986 resultados para Truck Trailer Combinations.


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This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.

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Constructing highways in dense urban areas is always a challenge. In Sao Paulo Metropolitan Region, heavy truck traffic contributes to clog streets and expressways alike. As part of the traffic neither originates nor head to the region, a peripheral highway has been proposed to reduce traffic problems. This project called Rodoanel, is an expressway approximately 175 km long. The fact that the projected south and north sections would cross catchments that supply most of the metropolis water demand was strongly disputed and made the environmental permitting process particularly difficult. The agency in charge commissioned a strategic environmental assessment (SEA) of a revamped project, and called it the Rodoanel Programme. However, the SEA report failed to satisfactorily take account of significant strategic issues. Among these, the highway potential effect of inducing urban sprawl over water protection zones is the most critical issue, as it emerged later as a hurdle to project licensing. Conclusion is that, particularly where no agreed-upon framework for SEA exists, when vertical tiering with downstream project EIA is sought, then a careful scoping of strategic issues is more than necessary. If an agreement on `what is strategic` is not reached and not recognized by influential stakeholders, then the unsettled conflicts will be transferred to project EIA. In such a context, SEA will have added another loop to the usually long road to project approval. (c) 2008 Elsevier Inc. All rights reserved.

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Mine simulation depends on data that is both coherent and representative of the mining operation. This paper describes a methodology for modeling operational data which has been developed for mine simulation. The methodology has been applied to a case study of an open-pit mine, where the cycle times of the truck fleet have been modeled for mine simulation purposes. The results obtained have shown that once the operational data has been treated using the proposed methodology, the system variables have proven to be adherent to theoretical distributions. The research indicated the need jar tracking the origin of data inconsistencies through the development of a process to manage inconsistent data from the mining operation.

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In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

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As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

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This work introduces the problem of the best choice among M combinations of the shortest paths for dynamic provisioning of lightpaths in all-optical networks. To solve this problem in an optimized way (shortest path and load balance), a new fixed routing algorithm, named Best among the Shortest Routes (BSR), is proposed. The BSR`s performance is compared in terms of blocking probability and network utilization with Dijkstra`s shortest path algorithm and others algorithms proposed in the literature. The evaluated scenarios include several representative topologies for all-optical networking and different wavelength conversion architectures. For all studied scenarios, BSR achieved superior performance. (C) 2010 Elsevier B.V. All rights reserved.

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In this work, a system using active RFID tags to supervise truck bulk cargo is described. The tags are attached to the bodies of the trucks and readers are distributed in the cargo buildings and attached to weighs and the discharge platforms. PDAs with camera and support to a WiFi network are provided to the inspectors and access points are installed throughout the discharge area to allow effective confirmations of unload actions and the acquisition of pictures for future audit. Broadband radio equipments are used to establish efficient communication links between the weighs and cargo buildings which are usually located very far from each other in the field. A web application software was especially developed to enable robust communication between the equipments for efficient device management, data processing and reports generation to the operating personal. The system was deployed in a cargo station of a Brazilian seashore port. The obtained results prove the effectiveness of the proposed system.

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Transmission and switching in digital telecommunication networks require distribution of precise time signals among the nodes. Commercial systems usually adopt a master-slave (MS) clock distribution strategy building slave nodes with phase-locked loop (PLL) circuits. PLLs are responsible for synchronizing their local oscillations with signals from master nodes, providing reliable clocks in all nodes. The dynamics of a PLL is described by an ordinary nonlinear differential equation, with order one plus the order of its internal linear low-pass filter. Second-order loops are commonly used because their synchronous state is asymptotically stable and the lock-in range and design parameters are expressed by a linear equivalent system [Gardner FM. Phaselock techniques. New York: John Wiley & Sons: 1979]. In spite of being simple and robust, second-order PLLs frequently present double-frequency terms in PD output and it is very difficult to adapt a first-order filter in order to cut off these components [Piqueira JRC, Monteiro LHA. Considering second-harmonic terms in the operation of the phase detector for second order phase-locked loop. IEEE Trans Circuits Syst [2003;50(6):805-9; Piqueira JRC, Monteiro LHA. All-pole phase-locked loops: calculating lock-in range by using Evan`s root-locus. Int J Control 2006;79(7):822-9]. Consequently, higher-order filters are used, resulting in nonlinear loops with order greater than 2. Such systems, due to high order and nonlinear terms, depending on parameters combinations, can present some undesirable behaviors, resulting from bifurcations, as error oscillation and chaos, decreasing synchronization ranges. In this work, we consider a second-order Sallen-Key loop filter [van Valkenburg ME. Analog filter design. New York: Holt, Rinehart & Winston; 1982] implying a third order PLL The resulting lock-in range of the third-order PLL is determined by two bifurcation conditions: a saddle-node and a Hopf. (C) 2008 Elsevier B.V. All rights reserved.

