Literatura académica sobre el tema "Whole engine modelling"

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Artículos de revistas sobre el tema "Whole engine modelling"

1

Chen, G. "Vibration modelling and verifications for whole aero-engine." Journal of Sound and Vibration 349 (August 2015): 163–76. http://dx.doi.org/10.1016/j.jsv.2015.03.029.

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2

Lolis, P., P. Giannakakis, V. Sethi, A. J. B. Jackson, and P. Pilidis. "Evaluation of aero gas turbine preliminary weight estimation methods." Aeronautical Journal 118, no. 1204 (2014): 625–41. http://dx.doi.org/10.1017/s0001924000009404.

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AbstractThe estimation of gas turbine engine weight during the preliminary or conceptual design phase is a key part of a Techno-economic Environmental Risk Analysis (TERA). Several methods that are available in the public domain are analysed and compared, in order to establish the physics driving them and their suitability for the weight estimation of modern gas turbine engines. Among the tested methods, only WATE managed to achieve acceptable accuracy for engine optimisation studies. This work demonstrates that the age and restrictions of existing ‘whole engine based’ methods, along with their dependency on old engine databases make them unsuitable for future and novel aero engines. A hybrid weight modelling approach is proposed as a solution permitting the creation of simple ‘whole engine based’ methods that do not depend on the availability of existing engine data, which are also subject to uncertainties and incoherencies.
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3

Giuntini, Sabrina, Antonio Andreini, Bruno Facchini, Marco Mantero, Marco Pirotta, and Sven Olmes. "Transient 2D FEM-fluid network coupling for thermo-mechanical whole gas turbine engine simulations: modelling features and applications." E3S Web of Conferences 197 (2020): 10012. http://dx.doi.org/10.1051/e3sconf/202019710012.

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In order to control the thermo-mechanical stresses that large heavy-duty power generation turbines have to face nowadays in their frequent operational transients, the analysis of the heat transfer between main flow, secondary air systems and structural components has to consider multi-physics coupled interactions, and has to be carried out with a whole engine modelling approach, simulating the entire machine in the real operating conditions. This is fundamental to guarantee a reliable assessment of life timing consumption and optimize clearances and temperature picks, through an efficient secondary air system design. It is here proposed a comprehensive description of modelling features and assumptions needed for the transient thermo-mechanical characterization of the whole engine through the application of a FEM-fluid network coupling methodology developed in collaboration with Ansaldo Energia and based on the open source code CalculiX®. In the present work the transient thermal modelling capability of the procedure will be verified through its application to a real whole engine geometry under a realistic transient cycle, comparing results with those of a reference FEM code.
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4

Giuntini, Sabrina, Antonio Andreini, Giulio Cappuccini, and Bruno Facchini. "Finite element transient modelling for whole engine-secondary air system thermomechanical analysis." Energy Procedia 126 (September 2017): 746–53. http://dx.doi.org/10.1016/j.egypro.2017.08.231.

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5

Giannella, Venanzio, Raffaele Sepe, Roberto Citarella, and Enrico Armentani. "FEM Modelling Approaches of Bolt Connections for the Dynamic Analyses of an Automotive Engine." Applied Sciences 11, no. 10 (2021): 4343. http://dx.doi.org/10.3390/app11104343.

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Three different finite element method (FEM) modelling approaches of bolt connections of a four-stroke, four-cylinder petrol engine are presented, and the related results compared in terms of preprocessing time and accuracy. A full 3D modelling of the bolt connections was preliminarily validated through a comparison with experimental test data available for the whole engine. Two further modelling approaches, a 1D approach and a contact-based (0D) approach, were benchmarked considering their influence on the accuracy for the dynamic analysis of an engine. Each of the three approaches presented pros and cons, even if the 1D modelling could be envisaged as the recommended one in most of cases.
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6

Altosole, M., and Massimo Figari. "Effective simple methods for numerical modelling of marine engines in ship propulsion control systems design." Journal of Naval Architecture and Marine Engineering 8, no. 2 (2011): 129–47. http://dx.doi.org/10.3329/jname.v8i2.7366.

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In the last year, the Department of Naval Architecture and Marine Engineering of Genoa University (now Department of Naval Architecture, Marine Technology and Electrical Engineering) collaborated to the design of the propulsion automation of two different naval vessels; within these projects the authors developed different ship propulsion simulators used to design and test the propulsion control schemes. In these time-domain simulators, each propulsion component is represented by a specific mathematical model, mainly based on algebraic and differential equations. One of the key aspects of the propulsion simulation is the engine dynamics. This problem in principle can be dealt with models based on thermodynamic principles, which are able to represent in detail the behaviour of many variables of interest (engine power and speed, air and gas pressures, temperatures, stresses, etc.). However, thermodynamic models are often characterized by a long computation-time and moreover their development usually requires the knowledge of specific engine information not always available. It is generally preferable to adopt simpler simulation models, for the development of which, very few kinds of information are necessary. In fact, for the rapid prototyping of control schemes, it is generally more important to model the whole plant (in a relatively coarse way) rather than the detailed model of some components. This paper deals with simple mathematical methods, able to represent the engine power or torque only, but they can be suitably applied to many types of marine engines in a straightforward way. The proposed simulation approaches derived from the authors’ experience, gained during their activity in the marine simulation field, and they are particularly suitable for a fast prototyping of the marine propulsion control systems. The validation process of these particular models, regarding a Diesel engine, a marine gas turbine and an electric motor, is illustrated based on the sea trials data and engine manufacturers’ data. Keywords: Dynamic simulation; marine engines performance; gas turbine; propulsion control. doi: http://dx.doi.org/10.3329/jname.v8i2.7366 Journal of Naval Architecture and Marine Engineering 8(2011) 129-147
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7

