• 한국국방경영분석학회지
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• 제18권2호
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• pp.181-191
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• 1992

In this paper in order to prevent break of operation of equipments resulted from the delay of parts supply, the continuous review(Q, r) inventory model with probabilistic lead time is developed. If the lead tire is random varivable, the cycle also is stochastic. Then it is not easy to obtain the total cost equation of this inventory model. Therefore it is assumed that one cycle is the interval of reorder points. When the lead time is assumed to have exponential probability distribution, the lot-size and reorder point which minimize total cost are obtained. And as the lead time increases, the order quantity and the total cost are greater, but the reorder point increases by a certain point of time and then decreases.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.347-349
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• 2014

Model verification and validation (V&V) is a current research topic to build computational models with high predictive capability by addressing the general concepts, processes and statistical techniques. The hypothesis test for validity check is one of the model validation techniques and gives a guideline to evaluate the validity of a computational model when limited experimental data only exist due to restricted test resources (e.g., time and budget). The hypothesis test for validity check mainly employ Type I error, the risk of rejecting the valid computational model, for the validity evaluation since quantification of Type II error is not feasible for model validation. However, Type II error, the risk of accepting invalid computational model, should be importantly considered for an engineered products having high risk on predicted results. This paper proposes a technique named as the response-adaptive experimental design to reduce Type II error by adaptively designing experimental conditions for the validation experiment. A tire tread block problem and a numerical example are employed to show the effectiveness of the response-adaptive experimental design for the validity evaluation.

• 한국정밀공학회지
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• 제31권3호
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• pp.253-259
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• 2014

This study proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

• 로봇학회논문지
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• 제13권3호
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• pp.174-181
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• 2018

For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

• International Journal of Aeronautical and Space Sciences
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• 제16권3호
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• pp.394-406
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• 2015

In this work, an efficient aircraft landing simulation strategy is proposed to develop an efficient and reliable hard-landing monitoring procedure. Landing stage is the most dangerous moment during operation cycle of aircraft and it may cause structural damage when hard-landing occurs. Therefore, the occurrence of hard-landing should be reported accurately to guarantee the structural integrity of aircraft. In order to accurately determine whether hard-landing occurs or not from given landing conditions, full nonlinear structural dynamic simulation can be performed, but this approach is highly time-consuming. Thus, a more efficient approach for aircraft landing simulation which uses a hierarchical aircraft landing model and an extended inertia relief technique is proposed. The proposed aircraft landing model is composed of a multi-body dynamics model equipped with landing gear and tire models to extract the impact force and inertia force at touch-down and a linear dynamic structural model with an extended inertia relief method to analyze the structural response subject to the prescribed rigid body motion and the forces extracted from the multi-body dynamics model. The numerical examples show the efficiency and practical advantages of the proposed landing model as an essential component of aircraft hard-landing monitoring procedure.

• 한국자동차공학회논문집
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• 제22권1호
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• pp.174-182
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• 2014

Recently, not only common types of hybrid electric vehicle (HEV) such as series or parallel but many other types of HEVs including 4WD hybrid electric vehicle have been developed and released. In this study, analysis of fuel economy and driving performance for 2WD and 4WD HEV are conducted using backward simulation based on dynamic programming. To analyze the characteristics of 4WD HEV, tire slip model based on vehicle dynamics was applied to the backward simulation program. As a result, 2WD HEV shows better fuel economy than 4WD HEV because of relatively simple configuration. However, in a severe road condition, 4WD HEV shows better driving performance that 2WD HEV had about 6% of impossible time to follow the driving cycle though the 4WD HEV had no impossible time.

• Computers and Concrete
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• 제19권3호
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• 한국ITS학회 논문지
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• 제14권2호
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• pp.30-38
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• 2015

본 연구는 동절기 도로관리서비스 향상과 도로의 안전성을 제고하기 위하여, 기존의 입력자료인 기상자료와 더불어 추가적으로 교통자료를 적용하여 노면온도를 예측할 수 있는 모형의 개발을 목표로 하였다. 노면온도 예측모형은 열수지법을 적용하였으며, 모형에서 교통량에 대한 고려는 차량 복사열, 타이어 마찰열로 구성하여 모형화하였다. 이 최종모형과 기상 조건을 기초로 한 초기 모형과 비교하여 노면온도에 미치는 교통량의 영향을 검토하였다. 제3경인고속도로의 실제 관측치과 두 모형에서 계산된 노면온도를 실제 노면온도 관측치와의 비교로 검증하였는데, 관측치와 예측치의 오차인 RMSE은 $1.97^{\circ}C$였다. 관측된 노면온도는 오전 6시부터 일사의 영향을 받아 급격히 상승하여 14시에 최대가되고, 그 후에는 감소한다. 모형 예측값은 관측값보다 오후에는 낮고, 야간에는 높게 나타났다. 이는 오후의 경우는 차량으로 인한 태양 복사열의 차폐, 야간의 경우는 차량열에 의한 열 공급이 주요 원인인 것으로 판단된다.

• 한국자동차공학회논문집
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• 제12권2호
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• pp.139-147
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• 2004

The purpose of engine control TCS is to regulate engine torque to keep driven wheel slip in a desired range. In this paper, engine control TCS using sliding mode control law based on engine model and estimated load torque is proposed. This system includes a two-level controller. Slip controller calculates desired wheel torque, and engine torque controller determines throttle angle for engine torque corresponding to desired wheel torque. Another issue is to measure load torque for model based controller design. Luenberger observer with state variables of load torque and engine speed solves this problem as estimating load torque. The performance of controller and observer is certificated by simulation using 8-degree vehicle model, Pacejka tire model, and 2-state engine model. The simulation results in various maneuvers during slippery and split road conditions showed that acceleration performance and ability of the vehicle with TCS is improved. Also, the load torque observer could estimate real load torque very well, so its performance was proved.

• 한국분무공학회지
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• 제27권3호
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• pp.155-160
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• 2022

Recently, major developed countries have strengthened automobile fuel efficiency regulations and carbon dioxide emission allowance standards to curb climate change caused by global warming worldwide. Accordingly, research and manufacturing on electric vehicles that do not emit pollutants during actual driving on the road are being conducted. Several automobile companies are producing and testing electric vehicles to commercialize them, but it takes a lot of manpower and time to test and evaluate mass-produced electric vehicles with driving mileage of more than 300km on a per-charge. Therefore, in order to reduce this, a simulation model was developed in this study. This study used vehicle information and MCT speed profile of small electric vehicle as basic data. It was developed by applying Simulink, which models the system in a block diagram method using MATLAB software. Based on the vehicle dynamics, the simulation model consisted of major components of electric vehicles such as motor, battery, wheel/tire, brake, and acceleration. Through the development model, the amount of change in battery SOC and the mileage during driving were calculated. For verification, battery SOC data and vehicle speed data were compared and analyzed using CAN communication during the chassis dynamometer test. In addition, the reliability of the simulation model was confirmed through an analysis of the correlation between the result data and the data acquired through CAN communication.