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The objective of this study was to evaluate the sensory stability of ultra-high temperature (UHT) milk subjected to different heat treatments and stored at room temperature in white high density polyethylene bottles (HDPE) pigmented with titanium dioxide. Two lots of 300 units each were processed, respectively, at 135 and 141 degrees C/10 s using indirect heating and subsequently aseptically filled in an ISO class 7 clean room. These experimental lots were evaluated for appearance, aroma, flavor, and overall appreciation and compared to samples of commercial UHT milk purchased from local commercial stores. The time-temperature combinations investigated did not affect either the acceptability or the shelf life of the milk. Despite the limited light barrier properties of HDPE bottles, the product contained in the package tested exhibited good stability, with a shelf life ranging from 4 to 11 wk. Within this time period, the acceptability of the experimental lots was similar to that of the commercial products. The results achieved in this study contribute to turn the low-cost UHT system investigated into a technically viable option for small-size dairy processing plants.

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At present, the cement industry generates approximately 5% of the world`s anthropogenic CO(2) emissions. This share is expected to increase since demand for cement based products is forecast to multiply by a factor of 2.5 within the next 40 years and the traditional strategies to mitigate emissions, focused on the production of cement, will not be capable of compensating such growth. Therefore, additional mitigation strategies are needed, including an increase in the efficiency of cement use. This paper proposes indicators for measuring cement use efficiency, presents a benchmark based on literature data and discusses potential gains in efficiency. The binder intensity (bi) index measures the amount of binder (kg m(-3)) necessary to deliver 1 MPa of mechanical strength, and consequently express the efficiency of using binder materials. The CO(2) intensity index (ci) allows estimating the global warming potential of concrete formulations. Research benchmarks show that bi similar to 5 kg m(-3) MPa(-1) are feasible and have already been achieved for concretes >50 MPa. However, concretes with lower compressive strengths have binder intensities varying between 10 and 20 kg m(-3) MPa(-1). These values can be a result of the minimum cement content established in many standards and reveal a significant potential for performance gains. In addition, combinations of low bi and ci are shown to be feasible. (c) 2010 Elsevier Ltd. All rights reserved.

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Hormones are likely to be important factors modulating the light-dependent anthocyanin accumulation. Here we analyzed anthocyanin contents in hypocotyls of near isogenic Micro-Tom (MT) tomato lines carrying hormone and phytochrome mutations, as single and double-mutant combinations. In order to recapitulate mutant phenotype, exogenous hormone applications were also performed Anthocyanin accumulation was promoted by exogenous abscisic acid (ABA) and inhibited by gibberellin (GA), in accordance to the reduced anthocyanin contents measured in ABA-deficient (notabills) and GA-constitutive response (procera) mutants. Exogenous cytokinin also enhanced anthocyanin levels in MT hypocotyls. Although auxin-insensitive chageotropica mutant exhibited higher anthocyanin contents, pharmacological approaches employing exogenous auxin and a transport inhibitor did not support a direct role of the hormone in anthocyanin accumulation Analysis of mutants exhibiting increased ethylene production (epwastic) or reduced sensitivity (Never ripe), together with pharmacological data obtained from plants treated with the hormone, indicated a limited role for ethylene in anthocyanin contents. Phytochrome-deficiency (aurea) and hormone double-mutant combinations exhibited phenotypes suggesting additive or synergistic interactions, but not fully espistatic ones, in the control of anthocyanin levels in tomato hypocotyls. Our results indicate that phytochrome-mediated anthocyanin accumulation in tomato hypocotyls is modulated by distinct hormone classes via both shared and independent pathways. (C) 2010 Elsevier Ireland Ltd. All rights reserved

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The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.

