Fuzzy Grey Relational Analysis Research Articles

Multivariable analysis of vortex generator-aided heat transfer enhancement for 18650 battery thermal management system

Currently, electric vehicles and hybrid cars have emerged as global solutions to replace internal combustion engine vehicles, with lithium-ion batteries being the most widely chosen option due to their low discharge rates and high energy density. Air-cooling systems, recognized for their cost-effectiveness and stability, are extensively employed in the thermal management systems of automotive batteries. However, conventional air-cooling models exhibit drawbacks in uniformly cooling battery packs. In this study, a numerical investigation is conducted to explore the enhanced cooling heat transfer facilitated by a vortex generator in the air-cooled battery thermal management system. The heat generation and transfer of a battery pack are analyzed using the experimentally validated 2C discharge heat dissipation model for batteries. The assessment focuses on the impact of a vortex generator on the heat transfer performance of a series-connected battery pack. The results indicate that fluid mixing, boundary layer modification, and flow instability are the primary factors contributing to enhanced heat transfer. Through the utilization of orthogonal experimental design and fuzzy grey relational analysis, the influence of three parameters (vortex generator position, angle of attack, and fin height) on thermal performance was systematically analyzed. The analysis reveals that the vortex generator position exerts the most significant impact on the heat transfer index, followed by height, with the angle having the least effect. Nusselt number and entropy generation were chosen as optimization indicators for a comparative analysis of enhancing heat transfer with and without optimized vortex generator assistance. The research results demonstrate that the optimal scenario occurs when entropy generation is minimized, resulting in a 56.4 % reduction in temperature difference (2.66 K) and a 12.1 % decrease in the maximum temperature (2.75 K). This study provides valuable guidance for further optimizing battery thermal management.

Multi-attribute fire safety evaluation of subway stations based on FANP – FGRA – Cloud model

With the rapid development of subway network, the fire safety of subway stations is becoming outstandingly important in the operation process. But there seem to be few studies developing quantitative models in the existing approaches. To this end, this study aims to develop a multi-attribute hybrid method by combining Fuzzy Analytic Network Process (FANP), and Fuzzy Grey Relational Analysis (FGRA) with Cloud model to evaluate fire safety of them. This research comprehensively sorts out and identifies high-frequency hazard factors associated with fire accidents at stations from personal, equipment, environmental and management aspects, and simultaneously explores dependencies and interactions among them. Seven typical transfer stations of Changsha subway network in China are studied by using the proposed approach, and the results show that: (1) the fire safety order from the best to the worst determined is FBH (A2), SWGY (A7), CSRS (A6), YWZ (A1), HTL (A5), HJT (A4) and WYGC (A3); (2) through comparing the results obtained by the proposed method with that determined fuzzy TOPSIS and fuzzy sum weighted method, it is proved that the method developed in this study is reliable and effective; and (3) sensitivity analysis indicates that the ranking order of stations is influenced by the fluctuation of criterion and sub-criterion weights.

Selection of suppliers using FBWM-FGRA hybrid approach in hospital food supply chain

In the current study, a new approach to assess and select food suppliers in hospitals is presented using integrated group evaluation method of fuzzy best- worst method (FBWM) and fuzzy gray relational analysis (FGRA). Evaluation criteria are selected by experts and weighed by the fuzzy best-worst method. After that, suppliers are rated using FGRA method. The proposed approach was implemented with seven criteria in one of the Iranian hospitals, and the results showed that quality, delivery time and trust criteria had the highest and skilled manpower and lack of surplus production criteria had the lowest score. Using FGRA, existing suppliers were ranked and the appropriate supplier was identified. In order to evaluate the reliability of the results, sensitivity analysis was performed on the criteria changes. The results showed that the supplier’s selection is greatly influenced by the criteria estimation values by the experts.

