AISI/DOE Advanced Process Control Program Vol. 4 of 6: ON-LINE, NON-DESTRUCTIVE MECHANICAL PROPERTY MEASUREMENT USING LASER-ULTRASOUND
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of this project was to demonstrate the feasibility to measure the mechanical properties, such as yield strength, tensile strength, elongation, strain hardening exponent and plastic strain ratio parameters, of low carbon steel sheets on the production line using laser ultrasound. The ultrasound generated by the developed apparatus travels mostly back and forth in the thickness of the steel sheet. By measuring the time delay between two echoes, and the relative amplitude of these two echoes, one can measure ultrasound velocity and attenuation. These are governed by the microstructure: grain size, crystallographic texture, dislocations, etc. Thus, by recording the time behavior of the ultrasonic signal, one can extract microstructural information. These microstructural information together with the modified Hall-Petch equation allow measurement of the mechanical properties. Through laboratory investigations with a laboratory laser ultrasound system, followed by the installation of a prototype system at LTV Steel Company's No.1 Inspection Line in Cleveland, all target mechanical properties of ultra low carbon (ULC), low carbon (LC) and high strength low alloy (HSLA) steel sample lots were measured meeting or nearly meeting all the target accuracies. Thus, the project realized its goal to demonstrate that the mechanical properties of low carbon steel sheets can be measured on-line using laser ultrasound
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it