Three computer simulation workflows based on Realflow and Grasshopper

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Three computer simulation workflows for long time scale sediment process based on Realflow and Grasshopper Zheyuliu Master of Landscape Architecture, University of Virginia

Abstract The aim of this paper is to establish workflows for data exchange between Realflow and Grasshopper. Based on the UVA 2020 Venice studio, by simulating the lagoon’s bottom terrain changes by constructing structures in the Venice Lagoon, this project starts to explore the significance of this workflow in design and research projects.

Introduction Venice Lagoon and Venice City have a very unique and complex land-water relationship. Connected to the Adriatic Sea, the Venice Lagoon has an average water depth of about two meters. Saltwater and river water carrying rich sediments merge, flow, erode, and settle in this vast water area. This complex water exchange process and flat topography form a unique tidal river network under the water surface and an ecological environment dominated by salt marshes. However, during industrial development in the past hundred years, Venice Lagoon was developed as a deep-water port. Excavating canals with a depth of more than ten meters, large-capacity cargo ships, and the fixing works for barrier islands and inlets have disrupted the original water exchange process and caused a large amount of sediment loss. Those changes caused the Venice Lagoon to lose its original morphological characteristics gradually. So far, 70% of the salt marshes have disappeared. The deepening lagoon and rising sea levels have seriously threatened the existence of Venice. Take this system’s complexity into consideration, it is almost impossible to reverse this deteriorating trend by relying on personal experience or possibility based on general knowledge. It was proved that due to human’s Water depth & tidal creek network: 1930 (left) ,2002 (right) thinking limitations, completely artificial interventions implanted in the natural environment often solve problems while also bringing more issues. We need to try to understand the natural evolution process while considering human needs. Through artificial intervention, adjust or accelerate the process of natural changes, leave room for natural forces to do works, and create a hybrid of natural and artificial. To achieve this, it means that the method and medium of inquiry must be able to target multiple quantities and reflect changes and mutual influences


in a longer time scale. RealFlow is a fluid and dynamics simulation tool for the 3D and visual effects industry, developed by Next Limit Technologies in Madrid, Spain. Since it is a simulation tool based on the time axis, the information obtained by the simulation at each instant within a certain time scale will be recorded. At the same time, it has an excellent ability to interface with different 3D software. However, the analysis and performance capabilities of Realflow are not strong enough for a landscape project, so I try to analyze and display the data simulated in Realflow through Rhino and Grasshopper.

Methods 1. Build an abstract model of the tidal river network growth process. Lagoons are different from beaches in general coastline areas. Due to the lagoon barriers’ protective effect, the impact of plagiarism from the freshwater rivers and seawater in the lagoon is always in a dynamic balance. The river water flowing from the mainland into the lagoon brought a lot of sediment. Due to the flat terrain, the water in the lagoon is shallow and slow. A large amount of sediment in the river water is deposited here and fixed by aquatic plants in their uninterrupted life cycle. The river water and sea water flowing in from the lagoon erode the tidal river network on the deposited silt in the cycle of high tide and low tide. High tidal flow will maintain channels, while slower flow velocity can lead to closure of tidal creeks as they become clogged with sediment.The main river channel is fixed by plants on both sides, and the area blocked by sediment will form new branches between the stable river channels under the action of erosion.

Abstract tidal creek network growth process.

2. Realflow simulation In Realflow, I use three Dyverso particle emitters to emit water particles and add Fill in Dyverso particle emitters to create a simulation environment between the two main tidal creeks. The orange Dyverso particles created by Fill in Dyverso particle emitters are used as the final output data source to show how the structure can shape the new terrain and tidal river network between the two channels under the influence of current. In this test field, I can test the different effects of structures by importing structures with various shapes without being affected by other variable elements.


