Application of chemical acoustic emission to industrial processes
Bibliographic record
Abstract
This thesis reports on two chemical acoustic emission studies of importance to Canadian Industry. The first demonstrated that the rate of evolution of hydrogen and oxygen from electrodes in an electrolysis cell may be conveniently monitored via its ultrasonic acoustic emission, in a non-intrusive manner. The apparatus used in this work consisted of a nickel anode, a stainless steel cathode, and a saturated calomel reference electrode, all situated in a three-chamber cell containing sodium hydroxide electrolyte solutions of various concentrations. The potential necessary for evolution of both hydrogen and oxygen was conclusively determined by the onset of bursts of acoustic emission. Individual acoustic emission signals, captured using a broadband transducer mounted on the working electrode, contained frequencies from 16 kHz to as high as 800 kHz. These were correlated with the release of streams of bubbles from the electrode's surface, both visually and via a chart recorder trace of peak acoustic intensity vs. time. Trends in several time-domain signal descriptors were observed with an increase in the applied voltage. Acoustic power spectra were obtained by averaging spectra from many acoustic signals. Estimates of rate of emission were made by integration of the peak acoustic level. The effects of applied potential and electrolyte concentration on the multiple bursts of acoustic emission were characterized and are presented as a system response surface. Increasing the applied potential resulted in greater rates of bubble emission, which increased the intensity of acoustic emission, but produced, essentially, an identical acoustic power spectrum. The extent of acoustic emission at high concentrations (2.0 M) and high applied potentials (3.0 - 4.0 V) was less than expected, which suggested a decrease in efficiency under these conditions. Evolution of gas from the electrolysis was compared with the root mean square (RMS) voltage of the acoustic signal. The acoustic RMS was found to correlate linearly with gas volume produced, and consequently it correlated linearly with current measurements. Further studies indicate that the formation of oxides on a clean electrode surface was accompanied by limited acoustic activity, but no such emissions were found for electrodes in which the oxide coating was already present. The second study sought to improve the method that industry uses to determine the sensitivity of compounds to impact. This method is particularly important in measuring the safety of handling explosive compounds in transport, and in storage. The apparatus used presently involves the dropping of a weight from a height onto a small sample, which is confined in a specially designed enclosure. A positive result only occurs when enough energy was supplied to cause an explosion. Whether a result is positive or negative is somewhat open to the interpretation of the operator. Signs of a positive result include smoke, piercing of a diaphragm, or the formation of a dark residue within the sample enclosure. The amount of potential energy (height x weight) required to cause a positive result in at least 50% of tests is termed the sensitivity value. Used in this conventional fashion, the instrument produced a single YES/NO decision per experiment. Many experiments were required to characterize each sample, in what is a very tedious procedure. In this present work it is shown that acoustic emission can be used to effectively monitor controlled explosive reactions occurring within the drop weight tester sample cavity. The acoustic emission resulting from the impact was captured using a broadband transducer mounted on a clip, which rested on the sample holder. Frequencies from 100 kHz to 1 MHz were captured. This has resulted in an automatic method for distinguishing between a positive and a negative result in calibration and solid sample tests. Spectrogram (plots time vs. frequency emission) analysis suggests that acoustic emission may be used to probe the mechanism of the explosion within the sample container. The high irrepeatability of results for the nitromethane samples was due to the piercing of the "O-ring" surrounding the sample, rather than the expected rupture of the diaphragm situated above it. The results show that better design of the present drop weight apparatus must be undertaken to improve the reproducibility. Acoustic emission will provide a useful means to quantify that improvement.
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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) | 0.000 | 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 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".