937 resultados para Head-On Vehicle-to-Vehicle Impact Tests.


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Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

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OBJECTIVES: Etravirine (ETV) is a novel nonnucleoside reverse transcriptase inhibitor (NNRTI) with reduced cross-resistance to first-generation NNRTIs, which has been primarily studied in randomized clinical trials and not in routine clinical settings. METHODS: ETV resistance-associated mutations (RAMs) were investigated by analysing 6072 genotypic tests. The antiviral activity of ETV was predicted using different interpretation systems: International AIDS Society-USA (IAS-USA), Stanford, Rega and Agence Nationale de Recherches sur le Sida et les hépatites virales (ANRS). RESULTS: The prevalence of ETV RAMs was higher in NNRTI-exposed patients [44.9%, 95% confidence interval (CI) 41.0-48.9%] than in treatment-naïve patients (9.6%, 95% CI 8.5-10.7%). ETV RAMs in treatment-naïve patients mainly represent polymorphism, as prevalence estimates in genotypic tests for treatment-naïve patients with documented recent (<1 year) infection, who had acquired HIV before the introduction of NNRTIs, were almost identical (9.8%, 95% CI 3.3-21.4). Discontinuation of NNRTI treatment led to a marked drop in the detection of ETV RAMs, from 51.7% (95% CI 40.8-62.6%) to 34.5% (95% CI 24.6-45.4%, P=0.032). Differences in prevalence among subtypes were found for V90I and V179T (P<0.001). Estimates of restricted virological response to ETV varied among algorithms in patients with exposure to efavirenz (EFV)/nevirapine (NVP), ranging from 3.8% (95% CI 2.5-5.6%) for ANRS to 56.2% (95% CI 52.2-60.1%) for Stanford. The predicted activity of ETV decreased as the sensitivity of potential optimized background regimens decreased. The presence of major IAS-USA mutations (L100I, K101E/H/P and Y181C/I/V) reduced the treatment response at week 24. CONCLUSIONS: Most ETV RAMs in drug-naïve patients are polymorphisms rather than transmitted RAMs. Uncertainty regarding predictions of antiviral activity for ETV in NNRTI-treated patients remains high. The lowest activity was predicted for patients harbouring extensive multidrug-resistant viruses, thus limiting ETV use in those who are most in need.

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This work describes an analytical approach to determine what degree of accuracy is required in the definition of the rail vehicle models used for dynamic simulations. This way it would be possible to know in advance how the results of simulations may be altered due to the existence of errors in the creation of rolling stock models, whilst also identifying their critical parameters. This would make it possible to maximize the time available to enhance dynamic analysis and focus efforts on factors that are strictly necessary.In particular, the parameters related both to the track quality and to the rolling contact were considered in this study. With this aim, a sensitivity analysis was performed to assess their influence on the vehicle dynamic behaviour. To do this, 72 dynamic simulations were performed modifying, one at a time, the track quality, the wheel-rail friction coefficient and the equivalent conicity of both new and worn wheels. Three values were assigned to each parameter, and two wear states were considered for each type of wheel, one for new wheels and another one for reprofiled wheels.After processing the results of these simulations, it was concluded that all the parameters considered show very high influence, though the friction coefficient shows the highest influence. Therefore, it is recommended to undertake any future simulation job with measured track geometry and track irregularities, measured wheel profiles and normative values of wheel-rail friction coefficient.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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Federal Highway Administration, Bureau of Motor Carrier Safety, Washington, D.C.

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Federal Highway Administration, McLean, Va.

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National Highway Traffic Safety Administration, Office of Vehicle Safety Compliance, Washington, D.C.