Kun Shan University

About: Kun Shan University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Heat transfer & Thin film. The organization has 1992 authors who have published 2928 publications receiving 45685 citations. The organization is also known as: Kūnshān Kējì Dàxué.

A new alternative fuel for reduction of polycyclic aromatic hydrocarbon and particulate matter emissions from diesel engines.

Abstract: This study investigated the emissions of polycyclic aromatic hydrocarbons (PAHs), carcinogenic potential of PAH and particulate matter (PM), brake-specific fuel consumption (BSFC), and power from diesel engines under transient cycle testing of six test fuels: premium diesel fuel (PDF), B100 (100% palm biodiesel), B20 (20% palm biodiesel + 80% PDF), BP9505 (95% paraffinic fuel + 5% palm biodiesel), BP8020 (80% paraffinic fuel + 20% palm biodiesel), and BP100 (100% paraffinic fuel; Table 1). Experimental results indicated that B100, BP9505, BP8020, and BP100 were much safer when stored than PDF. However, we must use additives so that B100 and BP100 will not gel as quickly in a cold zone. Using B100, BP9505, and BP8020 instead of PDF reduced PM, THC, and CO emissions dramatically but increased CO2 slightly because of more complete combustion. The CO2-increased fraction of BP9505 was the lowest among test blends. Furthermore, using B100, B20, BP9505, and BP8020 as alternative fuels reduced total PAHs...

Analytical solutions of bio-heat conduction on skin in fourier and non-fourier models

Abstract: In general, the transport of thermal energy in living tissue is a complex process. The analysis of the heat conduction of skin tissue is helpful for understanding of the bio-thermo-mechanical behavior of skin tissue. So far, three kinds of conduction law — (1) the Fourier model, (2) the C-V model and (3) dual-phase-lag (DPL) model — are often investigated in bio-thermal transfer process. In this study, the mathematical model of heat conduction of the skin tissue subjected to a general transient heating at the skin surface was established. The analytical solutions of these three conduction models are presented. In addition, the measure of thermal injury of the skin tissue subjected to a harmonic heating was investigated. It was found that the phenomenon of Fourier model is greatly different to those of the C-V and DPL models. Moreover, the effects of the phase lags, the heating frequency, and the heat quantity on the temperature variation and the index of thermal injury were significant. In sum, the analytical method can be used to solve the conduction problem of any one-layer tissue.

Relationships among industry environment, diversification motivations and corporate performance

Abstract: Purpose – This paper aims to examine empirically the relationships among industry environment, diversification motivations and corporate performance for a sample of Taiwanese automobile enterprises.Design/methodology/approach – A 55‐item survey questionnaire was developed to obtain the responses from companies in the automobile industry in Taiwan. Independent sample t‐test and χ2 tests were employed to confirm the homogeneity between the respondents and non‐respondents by firm's characteristics, including by industry, number of employees, and capital.Findings – The results suggest that industry environment has positive and significant impact on diversification motivations, and has positive but not significant impact on corporate performance. Diversification motivations has positive and significant impact on corporate performance. The results also indicate that firms of higher capital amounts have greater influence on diversification motivations and corporate performance, firms of publicly listed have grea...

A hybrid method for one-day ahead hourly forecasting of PV power output

Abstract: This paper proposes a hybrid method combining support vector regression (SVR) and fuzzy inference method for one-day ahead hourly forecasting of photovoltaic (PV) power output. The proposed method comprises training stage and forecasting stage. In the training stage, a number of SVR models are used to learn the collected input/output data sets. To achieve accurate forecast, the fuzzy inference method is used to select an adequate trained model in the forecasting stage, according to the weather information collected from Taiwan Central Weather Bureau (TCWB). The proposed approach is verified on a practical PV power generation system. Numerical results show that the proposed approach achieves better forecasting accuracy than the simple SVR and traditional artificial neural network (ANN) methods.