A NEW DERIVATIVE FREE OPTIMIZATION METHOD BASED ON CONIC INTERPOLATION MODEL

In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model function, the collinear scaling formula, quadratic approximation and interpolation. All the parameters in this model are determined by objective function interpolation condition. A new derivative free method is developed based upon this model and the global convergence of this new method is proved without any information on gradient.

Development and application of a two-dimensional water quality model for the Daqinghe River Mouth of the Dianchi Lake

Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, a two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration （ADI） method. The parameters of the water quality module were obtained through the in situ experiments and the laboratory analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables, i.e., water level, COD （in CODcr）, NH4＋-N and PO43-P the minimum value of the coefficient of determination （COD） was 0.69, indicating the model performed reasonably well. The developed model was then applied to simulate the water quality changes at a downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of COD and PO43-P about 15%. Such a load reduction, unfortunately, would have very little effect on the NH4^＋-N removal. Moreover, the water quality at the outlet cross-section would be still in class V （3838-02）, indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations.

Assimilating the along-track sea level anomaly into the regional ocean modeling system using the ensemble optimal interpolation

The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.

Simulation of two-dimensional interior ballistics model of solid propellant electrothermal-chem ical launch with discharge rod plasma generator

Instead of the capillary plasma generator(CPG),a discharge rod plasma generator(DRPG)is used in the30 mm electrothermal-chemical(ETC)gun to improve the ignition uniformity of the solid propellant.An axisymmetric two-dimensional interior ballistics model of the solid propellant ETC gun(2D-IB-SPETCG)is presented to describe the process of the ETC launch.Both calculated pressure and projectile muzzle velocity accord well with the experimental results.The feasibility of the 2D-IB-SPETCG model is proved.Depending on the experimental data and initial parameters,detailed distribution of the ballistics parameters can be simulated.With the distribution of pressure and temperature of the gas phase and the propellant,the influence of plasma during the ignition process can be analyzed.Because of the radial flowing plasma,the propellant in the area of the DRPG is ignited within 0.01 ms,while all propellant in the chamber is ignited within 0.09 ms.The radial ignition delay time is much less than the axial delay time.During the ignition process,the radial pressure difference is less than 5 MPa at the place 0.025 m away from the breech.The radial ignition uniformity is proved.The temperature of the gas increases from several thousand K(conventional ignition)to several ten thousand K(plasma ignition).Compare the distribution of the density and temperature of the gas,we know that low density and high temperature gas appears near the exits of the DRPG,while high density and low temperature gas appears at the wall near the breech.The simulation of the 2D-IB-SPETCG model is an effective way to investigate the interior ballistics process of the ETC launch.The 2D-IB-SPETC model can be used for prediction and improvement of experiments.

Individual-tree diameter growth model for Korean pine plantations based on optimized interpolation of meteorological variables

To explore the influence of meteorological variables on the growth of Korean pine(Pinus koraiensis Sieb.et Zucc.) plantations and provide a scientific reference for the production and management of Korean pine,three approaches to interpolate meteorological variables during the growing season(i.e.,May-September) were compared in Heilongjiang Province,China.Optimized meteorological variable interpolation results were then combined with stand and individual tree variables,based on data from 56 sample plots and 2886 sample trees from Korean pine plantations in two regions of the province to develop an individualtree diameter growth model(Model I) and an individualtree diameter growth model with meteorological variables(Model Ⅱ) using a stepwise regression method.Moreover,an individual-tree diameter growth model with regional effects(Model Ⅲ) was developed using dummy variables in the regression,and the significance of introducing these dummy variables was verified with an F-test statistical analysis.The models were validated using an independent data set,and the predictive performance of the three models was assessed via the adjusted coefficient of determination(R_(a)^(2)) and root mean square error(RMSE).The results suggest that the growth increment in tree diameter of Korean pine plantations was significantly correlated with the natural logarithm of initial diameter(ln D),stand basal area(BAS),logarithmic deformation of the stand density index(ln SDI),ratio of basal area of trees larger than the subject tree to their initial diameter at breast height(DBH)(BAL/D),and the maximum growingseason precipitation(Pgmax).The individual-tree diameter growth models of Korean pine plantations developed in this study will provide a good basis for estimating and predicting growth increments of Korean pine forests over larger areas.