Research on lean management and innovation capability evaluation of technological small and medium sized enterprises under probabilistic hesitant fuzzy sets

The lean management and innovation capability evaluation of technological small and medium sized enterprises is a classical multi-attributes group decision-making (MAGDM). Recently, the probabilistic hesitant fuzzy sets (PHFSs) have been extended to apply in many fields. However, the existing models don’t evaluate the alternative considering the psychological factors. Thus, in this paper, an extended probabilistic hesitant fuzzy grey relational analysis (PHF-GRA) method is proposed to reduce the restrictions of GRA method by combining with cumulative prospect theory (CPT), considering the psychological preference. In addition, the PHFSs assigns probability values to different degrees of hesitancy, which shows its superiority in complex environment. At the same time, the weight vectors of each attribute are calculated by the entropy values of different foreground decision elements. Then, probabilistic hesitant fuzzy GRA (PHF-GRA) model based on CPT model is constructed for MAGDM under PHFSs. Finally, a practical example study for lean management and innovation capability evaluation of technological small and medium sized enterprises is constructed to validate the proposed GRA (PHF-GRA) model based on model CPT and some comparative studies are constructed to verify the applicability.

A practical decision-making framework for highway transportation scheme selection based on the triangular fuzzy neutrosophic information

In recent years, due to the further development of the market economy, the internal competition in the large-cargo transportation industry has become increasingly fierce, and the profit space has been greatly compressed. Therefore, large-cargo logistics enterprises are paying more and more attention to the research of highway transportation route plan. The highway transportation scheme selection is looked as the multi-attribute decision-making (MADM). In this paper, the triangular fuzzy neutrosophic numbers (TFNN) grey relational analysis (TFNN-GRA) method is established based on the classical grey relational analysis (GRA) and triangular fuzzy neutrosophic sets (TFNSs) with completely unknown weight information. In order to obtain the weight values, the information Entropy is established to obtain the weight values based on the score and accuracy functions under TFNSs. Then, combining the traditional fuzzy GRA model with TFNSs information, the TFNN-GRA method is set up and the computing steps for MADM are established. Finally, a numerical example for highway transportation scheme selection was established and some comparisons are established to study the advantages of TFNN-GRA. The main contributions of this paper are established as follows: (1) the information Entropy is established to obtain the weight values based on the score and accuracy functions under TFNSs; (2) the TFNN-GRA method is established with completely unknown weight information. (2) the TFNN-GRA method is established and the computing steps for MADM are established. (3) Finally, a numerical example for highway transportation scheme selection was established and some comparisons is employed to study advantages of TFNN-GRA method.

Methodology for risk assessment of engineering procurement construction project based on the probabilistic hesitant fuzzy multiple attributes group decision making

With the continuous development of China’s economic system, the development of the construction industry is becoming more and more rapid, and the number and scale of construction projects are increasing. Due to the characteristics of large projects and long cycles, there are a large number of construction parties involved in construction projects. The increase in the number of participating partners makes it difficult for their projects to be integrated and managed by management departments such as owners, let alone for various parties to collaborate in the construction of projects. In order to effectively solve this problem, the engineering procurement construction (EPC) general contracting model has emerged. The risk assessment of EPC project is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the risk assessment of EPC project. In this paper, the classical grey relational analysis (GRA) method is extended to PHFSs. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are introduced. Then, the definition of the score values is employed to obtain the attribute weights based on the information entropy. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for risk assessment of EPC project is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.

An evaluation model of sustainable efficiency for container terminals

AbstractThe purpose of this paper is to evaluate the sustainable efficiency of container terminals (CTs). By the definition of United Nations Conference on Trade and Development (UNCTAD), business sustainable development includes three domains: Economics, Environment, and Society. Accordingly, based on the definition and the practical features of CT operations, this paper assesses sustainable efficiency for CTs from three perspectives: container throughput, CO2 emissions, and occupational safety. In this paper, a modality movement and a fuzzy grey relational analysis (GRA) approach are first proposed to estimate CO2 emissions and occupational safety index for CT operators, respectively. A hybrid slacks‐based measure (SBM)‐DEA model is then developed to assess the sustainable efficiency of CT operators. Finally, the CT operators in the Port of Kaohsiung are empirically investigated to validate the research model. Based on the results, theoretical and practical implications for the management of CT operators and port authorities are discussed.

