From f99755c2967de765eaed86d5ddbb60ab43a0142d Mon Sep 17 00:00:00 2001 From: visr Date: Tue, 1 Oct 2024 07:09:39 +0000 Subject: [PATCH] deploy: d5386277b421395a0cc8591384e0b9dc6e5c099f --- concept/allocation.html | 28 +++++++++++----------- reference/node/basin.html | 14 +++++------ reference/node/discrete-control.html | 2 +- reference/node/manning-resistance.html | 2 +- reference/node/tabulated-rating-curve.html | 2 +- reference/test-models.html | 2 +- reference/validation.html | 4 ++-- search.json | 2 +- tutorial/irrigation-demand.html | 4 ++-- tutorial/reservoir.html | 4 ++-- 10 files changed, 32 insertions(+), 32 deletions(-) diff --git a/concept/allocation.html b/concept/allocation.html index fd6c29a29..733b3ea7d 100644 --- a/concept/allocation.html +++ b/concept/allocation.html @@ -578,7 +578,7 @@

4.4 Example

The following is an example of an optimization problem for the example shown here:

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+
Code 
using Ribasim
@@ -600,27 +600,27 @@ 
println(p.allocation.allocation_models[1].problem)
-
Min F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²
+
Min F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²
 Subject to
- flow_conservation[Basin #2] : -F[(Basin #2, UserDemand #3)] + F[(UserDemand #3, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] = 0
- flow_conservation[Basin #5] : -F[(Basin #5, UserDemand #6)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] = 0
- flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0
- flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #8)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0
+ flow_conservation[Basin #2] : -F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] - F[(Basin #2, UserDemand #3)] + F[(UserDemand #3, Basin #2)] + F[(FlowBoundary #1, Basin #2)] = 0
  flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0
+ flow_conservation[LinearResistance #4] : F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] - F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] = 0
+ flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] = 0
+ flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, Terminal #8)] = 0
  source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
  source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
  source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
- F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
- F[(Basin #5, UserDemand #6)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
- F[(LinearResistance #4, Basin #5)] ≥ 0
- F[(Basin #5, LinearResistance #4)] ≥ 0
- F[(FlowBoundary #1, Basin #2)] ≥ 0
- F[(UserDemand #6, Basin #5)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
+ F[(UserDemand #6, Basin #5)] ≥ 0
+ F[(LinearResistance #4, Basin #5)] ≥ 0
+ F[(Basin #5, LinearResistance #4)] ≥ 0
  F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
+ F[(Basin #5, UserDemand #6)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
+ F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
diff --git a/reference/node/basin.html b/reference/node/basin.html index bc4d54234..6637edc1b 100644 --- a/reference/node/basin.html +++ b/reference/node/basin.html @@ -476,7 +476,7 @@

1.2.1 Interpolation

At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.

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Code 
import numpy as np
@@ -675,7 +675,7 @@ 

 
1.4.1.1 Level to area

 
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.

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 Code
 
fig, ax = plt.subplots()
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\[
     S(h) = \int_{h_0}^h A(h')\text{d}h'.
 \]

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+

 

 Code
 
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -803,7 +803,7 @@ 

 
1.4.1.3 Interactive basin example

 
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.

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+

 

 Code
 
import plotly.graph_objects as go
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fig.show()

 

 

-