Becca scrutineering review

.gitignore

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+*.pyc
+.vscode/*
+.DS_Store
+src/modules/__pycache__/*
+data/mesh_convergence/convergence.csv
+data/mesh_convergence/convergence.csv
+data/sensitivities/*
+src/__init__.py
+src/modules/__init__.py
+data/sensitivities/0      3.629951
+1      0.100001
+2      5.223716
+3     17.742484
+4    -16.034721
+5      5.502716
+6     14.803371
+7     12.277340
+8      5.836918
+9     28.595590
+10     0.051935
+11     5.499162
+Name: 232, dtype: float64_total_SI_convergece.csv
+data/sensitivities/first_3.6.csv
+data/sensitivities/first_sensitivity.csv
+data/sensitivities/second_3.6.csv
+data/sensitivities/second_sensitivity.csv
+data/sensitivities/total_3.6.csv
+data/sensitivities/total_sensitivity.csv
+data/sensitivities/200_first.csv
+src/post_pro/plots/*

.gitmodules

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+[submodule "sea-lab-utils"]
+	path = sea-lab-utils
+	url = https://github.com/symbiotic-engineering/sea-lab-utils.git

README

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+Multi-Objective Multidisciplinary Optimization of Wave Energy Converter Array Layout and Controls
+Authors: Kapil Khanal, Nate DeGoede, Olivia Vitale, Maha Haji,
+
+
+- Multidisciplinary formulation to optimize the configuration of the array of Wave energy converter is presented.
+- Optimal controls for each Wave energy converter within the layout.
+- Regression model for interpretation of the trade-off between objectives for optimal designs prompts additional analysis.
+- Post optimality global sensitivity analysis of a set of optimal designs reveals that the expected variance in optimal LCOE (minimized) is very sensitive to the variance in wave frequency $(\omega)$ and interest rate.
+
+
+
+PROJECT STRUCTURE
+
+├── __init__.py
+├─data <- All relevant data.
+├──── experiments <- Single objective experiments.
+│   ├─ grid.pdf,line.pdf,random.pdf
+│──── mesh_convergence <- data from mesh convergence
+│   ├─ convergence.csv
+│──── paretos <- dominant designs objective and dvs
+│   ├─ FinaldomDesign.csv , FinaldomObjective
+│──── sensitivities
+│   ├─ total.csv,first.csv,second.csv
+├── notebooks <- nominal run --not required
+├── src <- Main source code for MDO
+│   ├── modules <- Each python file is a disciplinary modules.
+│     ├── distances.py <- To find maximum and minimum spacing in array.
+│     ├── dynamics_contrrols.py <- Calculate motion and power of the WEC.
+│     ├── econ.py <- Calculates Capex / Opex and LCOE model.
+│     ├── hydro_terms.py <- Get all the hydro terms. (A,B,F,C,M)
+│     ├── model_nWECs.py <- Utility functions to call the multidisciplinary analysis (MDA)
+│     ├── wec_array_initialization.py <- Utility function to get array of bodies and their neighbors if required.
+│   ├── optimization_interfaces
+│     ├── multi_objective_opt.py <- Calls the optimizer for multi Objectives [J1,J2]
+│     ├── single_objective_opt.py <- Calls the optimizer for single Objective at a time.
+│   ├── post_pro
+│     ├── plots
+│       ├── *.pdf <- contains all the figures.
+│     ├── mesh_convergence.py <- Performs mesh convergence for the design 
+│     ├── pareto_analysis.py <- Ad-hoc regression model for pareto design analysis
+│     ├── plot_design.py <- plots any designs
+│     ├── plot_pareto.py <- plots the pareto designs. 
+│     ├── plot_qfactor.py <- plots the qfactor for pareto designs
+│     ├── plot_sensitivity.py <- plots the sensitivity of the design to the parameters
+│     ├── q.py <- Calculates thee q-factor
+│     ├── sensitivity.py <- Calculates the sensitivity upto second order.
+│     ├── wave_field.py <- plots the wave_field for optimal designs 
+├─ requirement.txt <- All the pacakges.
+├─ environment.yml <- All the pacakges.
+
+
+
+ Note: Run code from src folder.

data/experiments/grid

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+"[ 9.98266494e+00  1.11091538e-01  5.95331100e+00  4.69333468e+02
+ -3.29995515e+02  5.91959873e+00  4.86152564e+02  1.77256214e+02
+  6.12891918e+00  3.51729113e+01  1.84925492e+02  6.02316413e+00]",[0.23373015]

data/experiments/line

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+"[ 9.84347267e+00  1.00423880e-01  6.16863211e+00  2.75571473e+02
+ -3.57408897e+02  6.01377418e+00 -3.14856237e+02 -2.73417677e+02
+  6.06350830e+00 -5.42394882e+01 -2.85793040e+02  6.29323481e+00]",[0.20782667]

data/experiments/random

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+"[ 9.98351142e+00  1.01277004e-01  6.12722078e+00  4.28642363e+02
+ -3.98138335e+02  6.26818100e+00 -2.09242767e+02  2.68234131e+02
+  5.96784344e+00 -3.39767380e+02  2.09554519e+02  6.16570801e+00]",[0.22149867]