Intelligent estimation on state of health of lithium-ion power batteries based on failure feature extraction

In order to provide an accurate and reliable effective state-of-health (SOH) estimation, a novel hybrid data-driven estimation method by failure feature extraction is proposed. Firstly, influencing factors which reflect the failure of lithium-ion power batteries are studied, and three failure features of lithium-ion power batteries used as inputs of the estimation model are extracted by fuzzy grey relational analysis (FGRA) method. Then, the improved Least Squares Support Vector Machine (LSSVM) model is employed to estimate the SOH under different ambient temperature conditions. The results show that CC charging time, CV charging capacity and CV charging average temperature are determined as the failure features of the SOH estimation model, whose correlation degree to the battery capacity are 0.8774, 0.8104 and 0.8771, respectively. Compared with SVM, the improved LSSVM model has higher SOH estimation accuracy for the lithium-ion power battery under different ambient temperature conditions. In addition, the SOH estimation curves basically matches the actual curves, where the SOH estimation errors are less than 0.02. Moreover, the mean square error accuracy of the prediction results is at the level of 0.00001, and the determination coefficient is between 0.92 and 0.997. This work provides reference for enhancing the SOH estimation performance and safety of lithium-ion power batteries.

Multi-objective optimization of performance characteristic of diesel particulate filter for a diesel engine by RSM-MOPSO during soot loading

Diesel particulate filter (DPF) is one of the effective technologies for controlling vehicle particulate matter (PM) emissions. In this research, a hybrid multi-objective optimization approach of FGRA-RSM-MOPSO was developed for DPF, with optimization objectives including maximum initial filtration efficiency and minimum pressure drop. Decision variables include diameter, length, wall thickness, porosity, and pore diameter. Firstly, a computational fluid dynamics (CFD) model for DPF was established, and sensitivity analysis of DPF structural parameters was conducted through fuzzy grey relational analysis (FGRA) to screen out key factors affecting DPF trap performance. Then, response surface methodology (RSM) was used to establish the mathematical relationship between key structural parameters, initial filtration efficiency, and pressure drop. Finally, multi-objective particle swarm optimization (MOPSO) is used to optimize the target and select the optimal solution from the Pareto front. Compared with the original DPF, the optimized DPF under standard operating conditions increased the initial filtration efficiency by 46.85% and reduced the pressure drop by 34.88%. The optimization effect is more pronounced under high load conditions.

Retracted: Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Retracted: Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method

Modified GRA method for probabilistic hesitant fuzzy MAGDM and application to network health performance evaluation of radial distribution system

Radial distribution system is an important link connecting power supply and users, and its power supply reliability is directly related to users. Radial distribution network reconfiguration can transform the network structure by changing the switching state of the distribution network lines, and achieve the goals of reducing network operational losses, improving power quality, and power supply reliability while meeting various constraints such as radial operation, power supply and demand balance, capacity, and voltage. Radial distribution systems have the characteristics of multiple components and complex structures. How to quickly and accurately evaluate the health performance of radial distribution systems and find an optimal solution for network reconfiguration are important issues in distribution network analysis. The network health performance evaluation of radial distribution system is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the network health performance evaluation of radial distribution system. In this paper, we extend the classical grey relational analysis (GRA) method to the probabilistic hesitancy fuzzy MAGDM with unknown weight information. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are briefly introduced. Then, the definition of the score values is employed to compute the attribute weights based on the information entropy method. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for network health performance evaluation of radial distribution system is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.

Operational efficiency evaluation of Urban and rural residents’ basic pension insurance system based on the triangular fuzzy neutrosophic GRA method

At present, the basic pension insurance system for urban and rural residents in China has played a positive role in guaranteeing the basic life of the elderly in urban and rural areas. At present, the basic pension insurance system for urban and rural residents is not perfect, and there is still a great lag in the formulation of cross-system and cross-regional policies. There are differences in treatment between groups, between regions and between urban and rural areas. The coverage is not comprehensive enough and there are still some people who are not included in the basic protection system, etc. People urgently need a social pension insurance system that can provide reliable and sustainable protection in their old age. The operational efficiency evaluation of urban and rural residents’ basic pension insurance systems is viewed as the multi-attribute decision-making (MADM). In this paper, the triangular fuzzy neutrosophic numbers grey relational analysis (TFNN-GRA) method is built based on the traditional grey relational analysis (GRA) and triangular fuzzy neutrosophic sets (TFNSs). Finally, a numerical example for operational efficiency evaluation of urban and rural residents’ basic pension insurance systems has been given and some comparisons are used to illustrate advantages of 2TLNN-GRA method.

