Monitoring of jute/hemp fiber hybrid laminates by nondestructive testing techniques
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
Abstract Damage following static indentation of jute/hemp (50 wt.% total fiber content) hybrid laminates was detected by a number of nondestructive testing (NDT) techniques, in particular, near (NIR) and short-wave (SWIR) infrared reflectography and transmittography, infrared thermography (IRT), digital speckle photography (DSP), and holographic interferometry (HI), to discover and evaluate real defects in a laminate with a complex structure. A comparative study between thermographic data acquired in the mid- (MWIR) and long-wave infrared (LWIR) spectrum bands, by pulsed (PT) and square pulse (SPT) thermography, is reported and analyzed. A thermal simulation by COMSOL ® Multiphysics (COMSOL Inc., Burlington, MA, USA) to validate the heating provided is also added. The robust SOBI (SOBI-RO) algorithm, available into the ICALAB Toolbox (BSI RIKEN ABSP Lab, Hirosawa, Japan) and operating in the MATLAB® (The MathWorks, Inc., Natick, MA, USA) environment, was applied on SPT data with results comparable to the ones acquired by several thermographic techniques. Finally, segmentation operators were applied both to the NIR/SWIR transmittography images and to a characteristic principal component thermography (PCT) image (EOF s ) to visualize damage in the area surrounding indentation.
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 | 0.000 | 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) | 0.000 | 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