Shear Wave Velocity Measurements in Tropical Peat Using In-house Device
Bibliographic record
Abstract
Many people in the construction industry will agree that peat is a problematic material due to its compressibility behaviour. However, construction on these areas are inevitable because of the scarcity in space and suitable land for development. Hence, there is a need for proper in-situ testing on soil properties before any construction work can be carried out in peat. Shear wave (S-wave) velocity (Vs ) used to compute the small strain shear modulus, (Go ) which is an essential parameter to design structures in earthquake and vibration prone areas. The most versatile method to assess is by measuring shear wave propagation through soil samples using bender elements tests (BET). Currently, BET is limited to laboratory environments, which can be time consuming and expensive. Therefore, a portable device of BET for peat has been proposed in this research which is simple to use and economical. The proposed setup consists of an oscilloscope, digital multimeter, signal generator, signal amplifier, direct current generator and a pair of piezoelectric bender elements. Peak-to-peak method from time domain (TD) technique is implemented as the method to analyse shear waves. To validate the function of the proposed device, different types of soil samples including Ottawa sand, Kaolin S300, Silty loam, Hemic, and Fibric peat were prepared. The peat samples for this study were collected from Pekan and Maran districts in Pahang, Malaysia. With a suitable frequency input from the sine wave generated, the Vs determined from the device was used to compute Go. Results show there is only a less than 10% error in when it was compared with the typical values of tropical peat. The proposed device is also effective to differentiate the type of soil sample when tested. In summary, the proposed in-house device can be used as an indicator and to find out the initial value of Vs and Go in tropical peat soil.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".