Performance assessment of two-dimensional hydraulic models for generation of flood inundation maps in mountain river basins

Hydraulic models for the generation of flood inundation maps are not commonly applied in mountain river basins because of the difficulty in modeling the hydraulic behavior and the complex topography. This paper presents a comparative analysis of the performance of four twodimensional hydraulic models (HEC-RAS 2D, Iber 2D, Flood Modeller 2D, and PCSWMM 2D) with respect to the generation of flood inundation maps. The study area covers a 5-km reach of the Santa B-arbara River located in the Ecuadorian Andes, at 2330 masl, in Gualaceo. The model's performance was evaluated based on the water surface elevation and flood extent, in terms of the mean absolute difference and measure of fit. The analysis revealed that, for a given case, Iber 2D has the best performance in simulating the water level and inundation for flood events with 20- and 50-year return periods, respectively, followed by Flood Modeller 2D, HEC-RAS 2D, and PCSWMM 2D in terms of their performance. Grid resolution, the way in which hydraulic structures are mimicked, the model code, and the default value of the parameters are considered the main sources of prediction uncertainty.

INTERPOLATION TECHNIQUE FOR SPARSE DATA BASED ON INFORMATION DIFFUSION PRINCIPLE-ELLIPSE MODEL

Addressing the difficulties of scattered and sparse observational data in ocean science,a new interpolation technique based on information diffusion is proposed in this paper.Based on a fuzzy mapping idea,sparse data samples are diffused and mapped into corresponding fuzzy sets in the form of probability in an interpolation ellipse model.To avoid the shortcoming of normal diffusion function on the asymmetric structure,a kind of asymmetric information diffusion function is developed and a corresponding algorithm-ellipse model for diffusion of asymmetric information is established.Through interpolation experiments and contrast analysis of the sea surface temperature data with ARGO data,the rationality and validity of the ellipse model are assessed.

HIGH RESOLUTION PARAMETRIC MODELLING FOR TWO-DIMENSIONAL RADAR TARGET USING PRONY ALGORITHM

On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.

An osculatory rational interpolation method of model reduction in linear system

A theorem for osculatory rational interpolation was shown to establish a new criterion of interpolation. On the basis of this conclusion a practical algorithm was presented to get a reduction model of the linear systems. Some numerical examples were given to explain the result in this paper.

NURBS Modeling and Curve Interpolation Optimization of 3D Graphics

In order to solve the problem of complicated Non-Uniform Rational B-Splines(NURBS)modeling and improve the real-time performance of the high-order derivative of the curve interpolation process,the method of NURBS modeling based on the slicing and layering of triangular mesh is introduced.The research and design of NURBS curve interpolation are carried out from the two aspects of software algorithm and hardware structure.Based on the analysis of the characteristics of traditional computing methods with Taylor series expansion,the Adams formula and the Runge-Kutta formula are used in the NURBS curve interpolation process,and the process is then optimized according to the characteristics of NURBS interpolation.This can ensure accuracy,and avoid the calculation of higher-order derivatives.Furthermore,the hardware modules for the Adams and Runge-Kutta formulas are designed by using the parallel hardware construction technology of Field Programmable Gate Array(FPGA)chips.The parallel computing process using FPGA is compared with the traditional serial computing process using CPUs.Simulation and experimental results show that this scheme can improve the computational speed of the system and that the algorithm is feasible.

A Numerical Algorithm Based on Quadratic Finite Element for Two-Dimensional Nonlinear Time Fractional Thermal Diffusion Model

In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+
t2)is obtained,which is verified by the numerical results.

Global Two-Dimensional Chemistry Model and Simulation of Atmospheric Chemical Composition

A global two-dimensional zonally averaged chemistry model is developed to study the chemi-cal composition of atmosphere. The region of the model is from 90°S to 90°N and from the ground to the altitude of 20 km with a resolution of 5° x 1 km. The wind field is residual circulation calcu-lated from diabatic rate. 34 species and 104 chemical and photochemical reactions are considered in the model. The sources of CH4, CO and NOx, which are divided into seasonal sources and non-seasonal sources, are parameterized as a function of latitude and time. The chemical composi-tion of atmosphere was simulated with emission level of CH4, CO and NOx in 1990. The results are compared with observations and other model results, showing that the model is successful to simu-late the atmospheric chemical composition and distribution of CH4. Key words Global two-dimensional chemistry model - Atmospheric composition - Emission This work was supported by the State Key Program for basic research “ Climate Dynamics and Cli-mate Prediction Theory” (Pandeng-yu-21).The authors would like to express their thanks to the National Oceanic and Atmospheric Administration (NOAA), Climate Monitoring and Diagnostics Laboratory (CMDL), Carbon Cycle Group for providing the observational data of CO and CH4.

