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1
Hendricks, Elbert. "Isothermal vs. Adiabatic Mean Value SI Engine Models." IFAC Proceedings Volumes 34, no. 1 (March 2001): 363–68. http://dx.doi.org/10.1016/s1474-6670(17)34424-5.
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HONG, Munan. "On-board Torque Estimation Base on Mean Value SI Engine Models." Journal of Mechanical Engineering 45, no. 04 (2009): 290. http://dx.doi.org/10.3901/jme.2009.04.290.
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Dickinson, Paul, Dariusz Cieslar, Keith Glover, Nick Collings, Yukio Yamashita, Yusuke Yashiro, and Toru Hoshi. "On-Engine Validation of Mean Value Models for IC Engine Air-Path Control and Evaluation." IFAC Proceedings Volumes 47, no. 3 (2014): 2987–93. http://dx.doi.org/10.3182/20140824-6-za-1003.01984.
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Zhang, Sheng Kai, Ren Yun Sun, Hao Ming Yan, and Ke Ren Wang. "Optimization Calibration of Engine Ignition Advance Angle Based on Engine Model." Applied Mechanics and Materials 483 (December 2013): 446–52. http://dx.doi.org/10.4028/www.scientific.net/amm.483.446.
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Based on the mean-value theorem of the engine, the mathematical models can be created for the four-stoke-cycle-CNG engine, style of YN30QNE. Furthermore, while the mean-value models set the basis for the external loading resistance model controller, the adjust-dimention-burning engine models give birth to the models, as well as the MAP figures, of the engines controlling of the advance angle of ignition. Finally what the tests show us are as follows. Firstly the advance angle of ignition does the same, as the rotating velocity increases, and on the condition of the same rotating velocity, the best suited advanced angle of ignition decreases reversely with the growing loading resistance of the engine. Secondly it not only brings us the rarely precise original MAP figures of the advance angle of ignition, but also shortens the development cycle. Lastly, in the process of the calibration, optimal functions are used to conduct the PID optimal designing for the external loading resistance controller, which makes the system converge faster, improves the efficiency of the calibration as well as optimizes the results of the calibration.
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Tian, Zhe, Xin Ping Yan, and Ye Ping Xiong. "Turbocharged Two-Stroke Diesel Engine of Large Vessels Modeling and Simulation." Applied Mechanics and Materials 235 (November 2012): 233–38. http://dx.doi.org/10.4028/www.scientific.net/amm.235.233.
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In this article, according to the work principle of turbocharged two-stroke diesel engine, the characteristic of volume method model is referenced to package the diesel engine and the packaged model is calculated. According to the Matlab/Simulink software platform, the model will be combined to form a full mean value engine model and join speed controller to control diesel engine speed. The variation of diesel engine’s various performance parameter and the dynamic characteristics based on the speed control law will be observed, which means reaching better purpose of using diesel engine. In the process of mean value engine model design, joining a scavenging coefficient and improving the excess air ratio will increase simulation precision. By means of the correlation analysis, the diesel engine models complying with the control requirements can be determined.
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Wu, Y.-Y., B.-C. Chen, and F.-C. Hsieh. "Modulization of four-stroke single-cylinder spark-ignition air-cooled engine models." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 221, no. 8 (August 1, 2007): 1015–26. http://dx.doi.org/10.1243/09544070jauto184.
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In order to satisfy different requirements for engine design and real-time simulation, modulization technology is used in this paper to establish the engine model for small-scale engines. The model consists of simple and complex modules of charging, torque, friction, and crankshaft dynamics, which are established in Matlab/Simulink and verified using the experimental data. Different sets of these modules can be selected for various applications. For engine design, a complex model, which consists of the wave-action charging module and the mean-value combustion module, is employed to study the effects of inlet and exhaust systems on torque output performance. For real-time simulation, different levels of complexity can be selected according to the hardware-in-the-loop requirement of the control verification.
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Katrašnik, Tomaž. "Transient Momentum Balance—A Method for Improving the Performance of Mean-Value Engine Plant Models." Energies 6, no. 6 (June 14, 2013): 2892–926. http://dx.doi.org/10.3390/en6062892.
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Gangopadhyay, Anupam, and Peter Meckl. "Modeling and Validation of a Lean Burn Natural Gas Engine." Journal of Dynamic Systems, Measurement, and Control 123, no. 3 (May 19, 1998): 425–30. http://dx.doi.org/10.1115/1.1386790.
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In this paper, a control-oriented model of a medium-duty throttle-body natural gas engine is developed. The natural gas engine uses lean-burn technology without exhaust gas recirculation (EGR). The dynamic engine model differs from models of gasoline engines by including the natural gas fuel dynamics in the intake manifold. The model is based on a mean value concept and has three state variables: intake manifold pressure, fuel fraction in the intake manifold and the engine rotational speed. The resulting model has been validated in steady-state and transient operation over the usual operating range of the engine between 800 rpm and 2600 rpm with air/fuel ratios ranging between 18.0 and 24.0.
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Guardiola, Carlos, Benjamin Pla, David Blanco-Rodriguez, and Pierre Olivier Calendini. "ECU-oriented models for NOx prediction. Part 1: a mean value engine model for NOx prediction." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 229, no. 8 (November 14, 2014): 992–1015. http://dx.doi.org/10.1177/0954407014550191.
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Tian, Fengjun, Yang Yang, Zhenxing Mao, and Wenyue Tang. "Forecasting daily attraction demand using big data from search engines and social media." International Journal of Contemporary Hospitality Management 33, no. 6 (May 18, 2021): 1950–76. http://dx.doi.org/10.1108/ijchm-06-2020-0631.
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Purpose This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media. Design/methodology/approach Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy. Findings Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error. Practical implications Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions. Originality/value This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.
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Siviero, C., R. Scattolini, A. Gelmetti, L. Poggio, and G. Serra. "Analysis & Validation of Mean Value Models for SI IC-Engines." IFAC Proceedings Volumes 28, no. 1 (March 1995): 1–6. http://dx.doi.org/10.1016/s1474-6670(17)45666-7.
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Wang, Yuan Qing, Guang Ren, Zeng Yan, and Yang Hui Tan. "The Application of Analytic Hierarchy Process in the Evaluation of Simulation Models of Marine Diesel Engine." Applied Mechanics and Materials 525 (February 2014): 203–9. http://dx.doi.org/10.4028/www.scientific.net/amm.525.203.
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Facing to the problem of hierarchical structure decision analysis which is made of scheme level + factor level + target level, the analytic hierarchy process gives a whole set of solution and process. This method is used to evaluate diesel engine simulation model. Evaluate original mean value model of large-scale low-speed marine diesel engine and the new one by this method. Calculated results prove this method is applicable.
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Kayaalp, Kiyas, and Sedat Metlek. "Prediction of burning performance and emissions indexes of a turboprop motor with artificial neural network." Aircraft Engineering and Aerospace Technology 93, no. 3 (March 18, 2021): 394–409. http://dx.doi.org/10.1108/aeat-08-2020-0177.
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Purpose The purpose of this paper is to estimate different air–fuel ratio motor shaft speed and fuel flow rates under the performance parameters depending on the indices of combustion efficiency and exhaust emission of the engine, a turboprop multilayer feed forward artificial neural network model. For this purpose, emissions data obtained experimentally from a T56-A-15 turboprop engine under various loads were used. Design/methodology/approach The designed multilayer feed forward neural network models consist of two hidden layers. 75% of the experimental data used was allocated as training, 25% as test data and cross-referenced by the k-fold four value. Fuel flow, rotate per minute and air–fuel ratio data were used for the training of emission index input values on the designed models and EICO, EICO2, EINO2 and EIUHC data were used on the output. In the system trained for combustion efficiency, EICO and EIUHC data were used at the input and fuel combustion efficiency data at the output. Findings Mean square error, normalized mean square error, absolute mean error functions were used to evaluate the error obtained from the system as a result of the test. As a result of modeling the system, absolute mean error values were 0.1473 for CO, 0.0442 for CO2, 0.0369 for UHC, 0.0028 for NO2, success for all exhaust emission data was 0.0266 and 7.6165e-10 for combustion efficiency, respectively. Originality/value This study has been added to the literature T56-A-15 turboprop engine for the current machine learning methods to multilayer feed forward neural network methods, exhaust emission and combustion efficiency index value calculation.
