• 제목/요약/키워드: Polynomial mathematical model

검색결과 87건 처리시간 0.024초

MEASUREMENT OF COASTAL EROSION ON THE EAST SEA USING CORONA SATELLITE IMAGERY

  • Park, Hee-Dae;Kim, Jong-Hong;Heo, Joon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.760-763
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    • 2006
  • In this paper, a small portion of coastline on the EAST SEA was studied using CORONA panoramic satellite photo and 1:5000 Korean National Topographic Map. The project site near Kangneung city was 3 Km shoreline on the Kangmoon Beach and the SongJeong Beach, which have suffered from severe erosion. The first and the most important step was to rectify a CORONA image over the project site. A rigid mathematical model and a heuristic polynomial transformation were used for the purpose. The rectified image was overlaid with 1:5000 Korean National Topographic Map produced by aerial mapping. Among numerous methods for shoreline erosion measurement, area-based approach was chosen and used for the computation for annual shoreline recession. The final result of the analysis was that the average recession in the period of 1963-1998 was 33.6m and the annual rate was 0.96m.

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Wavelength Assignment Optimization in SDH over WDM Rings

  • Chung, Jibok;Lee, Heesang;Han, ChiMoon
    • Management Science and Financial Engineering
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    • 제9권1호
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    • pp.11-27
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    • 2003
  • In this study, we propose a mathematical model based on the graph theory for the wavelength assignment problem arising in the design of SDH (Synchronous Digital Hierarchy) over WDM (Wavelength Division Multiplexing) ring networks. We propose a branch- and -price algorithm to solve the suggested models effectively within reasonable time in realistic SDH over WDM ring networks. By exploiting the structure of ring networks, we developed a polynomial time algorithm for efficient column generation and a branching rule that conserves the structure of column generation. In a computer simulation study, the suggested approach can find the optimal solutions within reasonable time and show better performance than the existing heuristics.

Locating and identifying model-free structural nonlinearities and systems using incomplete measured structural responses

  • Liu, Lijun;Lei, Ying;He, Mingyu
    • Smart Structures and Systems
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    • 제15권2호
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    • pp.409-424
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    • 2015
  • Structural nonlinearity is a common phenomenon encountered in engineering structures under severe dynamic loading. It is necessary to localize and identify structural nonlinearities using structural dynamic measurements for damage detection and performance evaluation of structures. However, identification of nonlinear structural systems is a difficult task, especially when proper mathematical models for structural nonlinear behaviors are not available. In prior studies on nonparametric identification of nonlinear structures, the locations of structural nonlinearities are usually assumed known and all structural responses are measured. In this paper, an identification algorithm is proposed for locating and identifying model-free structural nonlinearities and systems using incomplete measurements of structural responses. First, equivalent linear structural systems are established and identified by the extended Kalman filter (EKF). The locations of structural nonlinearities are identified. Then, the model-free structural nonlinear restoring forces are approximated by power series polynomial models. The unscented Kalman filter (UKF) is utilized to identify structural nonlinear restoring forces and structural systems. Both numerical simulation examples and experimental test of a multi-story shear building with a MR damper are used to validate the proposed algorithm.

Effect of nano glass cenosphere filler on hybrid composite eigenfrequency responses - An FEM approach and experimental verification

  • Pandey, Harsh Kumar;Hirwani, Chetan Kumar;Sharma, Nitin;Katariya, Pankaj V.;Dewangan, Hukum Chand;Panda, Subrata Kumar
    • Advances in nano research
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    • 제7권6호
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    • pp.419-429
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    • 2019
  • The effect of an increasing percentage of nanofiller (glass cenosphere) with Glass/Epoxy hybrid composite curved panels modeled mathematically using the multiscale concept and subsequent numerical eigenvalues of different geometrical configurations (cylindrical, spherical, elliptical, hyperboloid and flat) predicted in this research article. The numerical model of Glass/Epoxy/Cenosphere is derived using the higher-order polynomial type of kinematic theory in association with isoparametric finite element technique. The multiscale mathematical model utilized for the customized computer code for the evaluation of the frequency data. The numerical model validation and consistency verified with experimental frequency data and convergence test including the experimental elastic properties. The experimental frequencies of the multiscale nano filler-reinforced composite are recorded through the impact hammer frequency test rig including CDAQ-9178 (National Instruments) and LABVIEW virtual programming. Finally, the nano cenosphere filler percentage and different design associated geometrical parameters on the natural frequency data of hybrid composite structural configurations are illustrated through a series of numerical examples.

