Error temperature variation

The FTS drive is delicate, and the effect of errors in the velocity of the drive is included in FllnS. However other effects like vibrations during the scan, metrology errors, temperature variations, among others must be taken into account because it can affect the readout of the position of the drive, and hence distort the recovered datacube. 

There have been few discussions of the specific problems inherent in the application of methods of curve matching to solid state reactions. It is probable that a degree of subjectivity frequently enters many decisions concerning identification of a best fit . It is not known, for example, (i) the accuracy with which data must be measured to enable a clear distinction to be made between obedience to alternative rate equations, (ii) the range of a within which results provide the most sensitive tests of possible equations, (iii) the form of test, i.e. f(a)—time, reduced time, etc. plots, which is most appropriate for confirmation of probable kinetic obediences and (iv) the minimum time intervals at which measurements must be made for use in kinetic analyses, the number of (a, t) values required. It is also important to know the influence of experimental errors in oto, t0, particle size distributions, temperature variations, etc., on kinetic analyses and distinguishability. A critical survey of quantitative aspects of curve fitting, concerned particularly with the reactions of solids, has not yet been provided [490]. 

The temperature variations within the solution were increased from Test 1 ( Tn which the initial polystyrene concentration was 0%) to Test 2 (in which it was 15 ) and to Test 3 (in which it was 30 ) respectively. The maximum temperature differences between T2 and T were only 10° in Test 1, and 15° in Test 2 but 78° in Test 3. The greater the temperature differences, the greater the error of calculating T. Hence, the computations for T were decreasingly accurate in Test 1, 2 and 3 respectively. 

By calibration on pHb at Tc the pH meter scale expresses the voltage in pH units at that temperature, so difficulties may arise when the test solution is measured at a deviating temperature T. If we assume for the present that the true pH value is not significantly altered by temperature variation (see later) and that the error in the pH read from the scale bears a linear relationship to the relative temperature difference we can correct pH, by... 

As early as 1972, Kuhn described a model in which he assumed that RNA replication with a certain error rate could have occurred without the participation of enzymes. Natural phenomena with cyclic behaviour are an important factor in Kuhn s thinking these drive duplication processes. Examples are summer and winter, day and night, or high and low tide (whereby the latter were probably subject to greater variations on the primeval Earth than they are today). These rhythms were often linked with considerable temperature variations, which, for example, made possible the transition from double to single strand RNA (and vice versa). It can be assumed that the cyclic variations involved reactions in which monomers were linked to form polymers. 

The total optical path difference between the two arms of the interferometer, for a sample length of about 50 mm, is of the order of 10 mm or less, minimizing the systematic error due to laser frequency fluctuations. To reduce the thermal effects on the interferometer assembly, the interferometer support plate is stabilized to a temperature slightly higher than room temperature and insulated from air currents by a polystyrene foam shield. The temperature variation of the interferometer support is kept below 0.1 K. 

The above measurement results also included the error contribution of the temperature cross-sensitivity of the device. From Fig. 7.11, the temperature dependence of the device was 0.074 nm °C Based on (7.6), the temperature crosssensitivity of the device was less than 3.2 x 10 6 RIU °C. Therefore, the total temperature cross-sensitivity-induced measurement error was about 2.8 x 10 4 RIU in Fig. 7.13 over the temperature variation of 87°C. The temperature dependence of the device was small and contributed only about 2.3% to the total refractive index variation over the entire temperature range. 

The temperature coefficient of conductance is approximately 1-2 % per °C in aqueous 2> as well as nonaqueous solutions 27). This is due mainly to thetemper-ature coefficient of change in the solvent viscosity. Therefore temperature variations must be held well within 0.005 °C for precise data. In addition, the absolute temperature of the bath should be known to better than 0.01 °C by measurement with an accurate thermometer such as a calibrated platinum resistance thermometer. The thermostat bath medium should consist of a low dielectric constant material such as light paraffin oil. It has been shown 4) that errors of up to 0.5 % can be caused by use of water as a bath medium, probably because of capacitative leakage of current. 