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Pasternak, Michal, Fabian Mauss, Christian Klauer, and Andrea Matrisciano. "Diesel engine performance mapping using a parametrized mixing time model." International Journal of Engine Research 19, no. 2 (July 17, 2017): 202–13. http://dx.doi.org/10.1177/1468087417718115.
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A numerical platform is presented for diesel engine performance mapping. The platform employs a zero-dimensional stochastic reactor model for the simulation of engine in-cylinder processes. n-Heptane is used as diesel surrogate for the modeling of fuel oxidation and emission formation. The overall simulation process is carried out in an automated manner using a genetic algorithm. The probability density function formulation of the stochastic reactor model enables an insight into the locality of turbulence–chemistry interactions that characterize the combustion process in diesel engines. The interactions are accounted for by the modeling of representative mixing time. The mixing time is parametrized with known engine operating parameters such as load, speed and fuel injection strategy. The detailed chemistry consideration and mixing time parametrization enable the extrapolation of engine performance parameters beyond the operating points used for model training. The results show that the model responds correctly to the changes of engine control parameters such as fuel injection timing and exhaust gas recirculation rate. It is demonstrated that the method developed can be applied to the prediction of engine load–speed maps for exhaust NOx, indicated mean effective pressure and fuel consumption. The maps can be derived from the limited experimental data available for model calibration. Significant speedup of the simulations process can be achieved using tabulated chemistry. Overall, the method presented can be considered as a bridge between the experimental works and the development of mean value engine models for engine control applications.
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Tu, Huan, and Hui Chen. "Modeling of a Compressor's Performance Map by Fitting Function Methodology." Advanced Materials Research 779-780 (September 2013): 1194–98. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.1194.
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To build a precise compressor model is a critical issue in the modeling and simulation of a turbocharged diesel engine. This paper proposes an exponential function for compressor flow model and a polynomial function for efficiency model. A case study of a compressor map for TCA88 turbocharger is implemented to verify the proposed model. Fitting results show that the compressor model performs in accordance with the manufacture compressor map. The compressor model can be applied to mean value models of turbocharged engines for non-linear control and state estimation.
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Anjum, Raheel, Aamer Iqbal Bhatti, Ahmed Yar, and Qadeer Ahmed. "Cyclic torque imbalance detection in gasoline engines using a uniform second-order sliding mode observer." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 13 (February 2, 2019): 3515–27. http://dx.doi.org/10.1177/0954407018820399.
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Engine torque imbalance is a wide-ranging problem which is caused due to variance of the combustion mixture in the engine cylinder. In this research work, cyclic torque imbalance detection is carried out by formulating a uniform second-order sliding mode observer using the First Principle–based Engine Model. Oscillations in the crankshaft angular speed were modeled in the novel First Principle–based Engine Model, which were suppressed in the Mean Value Engine Models. Cyclic torque imbalance is simulated at multiple instances by varying the injected fuel mass. Estimation of the net piston force is carried out for cyclic torque imbalance detection using rotational dynamics of the engine model. This force is treated as unknown input to the torque production subsystem of the model. Cyclic torque imbalance detection is validated using the GT-Power engine model. Variations in the cyclic torque were detected proximate to actual values which demonstrated validity of the proposed technique.
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Llamas, Xavier, and Lars Eriksson. "Control-oriented modeling of two-stroke diesel engines with exhaust gas recirculation for marine applications." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 233, no. 2 (May 11, 2018): 551–74. http://dx.doi.org/10.1177/1475090218768992.
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Large marine two-stroke diesel engines are widely used as propulsion systems for shipping worldwide and are facing stricter NO x emission limits. Exhaust gas recirculation is introduced to these engines to reduce the produced combustion NO x to the allowed levels. Since the current number of engines built with exhaust gas recirculation is low and engine testing is very expensive, a powerful alternative for developing exhaust gas recirculation controllers for such engines is to use control-oriented simulation models. Unfortunately, the same reasons that motivate the use of simulation models also hinder the capacity to obtain sufficient measurement data at different operating points for developing the models. A mean value engine model of a large two-stroke diesel with exhaust gas recirculation that can be simulated faster than real time is presented and validated. An analytic model for the cylinder pressure that captures the effects of changes in the fuel control inputs is also developed and validated with cylinder pressure measurements. A parameterization procedure that deals with the low number of measurement data available is proposed. After the parameterization, the model is shown to capture the stationary operation of the real engine well. The transient prediction capability of the model is also considered satisfactory which is important if the model is to be used for exhaust gas recirculation controller development during transients. Furthermore, the experience gathered while developing the model about essential signals to be measured is summarized, which can be very helpful for future applications of the model. Finally, models for the ship propeller and resistance are also investigated, showing good agreement with the measured ship sailing signals during maneuvers. These models give a complete vessel model and make it possible to simulate various maneuvering scenarios, giving different loading profiles that can be used to investigate the performance of exhaust gas recirculation and other controllers during transients.
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Luo, Jun, Qin Teng, and Peng An. "The Study of Signal Characteristics of Critical Sensors on a Coal-Bed Gas Engine." Applied Mechanics and Materials 130-134 (October 2011): 1109–13. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.1109.
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In order to solve the signal processing problems appeared in conventional engine control systems, the Discrete Fourier Transform (DFT) was used for frequency domain analysis, on this basis, it’s possible to make suggestions as to the selection of real-time sampling frequency and sensor signal averaging strategies as well as analog/digital anti-aliasing filter parameters in engine control system. To describe pumping fluctuations existing in model-based engine control system for a coal-bed engine, the pumping fluctuation models of air and fuel gas mass flow rate in intake manifold during steady-state operations were established based on the result of signal frequency domain analysis, thus it’s possible to optimize the conventional Mean Value Engine Model.
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Kocher, Michael F., Bryan J. Smith, Roger M. Hoy, Jeffrey C. Woldstad, and Santosh K. Pitla. "Fuel Consumption Models for Tractor Test Reports." Transactions of the ASABE 60, no. 3 (2017): 693–701. http://dx.doi.org/10.13031/trans.12121.
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Abstract. Five models for estimating fuel consumption for agricultural tractors with partial drawbar loads were compared. Data were collected from eight John Deere tractors, JD 7230R (e23), 7250R (e23), 7270R (e23), 7290R (e23), 8320R (16 speed), 7290R (IVT), 8345RT (IVT), 8370R (IVT), on the drawbar test track at the Nebraska Tractor Test Lab. The tractors were tested with seven load levels per speed at three different travel speeds as close as possible to 7.5, 10, and 13 km h-1. The IVT tractors were operated in auto mode, and the geared tractors were shifted up three gears and throttled back to the same travel speeds as obtained with the original gear (before shifting up) at maximum drawbar power. The seven loads were selected at 30%, 40%, 50%, 60%, 70%, 75%, and 80% of the drawbar pull at maximum power and rated engine speed at the selected travel speed. Model 1 (fuel consumption as a linear function of drawbar power on concrete), currently used in OECD Code 2, Section 4.4.8, resulted in a separate equation for each speed tested. When regression mean square errors were used for statistical comparison of the five fuel consumption models, model 5 (fuel consumption as a linear function of drawbar power and travel speed on concrete, and engine speed) was not significantly different from the model currently used in OECD Code 2, Section 4.4.8 (model 1, fuel consumption as a linear function of drawbar power on concrete, with separate equations specific to the three speeds tested). The simplest model (model 2), which used a single equation for fuel consumption as a linear function of drawbar power on concrete over the range of speeds tested, had significantly higher regression mean square errors compared to model 1 for half of the eight tractors tested. Model 5 (fuel consumption as a linear function of drawbar power and travel speed on concrete, and engine speed) was determined to be the best of the five models for estimating fuel consumption, with a single equation applicable over the range of speeds tested. Model 3 (fuel consumption as a linear function of drawbar power and travel speed on concrete) provided a statistically equivalent fuel consumption estimate to model 5 without the drawback of requiring an input value for engine speed. Keywords: Drawbar power, Engine speed, Fuel consumption, Model, Partial drawbar loads, Tractors, Travel speed.
