Rheological Modelling of Bio-fluids Using Moving Coil Transducers
Bibliographic record
Abstract
Extended Abstract Blood rheology is the study of flow properties of plasma and cells that may alter in disease processes. Rheometers can be of very simple or complex structures in construction, depending on the type of application they are used [1]. Hemorheology allows only certain types of equipment to be used in biomedical applications. Some researchers [2] used impedance spectroscopy as a means of analysis for the rheological properties of a liquid, using a mixture of Genetic and the Nelder-Mead simplex algorithm to obtain the equivalent circuit parameters of the measurement system (vibrating wire method). In our project (presented here), we use a rather straightforward procedure, based on the electrical equivalent circuit synthesis and realization for moving coil transducers that can be performed using a model based circuit topology, since this equivalent circuit can be analysed as a driving point impedance where . Thiele parameters” constitute the equivalent circuit elements. In this work, we present the results of our laboratory measurements using a moving coil transducer and various fluids. Equivalent circuit parameters were obtained by measuring and recording the impedance versus frequency data. All measurements were conducted around the same temperature (24°C). Calibration measurements are performed in air using an empty polystyrene cup in a test box, and using a moving coil transducer with hollow spindle attachment. Then, similar measurements and recordings are repeated for a test cup filled with distilled water as the second calibration fluid, and various test fluids mimicking blood and plasma [3]. Driving point impedance functions for each case are calculated based on the results of these measurements. Finally, Thiele model parameters are implemented to set up driving point impedance functions for each corresponding measurement case. It is to be noted here that, there is only a slight difference between measured and computed vibration magnitude spectral results. The small difference is the observed weak amplitude peak at f = 3 kHz in measurements, which does not appear in computationally obtained spectra. We noted that temperature is an important factor in this kind of measurement. We used a method to interpolate reported water viscosity values. Provision of Standard Viscosity samples greatly improves quantitative studies. Similar data is required for any fluid sample. This can be advantageous to re-scale the equipment for viscosity measurements performed at different temperatures. Therefore, an empirical equation will be more reliable with the addition of temperature dependence parameter. It has been noted that there are meaningful relationships between measured parameters and the polynomial coefficients of synthesized third order driving point impedance functions. Preliminary results of these experiments have been found to be in good agreement with theory.
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.
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".