• 제목/요약/키워드: Deterministic Prediction

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핵연료 파손 예측을 위한 경험적 자료와 결정론적 모델의 접합 방법 (A Study on the Method of Combining Empirical Data and Deterministic Model for Fuel Failure Prediction)

  • Cho, Byeong-Ho;Yoon, Young-Ku;Chang, Soon-Heung
    • Nuclear Engineering and Technology
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    • 제19권4호
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    • pp.233-241
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    • 1987
  • 본 연구는 제한된 수의 핵연료의 경험적 파손자료로부터 핵연료 파손 확률을 현실적으로 예측하기 위해 결정론적 모델로부터의 파손화률 예측치와 실제 경험적 자료로부터의 파손 확률 예측치를 접합하는 방법을 시도하였다. 이 접합 방법에 의한 파손 화률 예측치는 결정론적 모델 또는 경험적 파손 자료로부터의 독립적인 예측치보다 신뢰도가 높다. 본 연구에서는 핵연료 성능 예측코드인 SPEAR의 방법론을 응용한 핵연료 파손 패턴의 체계적 발견법 (hierarchical pattern discovery)이 접합 모델에서의 결정론적 모델로부터의 예측치에 대한 가중치와 패턴 경계를 체계적으로 찾기 위해 고안되었다. 이 연구에서 개발된 접합 방법을 PROFIT모델과 경험적 파손자료를 이용하여 CANDU형 핵연료 재장전중 출력 상승에 의해 수반되는 핵연료파손 예측에 적응시켜 보았다.

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DEVELOPMENT OF THE HANSEL-SPITTEL CONSTITUTIVE MODEL GAZED FROM A PROBABILISTIC PERSPECTIVE

  • LEE, KYUNGHOON;KIM, JI HOON;KANG, BEOM-SOO
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제21권3호
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    • pp.155-165
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    • 2017
  • The Hansel-Spittel constitutive model requires a total of nine parameters for flow stress prediction. Typically, the parameters are estimated by least squares methods for given tensile test measurements from a deterministic perspective. In this research we took a different approach, a probabilistic viewpoint, to see through the development of the Hansel-Spittel constitutive model. This perspective change showed that deterministic least squares methods are closely related to statistical maximum likelihood methods via Gaussian noise assumption. More intriguingly, this perspective shift revealed that the Hansel-Spittel constitutive model may leave out deterministic trends in residuals despite nearly perfect agreement with measurements. With tensile test measurements of AA1070 aluminum alloy, we demonstrated this deficiency of the Hansel-Spittel constitutive model, suggesting room for improvement.

Prediction of SST for Operational Ocean Prediction System

  • Kang, Yong-Quin
    • Ocean and Polar Research
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    • 제23권2호
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    • pp.189-194
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    • 2001
  • A practical algorithm for prediction of the sea surface temperatures (SST)from the satellite remote sensing data is presented in this paper. The fluctuations of SST consist of deterministic normals and stochastic anomalies. Due to large thermal inertia of sea water, the SST anomalies can be modelled by autoregressive or Markov process, and its near future values can be predicted provided the recent values of SST are available. The actual SST is predicted by superposing the pre-known SST normals and the predicted SST anomalies. We applied this prediction algorithm to the NOAA AVHRR weekly SST data for 18 years (1981-1998) in the seas adjacent to Korea (115-$145^{\circ}E$, 20-$55^{\circ}N$). The algorithm is applicable not only for prediction of SST in near future but also for nowcast of SST in the cloud covered regions.

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PNU CGCM 앙상블 예보 시스템의 겨울철 남한 기온 예측 성능 평가 (Evaluation of PNU CGCM Ensemble Forecast System for Boreal Winter Temperature over South Korea)