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Kyprianou, A., J. Giacomin, K. Worden, M. Heidrich, and J. Bocking. "Differential evolution based identification of automotive hydraulic engine mount model parameters." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 214, no. 3 (March 1, 2000): 249–64. http://dx.doi.org/10.1243/0954407001527402.
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Hydraulic engine mounts are commonly used in automotive applications, and numerical models exist for performing full-vehicle noise, vibration and harshness (NVH) studies by means of multibody simulation. The parameters of these models are usually determined by the manufacturer from first-principle numerical calculations, or by means of direct testing of the individual components. This paper describes, instead, a four-step identification method developed to determine the parameter values of a specific hydromount numerical model, the Freudenberg hydromount equations, a set of highly non-linear piecewise-continuous differential equations. The identification procedure is based on two concepts, the first being the use of the differential evolution algorithm for determining optimal parameter values, while the second is the use of data obtained from a series of experimental tests of progressively higher displacement amplitude. Identified parameters provide models whose mean square errors between the calculated output force time history and the experimentally measured force time history are typically of the order of 1-2 per cent.
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Son, C. H., T. A. Shethaji, C. J. Rutland, H. Barths, A. Lippert, and S. H. El Tahry. "Application of non-linear turbulence models in an engine-type flow configuration." International Journal of Engine Research 8, no. 5 (October 1, 2007): 449–64. http://dx.doi.org/10.1243/14680874jer00707.
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Three non-linear k-ε models were implemented into the multi-dimensional computational fluid dynamics code GMTEC with the purpose of comparing them with existing linear k-ε models including renormalization group variations. The primary focus of the present study is to evaluate the potential of these non-linear models in engineering applications such as the internal combustion engine. The square duct flow and the backwards-facing step flow were two simple test cases chosen for which experimental data are available for comparison. Successful simulations for these cases were followed by simulations of an engine-type intake flow to evaluate the performance of the non-linear models in comparison with experimental data and the standard linear k-ε models as well as two renormalization group types. All the non-linear models are found to be an improvement over the standard linear model, but mostly in simple flows. For more complex flows, such as the engine-type case, only the cubic non-linear models appear to make a modest improvement in the mean flow but without any improvement in the root-mean-square values. These improvements are overshadowed by the stiffness of the cubic models and the requirements for smaller time steps. The contributions of each non-linear term to the Reynolds stress tensor are analysed in detail in order to identify the different characteristics of the different non-linear models for engine intake flows.
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Prayogo, Janny Eka, Aries Suharso, and Adhi Rizal. "Analisis Perbandingan Model Matrix Factorization dan K-Nearest Neighbor dalam Mesin Rekomendasi Collaborative Berbasis Prediksi Rating." Jurnal Informatika Universitas Pamulang 5, no. 4 (December 31, 2021): 506. http://dx.doi.org/10.32493/informatika.v5i4.7379.
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Rating is a form of assessment of the likes or dislikes of a user or customer for an item. Where the higher the rating number given, the item is preferred by customers or users. In the recommendation engine, a set of ratings can be predicted and used as an object to generate a recommendation by the Collaborative Filtering method. In the Collaborative Filtering method, there is a rating prediction model, namely the Matrix Factorization and K-Nearest Neighbor models. This study analyzes the comparison of the two prediction models based on the value of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and the prediction results generated using the movielens film rating dataset. From the analysis and testing results, it was found that MAE = 0.6371 and RMSE = 0.8305 for the Matrix Factorization model, while MAE = 0.6742 and RMSE = 0.8863 for the K-Nearest Neighbor model. The best model is Matrix Factorization because the MAE and RMSE values are lower than the K-Nearest Neighbor model and have the closest predicted rating results from the original rating value.
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K. Parida, M., and I. Routaray. "RSM Analysis of In-cylinder Pressure in a DICI Engine Fueled with Argemone Mexicana Biodiesel-diesel Blends." International Journal of Engineering & Technology 7, no. 4.5 (September 22, 2018): 28. http://dx.doi.org/10.14419/ijet.v7i4.5.20003.
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In the current analysis engine load, compression ratio and bio-diesel blends are taken as input parameters to evaluate the combustion parameter i.e maximum in cylinder pressure with methyl esters of Argemone Mexicana and its diesel blends in a VCR multi-fuel engine. Response surface method of Full Factorial Design (FFD) is used in the present study for modelling and analyzing the combustion parameter with Minitab-14.0 software. The response surface and contour plots of different models are plotted by holding mean value of other input parameter. The developed model, data regression, significance analysis and individual model coefficients were studied and presented for model validation.
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Tadros, Mina, Manuel Ventura, and C. Guedes Soares. "Data Driven In-Cylinder Pressure Diagram Based Optimization Procedure." Journal of Marine Science and Engineering 8, no. 4 (April 21, 2020): 294. http://dx.doi.org/10.3390/jmse8040294.
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An engine optimization model is developed to fit the calculated in-cylinder pressure diagram to the experimental data by finding the optimal values of the start angle of injection and the amount of injected fuel for different engine loads. Firstly, the engine model is built in Ricardo Wave software and some parts are calibrated using data collected from the manufacturer. Then, an optimization process is performed based on the fitness function that includes the objective of the study and the penalty functions to express constraints. This optimization environment simulates the performance of a marine generator system for three different loads by minimizing the mean absolute percentage error (MAPE) between the in-cylinder pressure simulated data and the measured data along 40 degrees of the combustion process and by verifying the firing pressure and the engine brake power. The percentage of error between the calculated and the real thermodynamic data does not exceed 3.4% and the MAPE between the calculated and the real in-cylinder pressure diagram along the combustion process does not exceed 5.7% for the different loads. The proposed method can be further used to find the optimal value of different input parameters during the calibration process of different engine numerical models.
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Shamekhi, Amir-Mohammad, and Amir H. Shamekhi. "A new approach in improvement of mean value models for spark ignition engines using neural networks." Expert Systems with Applications 42, no. 12 (July 2015): 5192–218. http://dx.doi.org/10.1016/j.eswa.2015.02.031.
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Żelazny, Katarzyna. "An Approximate Method for Calculation of Mean Statistical Value of Ship Service Speed on a Given Shipping Line , Useful in Preliminary Design Stage." Polish Maritime Research 22, no. 1 (January 1, 2015): 28–35. http://dx.doi.org/10.1515/pomr-2015-0005.
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Abstract During ship design, its service speed is one of the crucial parameters which decide on future economic effects. As sufficiently exact calculation methods applicable to preliminary design stage are lacking the so called contract speed which a ship reaches in calm water is usually applied. In the paper [11] a parametric method for calculation of total ship resistance in actual weather conditions (wind, waves, sea current), was presented. This paper presents a parametric model of ship propulsion system (screw propeller - propulsion engine) as well as a calculation method, based on both models, of mean statistical value of ship service speed in seasonal weather conditions occurring on shipping lines. The method makes use of only basic design parameters and may be applied in preliminary design stage.
