• International Journal of CAD/CAM
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• 제6권1호
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• pp.9-17
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• 2006

Performing inspections for Hull Condition Monitoring and Assessment as stipulated in IACS unified requirements and IMO's Condition Assessment Scheme (CAS) IMO Resolution MEPC.94(46), 2001, Condition Assessment Scheme, IMO Resolution MEPC.111(50), 2003, Amendments to regulation 13G, addition of new regulation 13H involves a huge amount of measurement data to be collected, processed, analysed and maintained. Information to be recorded consists of thickness measurements and visual assessment of coating and cracks. The amount of data and increasing requirements with respect to condition assessment demand efficient computer support. Currently, due to the lack of standardization for this kind of data, the thickness measurements are recorded manually on ship drawings or tables. In this form, handling of the measurements is tedious and error-prone and assessment is difficult. Data reporting and analysis takes a long time, leading to some repairs being performed only at the next docking of the ship or making an additional docking necessary. The recently started ED funded project CAS addresses this topic and develops-as a first step-a data model for Hull Condition Monitoring and Assessment (HCMA) based on XML-technology. The model includes simple geometry representation to facilitate a graphically supported data collection as well as an easy visualisation of the measurement results. In order to ensure compatibility with the current way of working, the content of the data model is strictly confined to the requirements of the measurement process. Appropriate data interfaces to classification software will enable rapid assessment by the classification societies, thus improving the process in terms of time and cost savings. In particular, decision-making can be done while the ship is still in the dock for maintenance.

• 한국축산식품학회지
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• 제35권1호
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• 한국환경과학회지
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• 제22권5호
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• pp.555-562
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• 2013

Jeju Island, the heaviest raining area in Korea, is a volcanic Island located at the southernmost of Korea, but most streams are of the dry due to its hydrological/geological characteristics different from those of inland areas. Therefore, there are limitations in applying the results from the mainland to the studies on stream run-off characteristics analysis and water resource analysis of Jeju Island. In this study, the SWAT(soil & water assessment tool) model is used for the Hwabuk stream watershed located east of the downtown to calculate the long-term stream run-off rate, and WMS(watershed modeling system) and HEC-HMS(hydrologic modeling system) models are used to figure out the stream run-off characteristics due to short-term heavy rainfall. As the result of SWAT modelling for the long-term rainfall-runoff model for Hwabuk stream watershed in 2008, 5.66% of the average precipitation of the entire basin was run off, with 3.47% in 2009, 8.12% in 2010, and root mean square error(RMSE) and determination coefficient($R^2$) was 496.9 and 0.87, respectively, with model efficient(ME) of 0.72. From the results of WMS and HEC-HMS models which are short-term rainfall-runoff models, unless there was a preceding rainfall, the runoff occurred only for rainfall of 40mm or greater, and the run-off duration averaged 10~14 hours.

• 한국정보통신학회논문지
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• 제10권3호
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• pp.459-466
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• 2006

열성능 평가를 위한 수치해석에서는 온도, 압력, 건도, 체적, 엔탈피, 엔트로피 등의 열역학적 성질들의 수치값이 필요하다. 그러나 이러한 성질들을 포함하고 있는 증기표를 그대로 사용할 수 없기 때문에, 효과적으로 모델링하여야 한다. 이러한 관점에서 함수근사 특성을 가진 신경회로망을 하나의 대안으로 검토하였다. 신경 회로망은 포화증기 영역과 과열증기 영역에 대해서 따로 구성하였다. 포화증기 영역에 대해서는 하나의 입력으로 7개의 출력을 얻을 수 있도록 하였으며, 각각 10개와 20개의 노드를 가진 은닉층을 구성 하였다. 과열증기 영역에 대해서는 2개의 입력으로 3개의 출력을 얻을 수 있도록 하였으며, 각각 15개와 25개의 노드를 가진 은닉층을 구성하였다. 제안된 모델은 온도, 엔탈피, 엔트로피의 백분율오차가 대부분 ${\pm}0.005%$, 압력이나 비체적의 백분율오차도 대부분 ${\pm}0.025%$ 범위 내로 수렴시킬 수 있었다. 이 성공적인 결과로부터 증기 표를 함수근사하는데 있어서 신경회로망이 아주 강력한 수단이 될 수 있음을 확인할 수 있었다.

• Environmental Engineering Research
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• 제25권4호
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• pp.479-487
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• 2020

Current assumptions are used in the formulation of pseudo-first (PFO) and second-order (PSO) models to describe the kinetic data of filtration based on ideal operating conditions. This paper presents a new model developed with pseudo n^th order and based on real assumption. A comparison was performed between PFO, PSO and the new model to highlight their performance and the optimisation of the pseudo-order equation, using MATLAB software. Adsorption characteristic of bovine serum albumin adsorption on the track-etched membrane are used as a medium based on protein filtration data were extracted from the literature for different concentrations to demonstrate the comparison between PFO/PSO and the new model. The pseudo first and second-order kinetic models were applied to test the experimental data and they did not provide reasonable values. The results show that the predicted values are consistent with experimental values giving a good correlation coefficient R² = 0.997 and a minimum root mean squared error RMSE = 0.0171. Indeed, the experimental results follow the new model and the optimal pseudo equation order n = 1.115, the most suitable curves for the new model. As a result, we used different experimental adsorption data from the literature to examine and check the applicability and validity of the model.

