Academic literature on the topic 'Turbina a ga'
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Journal articles on the topic "Turbina a ga"
Nikolić, Gojko. "Originalnost izuma Fausta Vrančića." Studia lexicographica 12, no. 23 (2019): 9–31. http://dx.doi.org/10.33604/sl.12.23.1.
Full textMrzljak, Vedran, Nikola Anđelić, Ivan Lorencin, and Sandi Sandi Baressi Šegota. "The influence of various optimization algorithms on nuclear power plant steam turbine exergy efficiency and destruction." Pomorstvo 35, no. 1 (June 30, 2021): 69–86. http://dx.doi.org/10.31217/p.35.1.8.
Full textYan, Tao, Xian Min Lin, and You Ping Zhong. "A Load Allocation Optimization among Turbine-Generators Based on GA-ACO." Advanced Materials Research 614-615 (December 2012): 1049–54. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.1049.
Full textLiu, Zheng, Xin Liu, Kan Wang, Zhongwei Liang, José A. F. O. Correia, and Abílio De Jesus. "GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades." Energies 12, no. 6 (March 15, 2019): 1026. http://dx.doi.org/10.3390/en12061026.
Full textAlawaad, Nasir Ahmed. "Steam turbine controllers design based on soft-computing techniques." IAES International Journal of Robotics and Automation (IJRA) 9, no. 4 (December 1, 2020): 281. http://dx.doi.org/10.11591/ijra.v9i4.pp281-291.
Full textSun, Wei, and Le Shen. "Comprehensive Evaluation of Wind Turbine Type Selection Based on GA-SVR Model." Advanced Materials Research 468-471 (February 2012): 579–82. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.579.
Full textNugroho, Herminarto, Nabilla Ananda Yusva, and Ortega Incon Marama Pandiangan. "Penerapan Metode Particle Swarm Optimization dan Genetic Algorithm pada Optimisasi Sudut Kelengkungan Turbin Air Banki Untuk Mendapatkan Efisiensi Daya Optimal." ENERGI & KELISTRIKAN 14, no. 1 (June 27, 2022): 82–89. http://dx.doi.org/10.33322/energi.v14i1.1636.
Full textJiao, Bin, and Zhi Wei Gao. "The Fault Diagnosis of Wind Turbine Gearbox Based on QGA—LSSVM." Applied Mechanics and Materials 543-547 (March 2014): 950–55. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.950.
Full textHe, Qing, and Jian Ding Zhang. "Application of Improved Genetic Algorithm in Maintenance Decision for Turbine-Generator Unit." Applied Mechanics and Materials 44-47 (December 2010): 2940–44. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.2940.
Full textWang, Li Ying, Wei Guo Zhao, and Chuan Hong Zhang. "Application of ANN Trained with GA in Energy Characteristics of Hydraulic Turbine." Advanced Materials Research 108-111 (May 2010): 692–95. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.692.
Full textDissertations / Theses on the topic "Turbina a ga"
Gobbato, Paolo. "Studio delle instabilità termoacustiche in un combustore di turbina a gas." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3427348.
Full textL'instabilità di combustione peggiora le prestazioni di un combustore a flusso continuo e pertanto deve essere considerata un fenomeno indesiderato. Fluttuazioni della pressione e del rilascio termico possono infatti causare vibrazioni meccaniche, rumore, formazione di punti caldi sulle pareti della camera di combustione e incremento delle emissioni inquinanti. La combustione instabile è particolarmente dannosa nei combustori per turbina a gas nei quali ampie oscillazioni di portata e di rilascio termico possono danneggiare irreparabilmente le parti fisse e rotanti della turbina. Nel lavoro che si presenta viene studiato il comportamento termoacustico di un combustore di turbina a gas. Il combustore esaminato è del tipo tubolare, con singolo bruciatore a fiamma diffusiva ed è stato modificato dal costruttore per essere alimentato non solo a gas naturale ma anche a idrogeno. Il processo di sviluppo è stato supportato da prove di combustione su scala reale eseguite su un banco prova in grado di riprodurre le condizioni di pieno carico. L’analisi termoacustica viene condotta seguendo una procedura di indagine basata sulla simulazione numerica del fenomeno mediante un codice numerico commerciale con modelli di turbolenza di tipo RANS. Nelle analisi numeriche i modelli numerici e le griglie di calcolo sono scelti in modo da minimizzare tempi e risorse di calcolo. In questo modo è possibile simulare un intervallo temporale sufficientemente ampio da consentire al sistema di evolvere liberamente fino alle condizioni di regime per poter così valutare l’eventuale presenza di instabilità termoacustiche. Le misure raccolte durante le prove sperimentali sono impiegate nei calcoli sia per l’imposizione delle condizioni al contorno sia per la valutazione dei risultati. I segnali di pressione registrati durante le simulazioni mostrano la permanenza di oscillazioni di pressione nel combustore caratterizzate da un’ampiezza piuttosto ridotta. Queste oscillazioni sono dunque ampiamente tollerabili dal sistema (la combustione è ovunque completa e non vi sono fenomeni di estinzione di fiamma e di surriscaldamento delle pareti del combustore), in accordo con quanto osservato durante le prove sperimentali. Gli spettri calcolati al termine delle simulazioni sono comparati con gli spettri acquisiti durante le prove di combustione. Dal confronto emerge una sostanziale corrispondenza tra i modi di vibrare calcolati e quelli misurati al banco prova.
