• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2004.03a
• /
• pp.671-686
• /
• 2004

The shock-induced combustion ramjet (shcramjet) is a hypersonic airbreathing propulsion concept which over-comes the drawbacks of the long, massive combustors present in the scramjet by using a standing oblique detonation wave (a coupled shock-combustion front) as a means of nearly instantaneous heat addition. A novel shcramjet combustor design that makes use of wedge-shaped flameholders to avoid detonation wave-wall interactions is proposed and analyzed with computational fluid dynamics (CFD) simulations in this study. The laminar, two-dimensional Navier-Stokes equations coupled with a non-equilibrium hydrogen-air combustion model based on chemical kinetics are used to represent the physical system. The equations are solved with the WARP (window-allocatable resolver for propulsion) CFD code (see: Parent, B. and Sislian, J. P., “The Use of Domain Decomposition in Accelerating the Convergence of Quasihyperbolic Systems”, J. of Comp. Physics, Vol. 179, No. 1,2002, pages 140-169). The solver was validated with experimental results found in the literature. A series of steady-state numerical simulations was conducted using WARP and it was deter-mined by means of thrust potential calculations that this combustor design is a viable one for shcramjet propulsion: assuming a shcramjet flight Mach number of twelve at an altitude of 36,000 m, the geometrical dimensions used for the combustor give rise to an operational range for combustor inlet Mach numbers between six and eight. Different shcramjet flight Mach numbers would require different combustor dimensions and hence a variable geometry system in or-der to be viable.

• Wind and Structures
• /
• v.4 no.3
• /
• pp.177-196
• /
• 2001

At present the most popular turbulence models used for engineering solutions to flow problems are the $k-{\varepsilon}$ and Reynolds stress models. The shortcoming of these models based on the isotropic eddy viscosity concept and Reynolds averaging in flow fields of the type found in the field of Wind Engineering are well documented. In view of these shortcomings this paper presents the implementation of a non-linear model and its evaluation for flow around a building. Tests were undertaken using the classical bluff body shape, a surface mounted cube, with orientations both normal and skewed at $45^{\circ}$ to the incident wind. Full-scale investigations have been undertaken at the Silsoe Research Institute with a 6 m surface mounted cube and a fetch of roughness height equal to 0.01 m. All tests were originally undertaken for a number of turbulence models including the standard, RNG and MMK $k-{\varepsilon}$ models and the differential stress model. The sensitivity of the CFD results to a number of solver parameters was tested. The accuracy of the turbulence model used was deduced by comparison to the full-scale predicted roof and wake recirculation zone lengths. Mean values of the predicted pressure coefficients were used to further validate the turbulence models. Preliminary comparisons have also been made with available published experimental and large eddy simulation data. Initial investigations suggested that a suitable turbulence model should be able to model the anisotropy of turbulent flow such as the Reynolds stress model whilst maintaining the ease of use and computational stability of the two equations models. Therefore development work concentrated on non-linear quadratic and cubic expansions of the Boussinesq eddy viscosity assumption. Comparisons of these with models based on an isotropic assumption are presented along with comparisons with measured data.

• Journal of the Society of Naval Architects of Korea
• /
• v.55 no.3
• /
• pp.215-221
• /
• 2018

The structural design of offshore installations against explosions has been required to protect vital areas (e.g. control room, worker's area etc.) and minimize the damage from explosion accidents. Because the explosion accident will not only result in significant casualties and economic losses, but also cause serious pollution and damage to surrounding environment and coastal marine ecosystems. Over the past two decades, an incredible efforts was made to develop reliable methods to reduce and manage the explosion risk. Among the methods Quantitative Risk Assessment and Management (QRA&M) is the one of cutting-edge technologies. The explosion risk can be quantitatively assessed by the product of explosion frequency based on probability calculation and consequence analyzed using computer simulations, namely Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA). However to obtain reliable consequence analysis results by CFD and FEA, uncertainties associate with modeling and simulation are needed to be identified and validated by comparison with experimental data. Therefore, large-scaled explosion test procedure is developed in this study. And developed test procedure can be helpful to obtain precious test data for the validation of consequence analysis using computer simulations, and subsequently allow better assessment and management of explosion risks.

• The Korean Journal of Ecology
• /
• v.25 no.4
• /
• pp.261-265
• /
• 2002

In order to elucidate the characteristics of standing crop biomass, production and nutrient content of dead bole in mature ecosystem, we surveyed the dynamics of decaying bole of old-aged deciduous forest in 1993 and 2002 in Kwangnung Experimetal Forest Station. In addition, we and estimated annual bole production, water content, wood density and nutrient content and compared the results with that of temperate ecosystem. Total dead wood biomass was estimated to be 5.6ton/ha in 1993 and 17.6 ton/ha in 2002. Standing dead tree accounted for a total of 1.1 ton/ha in 1993 and 4.8 ton/ha in 2002, which was 20% and 27$\%$ of the sum of dead bole mass in 1993 and 2002, respectively. Annual production of bole biomass was 1.3 ton/ha/yr. These values fall into the low range of dead wood biomass for the mature temperate ecosystems. Tree species composing standing bole was mainly Quercus and Carpinus trees. This bole species composition resembles alive species composition of this forest. Water content of bole increased as positive logarithmically, but wood density of bole decreased as negative exponentially along with the progress of decay. N, P, Ca and Mg concentrations in decaying boles generally increased with decay, except for K. Annual nutrient input via dead bole is 1.6 kg/ha/yr for N, 0.04 kg/ha/yr for P, 1.0 kg/ha/yr for K, 1.7 kg/ha/yr for Ca and 0.3 kg/ha/yr for Mg, respectively.