  • 안중배;이준리;조세라
    • 대기
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    • 제28권4호
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    • pp.509-520
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    • 2018
  • The performance of the newly designed Pusan National University Coupled General Circulation Model (PNU CGCM) Ensemble Forecast System which produce 40 ensemble members for 12-month lead prediction is evaluated and analyzed in terms of boreal winter temperature over South Korea (S. Korea). The influence of ensemble size on prediction skill is examined with 40 ensemble members and the result shows that spreads of predictability are larger when the size of ensemble member is smaller. Moreover, it is suggested that more than 20 ensemble members are required for better prediction of statistically significant inter-annual variability of wintertime temperature over S. Korea. As for the ensemble average (ENS), it shows superior forecast skill compared to each ensemble member and has significant temporal correlation with Automated Surface Observing System (ASOS) temperature at 99% confidence level. In addition to forecast skill for inter-annual variability of wintertime temperature over S. Korea, winter climatology around East Asia and synoptic characteristics of warm (above normal) and cold (below normal) winters are reasonably captured by PNU CGCM. For the categorical forecast with $3{\times}3$ contingency table, the deterministic forecast generally shows better performance than probabilistic forecast except for warm winter (hit rate of probabilistic forecast: 71%). It is also found that, in case of concentrated distribution of 40 ensemble members to one category out of the three, the probabilistic forecast tends to have relatively high predictability. Meanwhile, in the case when the ensemble members distribute evenly throughout the categories, the predictability becomes lower in the probabilistic forecast.

Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting

  • Kim, Yongdai;Kim, Woosung;Ohn, Ilsang;Kim, Young-Oh
    • Communications for Statistical Applications and Methods
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    • 제24권1호
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    • pp.67-80
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    • 2017
  • Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

Prediction of Strong Ground Motion in Moderate-Seismicity Regions Using Deterministic Earthquake Scenarios

  • 강태섭
    • 한국지진공학회논문집
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    • 제11권4호
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    • pp.25-31
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    • 2007
  • For areas such as the Korean Peninsula, which have moderate seismic activity but no available records of strong ground motion, synthetic seismograms can be used to evaluate ground motion without waiting for a strong earthquake. Such seismograms represent the estimated ground motions expected from a set of possible earthquake scenarios. Local site effects are especially important in assessing the seismic hazard and possible ground motion scenarios for a specific fault. The earthquake source and rupture dynamics can be described as a two-step process of rupture initiation and front propagation controlled by a frictional sliding mechanism. The seismic wavefield propagates through heterogeneous geological media and finally undergoes near-surface modulations such as amplification or deamplification. This is a complex system in which various scales of physical phenomena are integrated. A unified approach incorporates multi-scale problems of dynamic rupture, radiated wave propagation, and site effects into an all-in-one model using a three-dimensional, fourth-order, staggered-grid, finite-difference method. The method explains strong ground motions as products of complex systems that can be modified according to a variety of fine-scale rupture scenarios and friction models. A series of such deterministic earthquake scenarios can shed light on the kind of damage that would result and where it would be located.

Fuzzy methodology application for modeling uncertainties in chloride ingress models of RC building structure

  • Do, Jeongyun;Song, Hun;So, Seungyoung;Soh, Yangseob
    • Computers and Concrete
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    • 제2권4호
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    • pp.325-343
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    • 2005
  • Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.

Ensemble Model Output Statistics를 이용한 평창지역 다중 모델 앙상블 결합 및 보정 (A Combination and Calibration of Multi-Model Ensemble of PyeongChang Area Using Ensemble Model Output Statistics)

  • 황유선;김찬수
    • 대기
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    • 제28권3호
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    • pp.247-261
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    • 2018
  • The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

A STUDY ON FUEL ESTIMATION ALGORITHMS FOR A GEOSTATIONARY COMMUNICATION & BROADCASTING SATELLITE

  • Eun, Jeong-Won
    • Journal of Astronomy and Space Sciences
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    • 제17권2호
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    • pp.249-256
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    • 2000
  • It has been developed to calculate fuel budget for a geostationary communication and broadcasting satellite. It is quite essential that the pre-launch fuel budget estimation must account for the deterministic transfer and drift orbit maneuver requirements. After on-station, the calculation of satellite lifetime should be based on the estimation of remaining fuel and assessment of actual performance. These estimations step from the proper algorithms to produce the prediction of satellite lifetime. This paper concentrates on the fuel estimation method that was studied for calculation of the propellant budget by using the given algorithms. Applications of this method are discussed for a communication and broadcasting satellite.

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A Deterministic Ray Tube Method for an Indoor Propagation Prediction Model

  • Suh, Choon-Gil;Koh, Hyung-Wha;Son, Hae-Won;Myung, Noh-Hoon
    • Journal of electromagnetic engineering and science
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    • 제1권1호
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    • pp.48-53
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    • 2001
  • This paper presents a new 3-D ray tracing technique based on the image theory with newly defined ray tubes. The proposed method can be applied to indoor environments with arbitrary building layouts and has high computational efficiency compared to the precedent methods resorting to the ray launching scheme. It predictions are in good agreement with the measurements.

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