A novel model based on the fuzzy Grey Relational Analysis (F-GRA) approach for selecting the appropriate high-speed train set

A novel model based on the fuzzy Grey Relational Analysis (F-GRA) approach for selecting the appropriate high-speed train set

Multi-objective design of laminated cooling configuration applied in gas turbine based on fuzzy grey relational analysis

Laminated cooling is a compound system consisting of different cooling units that can provide effective protection to the hot components in next generation gas turbines. In the present work, using validated numerical simulations, the influential levels of geometrical parameters in laminated cooling configuration (film hole diameter, pin-fin diameter, impingement hole diameter and film hole inclined angle) on multi-objective functions (overall cooling effectiveness, friction loss and temperature uniformity) are calculated and ranked by fuzzy grey relational analysis (FGRA). The FGRA results indicate that the film hole diameter is the primary influence factor on the overall cooling effectiveness and temperature uniformity, but insensitive to the friction loss. Based on this finding, two novel laminated cooling configurations with revised film-hole shapes, i.e., fan-shaped film holes and discrete rectangular film slots, are proposed to meet the multi-objective requirement. Through calculations, it is proved that the overall cooling effectiveness of the discrete film slots with a width of 0.5 mm can be increased by approximately 20%, whereas the additional friction loss is negligible (the increase of flow resistance coefficient is only 0.06 at mass flow ratio equals to 1.19%). Meanwhile, the acceptable temperature uniformity along with high overall cooling effectiveness, low friction loss can be obtained with the design of the fan-shaped film holes. The present work provides a novel analytical method for the multi-influence-factor problem and multi-objective design of complex laminated cooling system in gas turbine application.

Performance evaluation of family business strategic transition based on the 2-tuple linguistic neutrosophic number multiple attribute group decision making

Since 2010, China’s traditional industry has entered a critical stage of development and enterprise reform and development is imminent. Product homogenization is serious in this market, so that the competition among enterprises is fierce. At the same time, international brands continue to enter the Chinese consumption market, which intensifies the competition and seriously squeezes the market share of Chinese local brands. However, the popularization and development of the Internet and the change of people’s consumption concept and level make the market put forward higher requirements for the development of business operation and many traditional family enterprises have embarked on the road of transformation. It is of great significance and value to clarify the influence of internal factors of family enterprises on strategic transformation. The performance evaluation of family business strategic transition is really a multiple attribute group decision making (MAGDM) problems. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is proposed along with on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Firstly, the 2TLNNSs is introduced. Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for performance evaluation of family business strategic transition has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Grey relational analysis method for typhoon vulnerability assessment of civil engineering structures based on the 2-tuple linguistic neutrosophic number.

As one of the severe natural disasters, typhoon hazard brings tremendous tragedy to human beings. The foreland in the southeast of China is one of the most typhoon prone areas in the world. There are amount of damage of civil engineering structures induced by typhoon every year. Especially for the spacious villages, the low-rise buildings are vulnerable to typhoon so that many of them are destroyed regionally. The typhoon vulnerability assessment of civil engineering structures is a classical multiple attribute group decision making (MAGDM) issues. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNSs) with incomplete weight information. For deriving the weight information of the attribute, an optimization model is built on the basis of the GRA, by which the attribute weights can be decided. Then, the optimal alternative is chosen through calculating largest relative relational degree from the 2-tuple linguistic neutrosophic number positive ideal solution (2TLNNPIS) which considers both the largest grey relational coefficient (GRC) from the 2TLNNPIS and the smallest GRC form 2-tuple linguistic neutrosophic number negative ideal solution (2TLNN NIS). Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for typhoon vulnerability assessment of civil engineering structures has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Purchase decision making of garage equipment using an integrated fuzzy AHP and grey relation analysis method

