1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022018 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 


22  using System;


23  using System.Collections.Generic;


24  using System.Linq;


25  using HeuristicLab.Random;


26 


27  namespace HeuristicLab.Problems.Instances.DataAnalysis {


28  class RocketFuelFlow : ArtificialRegressionDataDescriptor {


29  public override string Name { get { return "Rocket Fuel Flow m_dot = p0 A / sqrt(T0) * sqrt(γ/R (2/(γ+1))^((γ+1) / (γ1)))"; } }


30 


31  public override string Description {


32  get {


33  return "A full description of this problem instance is given in: " + Environment.NewLine +


34  "Chen Chen, Changtong Luo, Zonglin Jiang, \"A multilevel block building algorithm for fast " +


35  "modeling generalized separable systems\", Expert Systems with Applications, Volume 109, 2018, " +


36  "Pages 2534 https://doi.org/10.1016/j.eswa.2018.05.021. " + Environment.NewLine +


37  "Function: m_dot = p0 A / sqrt(T0) * sqrt(γ/R (2/(γ+1))^((γ+1) / (γ1)))" + Environment.NewLine +


38  "with p0 ∈ [4e5 Pa, 6e5 Pa]," + Environment.NewLine +


39  "A ∈ [0.5m², 1.5m²]," + Environment.NewLine +


40  "T0 ∈ [250°K, 260°K]," + Environment.NewLine +


41  "γ=1.4 and R=287 J/(kg*K)" + Environment.NewLine +


42  "The factor sqrt(γ/R (2/(γ+1))^((γ+1) / (γ1))) is constant as γ and R are constants.";


43  }


44  }


45 


46  protected override string TargetVariable { get { return "m_dot"; } }


47  protected override string[] VariableNames { get { return new string[] { "p0", "A", "T0", "m_dot" }; } }


48  protected override string[] AllowedInputVariables { get { return new string[] { "p0", "A", "T0" }; } }


49  protected override int TrainingPartitionStart { get { return 0; } }


50  protected override int TrainingPartitionEnd { get { return 100; } }


51  protected override int TestPartitionStart { get { return 100; } }


52  protected override int TestPartitionEnd { get { return 200; } }


53 


54  public int Seed { get; private set; }


55 


56  public RocketFuelFlow() : this((int)System.DateTime.Now.Ticks) { }


57 


58  public RocketFuelFlow(int seed) {


59  Seed = seed;


60  }


61 


62  protected override List<List<double>> GenerateValues() {


63  var rand = new MersenneTwister((uint)Seed);


64 


65  List<List<double>> data = new List<List<double>>();


66  var p0 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 4.0e5, 6.0e5).ToList();


67  var A = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.5, 1.5).ToList();


68  var T0 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 250.0, 260.0).ToList();


69 


70  List<double> m_dot = new List<double>();


71  data.Add(p0);


72  data.Add(A);


73  data.Add(T0);


74  data.Add(m_dot);


75  double R = 287.0;


76  double γ = 1.4;


77  var c = Math.Sqrt(γ / R * Math.Pow(2 / (γ + 1), (γ + 1) / (γ  1)));


78  for (int i = 0; i < p0.Count; i++) {


79  double m_dot_i = p0[i] * A[i] / Math.Sqrt(T0[i]) * c;


80  m_dot.Add(m_dot_i);


81  }


82 


83  return data;


84  }


85  }


86  }