Statistical Modeling with a Hidden Markov Tree and High-resolution Interpolation for Spaceborne Radar Reflectivity in the Wavelet Domain

With the increasing availability of precipitation radar data from space,enhancement of the resolution of spaceborne precipitation observations is important,particularly for hazard prediction and climate modeling at local scales relevant to extreme precipitation intensities and gradients.In this paper,the statistical characteristics of radar precipitation reflectivity data are studied and modeled using a hidden Markov tree(HMT)in the wavelet domain.Then,a high-resolution interpolation algorithm is proposed for spaceborne radar reflectivity using the HMT model as prior information.Owing to the small and transient storm elements embedded in the larger and slowly varying elements,the radar precipitation data exhibit distinct multiscale statistical properties,including a non-Gaussian structure and scale-to-scale dependency.An HMT model can capture well the statistical properties of radar precipitation,where the wavelet coefficients in each sub-band are characterized as a Gaussian mixture model(GMM),and the wavelet coefficients from the coarse scale to fine scale are described using a multiscale Markov process.The state probabilities of the GMM are determined using the expectation maximization method,and other parameters,for instance,the variance decay parameters in the HMT model are learned and estimated from high-resolution ground radar reflectivity images.Using the prior model,the wavelet coefficients at finer scales are estimated using local Wiener filtering.The interpolation algorithm is validated using data from the precipitation radar onboard the Tropical Rainfall Measurement Mission satellite,and the reconstructed results are found to be able to enhance the spatial resolution while optimally reproducing the local extremes and gradients.

Comprehensive two-dimensional river ice model based on boundary-fitted coordinate transformation method

River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.

Comparative study and error analysis of digital elevation model interpolations

Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe and simulate key hydrological features such as rivers and drainage borders.Taking a hilly region in southwestern China as a research area and using ArcGISTM software,we analyzed the errors of different interpolations to obtain distributions of the errors and precisions of different algorithms and to provide references for DEM productions.The results show that different interpolation errors satisfy normal distributions,and large error exists near the structure line of the terrain.Furthermore,the results also show that the precision of a DEM interpolated with the Australian National University digital elevation model(ANUDEM) is higher than that interpolated with TIN.The DEM interpolated with TIN is acceptable for generating DEMs in the hilly region of southwestern China.

Curve interpolation model for visualising disjointed neural elements

Neuron cell are built from a myriad of axon and denddte structures. It transmits electrochemical signals between the brain and the nervous system. Three-dimensional visualization of neuron structure could help to facilitate deeper understanding of neuron and its models. An accurate neuron model could aid understanding of brain＇s functionalities, diagnosis and knowledge of entire nervous system. Existing neuron models have been found to be defective in the aspect of realism. Whereas in the actual biological neuron, there is continuous growth as the soma extending to the axon and the dendrite; but, the current neuron visualization models present it as disjointed segments that has greatly mediated effective realism. In this research, a new reconstruction model comprising of the Bounding Cylinder, Curve Interpolation and Gouraud Shading is proposed to visualize neuron model in order to improve realism. The reconstructed model is used to design algorithms for generating neuron branching from neuron SWC data. The Bounding Cylinder and Curve Interpolation methods are used to improve the connected segments of the neuron model using a series of cascaded cylinders along the neuron＇s connection path. Three control points are proposed between two adjacent neuron segments. Finally, the model is rendered with Gouraud Shading for smoothening of the model surface. This produce a near-perfection model of the natural neurons with attended realism. The model is validated by a group of bioinformatics analysts＇ responses to a predefined survey. The result shows about 82% acceptance and satisfaction rate.

DETERMINATION OF PARAMETERS IN A TWO-DIMENSIONAL MODEL FOR FIXED-BED ADSORBERS

A new method is proposed for the determination of the parameters in a two-dimensionalmodel which characterizes the properties of axial and radial mixing and mass transport in afixed-bed adsorber.Parameter estimation for the model is carried out with methane-air-5A molecularsieve in a bed under the condition of step injection of tracer from a point on the main axis of thebed by the curve fitting method in the time domain.