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Obeidat, Anas, Teis Schnipper, Kristian M. Ingvorsen, Sajjad Haider, Knud Erik Meyer, Stefan Mayer, and Jens H. Walther. "Large eddy simulations of the influence of piston position on the swirling flow in a model two-stroke diesel engine." International Journal of Numerical Methods for Heat & Fluid Flow 24, no. 2 (February 25, 2014): 325–41. http://dx.doi.org/10.1108/hff-09-2011-0189.
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Purpose – The purpose of this paper is to study the effect of piston position on the in-cylinder swirling flow in a simplified model of a large two-stroke marine diesel engine. Design/methodology/approach – Large eddy simulations with four different models for the turbulent flow are used: a one-equation model, a dynamic one-equation model, a localized dynamic one-equation model and a mixed-scale model. Simulations are carried out for two different geometries corresponding to 100 and 50 percent open scavenge ports. Findings – It is found that the mean tangential profile inside the cylinder changes qualitatively with port closure from a Lamb-Oseen vortex profile to a solid body rotation, while the axial velocity changes from a wake-like profile to a jet-like profile. The numerical results are compared with particle image velocimetry measurements, and in general, the authors find a good agreement. Research limitations/implications – Considering the complexity of the real engine, the authors designed the engine model using the simplest configuration possible. The setup contains no moving parts, the combustion is neglected and the exhaust valve is discarded. Originality/value – Studying the flow in a simplified engine model, the setup allows studies of fundamental aspects of swirling flow in a uniform scavenged engine. Comparing the four turbulence models, the local dynamic one-equation model is found to give the best agreement with the experimental results.
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KOWALSKI, Jerzy. "The model of combustion process in the marine 4-stroke engine for exhaust gas composition assessment." Combustion Engines 165, no. 2 (May 1, 2016): 60–69. http://dx.doi.org/10.19206/ce-2016-208.
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The paper presents the model of combustion process in the marine, turbocharged, 4-stroke and Diesel engine. The main target of modeling is the assessment of the exhaust gas composition. Presented multi-zone, 3-D model of combustion process consists of the following sub-models of processes: the fuel injection, the brake-up and the evaporation of fuel and the turbulence flow and the heat transfer phenomena. Presented model basis on the 3Z-ECFM mechanism of combustion and the initial and boundary conditions collected during direct measurements. The positive validation of the calculation results are obtained for mean and maximum value of the combustion pressure and values of oxygen and nitric oxides fractions in the exhaust gas. Unfortunately, fractions of carbon compounds in the exhaust gas are not properly calculated.
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Sivertsson, Martin, and Lars Eriksson. "Optimal stationary control of diesel engines using periodic control." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 4 (August 5, 2016): 457–75. http://dx.doi.org/10.1177/0954407016640631.
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Measurements and optimal control are used to study whether the fuel economy of a diesel engine can be improved through periodic control of the wastegate, illustrating how modern optimal control tools can be used to identify non-trivial solutions that can improve performance. The measurements show that the pumping torque of the engine is changed when the wastegate is controlled in a periodic manner versus stationary even if the mean position is the same. If this decreases the fuel consumption or not is seen to be frequency and operating point dependent. The measurements indicate that the phenomenon occurs in the time scales capturable by mean value engine models (MVEM). The operating points are further analyzed using a MVEM and optimal control. It is shown that whether the optimal solution exhibits periodic oscillations or not is operating point dependent, but is not due to the instantaneous nature of the controls. Even if an actuator model is added the oscillations persist for reasonable time constants, the frequency of the oscillations is however affected. Further it is shown that the periodic control can be predicted by optimal periodic control theory and that the frequency of the control affects the resulting efficiency.
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Товкач, Сергій Сергійович. "ПІДХІД НЕЧІТКОЇ КЛАСТЕРИЗАЦІЇ В РОЗПОДІЛЕНИХ ІНФОРМАЦІЙНИХ СИСТЕМАХ АВІАЦІЙНИХ ДВИГУНІВ." Aerospace technic and technology, no. 7 (August 31, 2020): 113–17. http://dx.doi.org/10.32620/aktt.2020.7.16.
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The article is devoted to the development of systematic approaches for the construction of a distributed information system (DIS) of aviation gas turbine engines (GTE). It is determined that the use of CALS-technologies (Continuous Acquisition and Life-Cycle Support), which should ensure the competitiveness of products on the world market, is essential for the integration of the aircraft engine industry into the world community of developers and manufacturers. The relevance of the use of CALS-technologies is due to the fact that today, in accordance with market requirements, the world's leading companies have set deadlines for the creation of a new design of the civil aviation engine of the fifth and sixth generations. The block-modular principle of engine construction - mathematical models and software - with the satisfaction of the criteria of divergence, transformation, and convergence has been considered. For a simplified search of the optimal technology for building a distributed information system of an aviation engine, the use of a fuzzy clustering approach is proposed, which is a design method with finding new knowledge about the gas turbine engine with highly efficient performance. By identifying methods of knowledge analysis and basic methods of clustering, that are K-means, graph clustering algorithms, algorithms of the FOREL family, hierarchical clustering, Kohonen neural network, algorithms of the KRAB family, fuzzy mean algorithms, subtractive, the application clustering in distributed information systems of aviation engines have been determined. For the convenient implementation of the defined method, a set of data objects of the GTE information system, which are contained in the experimental files, are considered. According to the results of the fuzzy clustering procedure, the coordinates of the class centers, the belonging of each data set to the classes, the values of the objective function, which have an approximate character, and are used for preliminary structuring of the data, are fixed. After research, it was determined that the integration of clustering algorithms should help build a more accurate model of the gas turbine engine and increase its speed.
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Gilioli, Andrea, Dario Braconi, and Mario Guagliano. "Fatigue design of a twin internal combustion engine for a light helicopter by a CAE-based approach." International Journal of Structural Integrity 8, no. 6 (December 4, 2017): 632–47. http://dx.doi.org/10.1108/ijsi-02-2017-0011.
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Purpose The purpose of this paper is to apply a computer-aided engineering approach in order to improve the performance and the reliability of an innovative internal combustion engine. The engine is called twin engine packs system and it consists into the presence of two independent piston engines working in the same crankcase, thus allowing the helicopter to meet the safety standards of the fail-safe design approach, as happens with the twin-turbine helicopters, but with reduced operative costs. The goal is to propose to the designers modifications aimed to improve the performance of the components. Design/methodology/approach The crankshaft, connecting rod and the piston of the engine have been investigated by means of numerical FE models. Numerical fatigue assessments have been performed along with vibrational modes and buckling analysis in order to verify the structural integrity of the system. Findings On the basis of the numerical results, some modifications have been proposed to the designers and the originally proposed geometry has been modified. Eventually, the mass of the engine has been reduced keeping a high reliability level. Practical implications The prototype of the engine has been built following the modifications proposed in this paper. This paper represents a comprehensive application of a CAE methodology to a real industrial application. Originality/value This paper shows a complete CAE procedure applied to a real working engine whose performances and reliability have been improved by following the findings of this paper.
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Iacovano, Clara, Fabio Berni, Alessio Barbato, and Stefano Fontanesi. "A Preliminary 1D-3D Analysis of the Darmstadt Research Engine Under Motored Condition." E3S Web of Conferences 197 (2020): 06006. http://dx.doi.org/10.1051/e3sconf/202019706006.
