• Journal of Food Hygiene and Safety
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• v.36 no.6
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• pp.504-509
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• 2021

The objective of this study was to develop dynamic model to describe the kinetic behavior of E. coli in sliced smoked duck. E. coli was detected in 2 sliced smoked duck samples (16.7%) at 1.23 log CFU/g. The maximum specific growth rate (𝜇_max) of E. coli ranged from 0.05 to 0.36 log CFU/g/h, and lag phase duration (LPD) ranged from 4.39 to 1.07 h, depending on the storage at 10-30℃, and h₀ value ranged from 0.24 to 0.51. The developed model was validated with observed values obtained at 13℃ and 25℃. The model performance was appropriate with 0.130 of root mean squared error (RMSE), and the dynamic model also described properly kinetic behavior of E. coli in sliced smoked duck samples. These results indicate that E. coli can contaminate sliced smoked ducks and the models developed with the E. coli isolates are useful in describing the kinetic behavior of E. coli in sliced smoked duck.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.244-254
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• 2002

To enhance the acceleration performance and fuel consumption rate of a vehicle, the torque converter is modified or newly-developed with reliable analysis model. Up to recently, the one dimensional performance model has been used for the analysis and design of torque converter. The model is described with constant parameters based on the concept of mean flow path. When it is used in practice, some experiential correction factors are needed to minimize tole estimated error. These factors have poor physical meaning and cannot be applied confidently to the other specification of torque converter. In this study, the detail dynamic model of torque converter is presented to establish the physical meaning of correction factors. To verify the validity of model, performance test was carried out with various input speed and oil temperature. The effect of oil temperature on the performance is analysed, and it is applied to the dynamic model. And, to obtain the internal flow pattern of torque converter, CFD(Computational Fluid Dyanmics) analysis is carried out on three-dimensional turbulent flow. Correction factors are determined from the internal flow pattern, and their variation is presented with the speed ratio of torque converter. Finally, the sensitivity of correction factors to the speed ratio is studied for the case of changing capacity factor with maintaining torque ratio.

• STI Policy Review
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• v.6 no.1
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• pp.1-23
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• 2015

Based on the work of Anand et al. (2013) we measure inclusive income growth, which combines growth in gross domestic product (GDP) per capita and growth in the equity of the income distribution. Extending the work of Causa et al. (2014), we estimate a dynamic simultaneous structural equations model of GDP per capita and inclusive income on panel data for 63 countries over the 1990-2013 period. We estimate both equations in error correction form by difference GMM (generalized method of moments). Among the explanatory variables of the level and the distribution of GDP per capita we include R&D (research and development) expenditure per capita. In OECD countries we obtain a large positive effect of R&D on GDP. R&D is found to have a positive effect on the social mobility index but its impact on the income equity index at first decreases, then switches around to become slightly positive in the long run. In non- OECD countries, R&D is found to decrease inclusive income, mostly through a negative growth effect but also because of a slightly increasing income inequity effect.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.335-341
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• 2010

To improve the performance of inner loop based on PD controller for a unmanned helicopter, neural networks are applied. The performance of PD controller designed on the response characteristics of error dynamics decreases because of uncertain nonlinearities of the system. The nonlinearities are decoupled to modified dynamic inversion model(MDIM) and are compensated by the neural networks. For the training of the neural networks, online weight adaptation laws which are derived from Lyapunov's direct method are used to guarantee the stability of the controller. The results of the improved performance of PD controller by neural networks are illustrated in the simulation of unmanned helicopter with nonlinearities,

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1722-1724
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• 2005

The focus of this paper is to develop a mathematical model for investigating the dynamic performance of a polymer electrolyte membrane fuel cell. The model in this work is based on physical laws having clear significance in replicating the fuel cell system and can easily be used to set up different operational strategies. Simulation results display the transient behavior of the voltage within each single cell, and also within a number of such single cells combined into a fuel cell stack system. A linear as well as a nonlinear analysis of the polymer electrolyte membrane fuel cell system(PEMFC) has been discussed in order to present a complete and comprehensive view of this kind of modeling. Also, a comparison of the two kinds of analysis has been performed. Finally, the various characteristics of the fuel cell system are plotted in order to help us understand its dynamic behavior. Results indicate that there is a considerable amount of error in the modeling process if we use a linear model of the fuel cell. Thus, the nonlinearities present in the fuel cell system should be taken into account in order to obtain a better understanding of the dynamic behavior of the fuel cell system.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.5
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• pp.401-407
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• 2016

