• Nuclear Engineering and Technology
• /
• v.52 no.5
• /
• pp.956-963
• /
• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.905-908
• /
• 2009

In the management of groundwater in coastal areas, saltwater intrusion associated with extensive groundwater pumping, is an important problem. The groundwater optimization model is an advanced method to study the aquifer and decide the optimal pumping rates or optimal well locations. Cheng and Park gave the analytical solutions to the optimization problems basing on Strack's analytical solution. However, the analytical solutions have some limitations of the property of aquifer, boundary conditions, and so on. A simulation-optimization numerical method presented in this study can deal with non-homogenous aquifers and various complex boundary conditions. This simulation-optimization model includes the sharp interface solution which solves the same governing equation with Strack's analytical solution, therefore, the freshwater head and saltwater thickness should be in the same conditions, that can lead to the comparable results in optimal pumping rates and optimal well locations for both of the solutions. It is noticed that the analytical solutions can only be applied on the infinite domain aquifer, while it is impossible to get a numerical model with infinite domain. To compare the numerical model with the analytical solutions, calculation of the equivalent boundary flux was planted into the numerical model so that the numerical model can have the same conditions in steady state with analytical solutions.

• Journal of Korean Institute of Industrial Engineers
• /
• v.32 no.1
• /
• pp.9-17
• /
• 2006

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

• Korean System Dynamics Review
• /
• v.13 no.2
• /
• pp.47-71
• /
• 2012

The purpose of this research is the examination of validity of data as well as simulation model, i.e. to simulate the real data in the SD model with the least error using the adjustments for the faithful reflection of real data to the simulation. In general, SD programs (e.g. VENSIM) utilize the Euler or Runge-Kutta method as an algorithm. It is possible to reflect the trend of real data via these two estimation methods however can cause the validity problem in case of the simulation requiring the accuracy as they have endogenous errors. In this article, the future population estimated by the Korea National Statistical Office (KNSO) to 2050 is simulated by the aging chain model, dividing the population into three cohorts, 0-14, 15-64, 65 and over cohorts by age and offering the adjustments to them. Adjustments are calculated by optimization with three different methods, optimization in EXCEL, manual optimization with iterative calculation, and optimization in VENSIM DSS, the results are compared, and at last the optimal adjustment set with the least error are found among them. The simulation results with the pre-determined optimal adjustment set are validated by methods proposed by Barlas (1996) and other alternative methods. It is concluded that the result of simulation model in this research has no significant difference from the real data and reflects the real trend faithfully.

• Journal of Korea Water Resources Association
• /
• v.46 no.4
• /
• pp.373-387
• /
• 2013

For the efficient operation and management of the water resources system, coordinated operation of weirs and reservoirs is required. A simulation based, and an optimization based approaches are available to deal with the operation and management problems. The simulation based approach does not guarantee an optimal solution, and the optimization based approach is not so flexible to consider, complex, nonlinear problems we will face when trying to allocate water to different uses, various demand sectors in a basin. Hence, it is important to develop a model that would compensate for the weak points in both models. We will compare and contrast intrinsic and extrinsic properties of two modeling approaches, addressing issues related to setting system operation and control rules that would lead us to more efficient use of water in the basin. As a result, we propose to use CoWMOM(Coordinated weirs and multi-reservoir operating model), a "simulation based" optimization model for a simple simulation of the past periods, and for the real-time simulation process considering uncertain inflow.

• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.5
• /
• pp.511-520
• /
• 2015

Inventory, cost, and the level of service are three interrelated key metrics that most supply chain organizations are striving to optimize. One way to achieve this goal is to create a simulation model to conduct sensitivity analysis and optimization on several different supply chain policies that can be implemented in actual operation. In this paper, a case of Xerox global supply chain modeling and analysis to assess several "what if" scenarios for the consumable policy safety stock is presented. The simulation model, combined with analytical cost model and optimization module, is used to optimize the policy safety stock level to achieve the lowest total value chain cost. It was shown quantitatively that the policy safety stock can be reduced, but it is offset by the inbound premium transportation cost to expedite supplies in shortage, and the outbound premium transportation cost to send supplies to customers via express shipment, requiring fine balance.

• Design & Manufacturing
• /
• v.16 no.1
• /
• pp.62-69
• /
• 2022

In the present study, the injection molding optimization of a large thick LH type elastic frames for the reduction of warpage was performed. Two kinds of fine and coarse finite element models were prepared to investigate the efficiency of analysis time and quality on simulation results. In order to derive injection molding conditions that can minimize distortion of parts, it was investigated that the effects of mold temperature, resin temperature, injection time, hold pressure switching time, holding pressure and the hold time on deformation characteristics using the design of experiments. The main influential factors on the warpage were found from the optimization simulation and the geometry data of the warpage result was converted into an initial model for injection simulation. It was shown that a coarse model with good mesh quality could be adapted for mold design since the total analysis time using the proposed model was reduced to 1/10. The suggested inversed warpage model produced the best minimized result of warpage.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1997.04a
• /
• pp.3-7
• /
• 1997

Simulation is commonly used to find the best values of decision variables for problems which defy analytical solutions. "Simulation Optimization" technique is used to optimize the expressed in analytical of mathematical models. In this research, we will study Reverse-Simulation optimization method which is quite different from current simulation optimization methods in literature. We will focus on the on-line determination of steady-state method which is very important issue in Reverse-Simulation optimization, and the construction of Reverse-Simulation algorithm with expert systems. Especially, in the case of multiple objectives because of the dependency of simulation model, all objectives do not satisfied simulataneously. In this paper, therefore, we process simulation optimization using objectives with priority to optimize multiple objectives under single run.ingle run.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.1086-1092
• /
• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them 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 used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.521-522
• /
• 2011