Experimental Methods

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Process Engineering

Synopsis:

How to measure temperature (thermocouples, thermistors, optical fibres, radiation thermometers), pressure transducers (and strain gauges), displacement and deformation (inductive probes, optical, cross correlation using multiple camera systems), flowrate (nozzles, turbines, electromagnetic, ultrasound, Coriolis forces).

Material properties measurement: rheometry (rotational and capillary viscometers) and elastic biomaterials (constitutive equations of e.g. vascular tissues and plastic materials). Real instruments are demonstrated during lectures and of course at laboratory experiments.

How to transfer and record data in PC. Interfaces and software (Labview).

Data processing and basic statistics. Evaluation of standard deviation of predicted quantities knowing errors of individual measurements (e.g. evaluate error of viscosity knowing error of measured rotational speed and torque of rotational rheometer). Analysis of measuring chains.

Regression analysis of recorded data (identification of mathematical models). Linear regression (orthogonal polynomials, estimate of errors and reliability intervals of identified parameters). How to linearize some engineering correlations. Calibration of multiple thermocouples and pressure transducers. Nonlinear methods (deterministic: Marquardt Levenberg, simplex methods, and stochastic methods of artificial intelligence: SOMA-self organizing mitigation algorithm).

Time courses processing. Integral characteristics of time responses. Moments of responses (mean response time and variance). Relationship between stimulus and response functions (convolution, transfer function). Laplace and Fourier transform of convolution and correlation, power spectral density. Discrete transforms (Nyquist frequency). How to smooth out a noise (local regression, median smoothing, Fourier filtering).

Requirements:

Basic mathematics (at a secondary school level, it means derivatives and ordinary differential equations). Basic physics (also at a secondary school level, Newton's law, electromagnetics...)

Syllabus of lectures:

1. A review of measurable properties and units. Revision of necessary background.

2. How to measure temperature (thermocouples, thermistors).

3. Temperature measurement using optical fibres (laser excited crystals] with application to microwave ovens, and radiation thermometers (single and dual-beam detectors, thermo cameras) with application to glass industry.

4. Pressure transducers (and strain gauges), displacement and deformation (inductive probes, optical, cross correlation using multiple camera systems),

5. Flowrate (nozzles, turbines, electromagnetic, ultrasound, Coriolis forces). Material properties measurement: rheometry (rotational and capillary viscometers)

6. Constitutive properties of elastic biomaterials (constitutive equations of e.g. vascular tissues and plastic materials).Real instruments are demonstrated during lectures and of course at laboratory experiments.

7. How to transfer and record data in PC. Interfaces and software (Labview).

8. Data processing and basic statistics. Evaluation of standard deviation of predicted quantities knowing errors of individual measurements (e.g. evaluate error of viscosity knowing error of measured rotational speed and torque of rotational rheometer). Analysis of measuring chains.

9. Regression analysis of recorded data (identification of mathematical models). Linear regression (orthogonal polynomials, estimate of errors and reliability intervals of identified parameters). How to linearize some engineering correlations. Calibration of multiple thermocouples and pressure transducers.

10. Nonlinear methods (deterministic: Marquardt Levenberg, simplex methods, and stochastic methods of artificial intelligence: SOMA-self organizing mitigation algorithm).

11. Time courses processing. Integral characteristics of time responses. Moments of responses (mean response time and variance). Relationship between stimulus and response functions (convolution, transfer function).

12. Laplace and Fourier transform of convolution and correlation, power spectral density. Discrete transforms (Nyquist frequency). How to smooth out a noise (local regression, median smoothing, Fourier filtering).

13. Discussion of labory experiments.

Syllabus of tutorials:

1. Biomechanics: hi-tech methods for measurement deformation of blood vessels loaded by inner pressure (confocal optical probes, spatial imaging using two high speed cameras and cross correlation of images). Described on www presentation.

2. Thermal properties of liquids. Application of thermocouples.

Study Objective:

Practical experience with experimental techniques applicable in practice (process and bioengineering)

Study materials:

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: