diff --git a/concept/allocation.html b/concept/allocation.html index d56eedc8c..af5f202d1 100644 --- a/concept/allocation.html +++ b/concept/allocation.html @@ -584,7 +584,7 @@

4.4 Example

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

-
+
Code 
using Ribasim
@@ -607,27 +607,27 @@ 
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
  source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
- source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
  source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 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
+ source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
+ flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0
  flow_conservation[Terminal #1] : F[(TabulatedRatingCurve #7, Terminal #1)] = 0
  flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #1)] + F[(Basin #5, TabulatedRatingCurve #7)] = 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
- 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
- F[(UserDemand #6, Basin #5)] ≥ 0
- F[(FlowBoundary #1, Basin #2)] ≥ 0
- F[(LinearResistance #4, Basin #5)] ≥ 0
- F[(Basin #5, LinearResistance #4)] ≥ 0
+ flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(UserDemand #6, Basin #5)] = 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
+ F[(UserDemand #3, Basin #2)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
  F[(TabulatedRatingCurve #7, Terminal #1)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(LinearResistance #4, Basin #5)] ≥ 0
+ F[(Basin #5, LinearResistance #4)] ≥ 0
+ F[(Basin #5, UserDemand #6)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
  F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
  F[(Basin #2, UserDemand #3)] ≥ 0
- F[(Basin #5, UserDemand #6)] ≥ 0
+ F[(UserDemand #6, Basin #5)] ≥ 0
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Here \(p > 0\) is the threshold value which determines the interval \([0,p]\) of the smooth transition between \(0\) and \(1\), see the plot below.

-
+
Code 
import numpy as np
diff --git a/reference/node/discrete-control.html b/reference/node/discrete-control.html
index 3c6183a56..cc838dc56 100644
--- a/reference/node/discrete-control.html
+++ b/reference/node/discrete-control.html
@@ -386,7 +386,7 @@ 
DiscreteControl

 
 
 
Set parameters of other nodes based on model state conditions (e.g. Basin level). The table below shows which parameters are controllable for a given node type.

-

+

 

 Code
 
using Ribasim
diff --git a/reference/test-models.html b/reference/test-models.html
index 07b620d55..b18ccc1e1 100644
--- a/reference/test-models.html
+++ b/reference/test-models.html
@@ -346,7 +346,7 @@ 
Test models

 
 
 
Ribasim developers use the following models in their testbench and in order to test new features.

-

+

 

 Code
 
import ribasim_testmodels
diff --git a/reference/validation.html b/reference/validation.html
index a91cb2e0e..5b3e1d91c 100644
--- a/reference/validation.html
+++ b/reference/validation.html
@@ -356,7 +356,7 @@ 
Validation

 

 
1 Connectivity

 
In the table below, each column shows which node types are allowed to be downstream (or ‘down-control’) of the node type at the top of the column.

-

+

 

 Code
 
using Ribasim
@@ -706,7 +706,7 @@ 
1 Connectivity
 
2 Neighbor amounts

 
The table below shows for each node type between which bounds the amount of in- and outneighbors must be, for both flow and control edges.

-

+

 

 Code
 
flow_in_min = Vector{String}()
diff --git a/search.json b/search.json
index 10be954f7..03d75e9aa 100644
--- a/search.json
+++ b/search.json
@@ -99,7 +99,7 @@
     "href": "concept/allocation.html#example",
     "title": "Allocation",
     "section": "4.4 Example",
-    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, NodeID(:FlowBoundary, 1, p), NodeID(:Basin, 2, p), 1.0)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²\nSubject to\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n 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\n flow_conservation[Terminal #1] : F[(TabulatedRatingCurve #7, Terminal #1)] = 0\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #1)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0\n 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\n 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\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, Terminal #1)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0",
+    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, NodeID(:FlowBoundary, 1, p), NodeID(:Basin, 2, p), 1.0)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²\nSubject to\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0\n flow_conservation[Terminal #1] : F[(TabulatedRatingCurve #7, Terminal #1)] = 0\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, Terminal #1)] + F[(Basin #5, TabulatedRatingCurve #7)] = 0\n flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(UserDemand #6, Basin #5)] = 0\n 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\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, Terminal #1)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(UserDemand #6, Basin #5)] ≥ 0",
     "crumbs": [
       "Concepts",
       "Implementation",