad del software Termotracker, así como su reproducibilidad de la temperatura de la piel en sujetos jóvenes, sanos y con normopeso. Finalmente, se analizó la respuesta térmica de la piel antes de un entrenamiento de resistencia, velocidad y fuerza, inmediatamente después y durante un período de recuperación de 8 horas. En cuanto a la revisión bibliográfica, hemos propuesto una clasificación para organizar los factores en tres grupos principales: los factores ambientales, individuales y técnicos. El análisis y descripción de estas influencias deben representar la base de nuevas investigaciones con el fin de utilizar la TI en las mejores condiciones. En cuanto a la reproducibilidad, los resultados mostraron valores excelentes para imágenes consecutivas, aunque la reproducibilidad de la TP disminuyó ligeramente con imágenes separadas por 24 horas, sobre todo en las zonas con valores más fríos (es decir, zonas distales y articulaciones). Las asimetrías térmicas (que normalmente se utilizan para seguir la evolución de zonas sobrecargadas o lesionadas) también mostraron excelentes resultados pero, en este caso, con mejores valores para las articulaciones y el zonas centrales (es decir, rodillas, tobillos, dorsales y pectorales) que las Zonas de Interés (ZDI) con valores medios más calientes (como los muslos e isquiotibiales). Los resultados de fiabilidad del software Termotracker fueron excelentes en todas las condiciones y parámetros. En el caso del estudio sobre los efectos de los entrenamientos de la velocidad resistencia y fuerza en la TP, los resultados muestran respuestas específicas según el tipo de entrenamiento, zona de interés, el momento de la evaluación y la función de las zonas analizadas. Los resultados mostraron que la mayoría de las ZDI musculares se mantuvieron significativamente más calientes 8 horas después del entrenamiento, lo que indica que el efecto del ejercicio sobre la TP perdura por lo menos 8 horas en la mayoría de zonas analizadas. La TI podría ser útil para cuantificar la asimilación y recuperación física después de una carga física de trabajo. Estos resultados podrían ser muy útiles para entender mejor el complejo sistema de termorregulación humano, y por lo tanto, para utilizar la TI de una manera más objetiva, precisa y profesional con visos a mejorar las nuevas aplicaciones termográficas en el sector de la actividad física y el deporte Infrared Thermography (IRT) is a safe, non-invasive and low-cost technique that allows the rapid and non-contact recording of the irradiated energy released from the body (Akimov & Son’kin, 2011; Merla et al., 2005; Ng et al., 2009; Costello et al., 2012; Hildebrandt et al., 2010). It has been used since the early 1960’s, but due to poor results as diagnostic tool and a lack of methodological standards and quality assurance (Head et al., 2002), it was rejected from the medical field. Nevertheless, the technological improvements of IRT in the last years have made possible a resurgence of this technique (Jiang et al., 2005; Vainer et al., 2005; Cheng et al., 2009; Spalding et al., 2011; Skala et al., 2012), paving the way to new applications not only focused on the diagnose usages. Among the new applications, we highlighted those in physical activity and sport fields, where it has been recently proven that a high resolution thermal images can provide us with interesting information about the complex thermoregulation system of the body (Hildebrandt et al., 2010), information than can be used as: training workload quantification (Čoh & Širok, 2007), fitness and performance conditions (Chudecka et al., 2010, 2012; Akimov et al., 2009, 2011; Merla et al., 2010; Arfaoui et al., 2012), prevention and monitoring of injuries (Hildebrandt et al., 2010, 2012; Badža et al., 2012, Gómez Carmona, 2012) and even detection of Delayed Onset Muscle Soreness – DOMS- (Al-Nakhli et al., 2012). Under this context, there is a relevant necessity to broaden the knowledge about factors influencing the application of IRT on humans, and to better explore and describe the thermal response of Skin Temperature (Tsk) in normal conditions, and under the influence of different types of exercise. Consequently, this study presents a literature review about factors affecting the application of IRT on human beings and a classification proposal about them. We analysed the reliability of the software Termotracker®, and also its reproducibility of Tsk on young, healthy and normal weight subjects. Finally, we examined the Tsk thermal response before an endurance, speed and strength training, immediately after and during an 8-hour recovery period. Concerning the literature review, we proposed a classification to organise the factors into three main groups: environmental, individual and technical factors. Thus, better exploring and describing these influence factors should represent the basis of further investigations in order to use IRT in the best and optimal conditions to improve its accuracy and results. Regarding the reproducibility results, the outcomes showed excellent values for consecutive images, but the reproducibility of Tsk slightly decreased with time, above all in the colder Regions of Interest (ROI) (i.e. distal and joint areas). The side-to-side differences (ΔT) (normally used to follow the evolution of some injured or overloaded ROI) also showed highly accurate results, but in this case with better values for joints and central ROI (i.e. Knee, Ankles, Dorsal and Pectoral) than the hottest muscle ROI (as Thigh or Hamstrings). The reliability results of the IRT software Termotracker® were excellent in all conditions and parameters. In the part of the study about the effects on Tsk of aerobic, speed and strength training, the results of Tsk demonstrated specific responses depending on the type of training, ROI, moment of the assessment and the function of the considered ROI. The results showed that most of muscular ROI maintained warmer significant Tsk 8 hours after the training, indicating that the effect of exercise on Tsk last at least 8 hours in most of ROI, as well as IRT could help to quantify the recovery status of the athlete as workload assimilation indicator. Those results could be very useful to better understand the complex skin thermoregulation behaviour, and therefore, to use IRT in a more objective, accurate and professional way to improve the new IRT applications for the physical activity and sport sector.