Improved Evaluation of Bender Element Testing for Different Confinement Stress Levels
Bibliographic record
Abstract
Accurate material characterization over time is crucial for the safety, efficiency, and sustainability of energy and environmental projects, as well as infrastructure resilience. This is particularly important in nuclear power plants and energy geo-structures. The Bender Element (BE) test is a non-destructive technique (NDT) used to assess small-strain properties of materials, including Shear Wave Velocity (Vs) and Shear Modulus (Gmax). BEs, made of piezoelectric materials, operate by applying an excitation voltage to a transmitter (Tx), generating shear waves that propagate through a specimen and are detected by a receiver (Rx). Small-strain properties are determined from the computed Vs. Despite standardized guidelines (e.g., ASTM D8295-19) and widespread BE applications in soil characterization, challenges persist in implementation and data interpretation. A major issue is the accurate determination of S-wave arrival time, often complicated by interference from P-waves and reflected waves, leading to measurement inaccuracies. A key knowledge gap exists in understanding BE interactions with different materials under varying confinement stresses. This research evaluates BE behavior under diverse conditions, proposing alternative methods to verify Vs measurements. The study comprises three phases: experimental testing, numerical modeling, and theoretical equation evaluation. BE lab tests were conducted using transparent soil under varying confinement stress, incorporating laser vibrometry to measure displacements on BE plates despite surrounding soil. Signal responses were analyzed in both time and frequency domains. Numerical modeling employs a novel finite difference simulation in FLAC3D (Itasca 2023), calibrated with experimental results. Additionally, the standard equation for BE resonant frequency prediction was assessed, considering confinement effects on system stiffness. The Hilbert Transform was applied to evaluate instantaneous frequency responses. The proposed method introduces new approaches for selecting S-wave arrival time, incorporating BE resonant frequency and time-domain frequency analysis. These findings enhance understanding of BE-sample interactions, improving the interpretation of BE test results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".