Two-dimensional hydrodynamic robust numerical model of soil erosion based on slopes and river basins

Erosion is an important issue in soil science and is related to many environmental problems,such as soil erosion and sediment transport.Establishing a simulation model suitable for soil erosion prediction is of great significance not only to accurately predict the process of soil separation by runoff,but also improve the physical model of soil erosion.In this study,we develop a graphic processing unit(GPU)-based numerical model that combines two-dimensional(2D)hydrodynamic and Green-Ampt(G-A)infiltration modelling to simulate soil erosion.A Godunov-type scheme on a uniform and structured square grid is then generated to solve the relevant shallow water equations(SWEs).The highlight of this study is the use of GPU-based acceleration technology to enable numerical models to simulate slope and watershed erosion in an efficient and high-resolution manner.The results show that the hydrodynamic model performs well in simulating soil erosion process.Soil erosion is studied by conducting calculation verification at the slope and basin scales.The first case involves simulating soil erosion process of a slope surface under indoor artificial rainfall conditions from 0 to 1000 s,and there is a good agreement between the simulated values and the measured values for the runoff velocity.The second case is a river basin experiment(Coquet River Basin)that involves watershed erosion.Simulations of the erosion depth change and erosion cumulative amount of the basin during a period of 1-40 h show an elevation difference of erosion at 0.5-3.0 m,especially during the period of 20-30 h.Nine cross sections in the basin are selected for simulation and the results reveal that the depth of erosion change value ranges from-0.86 to-2.79 m and the depth of deposition change value varies from 0.38 to 1.02 m.The findings indicate that the developed GPU-based hydrogeomorphological model can reproduce soil erosion processes.These results are valuable for rainfall runoff and soil erosion predictions on rilled hillslopes and river basins.

Impact of Large Fresh Water Discharges into Hakata Bay Due to Torrential Rain Using Nested Two-Dimensional Convective-Dispersive Model

In this study, numerical simulation of a two-dimensional convective-dispersive model in Hakata Bay, Japan, is performed to analyze the impact of major river discharges due to torrential rain in Fukuoka City. Tank models are applied to calculate river discharges, which are taken into consideration as river inflow in the hydrodynamic model of Hakata Bay. A two-way nesting “edge” technique is developed and applied in the model in order to consider the influence of narrow and complex geographical features. The area around “Island City” and Imazu Bay are calculated in high resolution. The resulting model has high reproducibility since the calculated river discharges, tidal current, and salinity show good agreement with observed data. To analyze the impact of large river discharges, the calculation period is set from 11 September 2002 to 21 September 2002 since there was torrential rain on September 16 in the given year in Fukuoka City (163.5 mm/d). The results show that low-salinity water covered the whole of the inner part of Hakata Bay, and water of lower salinity than outer sea water (<34.0 psu) spread out to the bay’s mouth two days after the torrential rain event. Fresh water covered the entire area of Imazu Bay and flowed out from the mouth of the Bay after the torrential rain event. The behavior of fresh water after a few days of torrential rain was remarkably different from normal discharge river flow. These results indicate that the environment in Imazu Bay can be degraded severely by torrential rain. Therefore, countermeasures to protect ecosystems in Hakata Bay must be examined immediately.

Fast forward modeling of gravity anomalies for two-dimensional bodies of arbitrary shape and density distribution

A fast and high precision spatial domain algorithm is presented for forward modeling of two-dimensional(2D)body gravity anomalies of arbitrary shape and density distribution.The new algorithm takes advantage of the convolution properties of the expression for 2D gravity anomalies,uses a rectangular cell as a grid subdivision unit,and then 2D bodies with irregular cross-sections are approximated by a combination of 2D bodies with a rectangular cross section.The closed-form expression is used to calculate the gravitational anomalies of the combination of 2D bodies with a rectangular cross section.To improve computing effi ciency,the new algorithm uses a fast algorithm for the implementation of the Toeplitz matrix and vector multiplication.The synthetic 2D models with rectangular and circular cross-sections and constant and variable densities are designed to evaluate the computational accuracy and speed of the new algorithm.The experiment results show that the computation costs less than 6 s for a grid subdivision with 10000×10000 elements.Compared to the traditional forward modeling methods,the proposed method significantly improved computational effi ciency while guaranteeing computational accuracy.