• 설비공학논문집
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• 제22권5호
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• pp.275-281
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• 2010

Car HVAC is one of main factors influencing a potential customer's first impression. It should be fault-free, which requires the most stable control performance. So, the control algorithm consists of a proportional feedback only, not with an integral action needed for elimination of steady-state errors. To reduce the errors and make the response faster, feedforward algorithm based on predicted thermal load is added. To evaluate the performance, car HVAC is dynamically modelled and its control logic is simulated. The results shows that the proportional feedback leads to about $4^{\circ}C$ of steady-state error. When the feedback is combined with the feedforward algorithm and with a set value update based on disturbances, it predicts less than $1^{\circ}C$ of control error and improved thermal comfort.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.673-678
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• 2000

This paper presents an indirect compensation of thermal errors during machining, in which thermal error is modeled as a linear regression of temperatures measured at 4 specified positions. In this regression model, weighting coefficients of the measured temperatures were estimated by using the least square method. The grinding test with compensation, after 4-hour warming-up operation before the test, showed that the maximum machining error of the work pieces was reduced to 12${\mu}{\textrm}{m}$ while it measured 28${\mu}{\textrm}{m}$ without compensation. Furthermore the standard deviation of machining errors was also reduced from 8${\mu}{\textrm}{m}$ to 2${\mu}{\textrm}{m}$.

• 한국항공우주학회지
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• 제44권1호
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• pp.80-87
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• 2016

본 논문에서는 계절 및 주야의 온도변화를 고려한 관측위성의 열지향오차해석을 실시한다. 관측위성은 임무수행기간 동안 다채널의 관측센서를 이용해서 지구표면의 영상을 촬영한다. 그러나 주야 및 계절별로 최대 200도의 온도환경 차이가 발생하며 이로 인해 관측센서 및 별추적기의 시선벡터가 변화되고 정해진 목표지점의 영상촬영이 어렵다. 이런 문제를 사전예측하고 대응하기 위해서 열지향오차해석을 실시한다. 우선 궤도열환경해석으로부터 도출된 성긴 온도장 정보를 상세한 구조유한요소모델에 PAT기법을 이용해 보간하여 온도변화에 따른 열변형해석을 수행하였다. PAT로 보간된 온도분포의 정확도를 검증하였으며, 열변형해석결과로부터 열지향오차를 도출하였다.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.303-308
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• 2022

Simulating the heat transfer in a composite material is an important topic in material science. Difficulties arise from the fact that adjacent materials cannot match perfectly, resulting in discontinuity in the temperature variables. Although there have been several numerical methods for solving the heat-transfer problem in imperfect contact conditions, the methods known so far are complicated to implement, and the computational times are non-negligible. In this study, we developed a ResNet-type deep neural network for simulating a heat transfer model in a composite material. To train the neural network, we generated datasets by numerically solving the heat-transfer equations with Kapitza thermal resistance conditions. Because datasets involve various configurations of composite materials, our neural networks are robust to the shapes of material-material interfaces. Our algorithm can predict the thermal behavior in real time once the networks are trained. The performance of the proposed neural networks is documented, where the root mean square error (RMSE) and mean absolute error (MAE) are below 2.47E-6, and 7.00E-4, respectively.

• 한국군사과학기술학회지
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• 제25권6호
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• pp.561-571
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• 2022

An optical mirror assembly is an opto-mechanically coupled system as the optical and mechanical behaviors interact. In the assembly, a flexure mount attached to an optical mirror should be flexible in the radial direction, but rigid for the remaining degrees of freedom for supporting the mirror rigidly and suppressing the wavefront error of the optical mirror. This work presents an optimal design of the flexure mount using topology optimization with thermal stress constraint. By simplifying the optical mirror assembly into finite shell elements, topology optimization model was built for efficient design and good machinability. The stress at the boundary between the optical mirror and the mount together with the first natural frequency were applied as constraints for the optimization problem, while the objective function was set to minimize the strain energy. As a result, we obtained the optimal design of the flexure mount yielding the improved wavefront error, proper rigidity, and machinability.