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In the present paper, 1D and 3D CFD models of the Darmstadt research engine undergo a preliminary validation against the available experimental dataset at motored condition. The Darmstadt engine is a single-cylinder optical research unit and the chosen operating point is characterized by a revving speed equal to 800 rpm with intake temperature and pressure of 24 °C and 0.95 bar, respectively. Experimental data are available from the TU Darmstadt engine research group. Several aspects of the engine are analyzed, such as crevice modeling, blow-by, heat transfer and compression ratio, with the aim to minimize numerical uncertainties. On the one hand, a GT-Power model of the engine is used to investigate the impact of blow-by and crevices modeling during compression and expansion strokes. Moreover, it provides boundary conditions for the following 3D CFD simulations. On the other hand, the latter, carried out in a RANS framework with both highand low-Reynolds wall treatments, allow a deeper investigation of the boundary layer phenomena and, thus, of the gas-to-wall heat transfer. A detailed modeling of the crevice, along with an ad hoc tuning of both blow-by and heat fluxes lead to a remarkable improvement of the results. However, in order to adequately match the experimental mean in-cylinder pressure, a slight modification of the compression ratio from the nominal value is accounted for, based on the uncertainty which usually characterizes such geometrical parameter. The present preliminary study aims at providing reliable numerical setups for 1D and 3D models to be adopted in future detailed investigations on the Darmstadt research engine.
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Ganapathy, Thirunavukkarasu, Parkash Gakkhar, and Krishnan Murugesan. "Artificial neural network modeling of jatropha oil fueled diesel engine for emission predictions." Thermal Science 13, no. 3 (2009): 91–102. http://dx.doi.org/10.2298/tsci0903091g.
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This paper deals with artificial neural network modeling of diesel engine fueled with jatropha oil to predict the unburned hydrocarbons, smoke, and NOx emissions. The experimental data from the literature have been used as the data base for the proposed neural network model development. For training the networks, the injection timing, injector opening pressure, plunger diameter, and engine load are used as the input layer. The outputs are hydrocarbons, smoke, and NOx emissions. The feed forward back propagation learning algorithms with two hidden layers are used in the networks. For each output a different network is developed with required topology. The artificial neural network models for hydrocarbons, smoke, and NOx emissions gave R2 values of 0.9976, 0.9976, and 0.9984 and mean percent errors of smaller than 2.7603, 4.9524, and 3.1136, respectively, for training data sets, while the R2 values of 0.9904, 0.9904, and 0.9942, and mean percent errors of smaller than 6.5557, 6.1072, and 4.4682, respectively, for testing data sets. The best linear fit of regression to the artificial neural network models of hydrocarbons, smoke, and NOx emissions gave the correlation coefficient values of 0.98, 0.995, and 0.997, respectively.
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Inyang, Udoinyang G., Samuel S. Udoh, and Oluwole C. Akinyokun. "Comparative Analysis of Neural Network Models for Petroleum Products Pipeline Monitoring." Studies in Engineering and Technology 4, no. 1 (April 6, 2017): 53. http://dx.doi.org/10.11114/set.v4i1.2340.
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In recent years, Neural Network (NN) has gained popularity in proffering solution to complex nonlinear problems. Monitoring of variations in Petroleum Products Pipeline (PPP) attributes (flow rate, pressure, temperature, viscosity, density, inlet and outlet volume) which changes with time is complex due to existence of non linear interaction amongst the attributes. The existing works on PPP monitoring are limited by lack of capabilities for pattern recognition and learning from previous data. In this paper, NN models with pattern recognition and learning capabilities are compared with a view of selecting the best model for monitoring PPP. Data was collected from Pipelines and Products Marketing Company (PPMC), Port Harcourt, Nigeria. The data was used for NN training, validation and testing with different NN models such as Multilayer Perceptron (MLP), Radial Basis Function (RBF), Generalized Feed Forward (GFF), Support Vector Machine (SVM), Time Delay Network (TDN) and Recurrent Neural Network (RNN). Neuro Solutions 6.0 was used as the front-end-engine for NN training, validation and testing while My Structured Query Language (MySQL) database served as the back-end-engine. Performance of NN models was measured using Mean Squared Error (MSE), Mean Absolute Error (MAE), Correlation Coefficient (r), Akaike Information Criteria (AIC) and Minimum Descriptive Length (MDL). MLP with one hidden layer and three processing elements performed better than other NN models in terms of MSE, MAE, AIC, MDL and r values between the computed and the desired output.
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Wang, Hai Yan, Lei Chen, and Ji An. "Dynamic Modeling of Marine Diesel Propulsion System in All Kind of Running Conditions." Advanced Materials Research 655-657 (January 2013): 98–104. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.98.
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For matching various working condition of ship propulsion system, a modified mean value model of a large-scale low-speed directly reversible marine diesel engine is put forward. A starting and braking torque module is added to the conventional model. A new friction model which considers static friction is adopted. So, the new model can run smoothly across all propulsion working condition, such as starting, running, braking, reversing, etc. The dynamic simulation models of propeller running across four quadrants and ship longitudinal motion are given too. The 5S60MC marine diesel engine equipped on a 76000DWT bulk carrier is taken as an example. The simulation results show that steady data of diesel are in good accordance with test-bed data, and dynamic data match to ship sea trial data in crash stop condition. The best is to read these instructions and follow the outline of this text.
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Shin, Seunghyup, Sangyul Lee, Minjae Kim, Jihwan Park, and Kyoungdoug Min. "Deep learning procedure for knock, performance and emission prediction at steady-state condition of a gasoline engine." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 14 (July 3, 2020): 3347–61. http://dx.doi.org/10.1177/0954407020932690.
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Recently, deep learning has played an important role in the rise of artificial intelligence, and its accuracy has gained recognition in various research fields. Although engine phenomena are very complicated, they can be predicted with high accuracy using deep learning because they are based on the fundamentals of physics and chemistry. In this research, models were built with deep neural networks for gasoline engine prediction. The model consists of two sub-models. The first predicts the knock occurrence, and the second predicts performance, combustion, and emissions. This includes maximum cylinder pressure, crank angle at maximum cylinder pressure, maximum pressure rise rate, and brake mean effective pressure, brake-specific fuel consumption, brake-specific nitrogen oxides, and brake-specific carbon oxide, which are representative results of the engine (for normal combustion cases without knock). Model input parameters were selected considering engine operating conditions, and physically measurable sensor values. For test cases, the accuracy of the first model for knock classification is 99.0%, and the coefficient of determination (R2) values for the second model are all above 0.99. Test times of both models were approximately 2 ms. The robustness of all the models was verified using K-fold cross-validation. A sensitivity study of accuracy, according to the amount of training utilized, was also conducted to determine how many data points are required to effectively train the deep learning model. Accordingly, a deep learning approach was applied to predict the steady-state conditions of a gasoline engine. Achieved model accuracies and robustness proved deep learning to be an effective modeling approach, and test time was recognized to be able to apply for the real-time prediction. The sensitivity analysis can be applied for the preliminary study to define the number of experimental points for the deep learning model.
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Usman, Muhammad, Haris Hussain, Fahid Riaz, Muneeb Irshad, Rehmat Bashir, Muhammad Haris Shah, Adeel Ahmad Zafar, et al. "Artificial Neural Network Led Optimization of Oxyhydrogen Hybridized Diesel Operated Engine." Sustainability 13, no. 16 (August 20, 2021): 9373. http://dx.doi.org/10.3390/su13169373.
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The prevailing massive exploitation of conventional fuels has staked the energy accessibility to future generations. The gloomy peril of inflated demand and depleting fuel reservoirs in the energy sector has supposedly instigated the urgent need for reliable alternative fuels. These very issues have been addressed by introducing oxyhydrogen gas (HHO) in compression ignition (CI) engines in various flow rates with diesel for assessing brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE). The enrichment of neat diesel fuel with 10 dm3/min of HHO resulted in the most substantial decrease in BSFC and improved BTE at all test speeds in the range of 1000–2200 rpm. Moreover, an Artificial Intelligence (AI) approach was employed for designing an ANN performance-predicting model with an engine operating on HHO. The correlation coefficients (R) of BSFC and BTE given by the ANN predicting model were 0.99764 and 0.99902, respectively. The mean root errors (MRE) of both parameters (BSFC and BTE) were within the range of 1–3% while the root mean square errors (RMSE) were 0.0122 kg/kWh and 0.2768% for BSFC and BTE, respectively. In addition, ANN was coupled with the response surface methodology (RSM) technique for comprehending the individual impact of design parameters and their statistical interactions governing the output parameters. The R2 values of RSM responses (BSFC and BTE) were near to 1 and MRE values were within the designated range. The comparative evaluation of ANN and RSM predicting models revealed that MRE and RMSE of RSM models are also well within the desired range but to be outrightly accurate and precise, the choice of ANN should be potentially endorsed. Thus, the combined use of ANN and RSM could be used effectively for reliable predictions and effective study of statistical interactions.
