Soil-water characteristic surface model of soil-rock mixture

The relationship between the water content or saturation of unsaturated soils and its matrix suction is commonly described by the soilwater characteristic curve(SWCC).Currently,study on the SWCC model is focused on fine-grained soils like clay and silty soils,but the SWCC model for grinding soil-rock mixture(SRM)is less studied.Considering that the SRM is in a certain compaction state in the actual project,this study established a surface model with three variables of coupling compaction degree-substrate suction-moisture content based on the Cavalcante-Zornberg soil-water characteristic curve model.Then,the influence of each fitting parameter on the curve was analyzed.For the common SRM,the soil-water characteristic test was conducted.Moreover,the experimental measurements exhibit remarkable consistency with the mode surface.The analysis shows that the surface model intuitively describes the soil-water characteristics of grinding SRM,which can provide the SWCC of soils with bimodal pore characteristics under specific compaction degrees.Furthermore,it can reflect the influence of compaction degrees on the SWCC of rock-soil mass and has a certain prediction effect.The SWCC of SRM with various soil-rock ratios have a double-step shape.With the increase in compaction degree,the curves as a whole tend toward decreasing mass moisture content.The curve changes are mainly concentrated in the large pore section.

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automatic recognition of the road surface from noise is performed based on the fuzzy clustering of normal vectors, with which the mean value is calculated and the projecting plane of point cloud is created to obtain the geometric model accordingly. Based on fuzzy clustering of the intensity attributed to each point, different objects on the road surface are assigned different colors for representing abundant appearances. This unsupervised method is demonstrated in the experiment and shows great effectiveness in reconstructing and rendering better road surface.

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model （DGVM） coupled with a land surface model （LSM） is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages （FCs） of plant functional type （PFT） in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model （CLM-DGVM）. Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region （TR） and the wet temperate climate region （WM）. In the tropical monsoon climate region （TM）, the TR and TM transition region （TR-TM）, the dry temperate climate region （DM）, the highland climate region （H）, and the boreal forest climate region （BF）, where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.

Surfel-based surface modeling for robotic belt grinding simulation

The new flee-form surface modelling technology for robotic belt grinding simulation presented in this paper is based on discrete surfel elements generated from the surface approximation point set and can facilitate the simulation implementation. A local process model exploits the advantage of surfel representation to compute the material removal rate and the final surface grinding error can be easily carried out. With the help of this system, robot programmers can improve the path planning and predict potential problems by visualizing the manufacturing process.

Case Analyses and Numerical Simulation of Soil ThermalImpacts on Land Surface Energy Budget Based on anOff-Line Land Surface Model

The statistical relationship between soil thermal anomaly and short-term climate change is presented based on a typical case study. Furthermore, possible physical mechanisms behind the relationship are re-vealed through using an off-line land surface model with a reasonable soil thermal forcing at the bottom of the soil layer. In the first experiment, the given heat flux is 5 W m2 at the bottom of the soil layer (in depth of 6.3 m) for 3 months, while only a positive ground temperature anomaly of 0.06°C can be found compared to the control run. The anomaly, however, could reach 0.65°C if the soil thermal conductivity was one order of magnitude larger. It could be even as large as 0.81°C assuming the heat flux at bottom is 10 W m-2. Mean-while, an increase of about 10 W m−2 was detected both for heat flux in soil and sensible heat on land sur-face, which is not neglectable to the short-term climate change. The results show that considerable response in land surface energy budget could be expected when the soil thermal forcing reaches a certain spatial-tem-poral scale. Therefore, land surface models should not ignore the upward heat flux from the bottom of the soil layer. Moreover, integration for a longer period of time and coupled land-atmosphere model are also necessary for the better understanding of this issue.

A New Approach for Parameter Optimization in Land Surface Model

In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation （CNOP） in a land surface model （LSM） using long-term enhanced field observations at Tongyu station in Jilin Province,China,combined with a sophisticated LSM （common land model,CoLM）.Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project （CEOP） that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments：First,a single-parameter optimization was performed,while the second and third experiments performed triple-and six-parameter optimizations,respectively.Notable improvements in simulating sensible heat flux （SH）,latent heat flux （LH）,soil temperature （TS）,and moisture （MS） at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.

A new GIS-compatible methodology for visibility analysis in digital surface models of earth sites

As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position and shapes of all objects that can sometimes act as visibility barriers.However,some barriers,for example vegetation,may be permeable to a certain degree.Despite extensive research and use of visibility analysis in different areas,standard GIS tools do not take permeability into account.This article presents a new method to calculate visibility through partly permeable obstacles.The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation.Each iteration result represents 1%of vegetation permeability,which can thus range from 1%to 100%visibility behind vegetation obstacles.The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software.The incorporation of the proposed method in GIS software would facilitate work in many fields,such as architecture,archaeology,radio communication,and the military.

Improving the Vegetation Dynamic Simulation in a Land Surface Model by Using a Statistical-dynamic Canopy Interception Scheme

Canopy interception of incident precipitation, as a critical component of a forest＇s water budget, can affect the amount of water available to the soil, and ultimately vegetation distribution and function. In this paper, a statistical-dynamic approach based on leaf area index and statistical canopy interception is used to parameterize the canopy interception process. The statistical-dynamic canopy interception scheme is implemented into the Community Land Model with dynamic global vegetation model （CLM-DGVM） to improve its dynamic vegetation simulation. The simulation for continental China by the land surface model with the new canopy interception scheme shows that the new one reasonably represents the precipitation intercepted by the canopy. Moreover, the new scheme enhances the water availability in the root zone for vegetation growth, especially in the densely vegetated and semi-arid areas, and improves the model＇s performance of potential vegetation simulation.

