From bd0d9158b431db41f4012638d7fc4b26f7d62c06 Mon Sep 17 00:00:00 2001 From: visr Date: Fri, 30 Aug 2024 07:38:32 +0000 Subject: [PATCH] deploy: 78149308b800d7843fed2e7890cc813e1c62b1e4 --- concept/allocation.html | 22 +++++++++--------- .../figure-html/cell-18-output-1.png | Bin 87048 -> 87112 bytes .../figure-html/cell-19-output-1.png | Bin 113521 -> 113351 bytes .../figure-html/cell-56-output-1.png | Bin 111236 -> 111240 bytes .../figure-html/cell-57-output-2.png | Bin 61190 -> 61162 bytes .../figure-html/cell-68-output-1.png | Bin 44258 -> 44271 bytes 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 +- 13 files changed, 25 insertions(+), 25 deletions(-) diff --git a/concept/allocation.html b/concept/allocation.html index 2f99c3d26..d42c3a268 100644 --- a/concept/allocation.html +++ b/concept/allocation.html @@ -574,7 +574,7 @@

4.4 Example

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

-
+
Code
using Ribasim
@@ -599,25 +599,25 @@ 

Min F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²
 Subject to
- F[(FlowBoundary #1, Basin #2)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
  F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
+ F[(UserDemand #6, Basin #5)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
+ F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
- F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
- F[(Basin #5, UserDemand #6)] ≥ 0
- F[(UserDemand #6, Basin #5)] ≥ 0
  F[(LinearResistance #4, Basin #5)] ≥ 0
  F[(Basin #5, LinearResistance #4)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
+ F[(Basin #5, UserDemand #6)] ≥ 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
- flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #8)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0
- flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(UserDemand #3, Basin #2)] = 0
- flow_conservation[Basin #5] : -F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] + F[(UserDemand #6, Basin #5)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] = 0
+ source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 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[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #8)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0
  flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0
+ flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, UserDemand #6)] = 0
+ flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0
 

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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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import numpy as np
@@ -671,7 +671,7 @@ 

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()
@@ -754,7 +754,7 @@ 

\[ S(h) = \int_{h_0}^h A(h')\text{d}h'. \]

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storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@ 

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
@@ -914,9 +914,9 @@ 

fig.show()

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