• International Journal of Fluid Machinery and Systems
• /
• v.9 no.4
• /
• pp.370-381
• /
• 2016

As a single-channel pump is used for wastewater treatment, this particular pump type can prevent performance reduction or damage caused by foreign substances. However, the design methods for single-channel pumps are different and more difficult than those for general pumps. In this study, a design optimization method to improve the hydrodynamic performance of a single-channel pump impeller is implemented. Numerical analysis was carried out by solving three-dimensional steady-state incompressible Reynolds-averaged Navier-Stokes equations using the shear stress transport turbulence model. As a state-of-the-art impeller design method, two design variables related to controlling the internal cross-sectional flow area of a single-channel pump impeller were selected for optimization. Efficiency was used as the objective function and was numerically assessed at twelve design points selected by Latin hypercube sampling in the design space. An optimization process based on a radial basis neural network model was conducted systematically, and the performance of the optimum model was finally evaluated through an experimental test. Consequently, the optimum model showed improved performance compared with the base model, and the unstable flow components previously observed in the base model were suppressed remarkably well.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.2
• /
• pp.105-110
• /
• 2015

This study proposes the more improved mathematical model than conventional that for the 3-DOF Helicopter System in Quanser Inc., and checks the validity about the proposed model by performance comparison between the controller based on the conventional model and that based on the proposed model. Research process is next : First, analyze the dynamics for the 3-DOF helicopter system and establish the linear mathematical model. Second, check the eliminated nonlinear-elements in linearization process for establishing the linear mathematical model. And establish the improved mathematical model including the parameters corresponding to the eliminated nonlinear-elements. At that time, it is used for modeling that Particle Swarm Optimization algorithm the meta-heuristic global optimization method. Finally, design the controller based on the proposed model, and verify the validity of the proposed model by comparison about the experimental results between the designed controller and the controller based on the conventional model.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.168-180
• /
• 2018

In order to achieve the high quality output voltage of single-phase voltage source inverters, in this paper an Adaptive Complementary Sliding Mode Control (ACSMC) is proposed. Firstly, the dynamics model of the single-phase inverter with lumped uncertainty including parameter variations and external disturbances is derived. Then, the conventional Sliding Mode Control (SMC) and Complementary Sliding Mode Control (CSMC) are introduced separately. However, when system parameters vary or external disturbance occurs, the controlling performance such as tracking error, response speed et al. always could not satisfy the requirements based on the SMC and CSMC methods. Consequently, an ACSMC is developed. The ACSMC is composed of a CSMC term, a compensating control term and a filter parameters estimator. The compensating control term is applied to compensate for the system uncertainties, the filter parameters estimator is used for on-line LC parameter estimation by the proposed adaptive law. The adaptive law is derived using the Lyapunov theorem to guarantee the closed-loop stability. In order to decrease the control system cost, an inductor current estimator is developed. Finally, the effectiveness of the proposed controller is validated through Matlab/Simulink and experiments on a prototype single-phase inverter test bed with a TMS320LF28335 DSP. The simulation and experimental results show that compared to the conventional SMC and CSMC, the proposed ACSMC control strategy achieves more excellent performance such as fast transient response, small steady-state error, and low total harmonic distortion no matter under load step change, nonlinear load with inductor parameter variation or external disturbance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.4
• /
• pp.109-119
• /
• 1999

Switched Reluctance Motor(SRM) have been expanding gradually their awlications in the variable speed drives due to their relatively low cost, simple and robust structure, controllability and high efficiency. In this paper neural network theory is used to detemrine fuzzy-neural network controller's membership ftmctions and fuzzy rules. In addition neural network emulator is used to emulate forward dynamics of SRM and to get error signal at fuzzy-neural controller output layer. Error signal is backpropagated through neural network emulator. The backpropagated error of emulator offers the path which reforms the fuzzy-neural network controller's mmbership ftmctions and fuzzy rules. 32bit Digital Signal Processor(TMS320C31) was used to achieve the high speed control and to realize the fuzzy-neural control algorithm. Simulation and experimental results show that in the case of load variation the proposed control rrethcd was superior to a conventional rrethod in the respect of speed response.sponse.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.2
• /
• pp.395-400
• /
• 2017

The paper discussed the air-to-fuel ratio control of automotive fuel-injection systems using the cerebellar model articulation controller(CMAC) neural network. Because of the internal combustion engines and fuel-injection's dynamics is extremely nonlinear, it leads to the discontinuous of the fuel-injection and the traditional method of control based on table look up has the question of control accuracy low. The advantages about CMAC neural network are distributed storage information, parallel processing information, self-organizing and self-educated function. The unique structure of CMAC neural network and the processing method lets it have extensive application. In addition, by analyzing the output characteristics of oxygen sensor, calculating the rate of fuel-injection to maintain the air-to-fuel ratio. The CMAC may easily compensate for time delay. Experimental results proved that the way is more good than traditional for petrol control and the CMAC fuel-injection controller can keep ideal mixing ratio (A/F) for engine at any working conditions. The performance of power and economy is evidently improved.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.1
• /
• pp.44-52
• /
• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.