• Nuclear Engineering and Technology
• /
• 제55권9호
• /
• pp.3367-3382
• /
• 2023

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian computational fluid dynamics method that has been widely used in the analysis of physical phenomena characterized by large deformation or multi-phase flow analysis, including free surface. Despite the recent implementation of eddy-viscosity models in SPH methodology, sophisticated turbulent analysis using Lagrangian methodology has been limited due to the lack of computational performance and numerical consistency. In this study, we implement the standard and dynamic Smagorinsky model and dynamic Vreman model as sub-particle scale models based on a weakly compressible SPH solver. The large eddy simulation method is numerically identical to the spatial discretization method of smoothed particle dynamics, enabling the intuitive implementation of the turbulence model. Furthermore, there is no additional filtering process required for physical variables since the sub-grid scale filtering is inherently processed in the kernel interpolation. We simulate lid-driven flow under transition and turbulent conditions as a benchmark. The simulation results show that the dynamic Vreman model produces consistent results with experimental and numerical research regarding Reynolds averaged physical quantities and flow structure. Spectral analysis also confirms that it is possible to analyze turbulent eddies with a smaller length scale using the dynamic Vreman model with the same particle size.

• 한국정밀공학회지
• /
• 제12권4호
• /
• pp.127-134
• /
• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents a generalized stochastic model of dynamic system subjected to bot external and parametric nonstationary stochastic input. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method. But the second moment equation is founded to constitute an infinite coupled set of differential equations, so this equations are numerically evaluated by cumulant neglect closure method and Runge-Kutta method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2006년도 춘계학술대회 논문집
• /
• pp.121-122
• /
• 2006

In the case of mechanical control systems, it is highly useful to be able to provide a compact model of the mechanical system to control engineers using the smallest number of variables, while still providing an accurate model. The reduced mechanical model can then be inserted into the complete mechanical control system models and used for system-level dynamic simulation. In this paper, a moment-matching based model order reduction (MOR) which reduces the number of degrees of freedom of an original finite element model via the Arnoldi process is considered to study the dynamic responses of a HDD actuator and suspension system.

• Earthquakes and Structures
• /
• 제5권1호
• /
• pp.111-127
• /
• 2013

This paper describes effects of infill walls on behavior of RC frame with low strength, including numerical modeling, modal testing and finite-element model updating. For this purpose full scaled, one bay and one story RC frame is produced and tested for plane and brick in-filled conditions. Ambient-vibration testis applied to identify dynamic characteristics under natural excitations. Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are used to obtain experimental dynamic characteristics. A numerical modal analysis is performed on the developed two-dimensional finite element model of the frames using SAP2000 software to provide numerical frequencies and mode shapes. Dynamic characteristics obtained by numerical and experimental are compared with each other and finite element model of the frames are updated by changing some uncertain modeling parameters such as material properties and boundary conditions to reduce the differences between the results. At the end of the study, maximum differences in the natural frequencies are reduced on average from 34% to 9% and a good agreement is found between numerical and experimental dynamic characteristics after finite-element model updating. In addition, it is seen material properties are more effective parameters in the finite element model updating of plane frame. However, for brick in-filled frame changes in boundary conditions determine the model updating process.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.754-759
• /
• 1993

An adaptive model predictive control (AMPC) strategy using auto-regression moving-average (ARMA) models is presented. The characteristic features of this methodology are the small computer memory requirement, high computational speed, robustness, and easy handling of nonlinear and time varying MIMO systems. Since the process dynamic behaviors are expressed by ARMA models, the model parameter adaptation is simple and fast to converge. The recursive least square (RLS) method with exponential forgetting is used to trace the process model parameters assuming the process is slowly time varying. The control performance of the AMPC is verified by both comparative simulation and experimental studies on distillation column control.

• 한국산학기술학회논문지
• /
• 제18권6호
• /
• pp.263-268
• /
• 2017

상용 마그네슘 합금의 경우, 상온에서 낮은 성형성을 갖기 때문에, 온간 성형 조건 하에서 성형 공정을 수행하는 것이 일반적이다. 마그네슘 합금은 온간 성형 과정 중에 동적 재결정(dynamic recrystallization, DRX)이 발생하여, 초기 결정립 사이즈가 급격하게 작아지며, 내부 전위 밀도가 낮아지게 된다. 이에 따라, 유동 응력 곡선은 세 단계의 복잡한 변형 경화 및 연화 현상을 보이게 된다. 첫 번째 구간에서는 변형률이 증가함에 따라, 가공 경화에 의해 응력이 증가하는 경향을 보이며, 두 번째 구간에서는 동적 재결정 현상에 의한 가공 연화로 응력이 갑작스럽게 감소한다. 세 번째 구간에서는 가공 경화와 가공 연화 사이의 평형에 의해, 응력이 일정하게 나타난다. 본 연구에서는, 성형 온도 $300^{\circ}C$, 변형률 속도는 0.001, 0.1, 1, 10/sec에서 AZ80 합금의 구성 방정식의 18개 변수들을 체계적으로 최적화하며, 유동 곡선의 정확도를 높일 수 있는 방식에 대해 제안하려고 한다. 또한 AZ80외에 AZ61도 추가적으로 최적화여 본 논문에서 제안한 최적화 방식의 성능을 증명하였다.

• Journal of the Korean Statistical Society
• /
• 제27권3호
• /
• pp.279-288
• /
• 1998

We propose a multiprocess dynamic Poisson model for the analysis of Poisson process with the covariates. The algorithm for the recursive estimation of the parameter vector modeling time-varying effects of covariates is suggested. Also the algorithm for forecasting of numbers of events at the next time point based on the information gathered until the current time is suggested.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.1705-1711
• /
• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• 한국소음진동공학회논문집
• /
• 제19권10호
• /
• pp.1034-1042
• /
• 2009

In this paper, the magic formula model was applied for a friction damper in a drum-type washing machine. To describe characteristics of the hysteretic damping force, Physical tests were first carried out to get experimental results using an MTS machine. Then, parameters for the magic formula model were determined from the experimental curves. The ADAMS and MATLAB programs were used for the multibody modeling of the damper and process for parameter identification. The model of drum-type washing machine was applied for a dynamic model of friction damper, in which the accuracy of the proposed damper model was verified.

• International Journal of Quality Innovation
• /
• 제3권2호
• /
• pp.174-182
• /
• 2002

System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.