989 resultados para Slow-Moving Vehicle Identification Emblems.
Evaluation of techniques for warning of slow-moving vehicles ahead: executive summary. Final report.
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Mode of access: Internet.
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Federal Highway Administration, Washington, D.C.
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This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.
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In the interaction between vehicles, pavements and bridges, it is essential to aim towards a reduction of vehicle axle forces to promote longer pavement life spans and to prevent bridges loads becoming too high. Moreover, as the road surface roughness affects the vehicle dynamic forces, an efficient monitoring of pavement condition is also necessary to achieve this aim. This paper uses a novel algorithm to identify the dynamic interaction forces and pavement roughness from vehicle accelerations in both theoretical simulations and a laboratory experiment; moving force identification theory is applied to a vehicle model for this purpose. Theoretical simulations are employed to evaluate the ability of the algorithm to predict forces over a range of bridge spans and to evaluate the influence of road roughness level on the accuracy of the results. Finally, in addressing the challenge for the real-world problem, the effects of vehicle configuration and speed on the predicted road roughness are also investigated in a laboratory experiment.
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The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.
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Travel time in an important transport performance indicator. Different modes of transport (buses and cars) have different mechanical and operational characteristics, resulting in significantly different travel behaviours and complexities in multimodal travel time estimation on urban networks. This paper explores the relationship between bus and car travel time on urban networks by utilising the empirical Bluetooth and Bus Vehicle Identification data from Brisbane. The technologies and issues behind the two datasets are studied. After cleaning the data to remove outliers, the relationship between not-in-service bus and car travel time and the relationship between in-service bus and car travel time are discussed. The travel time estimation models reveal that the not-in-service bus travel time are similar to the car travel time and the in-service bus travel time could be used to estimate car travel time during off-peak hours
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A new technique named as model predictive spread acceleration guidance (MPSAG) is proposed in this paper. It combines nonlinear model predictive control and spread acceleration guidance philosophies. This technique is then used to design a nonlinear suboptimal guidance law for a constant speed missile against stationary target with impact angle constraint. MPSAG technique can be applied to a class of nonlinear problems, which leads to a closed form solution of the lateral acceleration (latax) history update. Guidance command assumed is the lateral acceleration (latax), applied normal to the velocity vector. The new guidance law is validated by considering the nonlinear kinematics with both lag-free as well as first order autopilot delay. The simulation results show that the proposed technique is quite promising to come up with a nonlinear guidance law that leads to both very small miss distance as well as the desired impact angle.
Nonlinear Suboptimal Guidance with Impact Angle Constraint for Slow Moving Targets in 1-D Using MPSP
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Using a recently developed method named as model predictive static programming (MPSP), a nonlinear suboptimal guidance law for a constant speed missile against a slow moving target with impact angle constraint is proposed. In this paper MPSP technique leads to a closed form solution of the latax history update for the given problem. Guidance command is the latax,which is normal to the missile velocity and the terminal constraints are miss distance and impact angle. The new guidance law is validated by considering the nonlinear kinematics with both lag-free and first order autopilot delay.
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Many particles proposed by theories, such as GUT monopoles, nuclearites and 1/5 charge superstring particles, can be categorized as Slow-moving, Ionizing, Massive Particles (SIMPs).
Detailed calculations of the signal-to-noise ratios in vanous acoustic and mechanical methods for detecting such SIMPs are presented. It is shown that the previous belief that such methods are intrinsically prohibited by the thermal noise is incorrect, and that ways to solve the thermal noise problem are already within the reach of today's technology. In fact, many running and finished gravitational wave detection ( GWD) experiments are already sensitive to certain SIMPs. As an example, a published GWD result is used to obtain a flux limit for nuclearites.
The result of a search using a scintillator array on Earth's surface is reported. A flux limit of 4.7 x 10^(-12) cm^(-2)sr^(-1)s^(-1) (90% c.l.) is set for any SIMP with 2.7 x 10^(-4) less than β less than 5 x 10^(-3) and ionization greater than 1/3 of minimum ionizing muons. Although this limit is above the limits from underground experiments for typical supermassive particles (10^(16)GeV), it is a new limit in certain β and ionization regions for less massive ones (~10^9 GeV) not able to penetrate deep underground, and implies a stringent limit on the fraction of the dark matter that can be composed of massive electrically and/ or magnetically charged particles.
The prospect of the future SIMP search in the MACRO detector is discussed. The special problem of SIMP trigger is examined and a circuit proposed, which may solve most of the problems of the previous ones proposed or used by others and may even enable MACRO to detect certain SIMP species with β as low as the orbital velocity around the earth.
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Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.
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This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.
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ABSTRACT In passato valeva il motto “grande è meglio”. Le aziende avevano enormi magazzini che riempivano fino a che questi riuscivano a contenere merce. Ciò avveniva nella convinzione che gli alti costi della gestione delle scorte sarebbero stati superati dalle vendite. Negli ultimi anni le aziende hanno però radicalmente cambiato il loro approccio alla gestione delle rimanenze: queste, vengono considerate un eccesso e i magazzini con elevate scorte vengono visti come un‟opportunità mancata e capitale sprecato. I produttori sono sempre più consapevoli della necessità di minimizzare l‟inventario e massimizzare la rotazione dei prodotti. In questo contesto si inseriscono le problematiche connesse alla gestione delle scorte, con particolare riferimento al fenomeno dello slow moving, espressione che indica tutti i materiali a lenta movimentazione stoccati a magazzino. Questi spesso rappresentano un importante onere finanziario per le aziende: si sostengono costi di immobilizzo del capitale, di stoccaggio del materiale oltre a quelli connessi al rischio di obsolescenza. Molto spesso si tende a trascurare il problema, fino a quando le dimensioni di quest‟ultimo si ingrandiscono al punto di diventare una priorità aziendale da cui si cerca una rapida soluzione. L‟elaborato presenta un preliminare studio di caso che ha costituito il punto di partenza per la progettazione di un action plan per la riduzione e lo smaltimento degli item obsoleti e a bassa movimentazione di una realtà aziendale italiana del settore metalmeccanico di cui si presentano anche i primi risultati dell‟implementazione. Dopo aver fornito una panoramica teorica sul ruolo e la gestione delle scorte, si passa ad analizzare il problema dello slow moving in una particolare realtà aziendale, la Biffi s.r.l. di Fiorenzuola d‟Arda (Piacenza), un‟ impresa che dal 1955 produce attuatori per valvole. Esaminato il mercato di riferimento, il tipo di prodotto e il processo di fabbricazione, si passa all‟as-is del magazzino. Attraverso tale analisi, vengono poste in risalto le problematiche legate all‟identificazione, classificazione e gestione dei codici slow moving. E‟ stato proprio lo studio di questi dati che ha posto le basi per lo sviluppo dell‟action plan per la razionalizzazione delle giacenze a magazzino. Nell‟ultima parte dell‟elaborato ho quindi descritto le azioni intraprese e presentato i risultati ottenuti, che hanno consentito risparmi significativi senza effettuare investimenti , ma semplicemente utilizzando al meglio le risorse già disponibili.