| Title: | Predictions of experimentally observed stochastic ground vibrations induced by blasting |
|---|
| Authors: | ID Kostić, Srđan (Author)
ID Perc, Matjaž (Author)
ID Vasović, Nebojša (Author)
ID Trajković, Slobodan (Author) |
|---|
| Files: |  PLoS_ONE_2013_Kostic_et_al._Predictions_of_Experimentally_Observed_Stochastic_Ground_Vibrations_Induced_by_Blasting.PDF (1,45 MB)
MD5: 5EACDAE7CF060DB21B614C2366807D09
 http://dx.plos.org/10.1371/journal.pone.0082056
|
|---|
| Language: | English |
|---|
| Work type: | Article |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: | FNM - Faculty of Natural Sciences and Mathematics
|
|---|
| Abstract: | In the present paper, we investigate the blast induced ground motion recorded at the limestone quarry “Suva Vrela” near Kosjerić, which is located in the western part of Serbia. We examine the recorded signals by means of surrogate data methods and a determinism test, in order to determine whether the recorded ground velocity is stochastic or deterministic in nature. Longitudinal, transversal and the vertical ground motion component are analyzed at three monitoring points that are located at different distances from the blasting source. The analysis reveals that the recordings belong to a class of stationary linear stochastic processes with Gaussian inputs, which could be distorted by a monotonic, instantaneous, time-independent nonlinear function. Low determinism factors obtained with the determinism test further confirm the stochastic nature of the recordings. Guided by the outcome of time series analysis, we propose an improved prediction model for the peak particle velocity based on a neural network. We show that, while conventional predictors fail to provide acceptable prediction accuracy, the neural network model with four main blast parameters as input, namely total charge, maximum charge per delay, distance from the blasting source to the measuring point, and hole depth, delivers significantly more accurate predictions that may be applicable on site. We also perform a sensitivity analysis, which reveals that the distance from the blasting source has the strongest influence on the final value of the peak particle velocity. This is in full agreement with previous observations and theory, thus additionally validating our methodology and main conclusions. |
|---|
| Keywords: | blasting, vibrations, surrogate data, deterministic chaos, stochasticity |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Year of publishing: | 2013 |
|---|
| Number of pages: | str. 1-13 |
|---|
| Numbering: | Letn. 8, št. 12 |
|---|
| PID: | 20.500.12556/DKUM-66290  |
|---|
| ISSN: | 1932-6203 |
|---|
| UDC: | 53 |
|---|
| ISSN on article: | 1932-6203 |
|---|
| COBISS.SI-ID: | 20244488 |
|---|
| DOI: | 10.1371/journal.pone.0082056 |
|---|
| NUK URN: | URN:SI:UM:DK:ZDNGLHW5 |
|---|
| Publication date in DKUM: | 19.06.2017 |
|---|
| Views: | 1069 |
|---|
| Downloads: | 342 |
|---|
| Metadata: |    |
|---|
| Categories: | Misc.
|
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