An integrated method of flammable cloud size prediction for offshore platforms

  • Zhang, Bin;Zhang, Jinnan;Yu, Jiahang;Wang, Boqiao;Li, Zhuoran;Xia, Yuanchen;Chen, Li
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제13권1호
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    • pp.321-339
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    • 2021
  • Response Surface Method (RSM) has been widely used for flammable cloud size prediction as it can reduce computational intensity for further Explosion Risk Analysis (ERA) especially during the early design phase of offshore platforms. However, RSM encounters the overfitting problem under very limited simulations. In order to overcome the disadvantage of RSM, Bayesian Regularization Artificial Neural (BRANN)-based model has been recently developed and its robustness and efficiency have been widely verified. However, for ERA during the early design phase, there seems to be room to further reduce the computational intensity while ensuring the model's acceptable accuracy. This study aims to develop an integrated method, namely the combination of Center Composite Design (CCD) method with Bayesian Regularization Artificial Neural Network (BRANN), for flammable cloud size prediction. A case study with constant and transient leakages is conducted to illustrate the feasibility and advantage of this hybrid method. Additionally, the performance of CCD-BRANN is compared with that of RSM. It is concluded that the newly developed hybrid method is more robust and computational efficient for ERAs during early design phase.

Mathematical Models to Describe the Kinetic Behavior of Staphylococcus aureus in Jerky

  • Ha, Jimyeong;Lee, Jeeyeon;Lee, Soomin;Kim, Sejeong;Choi, Yukyung;Oh, Hyemin;Kim, Yujin;Lee, Yewon;Seo, Yeongeun;Yoon, Yohan
    • 한국축산식품학회지
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    • 제39권3호
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    • pp.371-378
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    • 2019
  • The objective of this study was to develop mathematical models for describing the kinetic behavior of Staphylococcus aureus (S. aureus) in seasoned beef jerky. Seasoned beef jerky was cut into 10-g pieces. Next, 0.1 mL of S. aureus ATCC13565 was inoculated into the samples to obtain 3 Log CFU/g, and the samples were stored aerobically at $10^{\circ}C$, $20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$, and $35^{\circ}C$ for 600 h. S. aureus cell counts were enumerated on Baird Parker agar during storage. To develop a primary model, the Weibull model was fitted to the cell count data to calculate Delta (required time for the first decimal reduction) and ${\rho}$ (shape of curves). For secondary modeling, a polynomial model was fitted to the Delta values as a function of storage temperature. To evaluate the accuracy of the model prediction, the root mean square error (RMSE) was calculated by comparing the predicted data with the observed data. The surviving S. aureus cell counts were decreased at all storage temperatures. The Delta values were longer at $10^{\circ}C$, $20^{\circ}C$, and $25^{\circ}C$ than at $30^{\circ}C$ and $35^{\circ}C$. The secondary model well-described the temperature effect on Delta with an $R^2$ value of 0.920. In validation analysis, RMSE values of 0.325 suggested that the model performance was appropriate. S. aureus in beef jerky survives for a long period at low storage temperatures and that the model developed in this study is useful for describing the kinetic behavior of S. aureus in seasoned beef jerky.

양자 우물 소자 모델링에 있어서 다중 에너지 부준위 Boltzmann 방정식의 Self-consistent한 해법의 개발 (Self-consistent Solution Method of Multi-Subband BTE in Quantum Well Device Modeling)

  • 이은주
    • 대한전자공학회논문지SD
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    • 제39권2호
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    • pp.27-38
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    • 2002
  • 양자 우물 반도체 소자 모델링에 있어서 양자 우물의 다중 에너지 부준위 각각에 대한 Boltzmann 방정식의 해를 직접적으로 구하는 self-consistent한 방법을 개발하였다 양자 우물의 특성을 고려하여 Schrodinger 방정식과 Poisson 방정식 및 Boltzmann 방정식으로 구성된 양자 우물 소자 모델을 설정하였으며 이들의 직접적인 해를 유한 차분법과 Gummel-type iteration scheme에 의해 구하였다. Si MOSFET의 inversion 영역에 형성되는 양자 우물에 적용하여 그 시뮬레이션 결과로부터 본 방법의 타당성 및 효율성을 보여 주었다.

