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This paper deals with the initial modeling of water salinity and its diffusion into the lakes during lock operation on the Panama Canal. A hybrid operational model was implemented using the AnyLogic software simulation environment. This was accomplished by generating an operational discrete-event simulation model and a continuous simulation model b...
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Context 1
... navigational channel of the Panama Canal is about 50 miles (80 km) long and extends from the Caribbean Sea to the Pacific ocean (see Figure 1). The canal includes Gatun Lake, a fresh water lake which has a surface area of 436 Km 2 (168.4 mi 2 ) at 26 m (85 ft) above mean sea level. ...Context 2
... addition, it was complemented by a data collection using historical data provided by the Panama Canal Authority (and data collected by the team). For convenience reference, the six locks (see Figure 1) are identified by the following notation [10]: L1: lowest lock on the Pacific side; L2: lock between Miraflores Lake and L1; L3: lock between Miraflores Lake and Gatun Lake (Pedro Miguel); L4: highest lock directly connected to Gatun Lake; L5: middle lock on Atlantic side; L6: lowest lock connected to Atlantic ocean. ...Citations
... The expanded Panama Canal has allowed and promoted the development of new studies where the operations in the locks have been statistically modeled such as Carral et al. [11]. While the previous studies have simulated different operations and conditions corresponding to the Panama Canal such as the exchanges of water in Gatun Lake [12], the salinity in the locks [12,13], and transit and operation [14][15][16], the present work includes for the first time in scientific literature a comprehensive qualitative and statistical analysis of the total time in transit through the set of navigable routes and locks that compose the new expanded Panama Canal. Apart from Carral et al. [11], there are no previous studies due to the fact that the completion of the expansion works is still very recent, in addition to the fact that the data are not freely accessible to the public. ...
In response to an increased reliance on bigger, Neopanamax-sized vessels for shipping, the Panama Canal has been expanded. Whilst the way that vessels transit the newly expanded canal has stayed the same, maneuvering operations have changed. As a result, transit times have been affected. In accordance with the size and cargo of vessels, canal navigation rules restrict how access channels (Culebra Cut, Gatún Lake, and seaways) and new locks (Cocolí and Agua Clara) are used. Larger sized, Neopanamax vessels will benefit most from the expanded canal. Since the canal opened on 26 June 2016, data on transit times have been gathered. With these data, a thorough statistical analysis should be carried out. The most influential variables on overall time in transit (TET), such as pilot skill and Culebra Cut or Gatun Lake transit times, are identified. Formulae based on multivariate linear regression can be extracted that will make it possible to establish a conductive methodology for estimating the transit time of a Neopanamax vessel. Taking into account the results of the statistical analysis, a proposal is included for improving Neopanamax traffic management, with views to reduce the TET, from a transit policy point of view. This is the first work in scientific literature that analyzes in detail, from qualitative and statistical approaches, the total time in transit through the set of navigable routes and locks that compose the new expanded Panama Canal.
Before you lies the book ‘Ports and Waterways - Navigating the changing world’, written by the Ports and Waterways team, part of the Civil Engineering and Geosciences faculty at Delft University of Technology. It integrates the content of a number of separate lecture notes we used in our teaching activities and updates this information where relevant. The integration reflects our vision that ports and waterways should be viewed as parts of a coherent system that supports waterborne supply chains, and that their integral design and operation is essential.
This paper presents preliminary analysis of the Panama Canal Expansion from the viewpoint of salinity in the Gatun Lake and the utilization of neural networks. This analysis utilized simulation modeling and artificial intelligence. We have built several discrete and system dynamics simulation models of the current Panama Canal operations and the future expansion which have been validated with historical and projected data and Turing/expert validation by engineers of the Panama Canal Authority. The simulation models have been exercised in order to generate enough information about the future expansion. This information has been used to develop neural networks that have the capability to indicate the volume of the Gatun Lake and its respective salinity taking into consideration lockages, spillovers, hydropower generation, fresh water supply volumes, and environmental factors such as precipitation, tides, and evaporation. Support vector machines were used to build time series regression models of the evaporation of Gatun Lake.
