scholarly journals Performance Index of Incremental Granular Model with Information Granule of Linguistic Intervals and Its Application

2020 ◽  
Vol 10 (17) ◽  
pp. 5929
Author(s):  
Chan-Uk Yeom ◽  
Myung-Won Lee ◽  
Keun-Chang Kwak

This paper addresses the performance index (PI) of an incremental granular model (IGM) with information granules of linguistic intervals. For this purpose, IGM is designed by combining a linear regression (LR) and an interval-based granular model (GM). The fundamental scheme of IGM construction comprises two essential phases: (1) development of LR as a basic model and (2) design of a local granular model, which attempts to reduce errors obtained by the LR model. Here, the local interval-based GM is based on an interval-based fuzzy clustering algorithm, which is materialized by information granulations. The PI of IGM is calculated by multiplying the coverage with specificity property, because the output of IGM is not a numerical value but a linguistic interval value. From the concept of coverage and specificity, we can construct information granules; thus, it is justified by the available experimental proof and presented as clearly defined semantics. To validate the PI method, an experiment is conducted on concrete compressive strength for civil engineering applications. The experimental results confirm that the PI of IGM is an effective performance evaluation method.

2011 ◽  
Vol 54 (6) ◽  
pp. 1046-1050 ◽  
Author(s):  
Yang Yang ◽  
Bo Peng ◽  
XuRong Dong ◽  
Li Fan ◽  
Li Liu ◽  
...  

2018 ◽  
Vol 89 (16) ◽  
pp. 3244-3259 ◽  
Author(s):  
Sumit Mandal ◽  
Simon Annaheim ◽  
Andre Capt ◽  
Jemma Greve ◽  
Martin Camenzind ◽  
...  

Fabric systems used in firefighters' thermal protective clothing should offer optimal thermal protective and thermo-physiological comfort performances. However, fabric systems that have very high thermal protective performance have very low thermo-physiological comfort performance. As these performances are inversely related, a categorization tool based on these two performances can help to find the best balance between them. Thus, this study is aimed at developing a tool for categorizing fabric systems used in protective clothing. For this, a set of commercially available fabric systems were evaluated and categorized. The thermal protective and thermo-physiological comfort performances were measured by standard tests and indexed into a normalized scale between 0 (low performance) and 1 (high performance). The indices dataset was first divided into three clusters by using the k-means algorithm. Here, each cluster had a centroid representing a typical Thermal Protective Performance Index (TPPI) value and a typical Thermo-physiological Comfort Performance Index (TCPI) value. By using the ISO 11612:2015 and EN 469:2014 guidelines related to the TPPI requirements, the clustered fabric systems were divided into two groups: Group 1 (high thermal protective performance-based fabric systems) and Group 2 (low thermal protective performance-based fabric systems). The fabric systems in each of these TPPI groups were further categorized based on the typical TCPI values obtained from the k-means clustering algorithm. In this study, these categorized fabric systems showed either high or low thermal protective performance with low, medium, or high thermo-physiological comfort performance. Finally, a tool for using these categorized fabric systems was prepared and presented graphically. The allocations of the fabric systems within the categorization tool have been verified based on their properties (e.g., thermal resistance, weight, evaporative resistance) and construction parameters (e.g., woven, nonwoven, layers), which significantly affect the performance. In this way, we identified key characteristics among the categorized fabric systems which can be used to upgrade or develop high-performance fabric systems. Overall, the categorization tool developed in this study could help clothing manufacturers or textile engineers select and/or develop appropriate fabric systems with maximum thermal protective performance and thermo-physiological comfort performance. Thermal protective clothing manufactured using this type of newly developed fabric system could provide better occupational health and safety for firefighters.


Author(s):  
Hao Sun ◽  
Jun Li ◽  
Liming Song ◽  
Zhenping Feng

The non-axisymmetric endwall profiling has been proven to be an effective tool to reduce the secondary flow loss in turbomachinery. In this work, the aerodynamic optimization for the non-axisymmetric endwall profile of the turbine cascade and stage was presented and the design results were validated by annular cascade experimental measurements and numerical simulations. The parametric method of the non-axisymmetric endwall profile was proposed based on the relation between the pressure field variation and the secondary flow intensity. The optimization system combines with the non-axisymmetric endwall parameterization method, global optimization method of the adaptive range differential evolution algorithm and the aerodynamic performance evaluation method using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) and k–ω SST turbulent with transition model solutions. In the part I, the optimization method is used to design the optimum non-axisymmetric endwall profile of the typical high loaded turbine stator. The design objective was selected for the maximum total pressure coefficient with constrains on the mass flow rate and outlet flow angle. Only five design variables are needed for one endwall to search the optimum non-axisymmetric endwall profile. The optimized non-axisymmetric endwall profile of turbine cascade demonstrated an improvement of total pressure coefficient of 0.21% absolutely, comparing with the referenced axisymmetric endwall design case. The reliability of the numerical calculation used in the aerodynamic performance evaluation method and the optimization result were validated by the annular vane experimental measurements. The static pressure distribution at midspan was measured while the cascade flow field was measured with the five-hole probe for both the referenced axisymmetric and optimized non-axisymmetric endwall profile cascades. Both the experimental measurements and numerical simulations demonstrated that both the secondary flow losses and the profile loss of the optimized non-axisymmetric endwall profile cascade were significantly reduced by comparison of the referenced axisymmetric case. The weakening of the secondary flow of the optimized non-axisymmetric endwall profile design was also proven by the secondary flow vector results in the experiment. The detailed flow mechanism of the secondary flow losses reduction in the non-axisymmetric endwall profile cascade was analyzed by investigating the relation between the change of the pressure gradient and the variation of the secondary flow intensity.


2012 ◽  
Vol 459 ◽  
pp. 432-436
Author(s):  
Jun Liu ◽  
Ye Nan Wang ◽  
Jian Hua Li ◽  
Rui Shen Chen

In this study, a new system performance evaluation method is introduced to the two-machine line. After that, the extended system aggregation model is developed and corresponding aggregation formulations are deduced.Different from traditional production models, the production line features unreliable buffers and multiple stochastic failure modes of the machines. The method is applicable to analyzing the cases arising from two or more stochastic events or more complex production lines


Sign in / Sign up

Export Citation Format

Share Document