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High-precision signal processing algorithm to evaluate SAW properties as a function of temperature
(2013)
This paper presents a signal processing algorithm which accurately evaluates the SAW properties of a substrate as functions of temperature. The investigated acoustic properties are group velocity, phase velocity, propagation loss, and coupling coefficient. With several measurements carried out at different temperatures, we obtain the temperature dependency of the SAW properties. The analysis algorithm starts by reading the transfer functions of short and long delay lines. The analysis algorithm determines the center frequency of the delay lines and obtains the delay time difference between the short and long delay lines. The extracted parameters are then used to calculate the acoustic properties of the SAW material. To validate the algorithm, its accuracy is studied by determining the error in the calculating delay time difference, center frequency, and group velocity.
As the population grows, so does the amount of biowaste. As demand for energy grows, biogas is a promising solution to the problem. Lignocellulosic materials are challenged of slow degradability due to the presence of polymers such as cellulose, lignin and hemicellulose. There are several pretreatment methods available to enhance the degradability of such materials, including enzymatic pretreatment. In this pretreatment, there are few parameters that can influence the results, the most important being the enzyme to solid ratio and the solid to liquid ratio. During this project, experiments were conducted to determine the optimal conditions for those two factors. It was discovered that a solid to liquid ratio of 31 g of buffer per 1 gram of organic dry matter produced the highest reducing sugar release in flasks when combined with 34 mg of protein per 1 gram of organic dry mass. Additionally, another experiment was carried out to investigate the impact of enzymatic pretreatment on biogas production using artificial biowaste as a substrate. Artificial biowaste produced 577,9 NL/kg oDM, while enzymatically pretreated biowaste produced 639,3 NL/kg oDM. This resulted in a 10,6% rise in cumulative biogas production compared to its use without enzymatic pretreatment. By the conclusion of the investigation, specific cumulative dry methane yields of 364,7 NL/kg oDM and 426,3 NL/kg oDM were obtained from artificial biowaste without and with enzymatic pretreatment, respectively. This resulted in a methane production boost of 16,9%. Additionally in case of the reactors with enzymatically pretreated substrate kinetic constant was lower more than double, where maximum volume of biogas increased, comparing to the reactors without enzymatic pretreatment.