Experimental Validation for Globally Optimized Tractor-Trailer Base Flaps
Jacob Andrew Freeman,
Mark Franklin Reeder,
Anna Christine Demoret
Issue:
Volume 4, Issue 4, July 2019
Pages:
103-117
Received:
2 July 2019
Accepted:
25 July 2019
Published:
13 August 2019
Abstract: Using wind-tunnel testing, this study validates a design that was globally optimized under uncertainty and used computational fluid dynamics. The computational study determined a design for a 3-D tractor-trailer base (back-end) drag-reduction device that reduces the wind-averaged drag coefficient by 41% at 57 mph (92 km/h). The wind-tunnel testing applies the same method of including some uncertainties, such that the design is relatively insensitive to variation in wind speed and direction, elevation, and installation accuracy. The validation testing shows a 20.1% reduction in wind-averaged drag coefficient, or 1.3% better than a non-optimized commercial design, and is conducted on a 1/24-scale model of the simplified tractor trailer at a trailer-width-based Reynolds number (ReW) of 4.9x105. Test data include both force and pressure measurements on the simplified tractor trailer, as well as pressure measurements on the tunnel wall. Measurements are taken at static side-slip angles to enable wind-averaged calculations. Since the original computations are conducted for a full-scale tractor-trailer at ReW = 4.4x106, this study does not fully validate the computational design due to the wind tunnel limitations and resulting inability to match the ReW; however, the results show qualitative and quantitative improvement over the non-optimized design.
Abstract: Using wind-tunnel testing, this study validates a design that was globally optimized under uncertainty and used computational fluid dynamics. The computational study determined a design for a 3-D tractor-trailer base (back-end) drag-reduction device that reduces the wind-averaged drag coefficient by 41% at 57 mph (92 km/h). The wind-tunnel testing ...
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Determining Optimal Tolling Rates for Border Regions Using Dynamic Modeling Methods
Jeffrey Shelton,
Peter Martin
Issue:
Volume 4, Issue 4, July 2019
Pages:
118-131
Received:
21 May 2019
Accepted:
23 July 2019
Published:
14 August 2019
Abstract: Many toll facilities have been faced with traffic shortfalls due to inaccurate and over-forecasted toll revenue projections. Therefore calculating optimal toll rates can be a difficult process. Toll rates are often set to reflect the revenue needed to pay back bonds issued to finance the roadway. This research provides an alternative approach to calculating toll rates where revenue can be maximized while still considering the socio-demographics of the region. Several different approaches used in the border region were explored and compared to field data on an existing toll facility in El Paso, Texas. An innovative simulation-based modeling approach was used to test both static and dynamic pricing algorithms. Static tolling results showed optimal toll rates of $0.14/mile and $0.08/mile for Border Highway West in the westbound and eastbound directions respectively. The Cesar Chavez Highway has optimal toll rates of $0.12 and $0.10/mile in the west and eastbound directions. The dynamic tolling approach showed a max toll rate of $1.56/mile for Cesar Chavez Highway (westbound) during the morning peak period and then incrementally decreased to the minimum toll rate. However, the eastbound direction never increased above the minimum toll rate of $0.08 mile. Border Highway West never increased above the minimum toll rate in either direction. The dynamic tolling algorithm prediction is more representative of the optimal tolling rates for the border region-with the exception of Cesar Chavez Highway westbound.
Abstract: Many toll facilities have been faced with traffic shortfalls due to inaccurate and over-forecasted toll revenue projections. Therefore calculating optimal toll rates can be a difficult process. Toll rates are often set to reflect the revenue needed to pay back bonds issued to finance the roadway. This research provides an alternative approach to ca...
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Innovation Mechanism of Traffic Demand Management
Qingyin Li,
Zhongjiao Xie,
Yongqing Guo,
Fulu Wei,
Yan Tian,
Yanfeng Zhang,
Chaoran Wang
Issue:
Volume 4, Issue 4, July 2019
Pages:
132-136
Received:
7 July 2019
Accepted:
13 August 2019
Published:
26 August 2019
Abstract: Traffic demand management is an effective way to solve the problem of urban traffic congestion. Due to the effects of the social economic development, population quality, scientific and technological level and other related factors, the existing traffic demand management systems are lack of effective coordination and management mechanism. Although the traffic demand management measures have achieved some results, but due to lack of effective coordination and management mechanism between them, resulting in poor practical application. By analyzing and summarizing the current situations of traffic demand management, the paper explores an innovative traffic demand management mechanism based on comprehensive traffic planning and modern information technology and economic means. Under the new demand management mechanism, the urban transportation system runs more orderly, which can help to largely increase residents' travel satisfaction and social and economic benefits. On the basis of analyzing and summarizing the current research status of traffic demand management, this paper conducts innovative research on traffic demand management mechanism based on the implementation effect of existing traffic demand management. In view of the existing shortcomings in the systematic and scientific traffic demand management, and insufficient traffic law enforcement quality problems, the paper explores the innovative traffic demand management mechanism based on comprehensive transportation planning, modern information technology and economic means.
Abstract: Traffic demand management is an effective way to solve the problem of urban traffic congestion. Due to the effects of the social economic development, population quality, scientific and technological level and other related factors, the existing traffic demand management systems are lack of effective coordination and management mechanism. Although ...
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