Dam breaching uncertainty and its effect in downstream areas

Proceedings of the Seventh International Conference on Hydroscience and Engineering, Philadelphia, PA, September 2006. http://hdl.handle.net/1860/732A flood forecasting methodology is presented for a hypothetical dam failure event and possible solutions are proposed that could lead to reduction of flood consequences. During recent years, many methods have been developed with the purpose of achieving a better representation of the processes involved in breaching of a dam. However, no single method, to the best of our knowledge, can be considered to fully represent and predict the breach characteristics with high accuracy. In this study, we estimate the breach characteristics using two separate breach models and compare the resulting peak outflows with the range of peak outflows obtained using the empirical formulations. Despite only 10% difference in the peak outflow values obtained from two breach models, significant discrepancy is observed in timing and shape of the hydrograph. The peak outflow obtained using Hagen’s empirical formula is almost the same as predicted using physically based models. Though the empirical formulations might be useful for ‘rough/fast’ prediction of the peak outflow values, it is not applicable for dam break flood forecasting task, where the knowledge about breach development in time is important. The resulting hydrographs, constituting the upstream boundary condition for the Sobek 1D2D hydrodynamic model led to two different flood progression scenarios at the areas downstream the dam. The difference in timing of the breach outflow hydrographs is preserved during the propagation of the flood wave up to 30km from the dam

Trickle-down strategies:integrating simulations with control loops of autonomous vessels on lab scale

This study integrates strategic decisions and operational control systems in autonomous shipping. By providing ships with situational information and adding a virtual operator, we show that vessels can make informed choices regarding their route and engine settings. To demonstrate this integration, we developed new components and put these to the test in three lab experiments. The green routing capability experiment showed the bridge between the control system of the autonomous vessel, operated via Robot Operating System (ROS), to the simulation environment of OpenCLSim. We developed a real-time variant of OpenCLSim and a communication component that could expose the state of the OpenCLSim simulation with the ROS system. This experiment showed that an autonomous vessel could follow a path provided by the simulation. The green steaming capability experiment showed that the ship could also adapt its speed based on information from the simulations. We developed an additional communication component capable of advising the vessel about its velocity. Together with the green-routing capability, this forms the basis for more complex experiments. The port layout experiment showed a potential use case of the green-routing and green-steaming capabilities. We created a waypoint layout similar to the port. While a ship is sailing, twelve simulations are computed every five seconds. The scenarios vary in engine order, route choices, resulting in varying emissions, fuel, and cost. We evaluated the impact of different tactics such as green-routing, green-steaming, and full-speed sailing on operational behavior like steering and engine order. Our approach, using a real-time version of a Vessel in the OpenCLSim simulation software, enabled predictive simulations to facilitate the chosen tactic based on a given strategy. Integrating simulations to evaluate the options with the control systems can develop into a valuable tool for optimizing vessel performance and reducing environmental impact in autonomous shipping operations.</p

Trickle-down strategies:integrating simulations with control loops of autonomous vessels on lab scale

This study integrates strategic decisions and operational control systems in autonomous shipping. By providing ships with situational information and adding a virtual operator, we show that vessels can make informed choices regarding their route and engine settings. To demonstrate this integration, we developed new components and put these to the test in three lab experiments. The green routing capability experiment showed the bridge between the control system of the autonomous vessel, operated via Robot Operating System (ROS), to the simulation environment of OpenCLSim. We developed a real-time variant of OpenCLSim and a communication component that could expose the state of the OpenCLSim simulation with the ROS system. This experiment showed that an autonomous vessel could follow a path provided by the simulation. The green steaming capability experiment showed that the ship could also adapt its speed based on information from the simulations. We developed an additional communication component capable of advising the vessel about its velocity. Together with the green-routing capability, this forms the basis for more complex experiments. The port layout experiment showed a potential use case of the green-routing and green-steaming capabilities. We created a waypoint layout similar to the port. While a ship is sailing, twelve simulations are computed every five seconds. The scenarios vary in engine order, route choices, resulting in varying emissions, fuel, and cost. We evaluated the impact of different tactics such as green-routing, green-steaming, and full-speed sailing on operational behavior like steering and engine order. Our approach, using a real-time version of a Vessel in the OpenCLSim simulation software, enabled predictive simulations to facilitate the chosen tactic based on a given strategy. Integrating simulations to evaluate the options with the control systems can develop into a valuable tool for optimizing vessel performance and reducing environmental impact in autonomous shipping operations.</p

DigiPACT: Green Steaming and Green Routing Experiments

README DigiPACT This document provides supporting information for the data files of the DigiPACT project. 3d.zip 3D visualizations including the lab-scale vessel apr 12 2023 max guidance in the loop &amp; working.zip Data recordings of the Port Call expriment conducted on April 12 (successful). jan 23 2023.zip Data recordings of the initial attempt at the Green Routing experiment conducted on January 23 (unsuccessful). jan 25 2023.zip Data recordings of the second attempt at the Green Routing experiment conducted on January 25 (unsuccessful). jan 30 2023.zip Data recordings of the third attempt at the Green Routing experiment conducted on January 30 (successful). mar 1 2023 velocity controller working first iteration.zip Data recordings of the Green Steaming experiment conducted on March 1 (successful). videos.zip Collection of videos made during the experiments