Zhang, Sanhua, Kunhao Tang, and Xinhong Zheng. "Modelling and optimal control of energy-saving-oriented automotive engine thermal management system." Thermal Science 25, no. 4 Part B (2021): 2897–904. http://dx.doi.org/10.2298/tsci2104897z.

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The thesis simulates the engine?s installation and uses conditions in the whole vehicle, such as the water tank, fan, the engine?s arrangement in the engine room, accessories and pipe-line connections, etc. to build a test bench for the engine thermal management system. According to the thermal management simulation analysis software KULI modelling, the article designs the bench test conditions according to the parameter input requirements of the thermal management simulation analysis software. The accuracy of the model is verified by comparing simulation and test data, and the NEDC driving cycle is used to simulate the performance of the vehicle cooling system to guide the selection and matching of thermal management system components.
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8

Rosli, M. Haziq Adham, M. Razali Hanipah, and Maurice Kettner. "The tuning of a small four-stroke spark ignition engine for flexible valve timings through numerical approach." MATEC Web of Conferences 255 (2019): 04004. http://dx.doi.org/10.1051/matecconf/201925504004.

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Variable valve timing has been implemented by various manufacturers to improve internal combustion engine performance while operating at wide speed and load ranges. A novel flexible valve timing system for a small four-stroke engine is currently under development by Automotive Engineering Research Group (AERG) in Universiti Malaysia Pahang (UMP). In this paper, a comprehensive intake and exhaust tuning for the flexible variable valve timing is presented. A numerical assessment has been conducted through one dimensional engine modelling and simulation using validated model. There are eight valve timing configurations investigated for the tuning for three main speed regions. The simulation shows a positive and significant impact to the engine performance in three approaches; namely late intake valve closing, early intake valve closing and late exhaust valve closing. These approaches sufficiently covered the whole range of engine speeds for optimum engine operational performance.
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9

Andreassi, L., S. Cordiner, and V. Rocco. "Modelling the early stage of spark ignition engine combustion using the KIVA-3V code incorporating an ignition model." International Journal of Engine Research 4, no. 3 (2003): 179–92. http://dx.doi.org/10.1243/146808703322223379.

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The evolution of early stages of homogeneous mixture combustion in spark ignition (SI) engines represents a critical period that greatly affects the whole combustion process. A proper description of this critical phase represents a major issue, which could strongly influence the overall model predictive capability (i.e. model ability to reproduce the real engine behaviour for a large range of operating conditions without any major tuning). Such requirements become even more important for the simulation of last-generation gasoline direct injection or lean stratified engines, where ignition could determine the functionality of the engine itself. In this paper, after a detailed analysis of the ignition physical process and its modelling issues, the predictive capability of the KIVA-3V code has been improved by substituting the original ignition procedure with a more detailed kernel evolution model based on the one presented by Herweg and Maly in 1992. The ignition model introduced in a KIVA-3V version already modified by the authors (re-zoning algorithm, combustion and turbulence models, cylinder wall heat transfer, etc.) has then been tested in order to assess its level of accuracy in describing this complex phenomenon, by varying the most critical engine operating conditions and keeping combustion tuning parameters unchanged. After comparing ignition model results with the corresponding ones presented by Herweg and Maly, a specific application of the overall model (KIVA-3V + ignition model + turbulent combustion model) has been made to perform an analysis of a compressed natural gas (CNG) fuelled engine for heavy-duty applications. To this aim, the in-cylinder combustion history and the related processes as the temperature distribution and NOx formation have been calculated and verified with reference to the experimental data measured in a wide range of operating conditions of an IVECO turbocharged engine.
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10

Siano, D., and R. Citarella. "Elastic Multi Body Simulation of a Multi-Cylinder Engine." Open Mechanical Engineering Journal 8, no. 1 (2014): 157–69. http://dx.doi.org/10.2174/1874155x01408010157.

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This paper analyzes the vibration behavior of an in-line 4-cylinder, 4-strokes, internal combustion turbocharged direct injection gasoline engine. A detailed multi-body numerical model of the engine prototype was used to characterize the whole engine dynamic behavior, in terms of forces and velocities. The crank train multi-body model was created starting from engine geometrical data, and the available combustion loads were employed for the Multi-Body Dynamic Simulation (MBDS). A combined usage of FEM and multi body methodologies were adopted for the dynamic analysis: both crankshaft and cylinder block were considered as flexible bodies, whereas all the other components were considered as rigid. The engine mounts were considered as flexible elements with given stiffness and damping. The hydrodynamic bearings were also modelling. The software LMS Virtual Lab (modules PDS and Motion) and ANSYS were used for the simulation.
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