Odofin, Sarah. "Robust fault diagnosis by GA optimisation with applications to wind turbine systems and induction motors." Thesis, Northumbria University, 2016. http://nrl.northumbria.ac.uk/36111/.
Full textBONO, ANDREA. "Criticità nelle esigenze e nelle offerte energetiche: il ruolo rilevante della progettazione e della gestione ottimizzata delle macchine a fluido e dei sistemi per la conversione di energia. Aspetti applicativi nella piccola fornitura di energia e nella propulsione navale." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046981.
Full textCAPPELLETTI, ALESSANDRO. "On the study of hydrogen fueling in premixed gas turbine combustor chamber." Doctoral thesis, 2013. http://hdl.handle.net/2158/794611.
Full textANDREINI, ANTONIO. "SVILUPPO DI MODELLI NUMERICI PER L’ANALISI DELLA COMBUSTIONE TURBOLENTA PREMISCELATA NELLE TURBINE A GAS." Doctoral thesis, 2004. http://hdl.handle.net/2158/771852.
Full textSiano, P., and Geev Mokryani. "Evaluating the Benefits of Optimal Allocation of Wind Turbines for Distribution Network Operators." 2015. http://hdl.handle.net/10454/9223.
Full textThis paper proposes a hybrid optimization method for optimal allocation of wind turbines (WTs) that combines a fast and elitist multiobjective genetic algorithm (MO-GA) and the market-based optimal power flow (OPF) to jointly minimize the total energy losses and maximize the net present value associated with the WT investment over a planning horizon. The method is conceived for distributed-generator-owning distribution network operators to find the optimal numbers and sizes of WTs among different potential combinations. MO-GA is used to select, among all the candidate buses, the optimal sites and sizes of WTs. A nondominated sorting GA II procedure is used for finding multiple Pareto-optimal solutions in a multiobjective optimization problem, while market-based OPF is used to simulate an electricity market session. The effectiveness of the method is demonstrated with an 84-bus 11.4-kV radial distribution system.
Book chapters on the topic "Turbina a ga"
Zhang, Jianxin, and Zhange Zhang. "GA Based Optimal Design for Megawatt-Class Wind Turbine Gear Train." In Lecture Notes in Computer Science, 323–32. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21963-9_30.
Full textSrivastava, Tushar, and M. M. Tripathi. "Predictive Analysis of Wind Turbine Output Power Using Support Vector Machine(SVM) Based on Genetic Algorithm(GA)." In Lecture Notes in Electrical Engineering, 117–33. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6840-4_10.
Full textSiano, P., G. Rigatos, and A. Piccolo. "Active Distribution Networks and Smart Grids: Optimal Allocation of Wind Turbines by Using Hybrid GA and Multi-Period OPF." In Atlantis Computational Intelligence Systems, 579–99. Paris: Atlantis Press, 2012. http://dx.doi.org/10.2991/978-94-91216-77-0_27.
Full textHamdan, Mohammad, and Mohammad Hassan Abderrazzaq. "Optimization of Small Wind Turbines Using Genetic Algorithms." In Renewable and Alternative Energy, 1484–99. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1671-2.ch052.
Full textConference papers on the topic "Turbina a ga"
Chen, Xiaomin, and Ramesh Agarwal. "Optimization of Flatback Airfoils for Wind Turbine Blades." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90373.
Full textChen, Xiaomin, and Ramesh Agarwal. "Optimization of Flatback Airfoils for Wind Turbine Blades Using a Multi-Objective Genetic Algorithm." In ASME 2012 6th International Conference on Energy Sustainability collocated with the ASME 2012 10th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/es2012-91004.
Full textKim, Youjin, Ali Al-Abadi, and Antonio Delgado. "Strategic Blade Shape Optimization for Aerodynamic Performance Improvement of Wind Turbines." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56836.
Full textChi, Zhongran, Jing Ren, and Hongde Jiang. "Cooling Structure Optimization for a Rib-Roughed Channel in a Turbine Rotor Blade." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94527.
Full textSampath, Suresh, Stephen Ogaji, and Riti Singh. "Improving Power Plant Availability Through Advanced Engine Diagnostic Techniques." In 2002 International Joint Power Generation Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/ijpgc2002-26080.
Full textDash, A. K., D. K. Agarwalla, H. C. Das, M. K. Pradhan, and S. K. Bhuyan. "Application of Genetic Algorithm for Fault Detection in Cracked Composite Structure." In ASME 2014 Gas Turbine India Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gtindia2014-8269.
Full textSafari, A., H. G. Lemu, and M. Assadi. "A Novel Combination of Adaptive Tools for Turbomachinery Airfoil Shape Optimization Using a Real-Coded Genetic Algorithm." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94093.
Full textQian, Dianwei, Jianqiang Yi, Xiangjie Liu, and Xin Li. "GA-based fuzzy sliding mode governor for hydro-turbine." In 2010 International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2010. http://dx.doi.org/10.1109/icicip.2010.5565249.
Full textGaravello, A., M. Russo, Claudio Comis da Ronco, R. Ponza, and E. Benini. "Aerodynamic Shape Optimization of Air-Intakes of a Helicopter Turboshaft." In ASME 2012 Gas Turbine India Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gtindia2012-9506.
Full textPaul, Diplina, and Abhisek Banerjee. "Genetic Algorithm Based Optimization Technique for Savonius-Style Wind Turbine." In ASME 2021 Gas Turbine India Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gtindia2021-76041.
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