The incidence of surge within axial compressors profoundly influences the efficacy and reliability of aero-engines. Conventional methodologies in engine design have predominantly concentrated on the precise and effici...
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The incidence of surge within axial compressors profoundly influences the efficacy and reliability of aero-engines. Conventional methodologies in engine design have predominantly concentrated on the precise and efficient forecasting of critical characteristics during such occurrences. This paper presents a novel approach for predicting the surge phenomenon in axial compressors. Surge is a major issue in the operation of axial compressors, causing reduced performance, increased wear and tear, and in some cases, complete machine failure. The proposed approach utilizes a neural network model based on the compressor's design data to forecast the behavior of the compressor's working map under off-design conditions. The model is verified using real data collected over five years during compressor operation, including the opening angle of the Inlet Guided Van (IGV), an important parameter often ignored or assumed to be fixed in previous studies. The results show that the neural network-based approach effectively predicts the compressor's behavior under different operating conditions, providing valuable insights into the onset of surge and offering a real-time surge prediction and control tool. The ability to predict the compressor's working map enables optimizing its performance and controlling instability. This model was validated by comparing its predictions with real operating conditions observed over five years across various compressor operating modes. As a result, this predictive model enables the safe operation of axial compressors by mitigating instability risks during operation. This study's findings highlight the model's effectiveness, as evidenced by the minimal error observed between the predicted and actual data collected across various compressor operating modes. The model exhibits a strong performance, characterized by a high regression factor of 0.92667 and a low mean squared error of 3.04465 x 10^-3. These numerical values underscore the reliability and pr
Due to the rapid growth of the Industrial IoT (IIoT), social media and digitization, and wireless communication technology in various sectors, data volume is increasing rapidly. Cloud computing is an emerging solution...
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In a network design, the control plane and the data plane are separated by the architectural concept of software defined networking (SDN). A centralised controller that serves as the only point of control for the whol...
In a network design, the control plane and the data plane are separated by the architectural concept of software defined networking (SDN). A centralised controller that serves as the only point of control for the whole network is introduced by the SDN architecture. The controller serves as a logically centralized entity in charge of communicating the appropriate rules to a switch's flow table. Using a single controller to handle a lot of flows becomes insufficient. A lot of large-scale networks have employed multi-controller SDN to meet their objectives. In this research, we use a multi-controller infinite buffer waiting queue model to analyze the system performance metrics. Both numerical and simulated assessments are used to illustrate the proposed model.
Efficient decision-making remains an open challenge in the research community,and many researchers are working to improve accuracy through the use of various computational *** this case,the fuzzification and defuzzifi...
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Efficient decision-making remains an open challenge in the research community,and many researchers are working to improve accuracy through the use of various computational *** this case,the fuzzification and defuzzification processes can be very *** is an effective process to get a single number from the output of a fuzzy *** defuzzification as a center point of this research paper,to analyze and understand the effect of different types of vehicles according to their *** this paper,the multi-criteria decision-making(MCDM)process under uncertainty and defuzzification is discussed by using the center of the area(COA)or ***,to find the best solution,Hurwicz criteria are used on the defuzzified ***-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy *** proposed technique considers all types of decision makers’perspectives such as optimistic,neutral,and pessimistic which is crucial in solving decisionmaking problems.A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among *** significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.
Dispatching vehicle fleets to serve flights is a key task in airport ground handling (AGH). Due to the notable growth of flights, it is challenging to simultaneously schedule multiple types of operations (services) fo...
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The reconstruction quality and shift multiplexing properties of self-referential holographic data storage (SR-HDS) with additional patterns which are designed with a target intensity of nonuniform distributions such a...
The reconstruction quality and shift multiplexing properties of self-referential holographic data storage (SR-HDS) with additional patterns which are designed with a target intensity of nonuniform distributions such as Gaussian are numerically evaluated.
作者:
Minh, Quang TranThai, Do ThanhDuc, Bui TienPhat, Nguyen Huu
Faculty of Computer Science and Engineering Department of Information Systems 268 Ly Thuong Kiet District 10 Ho Chi Minh City Viet Nam
Linh Trung Ward Thu Duc District Ho Chi Minh City Viet Nam
Faculty of Information Technology Department of Information Systems 300A Nguyen Tat Thanh Street Ward 13 District 4 HCMC Viet Nam Hanoi University of Science and Technology
School of Electrical and Electronic Engineering Hanoi Viet Nam
Data warehouse (DW) and Business Intelligence (BI) provide mechanisms for companies to exploit their data reaching the goal of making better, more efficient decisions. However, from the perspective of business users, ...
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This study presents a reliable model using Aspen Plus process simulator capable of performing a sensitivity analysis of the downdraft gasification linked to hydrogen production unit. Effects of key factors, including ...
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This study presents a reliable model using Aspen Plus process simulator capable of performing a sensitivity analysis of the downdraft gasification linked to hydrogen production unit. Effects of key factors, including gasification temperature and steam to biomass ratio (SBR) on the syngas composition, calorific value of syngas and hydrogen production are discussed and then the optimal conditions for maximum hydrogen production are extracted. The model is validated by experimental and other modeling data and found to be in great agreement. The sensitivity analysis results obtained by only using air as gasification agent indicate that higher temperatures are favorable for a product gas with higher hydrogen content and calorific value. Moreover, steam consumption as gasifying agent leads to increasing the hydrogen content and heating value of the syngas compared to the use of air as gasification agent. Finally, the results show that the optimal conditions to have the highest value of hydrogen output from sawdust downdraft gasification are 800˚C as gasifier temperature and 0.6 for SBR.
The in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine a...
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The Capacitated Vehicle Routing Problem (CVRP) is an NP-optimization problem (NPO) that arises in various fields including transportation and logistics. The CVRP extends from the Vehicle Routing Problem (VRP), aiming ...
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