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Wiguna, Bagus Satria, Cinthia Vairra Hudiyanti, Alqis Alqis Rausanfita, and Agus Zainal Arifin. "Sarcasm Detection Engine for Twitter Sentiment Analysis using Textual and Emoji Feature." Jurnal Ilmu Komputer dan Informasi 14, no. 1 (February 28, 2021): 1–8. http://dx.doi.org/10.21609/jiki.v14i1.812.
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Twitter is a social media platform that is used to express sentiments about events, topics, individuals, and groups. Sentiments in Tweets can be classified as positive or negative expressions. However, in sentiment, there is an expression that is actually the opposite of what is mean to be, and this is called sarcasm. The existence of sarcasm in a Tweet is difficult to detect automatically by a system even by humans. In this research, we propose a weighting scheme based on inconsistency between sentimen of tweet contain in Indonesian and the usage of emoji. With the weighting scheme for the detection of sarcasm, it can be used to find out a sentiment about a event, topic, individual, group, or product's review. The proposed method is by calculating the distance between the textual feature polarity score obtained from the Convolutional Neural Network and the emoji polarity score in a Tweet. This method is used to find the boundary value between Tweets that contain sarcasm or not. The experimental results of the model developed, obtained f1-score 87.5%, precision 90.5% and recall 84.8%. By using the textual features and emoji models, it can detect sarcasm in a Tweet.
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Dowell, Peter G., Sam Akehurst, and Richard D. Burke. "Characterisation and optimisation of a real-time diesel engine model." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 14 (February 1, 2017): 1913–34. http://dx.doi.org/10.1177/0954407017691618.
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Accurate real-time engine models are an essential step to allow the development of control algorithms in parallel to the development of engine hardware using hardware-in-the-loop applications. A physics-based model of the engine high-pressure air path and combustion chamber is presented. The model was parameterised using data from a small set of carefully selected operating conditions for a 2.0 l diesel engine. The model was subsequently validated over the complete engine operating map with exhaust gas recirculation and without exhaust gas recirculation. A high level of fit was achieved with R2 values above 0.94 for the mean effective pressure and above 0.99 for the air flow rate. The model run time was then reduced for real-time application by using forward differencing and single-precision floating-point numbers and by calculating the in-cylinder prediction for only a single cylinder. A further improvement of 25% in the run time was achieved by improving the submodels, including the strategic use of one-dimensional and two-dimensional look-up tables with optimised resolution. The model exceeds the performance of similar models in the literature, achieving a crank angle resolution of 0.5° at 4000 r/min. This simulation step size still yields good accuracy in comparison with a crank angle resolution of 0.1° and was validated against the experimental results from a New European Driving Cycle. The real-time model allows the development of control strategies before the engine hardware is available, meaning that more time can be spent to ensure that the engine can meet the performance and the emissions requirements over its full operating range.
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Hershan, D. G. "EFFECT OF COMPOSITION OF FUEL CONTAINING BUTANOL ON WORKING PROCESS PARAMETERS OF DIESEL ENGINE." Science & Technique 16, no. 3 (May 26, 2017): 225–31. http://dx.doi.org/10.21122/2227-1031-2017-16-3-225-231.
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Computational researches the effect of composition of fuel containing butanol on working process parameters of 4ЧН 11/12,5 diesel engine on the external speed characteristic have been conducted. Nominal power is 140 kW at engine speed 2300 min–1. The engine is equipped with gas turbine pressure charging with intercooling of charging air, accumulator-type fuel-handling system. Calculations of the working process have been made in accordance with the developed computer program and models. Investigations have been carried out in two stages: without any changes in regulation of fuel-handling system and with cyclic fuel delivery that ensure such value of excess air factor at various operational modes which corresponds to the operation with diesel fuel. All the obtained results have been analyzed in the paper. The paper shows changes in mean indicated pressure, specific indicated fuel consumption, indicated efficiency, specific nitrogen oxides emissions for various modes in question while using 5, 10, 15, 20, 25 and 30 % mixture of diesel fuel with butanol. Dependences of parameters pertaining to diesel operation have been determined according to external speed characteristic for various mixtures and the obtained data make it possible to justify parameters of the fuel-handling system. It has been recommended to use a diesel fuel-butanol mixture containing 15 % of butanol without any changes in regulating and design engine parameters. It has been revealed that in order to improve parameters of the engine operational process mixture composition must be changed while changing the operational mode. An injector nozzle with a compound needle for the fuel-handling system has been developed and it allows to change fuel composition according to engine operational mode.
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Heredia Quintana, Sebastián, and Andres David Morales-Rojas. "Desarrollo y validación de un modelo cero dimensional de dos zonas para el análisis de la combustión en motores de encendido provocado." Revista CINTEX 23, no. 2 (December 31, 2018): 25–33. http://dx.doi.org/10.33131/24222208.321.
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The growth of the automotive fleet in cities and the imminent depletion of traditional hydrocarbon deposits mean that research in the field of internal combustion engines focuses on generating strategies and developing technologies that allow a reduction in fuel consumption and pollutants emissions. The use of numerical models for simulation is an important tool for both researchers and designers as they allow to approach the performance of the engines under certain operating conditions without incurring in the expense involved in experimental studies and allow analyzing multiple phenomena that occur during combustion that are not easily evaluable from experimental measurements. In this study, a zero-dimensional two zones model which separates the combustion chamber into burned and unburned gases was developed seeking to study the combustion process in ignition engines using gaseous renewable fuel (biogas), using the Law of Wiebe and the chemical equilibrium to simulate the combustion process and the Woschni's semi-empirical correlation for heat transfer. The model is calibrated with information obtained from a high compression ratio (15.5: 1) engine of the combustion and thermal machines laboratory of the University of Antioquia. The main variables of combustion and engine performance (heat release rate, maximum pressure, indicated work, among others) were compared with the results of the model, as well as the emissions generated from CO and NO. There are low errors between the experimental values predicted by the model, with errors less than 10% for the main variables, except for the indicated work, with errors of 27%, and errors between 18% and 49% for the generated emissions, obtaining the highest errors as the degree of load of the motor increases.
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Muzychuk, Vasyl, Vitaliy Komaha, Oleksii Tokarchuk, and Oleksandr Kukharchuk. "RESEARCH OF RESIDUAL LIFETIME OF DIESEL ENGINES FUEL INJECTION EQUIPMENT BY MEANS OF FUEL INJECTION MATHEMATIC SIMULATION." ENGINEERING, ENERGY, TRANSPORT AIC, no. 4(111) (December 18, 2020): 33–47. http://dx.doi.org/10.37128/2520-6168-2020-4-4.
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On the basis of the engineering practices of the last 3-4 decades, it is known, tested and proven that, while mathematical models provide reliable descriptions of processes, cycles or physical phenomena, in theoretical research the theory of small deviations is comprehensively preferable to any experiment on regulating characteristics. Considering the fact that all parameters and characteristics are sometimes interconnected by nonlinear dependences, it is impossible to distinguish the influence of a specific parameter on the sought-for value, and can be even hazardous if the determinant argument or its derivative has extreme values. The role of mathematic simulation to determine the residual lifetime of the fuel injection equipment of diesel engines was established. It was also noted that for a reliable description of the processes going on in the fuel injection equipment it is advisable to use the method of small deviations. The mathematical model is based on the known physical laws that describe the interdependence of the two groups of parameters: engine variables and performance parameters - both within the groups and between them. The transition of classical differential equations describing the processes of fuel supply and injection taking into account fuel leaks in precision pairs to the equations with small deviations of parameters is shown. An analysis of correlations between the parameters of injection, fuel supply and fuel leakage was carried out and the most influential parameters were found. The influence coefficients are found and correlations between the influence coefficients and the corresponding parameters are constructed. We used the correlations found to describe the influence of the technical condition of precision pairs on the engine performance indicators. The correlations between the change in injection patterns and small deviations of the parameters describing technical condition of precision pairs are also established.
