Notre Dame University (Louaize) Faculty of Engineering Department of Civil & Environmental Engineering CEN 465 Environmental Engineering Laboratory Lab # 1 Temperature and Water Content Measurement Prepared by: Michella Dib Submitted to: Dr. Yara Medawar February 7, 2018 Part 1: Results This experiment was done by measuring temperature and moisture content of random soil directly below the surface and deeper. No equations were used along the session (No calculation was done). The results are presented in tabulated and graphical forms. Table 1: Variation of moisture content, and temperature of different soil layers Depth(cm) Moisture content w(%) Temperature T(̊C) 5 16.2 20 10 17.1 19.1 15 19 19 Figure 1: Variation of moisture …show more content…
Description of Data The initial set of measurements is done varying the soil depth. As going deeper, the moisture content is getting higher (16.2% to 19%) while the temperature is getting cooler (20 C to 19 C). Going farther from the initial reference point(1m, 2m, and 3m), the temperature decreases from 20 C to 16.6 C, but the moisture content is increasing from 16.2% to 20.9%. Figure 4: Running the experiment For same depth measurements, moisture content varies +0.4% after 5 minutes then it continues in increasing to reach 21.4 % after 15 min. In parallel, the temperature of the soil decreases 0.4 C after the first 5 minutes then reaches the value of 16 C after 15 min. 2.b. Analysis of Data Figure 5: Reading the …show more content…
Different result was encountered with the temperature as it was decreasing with time . An important issue limiting the applicability of the TDR is the effect of the main assumption (of the device run) that only the real part of the dielectric permittivity determines the value of the TDR-measured apparent dielectric permittivity. This statement is not applicable for conductive soils (clay soils) or where high concentrations of electrolyte are present in the soil solution (saline soils) because, under these conditions, the contribution of the imaginary part is important (Bittelli et al., 2008; Topp et al., 2000). As a concise conclusion, no theoretical data is given or calculated to know if the measurement is precise, however, lots of factors could affect the measurement. One of the main effects of dielectric losses on the TDR measurement is overestimation of WC. From what could affect the results: Vaporization of water during the experiment (at noon
The design relied on two Schmitt triggers to generate the two different tones while using the transistors to act as a switch. This causes it to trigger continuously between two unstable states, allowing automatic switching between two frequencies producing two different tones. The RC values between the two Schmitt triggers will differ. Capacitors charge and discharge faster when it’s resistance is smaller.
The temperature probe was then quickly cooled to room temperature. When this was achieved, the hot water was immediately transferred into the calorimeter. This method of keeping the temperature probe cooled before measuring a new temperature was repeated throughout the entire experiment. Temperature data was collected for 180 s while swirling the temperature inside the calorimeter. The calorimeter still contained the warm water.
K.D.A. Saboia et al. , (2007) have been prepared the Bi4Ti3O12–CaCu3Ti4O12 {[BIT(X)–CCTO(100-X)]} composite powders through solid state reaction method and calcined in the range of 900 to 1020 ºC for 12 h. The as-prepared powders have modified in the form of thick film onto alumina ceramic substrate by utilizing screen printing. At 100 Hz, the value of dielectric constant (κ) of CCTO100 and BIT100 is 316.61 and 53.64 respectively. Conversely, the composite with X=20 % shows an unexpected dielectric constant of 409.71, which is around 20% higher in comparison with the CCTO.
Freshwater is also looked at as floodplain management is observed. The patterns of environmental quality are also examined. My hypothesis is that pH levels and drainage account for the significant differences in vegetation between the areas. This is because both drainage and pH levels play a role in what type of soil is available. The pH level determines the types of plants that grow and the drainage effects the type of soil present, which influences the
Bernardo Garcia UIN 32500959 The climate classification system I choose to implement is based on two variables the Average Annual Precipitation in Texas [1] and the Average Annual temperature in Texas [2]. The average annual precipitation is broken down in to four range; 0 to 26 inches of rainfall, 26 to 38 inches of rainfall, 38 to 50 inches of rainfall and lastly rainfall above 50 inches. The Average Annual temperature map is broken down in 5 ranges starting from 50 F-55 F, 55 F – 60 F, 60 F – 65 F, 65 F-70 F and finally 70 F above. By paring the range of the temperature map and the precipitation map give me 14 category to show both the rainfall by inches and temperature by Fahrenheit, with this information I can discern on where the best place to plant plants or crops
If the temperature is dropping and the dew point is holding steady, what is your forecast for the relative humidity? Explain your answer. The relative humidity would increase if the temperature dropped and the dew point remained steady. Cooled air is unable to retain much moisture and saturates the air, therefore it increases the relative humidity. If the temperature decreases, the relative humidity will increase as a result in this situation.