• 한국생산제조학회지
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• 제23권1호
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• pp.1-6
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• 2014

This paper describes a method of estimating and evaluating the volumetric errors of multi-axis machine tools. The estimation method is based on a generic model that was developed from conventional kinematic error models for the geometric and thermal errors to help predict the volumetric error easily in various configurations. To demonstrate the advantages of the model, an application in the early stages of a five-axis machine tool design is presented as an example. The model was experimentally evaluated for a four-axis machine tool by using the data from ISO230-6 and R-test measurements to compare the estimated and measured volumetric errors.

• Composites Research
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• 제34권6호
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• pp.426-433
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• 2021

탄소 섬유 강화 복합재료는 오토클레이브 공정 시 발생하는 잔류응력이 발생하고, 스프링 인, 뒤틀림과 같은 열변형으로 인해 치수 결함이 발생한다. 열변형의 주요원인은 제품의 형상, 수지의 화학 수축과 열팽창, 몰드의 재질과 표면 상태에 따른 몰드 효과 등 다양한 요인에 의해 발생한다. 본 연구는 열변형을 예측하기 위해 점탄성 모델 해석 기법을 평판 모델에 적용하여 열변형의 주요 원인인 수지의 화학 수축과 열팽창의 영향을 분석했고, 몰드 유무에 따른 3-D 점탄성 모델의 해석 기법을 검증했다. 검증된 3-D 점탄성 모델의 해석 기법을 이용하여 L-형상의 몰드 효과를 분석한 결과, 동일한 재질의 몰드를 사용했더라도 표면 상태에 따라 잔류 변형이 다르게 나타났다.

• International Journal of Precision Engineering and Manufacturing
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• 제4권2호
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• pp.71-76
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• 2003

A virtual machine tool (VMT) is presented in this two-part paper. In Part 1, the analytical foundation for a virtual machining system is developed, which is envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes. The VHT system undergoes "pseudo-real machining", before actual cutting with a CNC machine tool takes place, to provide the proper cutting conditions for process planners and to compensate or control the machining process in terms of the productivity and attributes of the products. The attributes can be characterized by the machined surface error, dimensional accuracy, roughness, integrity, and so forth. The main components of the VMT are the cutting process, application, thermal behavior, and feed drive modules. In Part 1, the cutting process module is presented. When verified experimentally, the proposed models gave significantly better prediction results than any other methods. In Part 2 of this paper, the thermal behavior and feed drive modules are developed, and the models are integrated into a comprehensive software environment.vironment.

• 한국정밀공학회지
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• 제18권11호
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• pp.74-79
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• 2001

In this two-part paper, a virtual machine tool (VMT) is presented. In part 1, the analytical foundation of a virtual machining system, envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes, is developed. The VMT system purposes to experience the pseudo-real machining before real cutting with a CNC machine tool, to provide the proper cutting conditions for process planners, and to compensate or control the machining process in terms of the productivity and attributes of products. The attributes can be characterized with the machined surface error, dimensional accuracy, roughness, integrity and so forth. The main components of the VMT are cutting process, application, thermal behavior and feed drive modules. In part 1, the cutting process module is presented. The proposed models were verified experimentally and gave significantly better prediction results than any other method. The thermal behavior and feed drive modules are developed in part 2 paper. The developed models are integrated as a comprehensive software environment in part 2 paper.

• 설비공학논문집
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• 제18권1호
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• pp.87-94
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• 2006

In this paper, we investigated a feasibility of applying highest and lowest temperatures of the next day forecasted from a meteorological observatory to operation of an air-conditioning system with thermal storage. First we investigated specific characteristics of the time series of forecasted temperatures and errors in Osaka from 1994 to 1996. Since the forecast error is not always small, it might be difficult to use the forecasted data without correction for the sizing and the control of the thermal storage system. On the other hand, the autocorrelation functions of the forecast errors decrease relatively slowly during high summer season when cooling thermal storage is required. Since the values of the autocorrelation function; for one day are larger than 0.4, not small, the forecast errors can be predicted by proper statistical analysis. Thus, the forecasted values of the highest temperatures for the next day were improved by using the stochastic time series models.