This paper describes the status of the pre-conceptual design activities in Europe to advance the technical basis of the design of a DEMOnstration Fusion Power Plant (DEMO) to come in operation around the middle of this century with the main aims of demonstrating the production of few hundred MWs of net electricity, the feasibility of operation with a closedtritium fuel cycle, and maintenance systems capable of achieving adequate plant availability. This is expected to benefit as much as possible from the ITER experience, in terms of design, licensing, and construction. Emphasis is on an integrated design approach, based on system engineering, which provides a clear path for urgent R&D and addresses the main design integration issues by taking account critical systems interdependencies and inherent uncertainties of important design assumptions (physics and technology). A design readiness evaluation, together with a technology maturation and down selection strategy are planned through structured and transparent Gate Reviews. By embedding industry experience in the design from the beginning it will ensure that early attention is given to technology readiness and industrial feasibility, costs, maintenance, power conversion, nuclear safety and licensing aspects.
With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similarity score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.
Smart technologies enabling connection among vehicles and between vehicles and infrastructure as well as vehicle automation to assist human operators are receiving significant attention as a means for improving road transportation systems by reducing fuel consumption-and related emissions-while also providing additional benefits through improving overall traffic safety and efficiency. For truck applications, which are currently responsible for nearly three-quarters of the total U.S. freight energy use and greenhouse gas (GHG) emissions, platooning has been identified as an early feature for connected and automated vehicles (CAVs) that could provide significant fuel savings and improved traffic safety and efficiency without radical design or technology changes compared to existing vehicles. A statistical analysis was performed based on a large collection of real-world U.S. truck usage data to estimate the fraction of total miles that are technically suitable for platooning. In particular, our analysis focuses on estimating "platoonable" mileage based on overall highway vehicle use and prolonged high-velocity traveling, and established that about 65% of the total miles driven by combination trucks from this data sample could be driven in platoon formation, leading to a 4% reduction in total truck fuel consumption. This technical potential for "platoonable" miles in the United States provides an upper bound for scenario analysis considering fleet willingness and convenience to platoon as an estimate of overall benefits of early adoption of connected and automated vehicle technologies. A benefit analysis is proposed to assess the overall potential for energy savings and emissions mitigation by widespread implementation of highway platooning for trucks.
An analysis of the flow field around a maple seed as it rotates and subsequent comparison to wind turbine blades is discussed. Physical values were determined experimentally from a real maple seed sample and high speed video imaging. Three dimensional computational fluid dynamics was used to simulate the maple seed in autorotation. Expected behaviors have been observed, parallels with wind turbine performance have been drawn, and potential for higher accuracy explained. Comparison of key performance quantities between the maple seed and true wind turbines has shown a potential for wind turbine design implications from the interesting maple seed geometry. The power coefficient for the maple seed from the analysis is 0.59 which compares to a range of 0.45 to 0.48 for many wind turbines and 0.593 maximum from the Betz limit. NomenclatureA = cross-sectional area of the stream tube boundary a = axial induction factor C p = power coefficient C pr = pressure coefficient c = chord F = axial force ρ = air density = mass flow rate Re = Reynolds Number = !"# ! U = axial absolute velocity component U 1 = upstream axial absolute velocity component U 2 = rotor plane axial absolute velocity component U 4 = downstream axial absolute velocity component v d = vertical velocity of maple seed α = angle of attack ω = rotational velocity µ = dynamic viscosity 3DBGB = Three Dimensional Blade Geometry Builder CFD = computational fluid dynamics DARPA = Defense Advanced Research Projects Agency LES = large eddy simulation DES = detached eddy simulation DNS = direct numerical simulation NREL = National Renewable Energy Laboratories RANS = Reynolds-Averaged Navier-Stokes UAV = unmanned aerial vehicle
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