To determine the 7r-A isotherms of dissolving films, two extrapolation methods were employed (29) either log tt at constant AT, or log AT at constant ir was plotted as a function of /1, where t is elapsed time. Extrapolation to t = 0 yields values of A or ir to within dr 5% for rapidly desorbing films. Palmitic acid at pH 9.2 was an exception its desorption rate was so rapid that the error in A was d= 10%. All the experiments were performed at 23° d= 0.5 °C. the maximum temperature variation during a single run was < 0.2 °C. The surface potential, AV, was monitored and found not to drift by more than 10 mv. during a single run. Reproducibility was d= 10 mv. 

Temperature variations in the instrument are a source of error and electrical power dissipation is limited to avoid the effects of self-heating. This is achieved by means of the four lead system shown in Fig 6.25ft. This minimises any effects of variations in temperature on the resistance RCL of the connections between the RTD and the bridge and is used normally with digital thermometers and data acquisition systems where the sensor non-linearity is corrected within the computer software. 

After a calibration has been established, we may proceed with the sample measurements, which can be done with a submersible probe, in a flow-through cell, or in a plastic cup filled sampled water. Temperature variations are a source of several errors that affect pH measurements, causing changes in the equilibrium of the calibration solutions and samples and the drift of reference electrode. That is why field pH meters have a built-in temperature probe and a temperature compensation capability. Although the meter measures the electromotive force or potential in millivolts, the meter software delivers the readings in pH units. For routine work, we... 

Because the temperature variation of 5 is to be compared with the strong exponential variation of e EIRT it is difficult to separate from experimental data the temperature dependence of 5 and E. For this reason it is a convenient working rule to assume that 5 is a constant. The activation energy E is then given by the slope of the line obtained by plotting 2.303 R log k against 1/T, as shown in Fig. 5. In most cases little error will be introduced by this simplification. 

Calibration is the largest source of error in the measurements. N0a permeation rates were determined by the rate of weight loss. Neighing errors amount to + 2%. The uncertainty in the NO/Oa titration method used to check the weight loss method is about 5%. Additional calibration errors of + 2% are caused by temperature variations of the permeation devices. 

Tavg represents the average absolute temperature between points 2 and 3, and temperature variations up to 20 percent from the average absolute value will introduce only a small error in the final result. The error introduced by using a constant favg (based on average temperature and pressure) instead of the exact... 

Random errors are always present and some sources are small random fluctuations in the settings of the variables which result in that the same experiments never yield exactly the same result upon repeated runs random variations of unknown factors which influence the result but which are not controlled in the experiment random events during the measurement process, e.g. spikes in signals from detectors, temperature variations in recording spectra. 

A common approximation used in the analysis of fins is to assume the fin temperature to vary in one direction only (along the fin length) and the temperature variation along other directions is negligible. Perhaps you arc wondering if this one-dimensional approximation is a reasonable one. This is certainly the case for fins made of thin metal sheets such as the fins on a car radiator, but wc wouldn t be so sure for fins made of thick materials. Studies have shown that the error involved in one-dimensional fin analysis is negligible (less Uian about 1 percent) when... 

In order to provide a means for the precise recalculation of nitrogen chemical shifts reported since 1972, it is necessary to have accurate values of the differences in the screening constants between neat CH3N02 and the large number of reference compounds which have so far been used. Table VII shows the results of precise, 4N measurements (61) which have been carried out in concentric spherical sample and reference containers in order to eliminate bulk susceptibility effects on the shifts. Since the technique adopted (61, 63) involves the accumulation of a large number of individually calibrated spectra with the subsequent use of a full-lineshape analysis by the differential saturation method, (63) the resulting random errors comprise those from minor temperature variations, phase drifts, frequency instability, sweep nonlinearity, etc. so that systematic errors should be insignificant as compared with random errors. 

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