source: stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Physics/FluidDynamics.cs @ 17174

Last change on this file since 17174 was 17174, checked in by mkommend, 2 months ago

#3014: Merged r17092, r17093, r17094, r17150 into stable.

File size: 4.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Random;
27
28namespace HeuristicLab.Problems.Instances.DataAnalysis {
29  public class FluidDynamics : ArtificialRegressionDataDescriptor {
30    public override string Name { get { return "Spinning cylinder flow Ψ = V_∞ r sin(θ) (1 - R²/r²) + Γ/(2 π) ln(r/R)"; } }
31
32    public override string Description {
33      get {
34        return "A full description of this problem instance is given in: " + Environment.NewLine +
35          "Chen Chen, Changtong Luo, Zonglin Jiang, \"A multilevel block building algorithm for fast " +
36          "modeling generalized separable systems\", Expert Systems with Applications, Volume 109, 2018, " +
37          "Pages 25-34 https://doi.org/10.1016/j.eswa.2018.05.021. " + Environment.NewLine +
38          "Function: Ψ = V_∞ r sin(θ) (1 - R²/r²) + Γ/(2 π) ln(r/R)" + Environment.NewLine +
39          "with uniform stream velocity V_∞ ∈ [60 m/s, 65 m/s]," + Environment.NewLine +
40          "angle for polar coordinate vector field θ ∈ [30°, 40°]," + Environment.NewLine +
41          "radius for polar coordinate vector field r ∈ [0.5m, 0.8m]," + Environment.NewLine +
42          "radius of cylinder R ∈ [0.2m, 0.5m]," + Environment.NewLine +
43          "vortex strength (induced by spinning) Γ ∈ [5 m²/s, 10 m²/s]" + Environment.NewLine +
44          "Note: the definition deviates from the definition used in the source above because here we have r > R meaning we want to calculate the flow _outside_ of the cylinder.";
45      }
46    }
47
48    protected override string TargetVariable { get { return "Ψ"; } }
49    protected override string[] VariableNames { get { return new string[] { "V_∞", "θ", "r", "R", "Γ", "Ψ", "Ψ_noise" }; } }
50    protected override string[] AllowedInputVariables { get { return new string[] { "V_∞", "θ", "r", "R", "Γ" }; } }
51    protected override int TrainingPartitionStart { get { return 0; } }
52    protected override int TrainingPartitionEnd { get { return 100; } }
53    protected override int TestPartitionStart { get { return 100; } }
54    protected override int TestPartitionEnd { get { return 200; } }
55
56    public int Seed { get; private set; }
57
58    public FluidDynamics() : this((int)System.DateTime.Now.Ticks) { }
59
60    public FluidDynamics(int seed) {
61      Seed = seed;
62    }
63
64    protected override List<List<double>> GenerateValues() {
65      var rand = new MersenneTwister((uint)Seed);
66
67      List<List<double>> data = new List<List<double>>();
68      var V_inf = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 60.0, 65.0).ToList();
69      var th = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 30.0, 40.0).ToList();
70      var r = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.5, 0.8).ToList();
71      var R = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.2, 0.5).ToList();
72      var G = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5, 10).ToList();
73
74      var Psi = new List<double>();
75      var Psi_noise = new List<double>();
76
77      data.Add(V_inf);
78      data.Add(th);
79      data.Add(r);
80      data.Add(R);
81      data.Add(G);
82      data.Add(Psi);
83      data.Add(Psi_noise);
84
85      for (int i = 0; i < V_inf.Count; i++) {
86        var th_rad = Math.PI * th[i] / 180.0;
87        double Psi_i = V_inf[i] * r[i] * Math.Sin(th_rad) * (1 - (R[i] * R[i]) / (r[i] * r[i])) +
88                     (G[i] / (2 * Math.PI)) * Math.Log(r[i] / R[i]);
89        Psi.Add(Psi_i);
90      }
91
92      var sigma_noise = 0.05 * Psi.StandardDeviationPop();
93      Psi_noise.AddRange(Psi.Select(md => md + NormalDistributedRandom.NextDouble(rand, 0, sigma_noise)));
94
95      return data;
96    }
97  }
98}
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