Structure of digital simulation

3. Grasshopper analysis and visualization To further analyze and visualize the obtained terrain change process, I exported the "sediment particles" in Realflow to Grasshopper and read them as mesh objects(every 100 frames). Further visualization and analysis of elevation changes in Grasshopper can clearly show the deposition and erosion occurring on the flat surface. All simulations and analysis are produced by Realflow version 10.0.0.0135, Rhino version 6.30, and its built-in grasshopper plugin. The detail tutorial about those three workflows is in the last section.

Result After turning on only one side of the water particle emitter for 200 frames to simulate the process of high tide, it can be observed that the initially flat sediments particles begin to appear undulating terrain. Different degrees of erosion appeared on both sides of the neatly arranged structure pattern one. Farther away from the eroded area downstream of pattern one, sediment began to accumulate


and caused the terrain to uplift. Sediments also began to accumulate in the interior and downstream side of the structure pattern two to form highlands. Turn on the water particle emitters on the other side from frame 200 to flip the water flow direction to simulate the ebb process. It can be observed that there is accumulation of sediment on the upstream side immediately adjacent to the structure pattern one. At the same time, there is obvious topography formed by accumulation of sediments next to the erosion area on both sides of the structure pattern. The interior of the structure pattern two and the longest side of the triangle also have apparent sediment accumulation. Thereafter, the above-mentioned operation is repeated in units of 400 frames. We can observe that due to the different positions of the two structural patterns and their different effects on the current, a tidal river network is gradually formed by the T-shaped structure.

Grasshopper visualization

Discussion Using the above method to simulate the T shape structure composed of two different pole arrangements can clearly show how sediments gradually accumulate in different areas around the structure to form highlands. Simultaneously, information such as the erosion at the bottom, the handling process, and the flow rate and direction of the water that caused these changes at every moment were also recorded. On the one hand, compared to traditional mapping and other 2D methods, this workflow can clearly show the continuous impact of the proposed intervention in three-dimensional space. Based on this workflow, we can realize the closed loop of "Scheme 1-SimulaGrasshopper visualization


tion-Analysis-Optimization-Scheme 2" during the process of deduction intervention. On the other hand, compared with the traditional physical model, the data that this method can record will be richer and more complete. Through the playback function, we can also observe the simulation results repeatedly from various angles to obtain more accurate judgments. The accuracy of digital simulation depends entirely on the setting information entered by the user. This means that the accuracy of the simulation will be limited by the user's ability. But this subjective influence and uncertainty can be gradually improved.

Tutorial Workflow 1: Terrain modeling based on water velocity

Triangular mesh is a file format that can be read by both realflow and rhino. Therefore, the triangle mesh and obj file formats are the main media for transferring information between the two software. 1. Build a test model in rhino and convert the nurbs model into a triangular mesh..

2. Export mesh to obj file and import Realflow. 3. Create a cube in realflow and use the scale tool to stretch the cube as a base.

4. Add Dyverso water emitter to the scene


5. Control the appearance and movement of particles by changing the speed range under the display menu and the initial velocity of the particle emitter.

6. In order to simulate the different processes of high tide and low tide. I copied the same particle emitter on the other side of the structure and temporarily stopped its simulation function.

High tide

7. Capture the water velocity map close to the ground from the bottom view as an information basis for analyzing sedimentation and erosion.

Low tide

8. Read the information of the two pictures through the image sampler and convert the grayscale image into terrain. High tide

High tide &Low tide

9. Spatial analysis of the terrain through grasshopper. For example, the accumulation pattern of sediment can be obtained through elevation analysis.


Grasshopper defination

Workflow 2: Simulation of terrain evolution based on sediment particles The second workflow pays more attention to sediment and bottom morphology.

1. Export structures from Rhino in the same way as the first workflow.

2. Different from the first workflow, the simulation environment for the second workflow is more complex. In addition to the structure, a container of water and sediment and the volume of sediment particles need to be created and derived from rhino.

It should be noted that these objects should be created together in rhino and exported in stages to ensure the correct positional relationship.