PurposeAutomobile maintenance garages require varieties of equipment for their smooth functioning. However, the purchase of the right equipment from alternatives is a tough task as it depends on several economic, technical, and environmental considerations, etc. Moreover, there are different sellers for such equipment, whose features would be satisfying the purchase criteria in varying levels or degrees. Hence, this purchase decision becomes a complex decision-making problem.Design/methodology/approachAn integrated multi-criteria decision-making approach that includes the combination of fuzzy AHP (analytic hierarchy process) and GRA (grey relational analysis) is used for the purchase decision-making of garage equipment. Various purchase decision criteria regarding garage equipment are assimilated through literature and interaction with garage professionals. The weightage of each purchase criteria of garage equipment is derived using fuzzy AHP. After the establishment of weights, various equipment suppliers are evaluated according to their conformance to the criteria using the GRA method.FindingsThe methodology of FAHP helped in ranking the different purchasing criteria based on their importance. It follows the following sequence: cost of ownership, technical specifications, operational characteristics, reliability and maintenance, after-sales support, commercial features, environmental pollution, and end of life characteristics. GRA methodology has been applied for the purchase of the best common rail test bench among alternatives according to their fulfillment of the purchase criteria requirements that are evaluated by a team of experts.Originality/valueThe integrated approach developed in this work for garage equipment purchase will help garage management to prioritize each supplier of the equipment based on their level of conformance to the purchase criteria.

A binary fuzzy goal programming model with fuzzy parameters to select the fruits and vegetables market hall location for Istanbul

In urban areas, delivery of the products necessary to survive to the desired points has vital importance, and public distribution centers (PDCs) are one of the most important components of this system. In this paper, we present a hybrid method to analyze the locations of F&VMHs which is one of the PDCs types. Firstly, the alternative numbers have been decreased by interval-valued trapezoidal fuzzy grey relational analysis (IVTFGRA) method. Secondly, we develop a binary fuzzy goal programming (BFGP) model with fuzzy parameters to determine the most appropriate F&VMH locations by taking into consideration costs, arrival times and CO2 emission goals. Then, the BFGP model is converted to standard FGP model. In the last stage, the constraints with fuzzy parameters are transformed to crisp constraints with Peidro et al. (2010)’s methodology. The results show that current F&VMHs need to be moved to the locations that are more cost effective and out of the city center.

Effects of inlet velocity and structure parameters on the performance of a rotary diesel particulate filter for truck diesel engine based on fuzzy grey relational analysis

In this paper, a three-dimensional mathematical model of the rotary diesel particulate filter (RDPF) for truck diesel engine is established according to the fluid mechanics and porous media theory. The effects of inlet velocity and structure parameters (diameter ratio, expansion angle and filter length) on the flow uniformity in the RDPF are investigated. Furthermore, the Fuzzy grey relational analysis (FGRA) is employed to make a weight analysis of the influences of structure parameters on the regeneration performance and pressure drop of the RDPF. The results show that the velocity uniformity in the RDPF can be improved by properly reducing the inlet velocity, diameter ratio or expansion angle θ1. The capture-regeneration volume ratio with 8–10 is appropriate range for the structural optimization. Finally, the expansion angle θ1 is the most important structure parameter for the filter regeneration performance (regeneration time R = 0.8467; regeneration efficiency R = 0.6849) and the diameter ratio is the most important structure parameter for the pressure drop at the capture-regeneration “balance point” (R = 0.9352).

CFD simulation and optimization of slurry erosion of PDC bits

Polycrystalline diamond compact (PDC) bits are subjected to harsh erosive conditions under downhole. The erosion resistance partly determines the rate of penetration and footage of the bit. This work aims to investigate the effects of key factors on the erosion resistance of PDC bits through numerical simulation and field trials, and then to optimize the bit hydraulic designs. Computational Fluid Dynamics (CFD) and Discrete Phase Model (DPM) model were used to simulate the evacuation and impingement of cuttings on the bit body at the bottom of the well. The reliability of the numerical simulation was verified by the bit conditions after the field testing. Fuzzy grey relational analysis (FGRA) was then employed to rank the correlation degree of various affecting factors. The FGRA results show that the mass flow rate has the greatest effect on the average erosion rate of PDC bits, followed by the flow rate. The most erosion-vulnerable areas on the bit body are the webbings between cutters as well as the blade front. To improve the erosion resistance from the perspective of the bit hydraulic design, three novel hydraulic structures were proposed: the optimized nozzle orientation, the multi-ridge guide, and the extended curved nozzle. Numerical simulations indicate that all of these novel designs have great potential to enhance the erosion resistance of PDC bits with the customized extended curved nozzle showing the best.