Chao-Yin Tsai

Optimization of suitable ethanol blend ratio for motorcycle engine using response surface method

In view of energy shortage and air pollution, ethanol-gasoline blended fuel used for motorcycle engine was studied in this work. The emissions of carbon monoxide (CO), nitrogen oxides (NOX) and engine performance of a 125 cc four-stroke motorcycle engine with original carburetor using ethanol-gasoline fuels were investigated. The model of three-variable Box Behnken design (BBD) was used for experimental design, the ethanol blend ratios were prepared at 0, 10, 20 vol%; the speeds of motorcycle were selected as 30, 45, 60 km/h; and the throttle positions were set at 30, 60, 90 %. Both engine performance and air pollutant emissions were then analyzed by response surface method (RSM) to yield optimum operation parameters for tolerable pollutant emissions and maximum engine performance. The RSM optimization analysis indicated that the most suitable ethanol-gasoline blended ratio was found at the range of 3.92–4.12 vol% to yield a comparable fuel conversion efficiency, while considerable reductions of exhaust pollutant emissions of CO (-29 %) and NOX (-12 %) when compared to pure gasoline fuel. This study demonstrated low ethanol-gasoline blended fuels could be used in motorcycle carburetor engines without any modification to keep engine power while reducing exhaust pollutants.

Using Optimization Methodology to Identify Suitable Biodiesel Blend Ratio

Biodiesel is a renewable alternative fuel produced from a wide range of vegetable oils and animal fats for use in compression ignition engines. It is rapidly expanding around the world, making it imperative fully to understand the impacts of biodiesel on the diesel engine combustion process and pollutant formation. Biodiesel can blend with diesel in any ratio, and the air pollutant emissions decreased with biodiesel content in fuels. However, biodiesel blend fuel reduced the diesel engine power output. Blend fuels containing 10, 20, 30, and 40% by volume of soybean biodiesel were used. ECOM-AC gas analyzer was used to measure the concentrations of CO, CO2, and NOx in the exhaust gas. The sampling of exhaust gas was taken in extension section of the exhaust pipe without catalytic converter. The engine experimental results showed these exhaust emissions were reduced for biodiesel blended fuels. However, additive for biodiesel was a slight increase in oxides of nitrogen (NOx) emission. From these statistical models, there are influences of biodiesel blend ratio, engine speed and throttle position. Statistical optimization methodology was used to investigate the mutual interaction between the emissions and engine performance. In this study, the suitable biodiesel blend ratio was about 2 ~ 7 %, it was the balance between exhaust emissions and engine performance.

Evaluation of Phalaenopsis flowering quality using near infrared spectroscopy

Carbohydrate contents have been demonstrated as indicators for flowering quality of Phalaenopsis plants. In this study, near infrared reflectance (NIR) spectroscopy was employed for quantitative analysis of carbohydrate contents like fructose, glucose, sucrose, and starch in Phalaenopsis. The modified partial least squares regression (MPLSR) method was adopted for spectra analyses of 176 grown plant samples (88 shoots and 88 roots), over the full wavelength range (FWR, 400 to 2498 nm). For fructose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.210% DW, SEV = 0.324% DW) in the wavelength ranges of 1400-1600, 1800-2000, and 2200-2300 nm. For glucose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.975, SEC = 0.196% DW, SEV = 0.264% DW) in the wavelength range of 1400-1600, 1800-2000, and 2100-2400 nm. For sucrose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.237% DW, SEV = 0.322% DW) in the wavelength range of 1300-1400, 1500-1800, 2000-2100, and 2200-2300 nm. For starch concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.873, SEC = 0.697% DW, SEV = 0.774% DW) in the wavelength ranges of 500-700, 1200-1300, 1700-1800, and 2200-2300 nm. This study successfully developed the calibration models for inspecting concentrations of carbohydrates to predict the flowering quality in different cultivation environments of Phalaenopsis. The specific wavelengths can be used to predict the quality of Phalaenopsis flowers and thus to adjust cultivation managements.

Spectral imaging approach to evaluate degree of tea fermentation by total catechins

Tea is one of the most widely consumed beverage in the world, only second to water. Different from black tea (fully fermented) and green tea (unfermented), partially fermented teas such as Oolong, Bouchong are popular in Taiwan, Japan, China and Asian countries. The quality assurance during the process of partially fermented tea is highly related to the fermentation degree of tea, which is the ratio of total catechins oxidized during tea fermentation. Spectral imaging system was developed in this study to evaluate the degree of tea fermentation, which consisted of lighting chamber, image acquisition modules, cameras, and liquid crystal tunable filter (LCTF, 400-1100 nm). Software programs of the system control and image processing were also developed. The spectra analyses were conducted; calibration models for the evaluation of total catechins were established by MPLSR (modified partial least square regression) and MLR (multiple linear regression) methods. The results showed that r (correlation coefficient), SEC (standard error of calibration), SEV (standard error of validation) were 0.99,4.56 mg/g, 5.67 mg/g for MPLSR model, and 0.99, 5.04 mg/g, 6.50 mg/g for MLR model respectively. Although MPLSR model has better prediction ability than MLR, MLR model has a potential to be integrated with multi-spectral image system to develop an on-line inspection system for monitoring fermentation degree of tea.