Browsing by Author "Huang, Chun-Lung"

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A FINITE-VOLUME-BASED APPROACH FOR DYNAMIC FLUID-STRUCTURE INTERACTION
(2013)
Tsui, Yeng-Yung
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Huang, Yi-Cheng
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Huang, Chun-Lung
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Lin, Shi-Wen
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機械工程學系
It is common to adopt finite-element methods to solve solid mechanics problems and finite-volume methods for fluid dynamics computations. The use of different methods causes complication of the solution procedure for problems involving both fluids and solids. In this study, a partitioned approach based on the finite-volume method for dynamic fluid-structure interaction is presented. The method is formulated in a way suitable for an unstructured mesh with arbitrary grid geometry. The variables for the fluid are stored at the centroids of grid cells, whereas those for the solid at the grid nodes. The latter arrangement makes it more suitable for large structure deformation. After spatial discretization for the solid using the finite-volume approach, the resulting system of ordinary differential equations is solved implicitly using the dual-time-stepping scheme. As for the fluid calculation, a pressure-based algorithm is employed and the time step is advanced in a prediction-correction manner. The finite-volume method for the solid is assessed by calculating the deformation and dynamics of a cantilever under various loads. Good agreement with analytical solutions is obtained. Then, the solution procedure is applied to two cases with coupled fluid flow and structure dynamics. One is the flow over a vertical plate with one end fixed on the floor in a channel. The other is the flow over a cylinder with a plate attached to it on the lee side.
A fuzzy decision model of risk assessment through fuzzy preference relations with users\' confidence-interval
(2006)
Wang, Ping
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Chao, Kuo-Ming
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Huang, Chun-Lung
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Lo, Chi-Chun
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Hu, Chia-Ling
Risk assessment for security management is a complex process which linked to substantial ambiguous However existing techniques of risk analysis determine the solution by the probability distribution function of threats and its impact loss In fact, it is difficult for users to collect precise and adequate events to estimate the Probability of threats and impact losses. Consequently, a fuzzy risk analysis model is developed to prioritize the risk ranking of assets. The proposed model uses Pseudo-Order Preference Model (POPM) to represent the imprecise preference degree of decision maker and determine the ranking of alternative using fuzzy majority concept It extends the traditional risk analysis using fuzzy multiple person decision making (MPDM) theory and POPM to risk analysis in fuzzy environment Finally, a real case of risk assessment for the Internet Data Center (IDC) is given to ifiustrate our approach.
A fuzzy model for selection of QoS-aware web services
(2006)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Huang, Chun-Lung
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Li, Yinsheng
With the increasing popularity of employing web services, quality of service (QoS) measure of service becomes a significant concern for service consumers and providers. However, current technologies are poor to identify the relative importance of non-functional QoS criteria for web services and they are not fitting well for selecting the appropriate service. In this paper, a new scheme for right selection of QoS-aware of web services which exploits fuzzy logic to locate and select the right service based on customer\'s preference or sath faction degree. The aim is to compute both finctional and non-functional weightings of QoS criteria and to assist customers to make the right choice.for web services.
A fuzzy outranking approach in risk analysis of web service security
(2007-03-01)
Wang, Ping
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Huang, Chun-Lung
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Younas, Muhammad
Risk analysis is considered as an important process to identify the known and potential vulnerabilities and threats in the web services security. It is quite difficult for users to collect adequate events to estimate the full vulnerabilities and probability of threats in the Web, due to the rapid change of the malicious attacks and the new computers vulnerabilities. In this paper, a fuzzy risk assessment model is developed in order to evaluate the risk of web services in a situation where complete information is not available. The proposed model extends Pseudo-Order Preference Model (POPM) to estimate the imprecise risk based on richness of information and to determine their ranking using a weighted additive rule. A case Study of a number of web services is presented in order to test the proposed approach.
Composition-balanced trimetallic MOFs as ultra-efficient electrocatalysts for oxygen evolution reaction at high current densities
(2020-12-15)
Raja, Duraisamy Senthil
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Huang, Chun-Lung
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Chen, Yu-An
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Choi, YongMan
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Lu, Shih-Yuan
Engineering synergistic effects of multi-component catalysts is the key for breakthrough catalyst design. Here, a maximized-entropy approach was proposed to maximize the synergistic effects for maximum enhancements in electrocatalytic efficiencies of multi-component catalysts. Accordingly, composition-balanced iron, cobalt, and nickel based trimetallic MOFs was developed and demonstrated outstanding oxygen evolution reaction (OER) performances with ultra-low overpotentials of 196 and 284 mV achieved at current densities of 10 and 1000 mA cm(-2), respectively, as well as an ultra-low Tafel slope of 29.5 mV dec(-1) in alkaline aqueous media. The catalyst was ultra-stable even when operated at ultra-high current densities, experiencing only 5% loss in current densities, when chronoamperometrically tested at an industrially relevant current density of 1000 mA cm(-2) for over 50 h. in situ Raman spectroscopy study and density functional theory simulations were conducted to explore the OER mechanism and to illustrate the validity of the proposed maximized-entropy approach.
QoS-aware mobile service transactions in a wireless environment
(2007-06-10)
Younas, Muhammad
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Chao, Kuo-Ming
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Wang, Ping
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Huang, Chun-Lung
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資訊管理與財務金融系註：原資管所+財金所
Mobile computing greatly facilitates the provision of mobile services using portable and handheld devices which are connected through wireless networks. A pre-requisite for the provision of an effective service is to ensure quality of service (QoS) during the concurrent execution of requests and system or network failures. This paper presents a new transaction management approach for the provision of mobile services which is based on advanced transaction models and fuzzy selection criteria. It employs a novel QoS consensus moderation approach in order to select preferred mobile services from among various alternatives, thus providing multiple pathways to the completion of mobile service transactions. Unlike traditional transaction management schemes, the proposed approach takes into account QoS attributes in the commit process of mobile service transactions. The proposed approach is implemented as a prototype tool and evaluated through a number of experiments. Experimental results show that the proposed approach effectively selects mobile services and significantly increases the throughput (i.e. commit rate) of mobile service transactions. Copyright (C) 2007 John Wiley & Sons, Ltd.
Service discovery through consensus-based preferences
(2006-07-01)
Huang, Chun-Lung
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Chao, Kuo-Ming
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Lo, Chi-Chun
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Wang, Ping
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Chung, Jen-Yao
The prevailing research trend is to discover and compose web services dynamically in order to develop composite services that provide enhanced functionality. Most existing discovery techniques do not take into account the diverse preferences and expectations of service consumers. For instance, searching for a web service (for cheap and convenient flights), does not involve only functional requirements, but it also includes subjective and fuzzy opinions in query terms such as "cheap and convenient". Different perceptions of such terms by service consumers and providers create serious problems in service discovery. This is compounded by the fact that they may have different preferences or opinions. This paper presents a new service discovery approach to model subjective and fuzzy opinions, and to assist them in reaching a consensus. The method achieves a common consensus on the distinct opinions and expectations of individual users. This process is iterative and additional fuzzy preferences can be included to improve precision rate in web service discovery.