단일 허브를 이용한 시간 제약이 존재하는 수거 및 배달 차량 경로 문제 (Pick Up and Delivery Vehicle Routing Problem Under Time Window Using Single Hub)

  • 김지용
    • 산업경영시스템학회지
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    • 제42권4호
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    • pp.16-22
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    • 2019
  • After Dantzig and Rasmer introduced Vehicle Routing Problem in 1959, this field has been studied with numerous approaches so far. Classical Vehicle Routing Problem can be described as a problem of multiple number of homogeneous vehicles sharing a same starting node and having their own routes to meet the needs of demand nodes. After satisfying all the needs, they go back to the starting node. In order to apply the real world problem, this problem had been developed with additional constraints and pick up & delivery model is one of them. To enhance the effectiveness of pick up & delivery, hub became a popular concept, which often helps reducing the overall cost and improving the quality of service. Lots of studies have suggested heuristic methods to realize this problem because it often becomes a NP-hard problem. However, because of this characteristic, there are not many studies solving this problem optimally. If the problem can be solved in polynomial time, optimal solution is the best option. Therefore, this study proposes a new mathematical model to solve this problem optimally, verified by a real world problem. The main improvements of this study compared to real world case are firstly, make drivers visit every nodes once except hub, secondly, make drivers visit every nodes at the right time, and thirdly, make drivers start and end their journey at their own homes.

Optimization of Algerian Thymus fontanesii Boiss. & Reut Essential Oil Extraction by Electromagnetic Induction Heating

  • Ali, Lamia Sid;Brada, Moussa;Fauconnier, Marie-Laure;Kenne, Tierry
    • Natural Product Sciences
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    • 제24권1호
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    • pp.71-78
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    • 2018
  • The present study deals with the determination of optimal values of operating parameters such as the temperature of heating, the mass of the plant material and the volume of water leading to the best yield of electromagnetic induction (EMI) heating extraction of Algerian Thymus fontanesii essential oil. After an appropriate choice of the three critical variables, eight experiments leaded to a mathematical model as a first-degree polynomial presenting the response function (yield) in the relation to the operating parameters. From the retained model, we were able to calculate the average response, the different effects and their interactions. The maximum of essential oil recovery percentage relative to the initial mass of plant material was 1.69%, and was obtained at ($140^{\circ}C$, 250 g and 4.5 L). The chemical composition of the Algerian T. fontanesii essential oil under the obtained optimal conditions ($140^{\circ}C$, 250 g and 4.5 L), determined by GC/MS and GC/FID, reveled of the presence of major components such as: carvacrol ($70.6{\pm}0.1%$), followed by p-cymene ($8.2{\pm}0.2%$).

Prediction and analysis of optimal frequency of layered composite structure using higher-order FEM and soft computing techniques

  • Das, Arijit;Hirwani, Chetan K.;Panda, Subrata K.;Topal, Umut;Dede, Tayfun
    • Steel and Composite Structures
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    • 제29권6호
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    • pp.749-758
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    • 2018
  • This article derived a hybrid coupling technique using the higher-order displacement polynomial and three soft computing techniques (teaching learning-based optimization, particle swarm optimization, and artificial bee colony) to predict the optimal stacking sequence of the layered structure and the corresponding frequency values. The higher-order displacement kinematics is adopted for the mathematical model derivation considering the necessary stress and stain continuity and the elimination of shear correction factor. A nine noded isoparametric Lagrangian element (eighty-one degrees of freedom at each node) is engaged for the discretisation and the desired model equation derived via the classical Hamilton's principle. Subsequently, three soft computing techniques are employed to predict the maximum natural frequency values corresponding to their optimum layer sequences via a suitable home-made computer code. The finite element convergence rate including the optimal solution stability is established through the iterative solutions. Further, the predicted optimal stacking sequence including the accuracy of the frequency values are verified with adequate comparison studies. Lastly, the derived hybrid models are explored further to by solving different numerical examples for the combined structural parameters (length to width ratio, length to thickness ratio and orthotropicity on frequency and layer-sequence) and the implicit behavior discuss in details.