The Average Maximum Temperature is 85.8°F in July, whereas the Lowest Average Minimum Temperature is 23.9°F in January. Also noted is the Average Annual Snowfall of 10.7 inches. Scientists are finding that the aquifer could be at risk with the climbing climate. It triggers an increase in rainfall rather than snowfall in the mountains resulting in less groundwater. Reduction of water supply is also because of streamflow timing due to increased
Hypothesis: Increasing substrate concentration will increase the initial reaction rate until it stops increasing and flattens out. Independent Variable: Substrate concentration Dependent Variable: The substrate itself, 1.0% Hydrogen Peroxide How Dependent Variable will be Measured: Hydrogen Peroxide will be used in every experiment, just with different test tubes. The amount of Hydrogen Peroxide in the mixing table is the amount that will be added to each test tube.
Figure two below illustrates monthly precipitations data for each year at Onondaga Park, Syracuse, NY in the years 2008 and 2010. These volumes were articulate as a percentage of the monthly normal precipitation for each month of the year. To compute this number, the deviation from normal in percentage, the equation below was used: ((Monthly Precipitation in cm)-(Normal Values in cm))/(Normal Values in cm)*100 Based on the volume computed using the equation above the bar graph was generated, the upper bars, that are above the zero deviation from normal in percentage illustrates the wettest months in Syracuse for years 2008 and 2010. The lower bars below the deviation from normal in percentage shows the dries months in Syracuse for years 2008 and 2010.
2.4 Band Division and Energy Computation: The power spectrum of the signal is multiplied by magnitude response of set of 33 triangular band pass filters and in the range 300Hz-2000Hz. Sub-bands are formed by using the logarithmic spacing. The positions of these filters are equally spaced along the Mel frequency, which is related to the common linear frequency f by following formula: Mel (f) = 1125* ln (1+f/700) (3) Mel frequency is proportional to the logarithm of linear frequency and which is close to the human perceptual system. 2.5 Sub Fingerprint Generation:
Ct ε0A (9)where ε0is the permittivity of the free space, C is the capacitance, t isthe thickness of the sample and A is the area of the cross section. Thedielectric constant has high values in the lower frequency regionand then it decreases with the applied log frequency as shown inFig. 10(a). The plot of the dielectric loss vs.
2.5 Soil analysis Soil of experimental field was analyzed for pH and available P. pH was measured using pH meter and method of Olsen et al. (1954) was used for the determination of available P. 2.8 Plant-soil experiment set
The pocket penetrometer is intended as a lightweight tool for use in the field to examine visual classification of soils. It indicates compressive strength, consistency and penetration resistance. However, the readings attained do not replace test results from a laboratory since a insignificant area of penetration test might give misleading results. (Gerald F. Gifford, Robert H. Faust, George B. Coltharp, 1977) Soil becomes compacted as soil particles are forced to pack more closely together.
In this experiment, the amount of water lost in the 0.99 gram sample of hydrated salt was 0.35 grams, meaning that 35.4% of the salt’s mass was water. The unknown salt’s percent water is closest to that of Copper (II) Sulfate Pentahydrate, or CuSO4 ⋅ 5H2O. The percent error from the accepted percent water in CuSO4 ⋅ 5H2O is 1.67%, since the calculated value came out to be 0.6 less than the accepted value of 36.0%.This lab may have had some issues or sources of error, including the possibility of insufficient heating, meaning that some water may not have evaporated, that the scale was uncalibrated, or that the evaporating dish was still hot while being measured. This would have resulted in convection currents pushing up on the plate and making it seem lighter by lifting it up
The extensive glaciations of the region has resulted in poorly developed top soil and soil horizons .Soils generally have low shrink swell potential because of their minimal clay content but high erosive potential because generally they are thin and