Loads Module

The loads module contains a set of functions to calculate quantities of interest for mechanical loads assessments.

Note

The names of the functions below are of the convention path.path.function. Only the function name is used when calling the function in MATLAB. For example, to call on mhkit.wave.io.read_NDBC_file simply use read_NDBC_file.

General

The graphics submodule contains functions to compute loads related metrics.

Functions

Description

bin_statistics

Bins calculated statistics against data signal (or channel) according to IEC TS 62600-3:2020 ED1.

damage_equivalent_load

Calculates the damage equivalent load of a single data signal (or channel) based on IEC TS 62600-3:2020 ED1.

blade_moments

Transfer function for deriving blade flap and edge moments using blade matrix.
mhkit.loads.general.damage_equivalent_load(data_signal, m, options)

Calculates the damage equivalent load of a single data signal (or channel) based on IEC TS 62600-3:2020 ED1. 4-point rainflow counting algorithm from fatpack module is based on the following resources:

  • C. Amzallag et. al. Standardization of the rainflow counting method for fatigue analysis. International Journal of Fatigue, 16 (1994) 287-293 ISO 12110-2, Metallic materials - Fatigue testing - Variable amplitude fatigue testing.

  • G. Marsh et. al. Review and application of Rainflow residue processing techniques for accurate fatigue damage estimation. International Journal of Fatigue, 82 (2016) 757-765

Parameters:

  • data_signal (vector) – Data signal being analyzed

  • m (double or int) – Fatigue slope factor of material

  • bin_num (int (optional)) – Number of bins for rainflow counting method (minimum=100) to call: get_DELs(data,chan_info,”bin_num”,binNum)

  • data_length (double or int (optional)) – Length of data in sec. Default for 1Hz is 600 seconds for 10min data to call: get_DELs(data,chan_info,”data_length”,t)

Returns:

DEL (Structure) – Damage equivalent load of signal

mhkit.loads.general.bin_statistics(data, bin_against, bin_edges, varargin)

Bins calculated statistics against data signal (or channel) according to IEC TS 62600-3:2020 ED1.

Parameters:

  • data (Strucutre or Table with handles- data.data and data.time) – data.data contains a vector or matrix containing time-series statistics of variables

  • bin_against (vector) – Data signal to bin data against (ie. current speed)

  • bin_edges (vector) – Bin edges with consistent step size.

  • data_signal (cell array (optional)) – List of data signal(s) to bin, default = all data signals

Returns:

bins (structure)

bins.averages = means of each bin

bins.std = standard deviation of each bin

mhkit.loads.general.blade_moments(blade_coefficients, flap_offset, flap_raw, edge_offset, edge_raw)

Transfer function for deriving blade flap and edge moments using blade matrix.

Parameters:

  • blade_coefficients (vector) – Derived blade calibration coefficients listed in order of D1, D2, D3, D4

  • flap_offset (double or int) – Derived offset of raw flap signal obtained during calibration process

  • flap_raw (vector) – Raw strain signal of blade in the flapwise direction

  • edge_offset (double or int) – Derived offset of raw edge signal obtained during calibration process

  • edge_raw (vector) – Raw strain signal of blade in the edgewise direction

Returns:

  • M_flap (vector) – Blade flapwise moment in SI units

  • M_edge (vector) – Blade edgewise moment in SI units

Graphics

The graphics submodule contains functions to plot loads data and related metrics. The functions are designed to work in parallel with the general submodule.

Functions

Description

plot_statistics

Plot showing standard raw statistics of variable

plot_bin_statistics

Plot showing standard binned statistics of single variable
mhkit.loads.graphics.plot_bin_statistics(bin_centers, bin_mean, bin_max, bin_min, bin_mean_std, bin_max_std, bin_min_std, options)

Plot showing standard binned statistics of single variable

Parameters:

  • bin_centers (vector) – x-axis bin center values

  • bin_mean (vector) – Binned mean statistical values of variable

  • bin_max (vector) – Binned max statistical values of variable

  • bin_min (vector) – Binned min statistical values of variable

  • bin_mean_std (vector) – Standard deviations of mean binned statistics

  • bin_max_std (vector) – Standard deviations of max binned statistics

  • bin_min_std (vector) – Standard deviations of min binned statistics

  • xlabel (string (optional)) – x-axis lable for the plot to call: binplotter(bcenters,bmean,bmax,bmin,bstdmean,bstdmax,bstdmin,”xlable”,xlable)

  • ylabel (string (optional)) – y-axis lable for the plot to call: binplotter(bcenters,bmean,bmax,bmin,bstdmean,bstdmax,bstdmin,”ylable”,ylable)

  • title (string (optional)) – title for the plot to call: binplotter(bcenters,bmean,bmax,bmin,bstdmean,bstdmax,bstdmin,”title”,title)

  • savepath (string (optional)) – path and filename to save figure. to call: binplotter(bcenters,bmean,bmax,bmin,bstdmean,bstdmax,bstdmin,”savepath”,savepath)

Returns:

figure (figure)

mhkit.loads.graphics.plot_statistics(x, y_mean, y_min, y_max, options)

Plot showing standard raw statistics of variable

Parameters:

  • x (vector) – vector of x-axis values

  • y_mean (vector) – Vector of mean values

  • y_max (vector) – Vector of max values

  • y_min (vector) – Vector of min values

  • y_stdev (vector (optional)) – Vector of stand drviations to call: statplotter(x,y_mean,y_max,y_min,”y_stdev”,vstdev)

  • xlabel (string (optional)) – x-axis lable for the plot to call: statplotter(x,y_mean,y_max,y_min,”xlable”,xlable)

  • ylabel (string (optional)) – y-axis lable for the plot to call: statplotter(x,y_mean,y_max,y_min,”ylable”,ylable)

  • title (string (optional)) – title for the plot to call: statplotter(x,y_mean,y_max,y_min,”title”,title)

  • savepath (string (optional)) – path and filename to save figure. to call: statplotter(x,y_mean,y_max,y_min,”savepath”,savepath)

Returns:

figure (figure) – scatter plot of statistics