ucla-geotech-tools 1.0.5

A collection of software tools developed by the UCLA geotechnical group

ucla_geotech_tools

This ucla_geotech_tools module contains software tools developed by the UCLA geotechnical engineering group. It consists of the following packages:

• auto_fchp
• response_spectrum
• ipyconsol
• 'random_field'

Installation

To install the ucla_geotech_tools module

pip install ucla_geotech_tools

To install a package from the module (e.g., auto_fchp)

pip install ucla_geotech_tools.auto_fchp

auto_fchp

Return the high-pass corner frequency value that stabilizes the displacement of a ground motion record.

The high-pass corner frequency, f_chp, is selected to satisfy two objectives:

1. The amplitude of a polynomial fit to the filtered displacement record divided by the amplitude of the filtered displacement record is within a tolerance of a specified target.
2. The amplitude of the initial portion of the displacement record before the p-wave arrival divided bythe amplitude of the filtered displacement record is within a tolerance of a specified target.

The value of f_chp is computed numerically using the Scipy package scipy.optimize.ridder(). Two initial values of f_chp are provided that bracket the root, and the Scipy package solves for the root that minimizes the objective function. The tolerance is on the value of f_chp, not on the value of the residual (i.e., xtol in optimize.ridder).

A value of f_chp is obtained first to satisfy objective 1. Objective 2 is optional, and if it is applied, the value of f_chp from objective 1 is checked against objective 2. If the residual from objective 2 is less than or equal to zero, f_chp is set equal to the value from objective 1. Otherwise, iterations are performed to satisfy objective 2.

Functions

get_fchp(**kwargs)

Return the high-pass corner frequency

Keyword Args:

• *dt : time step in seconds (float, required)
• *acc : acceleration array in L/s/s, where L is length (Numpy array dtype=float, required)
• target: desired ratio of polynomial fit amplitude to displacement amplitude (default=0.02)
• tol: tolerance for fchp (default=0.001)
• poly_order: order of polynomial to fit to filtered displacement record (default=6)
• maxiter: maximum number of iterations (default=30)
• fchp_min: minimum frequency in Hz to consider for fchp (default=0.001)
• fchp_max: maximum frequency in Hz to consider for fchp (default=0.5)
• tukey_alpha: alpha parameter for scipy.signal.windows.tukey (default=0.05)
• apply_disp_ratio: flag to indicate whether to apply objective 2 (default=0)
• disp_ratio_time: duration in seconds of the initial portion of the record before the p-wave arrival (default=30)
• disp_ratio_target: target ratio of amplitude of initial portion of displacement record to amplitude of displacement record

get_residual1(fchp, *args):

Return the residual defined as disp_fit/disp_filt - target.

Args:

• fchp: High-pass corner frequency (float)
• Fdisp: Fourier coefficients of displacement record (Numpy array, dtype=complex)
• time = time values (Numpy array, dtype=float)
• poly_order = Order of polynomial to fit to filtered displacement (float)
• target = Desired ratio of polynomial fit amplitude to displacement signal amplitude (float)
• freq = Numpy array containing frequency values

Computed variables:

• filt = Coefficients of 5th order Butterworth filter
• Fdisp_filt = Numpy array containing Fourier coefficients of filtered displacement record
• disp_filt = Numpy array containing filtered displacement record
• coef = Coefficients of polynomial fit to displacement record
• disp_fit = Numpy array containing polynomial fit ordinates at each time

get_residual2(fchp, *args):

Returns the residual defined as disp_init/disp - target.

Args:

• fchp = High-pass corner frequency
• Fdisp = Numpy array containing Fourier coefficients of displacement record
• time = Numpy array containing time values
• disp_time = Duration of initial portion of record before p-wave arrival
• disp_target = Desired ratio of amplitude of initial portion of displacement record to amplitude of displacement record
• freq = Numpy array containing frequency values

Computed variables:

• filt = Coefficients of 5th order Butterworth filter
• Fdisp_filt = Numpy array containing Fourier coefficients of filtered displacement record
• disp_filt = Numpy array containing filtered displacement record

response_spectrum

response_spectrum computes a psuedo-acceleration response spectrum from an input ground motion or set of ground motions sampled at a constant frequency. Calculates are performed in the frequency domain by

1. taking the Fourier transform of the input motion(s)
2. multiplying by the transfer function for computing the motion of a single-degree-of-freedom (SDOF) oscillator with natural period T and damping D
3. computing the peak acceleration amplitude for the SDOF oscillator
4. repeating steps 2 and 3 for a range of user-specified periods

Functions

get_response_spectrum(**kwargs)

Returns a Numpy array containing response spectra

Keyword Args:

• *motions = Numpy array (M x N) containing acceleration data, where M is the number of motions and N is the number of data points in each motion. All motions must have the same number of data points. Python lists are not allowed; only Numpy arrays (required)
• *dt = time step in seconds (required)
• D = damping (default = 0.05)
• T = array of natural periods (default = array used for NGAwest2 project)
• zeropad = 1: apply zero padding to speed up FFT operation, 0: do not pad with zeros (default = 1)

get_ngawest2_T()

Returns a Numpy array containing NGAWest2 natural periods

ipyconsol

Documentation coming soon

random_field

Documentation coming soon