• 환경영향평가
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• 제20권5호
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• 상하수도학회지
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• 제28권6호
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• pp.735-745
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• 2014

This paper presents PKES(PuKyung -Excel based Simulator) for WWTPs(wastewater treatment plants) by using MS Excel and VBA(Visual Basic for Application). PKES is a user-friendly simulator for the design and optimization of the whole plant including biological and physico-chemical processes for the wastewater and sludge treatment. PKES calculates the performance under steady or dynamic state and allows changing the mathematical model by the user. Mathematical model implemented in PKES is a improved integration model based on ASM2d and ADM1 for simulation of AS(activated sludge) and AD(anaerobic digestion). Gaseous components of $N_2$, $N_2O$, $CO_2$ and $CH_4$ are added for estimation of GHGs(greenhouse gases) emission. The simulation results for comparison between PKES and Aquasim(EAWAG) showed about the same effluent concentrations. As a result of verification using by measured data of BOD, TSS, TN and TP for 2 years of operation, calculated effluent concentrations were similar to measured effluent concentrations. The values of average RMSE(root mean square error) were 1.9, 0.8, 1.6 and 0.2 mg/L for BOD, TSS, TN and TP, respectively. Total GHGs emission of WWTP calculated by PKES was 138.5 ton-$CO_2$/day and GHGs emissions of $N_2O$, $CO_2$ and $CH_4$ were calculated at 21.7, 28.9 and 87.9 ton-$CO_2$/day, respectively. GHGs emission of activated sludge was 32.5 % and that of anaerobic digestion was 67.5 %.

• 대한전자공학회논문지
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• 제22권3호
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• pp.95-102
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• 1985

반도체 내에서의 불순물 분포를 구하기 위한 2차원 확산문제를 푸는 효과적인 수치 해법을 제시하였다. ADI(Alternating Direction Implicit) 방법과 Gauss 소거법의 조합에 의한 수치해법을 사용하므로써 SOR(Successive Over-Relaxation)이나 stone 방법에 비하여 전산기의 메모리 사용량을 중가시키지 않 고도 거의 모든 확산 조건에 대하여 CP비시간을 1/3 이하로 줄일 수 있었다. 상대오차의 크기를 0.01%이내로 하고 1차원과 2차원 문제에 대하여, 여러가지 수치해법의 CPU를 비교하였다. 1차원 계산결과와 실험결과가 잘 일치하였고, 2차원 계산결과를 1차원 계산결과와 잘 비교한 결과, 일치함을 알 수 있었다.

• 한국수자원학회논문집
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• 제43권3호
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• pp.275-282
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• 2010

암거의 규격 설계는 상류부의 수위를 과다하게 상승시키지 않는 상태에서 안전하게 계획홍수량을 하류로 소통시킬 수 있도록 최적의 단면을 결정하는 것이다. 현재 국내 암거 설계는 한국도로공사(1991)에서 발표한 "도로배수계획"을 이용하고 있는데, 이는 주로 미국도로성(FHWA)에서 발표한 설계기법을 따른 것이다. 이 기법은 계산 도표를 이용하여 설계하는 방법으로 주관적인 오차가 생길 수 있으며 전산해석에 있어서도 큰 장애요인이 될 수 있다. 본 연구에서는 기존 연구에서 기술된 암거 설계법을 전반적으로 재검토하여 일부 수식 전개 과정에서 발생한 오류를 수정하고, 암거의 규격 산정 시 암거의 형상을 미리 결정하여 암거 프로그램 개발 시 효율적일 것으로 판단되는 새로운 방법을 개발하였다. 특히 원형 암거의 수리해석 시 한계수심과 한계조건 속도수두의 해를 미국도로성에서는 계산도표를 이용하여 구하는 기법을 제시한 반면에 본 연구에서는 양해적 산정식으로 구하는 기법을 개발하였다.

• 한국측량학회지
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• 제21권4호
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• pp.365-371
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• 2003

고해상도의 디지털 카메라는 근거리 수치사진측량에서 널리 유용하게 사용되고 있으며 점차 활용도가 증가하고 있다. 또한 사진측량 장비의 급속한 발전으로 정밀도가 많이 향상되었고 컴퓨터를 이용한 지형공간정보체계기술의 발달로 더욱 정밀한 3차원 지형의 재현과 면적 및 토공량 산정이 가능하게 되었다. 본 연구에서는 휴대가 간편하고 수치영상의 자체저장능력을 지닌 디지털 카메라를 이용하여 촬영조건의 다양한 변화에 따른 위치오차를 분석하였으며 광속조정을 통하여 높은 정확도의 화소 좌표를 획득하여 3차원 지형의 모니터링을 위한 기초자료로 사용할 수 있도록 하였다. 또한 근거리 수치사진측량기법의 국부지역모형생성과 문화재의 보존과 복원을 보다 효율적으로 하기 위해 수치 정보 분석에 관한 연구를 수행하여 봉분의 3차원 구현에 대한 활용방안을 모색하였다.