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Dare, A. A., Olanrewaju Olatunde, O. S. Ismail, A. S. Shote, O. J. Alamu, and M. A. Sulaiman. "INVESTIGATION OF MULTI-ZONE MODELS FOR SPARK IGNITION ENGINE FUELED WITH ETHANOL." IIUM Engineering Journal 22, no. 2 (July 4, 2021): 339–51. http://dx.doi.org/10.31436/iiumej.v22i2.1550.
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This research is aimed at investigating the effect of using ethanol (E100) in multi-zone model analysis consisting of multi-combustion chamber zoning cases. The first case considered is a three-zone model that has an unburned zone, burned zone, and transitory zone. The second case model is also three-zone, consisting of an unburned zone and two partitioned burned zones. The burned zone was imagined partitioned into burned zone-1 and burned zone-2 under uneven fuel distribution having different equivalent ratios. The third case is a four-zone model including two regions of burned zone, an unburned zone and a transitory zone, which is unburned burned zone containing a mixture of unburned and burned gases. Arbitrary constants for each of the unburned (CC1) and burned (CC2) Zone leakages in the unburned burned Zone are 0.00025, 0.0005, 0.001, 0.002, 0.005, 0.1 and 0.5. The Mass Fraction Burned (MFB) for zone-1, x1 and burned zone-2, x2 are computed using Partitioned Burnt Zones Ratios (PBZR) of 2:8, 3:7, 4:6, 5:5, 6:4, 7:3 and 8:2. Two equivalent ratios, one for each fuel MFB (?1, ?2), (0.8, 0.6) and (0.6, 0.8) are analyzed using fuel blends of varying percentage. A comparison of values of the three zoning cases is done using peak values from the three-zone models to evaluate the four-zone model. The model was compared with a spark ignition engine (SIE) operating with a premium motor spirit (PMS) serving as baseline. The engine operating conditions were set at an engine speed of 2000 rpm, -35bTDC ignition time, and burn duration at 60 oC. The indicated mean effective pressure (IMEP), thermal efficiency (?), cylinder pressure and emission fraction from the developed models and those of two-zone analysis obtained agreed with literature values. The result showed it is undesirable to have a high volume of burned charge as infiltrate. The three-zone segmented model predicted the highest engine thermal efficiency and peak pressure at mass burn ratio of 7:3. A general reduction in N2 emission was observed for the three-zone transitional and four-zone models. ABSTRAK: Kajian ini menilai kesan etanol (E100) dalam analisis model zon-berbilang yang terdapat pada masalah pengezonan kebuk pembakaran-berbilang. Kes pertama yang diambil kira adalah model tiga-zon yang mempunyai zon tidak terbakar, zon terbakar dan zon peralihan. Model kedua merupakan juga tiga-zon yang terdiri daripada zon tidak-terbakar dan dua zon bahagian yang terbakar. Zon yang terbakar dibahagikan kepada zon-1 terbakar dan zon-2 terbakar di bawah kebakaran tidak sekata yang mempunyai nisbah berlainan. Kes ketiga adalah model zon-keempat termasuk dua kawasan zon terbakar, zon tidak-terbakar dan zon peralihan iaitu zon terbakar tidak-terbakar di mana ia adalah campuran gas terbakar dan tidak-terbakar. Tetapan sebarangan bagi setiap zon kebocoran tidak-terbakar (CC1) dan terbakar (CC2) dalam zon terbakar tidak-terbakar adalah 0.00025, 0.0005, 0.001, 0.002, 0.005, 0.1 dan 0.5. Pecahan Jisim Terbakar (MFB) bagi zon-1, x1 dan zon-2 terbakar, x2 dikira menggunakan Nisbah Zon Bahagian Terbakar (PBZR) sebanyak 2:8, 3:7, 4:6, 5:5, 6:4, 7:3 dan 8:2. Nisbah dua persamaan, setiap satu bahan api MFB adalah (?1, ?2), (0.8, 0.6) dan (0.6, 0.8) dan diuji menggunakan pelbagai peratus bahan api campuran. Nilai perbandingan bagi tiga kes zon dibuat menggunakan nilai puncak dari model tiga-zon bagi menilai model empat-zon. Model ini dibandingkan dengan enjin cucuhan bunga api (SIE) beroperasi dengan motor alkohol premium (PMS) sebagai garis asas. Keadaan operasi enjin adalah dihadkan pada 2000 rpm kelajuan enjin, masa pencucuhan -35bTDC dan tempoh pembakaran pada 60 oC. Tekanan berkesan min tertunjuk (IMEP), kecekapan haba tertunjuk (?), tekanan silinder dan pecahan pengeluaran dari model yang dibangunkan dan analisis dua-zon yang terhasil adalah sama dengan nilai literatur. Dapatan kajian menunjukkan cas terbakar pada isipadu yang banyak adalah tidak diingini sebagai penyerap. Model tiga bahagian zon menunjukkan kecekapan haba enjin tertinggi dan tekanan puncak pada jisim bakar dengan nisbah 7:3. Manakala, pengurangan umum telah diperhatikan pada pengeluaran N2 di peralihan tiga-zon dan model empat zon.
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Wang, Jiayue, Tongtong Li, Hailong Yang, Tian Hu, Lei Nie, Fei Wang, Manel Alcalà, and Hengchang Zang. "Geographical origin discrimination and polysaccharides quantitative analysis of Radix codonopsis with micro near-infrared spectrometer engine." Journal of Innovative Optical Health Sciences 11, no. 01 (November 20, 2017): 1850004. http://dx.doi.org/10.1142/s1793545818500049.
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At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM’s modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration ([Formula: see text]), correlation coefficient of prediction ([Formula: see text]), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of [Formula: see text], [Formula: see text], RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734[Formula: see text]g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM.
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Rowbury, D. A., M. L. G. Oldfield, and G. D. Lock. "A Method for Correlating the Influence of External Crossflow on the Discharge Coefficients of Film Cooling Holes." Journal of Turbomachinery 123, no. 2 (February 1, 2000): 258–65. http://dx.doi.org/10.1115/1.1354137.
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An empirical means of predicting the discharge coefficients of film cooling holes in an operating engine has been developed. The method quantifies the influence of the major dimensionless parameters, namely hole geometry, pressure ratio across the hole, coolant Reynolds number, and the freestream Mach number. The method utilizes discharge coefficient data measured on both a first-stage high-pressure nozzle guide vane from a modern aero-engine and a scale (1.4 times) replica of the vane. The vane has over 300 film cooling holes, arranged in 14 rows. Data was collected for both vanes in the absence of external flow. These noncrossflow experiments were conducted in a pressurized vessel in order to cover the wide range of pressure ratios and coolant Reynolds numbers found in the engine. Regrettably, the proprietary nature of the data collected on the engine vane prevents its publication, although its input to the derived correlation is discussed. Experiments were also conducted using the replica vanes in an annular blowdown cascade which models the external flow patterns found in the engine. The coolant system used a heavy foreign gas (SF6 /Ar mixture) at ambient temperatures which allowed the coolant-to-mainstream density ratio and blowing parameters to be matched to engine values. These experiments matched the mainstream Reynolds and Mach numbers and the coolant Mach number to engine values, but the coolant Reynolds number was not engine representative (Rowbury, D. A., Oldfield, M. L. G., and Lock, G. D., 1997, “Engine-Representative Discharge Coefficients Measured in an Annular Nozzle Guide Vane Cascade,” ASME Paper No. 97-GT-99, International Gas Turbine and Aero-Engine Congress & Exhibition, Orlando, Florida, June 1997; Rowbury, D. A., Oldfield, M. L. G., Lock, G. D., and Dancer, S. N., 1998, “Scaling of Film Cooling Discharge Coefficient Measurements to Engine Conditions,” ASME Paper No. 98-GT-79, International Gas Turbine and Aero-Engine Congress & Exhibition, Stockholm, Sweden, June 1998). A correlation for discharge coefficients in the absence of external crossflow has been derived from this data and other published data. An additive loss coefficient method is subsequently applied to the cascade data in order to assess the effect of the external crossflow. The correlation is used successfully to reconstruct the experimental data. It is further validated by successfully predicting data published by other researchers. The work presented is of considerable value to gas turbine design engineers as it provides an improved means of predicting the discharge coefficients of engine film cooling holes.