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The representation of sustainability concerns in industrial forests management plans, in relation to environmental, social and economic aspects, involve a great amount of details when analyzing and understanding the interaction among these aspects to reduce possible future impacts. At the tactical and operational planning levels, methods based on generic assumptions usually provide non-realistic solutions, impairing the decision making process. This study is aimed at improving current operational harvesting planning techniques, through the development of a mixed integer goal programming model. This allows the evaluation of different scenarios, subject to environmental and supply constraints, increase of operational capacity, and the spatial consequences of dispatching harvest crews to certain distances over the evaluation period. As a result, a set of performance indicators was selected to evaluate all optimal solutions provided to different possible scenarios and combinations of these scenarios, and to compare these outcomes with the real results observed by the mill in the study case area. Results showed that it is possible to elaborate a linear programming model that adequately represents harvesting limitations, production aspects and environmental and supply constraints. The comparison involving the evaluated scenarios and the real observed results showed the advantage of using more holistic approaches and that it is possible to improve the quality of the planning recommendations using linear programming techniques.

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Leaf wetness duration (LWD) is related to plant disease occurrence and is therefore a key parameter in agrometeorology. As LWD is seldom measured at standard weather stations, it must be estimated in order to ensure the effectiveness of warning systems and the scheduling of chemical disease control. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results for operational use. However, the requirement of net radiation (Rn) is a disadvantage foroperational physical models, since this variable is usually not measured over crops or even at standard weather stations. With the objective of proposing a solution for this problem, this study has evaluated the ability of four models to estimate hourly Rn and their impact on LWD estimates using a Penman-Monteith approach. A field experiment was carried out in Elora, Ontario, Canada, with measurements of LWD, Rn and other meteorological variables over mowed turfgrass for a 58 day period during the growing season of 2003. Four models for estimating hourly Rn based on different combinations of incoming solar radiation (Rg), airtemperature (T), relative humidity (RH), cloud cover (CC) and cloud height (CH), were evaluated. Measured and estimated hourly Rn values were applied in a Penman-Monteith model to estimate LWD. Correlating measured and estimated Rn, we observed that all models performed well in terms of estimating hourly Rn. However, when cloud data were used the models overestimated positive Rn and underestimated negative Rn. When only Rg and T were used to estimate hourly Rn, the model underestimated positive Rn and no tendency was observed for negative Rn. The best performance was obtained with Model I, which presented, in general, the smallest mean absolute error (MAE) and the highest C-index. When measured LWD was compared to the Penman-Monteith LWD, calculated with measured and estimated Rn, few differences were observed. Both precision and accuracy were high, with the slopes of the relationships ranging from 0.96 to 1.02 and R-2 from 0.85 to 0.92, resulting in C-indices between 0.87 and 0.93. The LWD mean absolute errors associated with Rn estimates were between 1.0 and 1.5h, which is sufficient for use in plant disease management schemes.

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Nowadays, the rising competition for the use of water and environmental resources with consequent restrictions for farmers should change the paradigm in terms of irrigation concepts, or rather, in order to attain economical efficiency other than to supply water requirement for the crop. Therefore, taking into account the social and economical role of bean activity in Brazil, as well as the risk inherent to crop due to its high sensibility to both deficit and excessive water, the optimization methods regarding to irrigation management have become more interesting and essential. This study intends to present a way to determine the optimal water supply, considering different combinations between desired bean yield and level of risk, bringing as a result a graph with the former associated with the latter, depending on different water depths.