Data for "Distribution of Time Scales Induces Slow Dynamics and Elastic Hysteresis in Sandstones: A Model of Non-equilibrium Strain"

The experimental data are obtained using Dynamic acoustoelastic testing on a sandstone sample. The experimental setup and signal processing are described in "Distribution of Time Scales Induces Slow Dynamics and Elastic Hysteresis in Sandstones: A Model of Non-equilibrium Strain" by Zeman, Kober and Scalerandi (2025).

DAET 2024-03-13

Use numpy (python) to open npz files.

param.npz: measurement parameters
    scp_channels: oscilloscope chanels measured
        pulse_s_tx: shear pulse generator
        pulse_s_rx: shear pulse receiver
        cnd_tx: conditioning channel generator
        cnd_rxv: endpoint velocity (vibrometer signal)
        cnd_sa: surface velocity on side (vibrometer signal), see msV to convert volts to m/s

pls_indexes.npz: time data, basic signal processing
    index: number of signal
    time_ns: measruement time in ns
    (signal)_pp: peak-to-peak amplitude
    (signal)_rms: signal rms
    (signal)_maxabs: signal maximum
    process: current process, preconditioning / conditioning / relaxation / chirp (resonance frequency estimation)
    cnd_pid: conditioning index

pls_velocity.npz: velocity variations
    dt_s_rx/tx: delay on receiver / generator in samples
    dvv_s: relative velocity variation
    s_rx/tx_pp/rms: peak-to-peak amplitude of pulse obtained using polynomial fit of extrema

cnd_indexes.npz: conditioning parameters
    index: conditioning index, see cnd_pid in pls
    amplitude: amplitude in volts
    f: frequency in Hz
    process: conditioning / chirp
    time_ns: time in ns
    duration: duration in seconds
    (signal)_pp/rms/maxabs: signal peak-to-peak amplitude / rms / maximum

pls_pulses.npz: settings for velocity estimation from pulses
   s_rx/tx_ref: reference signal (averaged first signals)
   s_rx/tx_start/end: pulse window
signal processing: 1) detrend and high pass filter (filt_s_sos) 2) raw correlation + window adjustement 3) correlation with subsample precision (quadratic fit of maximum)