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Scales and Graphs
Published in Joanne Kirkpatrick Price, Basic Math Concepts, 2018
The scales described thus far are arithmetic scales—scales with equal divisions. Another type of scale, a logarithmic scale, is used frequently for engineering data. These scales do not have equal divisions between points since the space is divided according to logarithmic values.∗
Linear Systems and Control
Published in Jitendra R. Raol, Ramakalyan Ayyagari, Control Systems, 2020
Jitendra R. Raol, Ramakalyan Ayyagari
For instance, ω=320 rad/sec lies approximately half-way between 100 rad/sec and 1000 rad/sec. It is easy to see that ω=32 rad/sec lies approximately half-way between 10 rad/sec and 100 rad/sec; ω=3200 rad/sec lies approximately half-way between 1000 rad/sec and 104 rad/sec. Figure 1.17b shows the frequencies within the decade 1≤ω≤10 rad/sec. The advantage of a logarithmic scale is very apparent as it compresses higher frequencies and expands the lower frequencies, thereby allowing us to visualize the response at both extremes with a comparable level of detail.
Study on the applicability of a stochastic typhoon model for probabilistic forecasting of storm surge induced by a typhoon
Published in Coastal Engineering Journal, 2020
Yukimasa Higaki, Yoshimitsu Tajima
The gray dots in Figure 6 show the distribution of all the obtained data of as a function of the atmospheric pressure drop, i.e., the difference between the atmospheric pressure outside the typhoon, , and the central pressure, . In the figure, both horizontal and vertical axes are plotted on a logarithmic scale. Since this figure focuses on relatively large positive , the figure shows higher than 0.4 hPa/hour. Red solid circles show the top 1% of among the data at each pressure with an interval of 5 hPa. Under such a large positive , should dominate , i.e., the decaying process should dominate the growing process. Based on this assumption, this study determined the magnitude of by an upper envelope of these plots. As seen in Figure 6, the top 1% clearly increases with the magnitude of the pressure drop, P0-Pc. Based on the plot shown in Figure 6, the present model simply determines by
Dielectric Properties Based Detection of Heavy Metal Contaminated Soil in the Frequency Range from 10 MHz to 1 GHz
Published in Soil and Sediment Contamination: An International Journal, 2018
Shaopeng Guan, Wenyu Liu, Wei Liu, Changxin Nai
Keeping the volumetric water content unchangeable (θ = 30%), the complex permittivity of samples with different chromium ion contents under different frequencies are shown in Figures 4 and 5. It can be seen that the chromium ion content in the soil also has significant impacts on the complex permittivity. The two figures have different horizontal axis variables. The horizontal axis variable in Figure 4 is the frequency, which reflects the variation of the complex permittivity with the change of the frequency. As the measurement frequency range is large, for convenience, a logarithmic scale is used. The horizontal axis variable in Figure 5 is the ionic content, which reflects the impact of ionic contents on the complex permittivity.
Observability and sensitivity analysis of lightcurve measurement models for use in space situational awareness
Published in Inverse Problems in Science and Engineering, 2019
For the observability analysis, the same two cases mentioned previously are used here and the analysis is performed as outlined in Section 7. The focus is on the attitude and the shape/size parameters since the measurements are directly influenced by these. Tables 5 and 6 summarize the results for both cases. Figures 8–11 show these same values in bar plots. The logarithmic scale has been used so that large variations are well displayed. The greater the value of the observability, the state or parameter is regarded as being more observable. If the state or parameter shows a zero, it is not observable.