User:Kczappa/CW:CityWater FAQ: Difference between revisions

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Since not all of the steps above are necessary while running scenarios, it is more common for a scenario to run faster than the initial upload. Running the scenario, however should take roughly the same amount of time as it would for the initial model upload. Both the number of pipes and the number of time steps contained within the model will increase the amount of time it takes to run the model, because the size of the model increases accordingly. The suggested amount of pipes for a given project is roughly around 10,000 – 15,000 pipes and 100 time steps since, at this time, CityWater best performs under these parameters.
Since not all of the steps above are necessary while running scenarios, it is more common for a scenario to run faster than the initial upload. Running the scenario, however should take roughly the same amount of time as it would for the initial model upload. Both the number of pipes and the number of time steps contained within the model will increase the amount of time it takes to run the model, because the size of the model increases accordingly. The suggested amount of pipes for a given project is roughly around 10,000 – 15,000 pipes and 100 time steps since, at this time, CityWater best performs under these parameters.


===Large Scale Models===
===Large Scale Model Run===
Ways to better the outcome of larger scale models include:
Ways to better the outcome of larger scale models include:
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Revision as of 14:02, 3 June 2020


CityWater Model Runs

When performing model runs with CityWater, it is common to see a lag in the amount of time it takes to process the run. When there are too many runs to perform simultaneously, CityWater uses a scheduling system to sort the model runs. To ensure that each product can get processed effectively without crashing, CityWater was designed to organize each run into a waiting queue which can be the cause of longer run times for the runs.

Three reasons why run times might be longer:

  1. Writing the results to the database – CityWater is must be able to access the results. Therefore, some of the time used to execute the run goes towards writing the results to the database so that the CityWater app can find and access the data that is needed.
  2. Performing extra analysis – One of the reasons it takes CityWater longer to run than in Epanet is because CityWater has to generate the zone, pressure swing, and peak-day fire flow layers which aren't offered in Epanet.
  3. Generating the visualization layers – CityWater uses visualization layers to display the model on the map which takes more time to generate which leads to a longer run time.

Running Scenarios

Since not all of the steps above are necessary while running scenarios, it is more common for a scenario to run faster than the initial upload. Running the scenario, however should take roughly the same amount of time as it would for the initial model upload. Both the number of pipes and the number of time steps contained within the model will increase the amount of time it takes to run the model, because the size of the model increases accordingly. The suggested amount of pipes for a given project is roughly around 10,000 – 15,000 pipes and 100 time steps since, at this time, CityWater best performs under these parameters.

Large Scale Model Run

Ways to better the outcome of larger scale models include:

  1. Reducing the number of pipes – An accurate Epanet model is not always contingent on a high number of pipes. Therefore, it is likely that reducing the pipes in a the model will still be effective.
  2. Reduce the number of time steps – When working with a larger model, it might be effective to reduce the typical 24 hours with a 15 minute time steps to an hourly time step over a span of 24 hours.
  3. Use the Viewing options – In a model, the exclusion of the Scenario, Fire Flow, or Schematic add-ons could benefit the project. With use of only the visualization capabilities, the model can still function even with larger projects because they are not highly influenced by the size of the model.