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Du, Zhicheng, Lin Xu, Wangjian Zhang, Dingmei Zhang, Shicheng Yu, and Yuantao Hao. "Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China." BMJ Open 7, no. 10 (October 2017): e016263. http://dx.doi.org/10.1136/bmjopen-2017-016263.
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ObjectivesHand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD.DesignEcological study.Setting and participantsInformation on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved.Outcome measuresA seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI.ResultsA high correlation between HFMD incidence and BDI (r=0.794, p<0.001) or temperature (r=0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of −345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%.ConclusionsAn ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings.
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Li, Jiwei, David E. Knapp, Mitchell Lyons, Chris Roelfsema, Stuart Phinn, Steven R. Schill, and Gregory P. Asner. "Automated Global Shallow Water Bathymetry Mapping Using Google Earth Engine." Remote Sensing 13, no. 8 (April 10, 2021): 1469. http://dx.doi.org/10.3390/rs13081469.
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Global shallow water bathymetry maps offer critical information to inform activities such as scientific research, environment protection, and marine transportation. Methods that employ satellite-based bathymetric modeling provide an alternative to conventional shipborne measurements, offering high spatial resolution combined with extensive coverage. We developed an automated bathymetry mapping approach based on the Sentinel-2 surface reflectance dataset in Google Earth Engine. We created a new method for generating a clean-water mosaic and a tailored automatic bathymetric estimation algorithm. We then evaluated the performance of the models at six globally diverse sites (Heron Island, Australia; West Coast of Hawaiʻi Island, Hawaiʻi; Saona Island, Dominican Republic; Punta Cana, Dominican Republic; St. Croix, United States Virgin Islands; and The Grenadines) using 113,520 field bathymetry sampling points. Our approach derived accurate bathymetry maps in shallow waters, with Root Mean Square Error (RMSE) values ranging from 1.2 to 1.9 m. This automatic, efficient, and robust method was applied to map shallow water bathymetry at the global scale, especially in areas which have high biodiversity (i.e., coral reefs).
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Pobikrowska, Katarzyna, and Tomasz Goetzendorf-Grabowski. "Stability analysis of the experimental airplane powered by a pulsejet engine." Aircraft Engineering and Aerospace Technology 91, no. 6 (June 10, 2019): 843–50. http://dx.doi.org/10.1108/aeat-07-2018-0184.
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Purpose This paper aims to present stability analysis of a small pulsejet-powered airplane. This analysis is a part of a student project dedicated to designing an airplane to test valved pulsejet engine in flight conditions. Design/methodology/approach The panel method was chosen to compute the airplane’s aerodynamic coefficients and derivatives for various geometry configurations, as it provides accurate results in a short computational time. Also, the program (PANUKL) that was used allows frequent and easy changes of the geometry. The evaluation of dynamic stability was done using another program (SDSA) equipped with means to formulate and solve eigenvalue problem for various flight speeds. Findings As a result of calculations, some geometry corrections were established, such as an increase of the vertical stabilizer’s size and a new wing position. Resulting geometry provides satisfactory dynamic and static stability characteristics for all flight speeds. This conclusion was based on criteria given by MIL-F-8785C specifications. This paper presents the results of the first and the final configuration. Practical implications The results shown in this paper are necessary for the continuation of the project. The aircraft’s structure was being designed in the same time as the calculations described in this paper proceeded. With a few modifications to make up for the changes of external geometry, the structure will be ready to be built. Originality/value The idea to design an airplane specifically to test a pulsejet in flight is a unique one. Most RC pulsejet-powered constructions that can be heard of are modified versions of already existing models. What adds more to the value of the project is that it is being developed only by students. This allows them to learn various aspects of aircraft design and construction on a soon-to-be real object.
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Ren, Diandong, and Lance M. Leslie. "Impacts of Climate Warming on Aviation Fuel Consumption." Journal of Applied Meteorology and Climatology 58, no. 7 (July 2019): 1593–602. http://dx.doi.org/10.1175/jamc-d-19-0005.1.
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AbstractFactors affecting aviation fuel efficiency are thermal and propulsive efficiencies, and overall drag on aircraft. An along-the-route integration is made for all direct flights in a baseline year, 2010, under current and future atmospheric conditions obtained from 26 climate models under the representative concentration pathway (RCP) 8.5 scenario. Thermal efficiency and propulsive efficiency are affected differently, with the former decreasing by 0.38% and the latter increasing by 0.35%. Consequently, the overall engine efficiency decrease is merely <0.02%. Over the same period, the skin frictional drag increases ~3.5% from the increased air viscosity. This component is only 5.7% of the total drag, and the ~3.5% increase in air viscosity accounts for a 0.2% inefficiency in fuel consumption. A t test is performed for the multiple-model ensemble mean time series of fuel efficiency decrease for two 20-yr periods centered on years 2010 and 2090, respectively. The trend is found to be statistically significant (p value = 0.0017). The total decrease in aircraft fuel efficiency is equivalent to ~0.68 billion gallons of additional fuel annually, a qualitatively robust conclusion, but quantitatively there is a large interclimate model spread.
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Song, Chunsheng, Yao Xiao, Chuanchao Yu, Wei Xu, and Jinguang Zhang. "H∞ active control of frequency-varying disturbances in a main engine on the floating raft vibration isolation system." Journal of Low Frequency Noise, Vibration and Active Control 37, no. 2 (August 21, 2017): 199–215. http://dx.doi.org/10.1177/1461348417725944.
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Reducing the vibration of marine power machinery can improve warships' capabilities of concealment and reconnaissance. Being one of the most effective means to reduce mechanical vibrations, the active vibration control technology can overcome the poor effect in low frequency of traditional passive vibration isolation. As the vibrations arising from operation of marine power machinery are actually the frequency-varying disturbances, the H∞ control method is adopted to suppress frequency-varying disturbances. The H∞ control method can solve the stability problems caused by the uncertainty of the model and reshape the frequency response function of the closed loop system. Two-input two-output continuous transfer function models were identified by using the system identification method and are validated in frequency domain of which all values of best fit exceeds 89%. The method of selecting the weighting functions on the mixed sensitivity problem is studied. Besides, the H∞ controller is designed for a multiple input multiple output (MIMO) system to suppress the single-frequency-varying disturbance. The numerical simulation results show that the magnitudes of the error signals are reduced by more than 50%, and the amplitudes of the dominant frequencies are attenuated by more than 10 dB. Finally, the single excitation source dual-channel control experiments are conducted on the floating raft isolation system. The experiment results reveal that the root mean square values of the error signals under control have fallen by more 74% than that without control, and the amplitudes of the error signals in the dominant frequencies are attenuated above 13 dB. The experiment results and the numerical simulation results are basically in line, indicating a good vibration isolation effect.