This paper describes the derivation methodology of the working torque predictive model that can be used in the initial design stages of the impact hammer tool. The working torque control mechanism is designed, taking into account various factors, such as the force of the spring and friction. Firstly, the analysis dynamic model for working environments was modeled as an additional bush and spring, and verified by comparing the test results of the working torque. Secondly, the main performance parameters of the working torque were theoretically defined by analyzing the operating mechanism. The equation to predict the working torque was derived using the dynamic analysis results according to the value changes of the parameters. The prediction equation of the working torque was validated by comparing the predicted results with the experimental data. The error difference between the experimental data and the predictive model results was found to be 8.62%.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.605-615
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• 2000

Cerebellar model articulation controller (CMAC) is introduced and used for the identification of structural dynamic model. CMAC has fascinating features in learning speed. It can learn structural response within a few seconds. Therefore it is suitable for the real time identification structures. Real time identification is required in the control of structure which may be damaged or undergo severe change in mechanical properties due to shrinkage or relaxation etc. In numerical examples, it is shown that CMAC trained with the dynamic response of three-story building can predict responses under not trained earthquakes with allowable error. Finally, CMAC has great potential in structural and control engineering.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.265-271
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• 2005

Randomness exists in engineering. Tolerance, assemble-error, environment temperature and wear make the parameters of a mechanical system uncertain. So the behavior or response of the mechanical system is uncertain. In this paper, the uncertain parameters are treated as random variables. So if the probability distribution of a random parameter is known, the simulation of mechanical multibody dynamics can be made by Monte-Carlo method. Thus multibody dynamics simulation results can be obtained in statistics. A new concept called functional reliability is put forward in this paper, which can be defined as the probability of the dynamic parameters(such as position, orientation, velocity, acceleration etc.) of the key parts of a mechanical multibody system belong to their tolerance values. A flexible mechanical arm with random parameters is studied in this paper. The length, width, thickness and density of the flexible arm are treated as random variables and Gaussian distribution is used with given mean and variance. Computer code is developed based on the dynamic model and Monte-Carlo method to simulate the dynamic behavior of the flexible arm. At the same time the end effector's locating reliability is calculated with circular tolerance area. The theory and method presented in this paper are applicable on the dynamics modeling of general multibody systems.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.501-506
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• 2001

Computer modeling is essential to evaluate possible design of suspension for a railway vehicles. By creating a simulation, the engineers are able to assess the feasibility of a given design and change the design factors to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have turned to surrogate modeling. A surrogate model is essentially a regression performed on a data sampling of the simulation. In the most general sense, metamodels(surrogate model) take the form $y(x)=f(x)+{\varepsilon}$, where y(x) is the true simulation output, f(x) is the metamodel output, and $\varepsilon$ is the error between the two. In this paper, a second order polynomial equation is partially used as a metamodel to represent the forty-six dynamic performances for high speed train. The number of factors as design variables of the metamodel is twenty-nine, which are composed the dynamic characteristics of suspension. This metamodel is used to search the optimum values of suspension characteristics which minimize the dynamic responses for high speed train. This optimization is a multi-objective problem which have many design variables. This paper shows that the response surface model which is made through the design of analysis of computer experiments method is very efficient to solve this complex optimization problem.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.18-24
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• 2006

This paper proposes a LuGre Model-Based Neural Network (MBNN) friction compensation algorithm for a linear motor stage. For matching the friction phenomena in both the motion-start region and the motion-reverse region, the LuGre dynamic model is employed into the proposed compensation algorithm. After training of the model-based neural network is completed, the estimated friction for compensation is obtained. From the obtained result we find that the new structure gains advantage over the non-friction compensation system on the performance of the compensator in both regions. The proposed compensator is evaluated and compared experimentally with an uncompensated system on a microcomputer controlled linear motor tracking system in the final section of the paper. The experimental results show the improvement on the maximum velocity error and the root mean square tracking error in the motion-start region ranges from 34% to 53% and from 53% to 75% respectively, and in the motion-reverse region from 48% to 65% and from 79% to 90% respectively.