3. After importing the object into Realflow, click on the volume to generate sediment, and click on "fill object" under the "Dyverso" menu.

4. Select Dyverso domain in the "Nodes" on the right and select "Granular" in the "type" drop-down menu. Realflow will automatically fill the object with particles used to simulate solids such as sand.

4. Based on the abstraction of the environment to be simulated, add Dyverso particle emitter in the same way as workflow 1.

5. In order to reduce the computational pressure and create a "water outlet" in the closed container, a "k volume" is added to the scene. By adjusting its size and position, it prevents water particles from touching the container wall and causing interference to the simulation.

6. After the simulation is complete, add a "particle mesh (legacy)" controller to the scene


7. Set the storage format of mesh to obj format in Realflow export center.

8. Select "particle mesh" and click "build mesh" to build sediment particles into terrain mesh. The mesh objects will be automatically stored as obj files in the meshes folder in the scene folder.

Take time scale of the simulation into consideration, the "build mesh sequence" can create a mesh for each frame to show the entire evolution process in detail.

9. Import the obj file into Grasshopper


3. Find the asc file and rename it to a text document with a suffix of .txt

4. Open text documents with office excel or similar software.

4. Change the data into a form that can be read by Grasshopper by searching and replacing.

5. Import the data into Grasshopper and split, and then restore the water particles based on the obtained data.


References Allen, J.R.L., 2000, Morphodynamics of Holocene salt marshes: A review sketch from the Atlantic and southern North Sea coasts of Europe: Quaternary Science Reviews, v. 19, p. 1155–1231, doi:10.1016/S0277-3791(99)00034-7. Bellucci, L.G., Frignani, M., Cochran, J.K., Albertazzi, S., Zaggia, L., Cecconi, G., and Hopkins, H., 2007, 210Pb and 137Cs as chronometers for salt marsh accretion in the Venice Lagoon—Links to fl ooding frequency and climate change: Journal of Environmental Radioactivity, v. 97, p. 85–102, doi:10.1016/j.jenvrad.2007.03.005. Day, J.W, et al. “Soil Accretionary Dynamics, Sea-Level Rise and the Survival of Wetlands in Venice Lagoon: A Field and Modelling Approach.” Estuarine, Coastal and Shelf Science, Academic Press, 25 May 2002, www.sciencedirect.com/science/article/pii/S027277149990522X. Ferrarin, C., et al. “Assessing Hydrological Effects of Human Interventions on Coastal Systems: Numerical Applications to the Venice Lagoon.” Hydrology and Earth System Sciences, Copernicus GmbH, 3 May 2013, hess.copernicus.org/articles/17/1733/2013/. García-Guaita, Fernando, et al. “Integrating Urban Metabolism, Material Flow Analysis and Life Cycle Assessment in the Environmental Evaluation of Santiago De Compostela.” Sustainable Cities and Society, Elsevier, 27 Apr. 2018, www.sciencedirect.com/science/article/pii/S2210670717317559. Pincetl, Stephanie, et al. “An Expanded Urban Metabolism Method: Toward a Systems Approach for Assessing Urban Energy Processes and Causes.” Landscape and Urban Planning, Elsevier, 2 July 2012, www.sciencedirect.com/science/article/pii/S0169204612001922. Rizzetto, Federica, and Luigi Tosi. “Rapid Response of Tidal Channel Networks to Sea-Level Variations (Venice Lagoon, Italy).” Global and Planetary Change, Elsevier, 2 June 2012, www.sciencedirect.com/science/article/pii/S0921818112001063. Zonta, Roberto, et al. “Sediment Texture and Metal Contamination in the Venice Lagoon (Italy): A Snapshot before the Installation of the MOSE System.” Estuarine, Coastal and Shelf Science, Academic Press, 7 Mar. 2018, www.sciencedirect.com/science/article/pii/S0272771417310491.


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