A Proper Time Integration with Split Stepping for the Explicit Free-Surface Modeling

Errors due to split time stepping are discussed for an explicit free–surface ocean model. In commonly used split time stepping, the way of time integration for the barotropic momentum equation is not compatible with that of the baroclinic one. The baroclinic equation has three–time–level structure because of leapfrog scheme. The barotropic one, however, has two–time–level structure when represented in terms of the baroclinic time level, on which the baroclinic one is integrated. This incompatibility results in the splitting errors as shown in this paper. The proper split time stepping is therefore proposed in such a way that the compatibility is kept between the barotropic and baroclinic equations. Its splitting errors are shown extremely small, so that it is particularly relevant to long–term integration for climate studies. It is applied to a free–surface model for the North Pacific Ocean.

The integration of nitrogen dynamics into a land surface model. Part 1: model description and site-scale validation

Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes.However,nutrient cycling is not taken into account in most land surface models for climate change.In this study,a nitrogen model,based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem,was incorporated into the Atmosphere–Vegetation Interaction Model(AVIM)to simulate the carbon cycle under nitrogen limitation.This new model,AVIM-CN,was evaluated against site-scale eddy covariance–based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset.Results showed that the annual mean gross primary production simulated by AVIM-CN(0.7073 gC m^-2 d^-1)was in better agreement with the corresponding flux data(0.5407 gC m^-2 d^-1)than the original AVIM(1.1403 gC m^-2 d^-1)at Damxung station.Similarly,ecosystem respiration was also down-regulated,from 1.7695 gC m^-2 d^-1 to 1.0572 gC m^-2 d^-1,after the nitrogen processes were introduced,and the latter was closer to the observed vales(0.8034 gC m^-2 d^-1).Overall,the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics.A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.

Subdivision surface modeling system based on arbitrary topological curves network and combined subdivision

Arbitrary topological curve network has no restriction in topology structure,so it has more powerful representing ability in defining complex surfaces.A complex surface modeling system is presented based on arbitrary topological curve network and the improved combined subdivision method,its functions including creating and editing curve network,and generating and modifying curve network＇s interpolated surface.This modeling system can be used to the process of products＇concept design,and its applications is also significant to the development of subdivision method.

A TECHNIQUE OF DIGITAL SURFACE MODEL GENERATION

It is usually a time-consuming process to real-time set up 3D digital surface model(DSM) of an object with complex surface.On the basis of the architectural survey project of"Chilin Nunnery Reconstruction",this paper investigates an easy and feasible way,that is,on project site,applying digital close range photogrammetry and CAD technique to establish the DSM for simulating ancient architectures with complex surface.The method has been proved very effective in practice.

Numerical Simulation of Injection Molding Cooling Process Based on 3D Surface Model

The design of the cooling system of injection molds directly affects both productivity and the quality of the final part. Using the cooling process CAE system to instruct the mold design, the efficiency and quality of design can be improved greatly. At the same time, it is helpful to confirm the cooling system structure and optimize the process conditions. In this paper, the 3D surface model of mold cavity is used to replace the middle-plane model in the simulation by Boundary Element Method, which break the bottleneck of the application of the injection molding simulation softwares base on the middle-plane model. With the improvements of this paper, a practical and commercial simulation software of injection molding cooling process named as HsCAE3D6.0 is developed.

An Adaptive and Image-guided Fusion for Stereo Satellite Image Derived Digital Surface Models

The accuracy of Digital Surface Models(DSMs)generated using stereo matching methods varies due to the varying acquisition conditions and configuration parameters of stereo images.It has been a good practice to fuse these DSMs generated from various stereo pairs to achieve enhanced,in which multiple DSMs are combined through computational approaches into a single,more accurate,and complete DSM.However,accurately characterizing detailed objects and their boundaries still present a challenge since most boundary-ware fusion methods still struggle to achieve sharpened depth discontinuities due to the averaging effects of different DSMs.Therefore,we propose a simple and efficient adaptive image-guided DSM fusion method that applies k-means clustering on small patches of the orthophoto to guide the pixel-level fusion adapted to the most consistent and relevant elevation points.The experiment results show that our proposed method has outperformed comparing methods in accuracy and the ability to preserve sharpened depth edges.

An Effective Surface Modeling Method for Car Styling from a Side-View Image

We introduce an almost-automatic technique for generating 3D car styling surface models based on a single side-view image. Our approach combines the prior knowledge of car styling and deformable curve network model to obtain an automatic modeling process. Firstly, we define the consistent parameterized curve template for 2D and 3D case respectivelyby analyzingthe characteristic lines for car styling. Then, a semi-automatic extraction from a side-view car image is adopted. Thirdly, statistic morphable model of 3D curve network isused to get the initial solution with sparse point constraints.Withonly afew post-processing operations, the optimized curve network models for creating surfaces are obtained. Finally, the styling surfaces are automatically generated using template-based parametric surface modeling method. More than 50 3D curve network models are constructed as the morphable database. We show that this intelligent modeling toolsimplifiesthe exhausted modeling task, and also demonstratemeaningful results of our approach.

Using UAVs for detection of trees from digital surface models

A difficult problem in forestry is tree inventory.In this study, a GoProHero attached to a small unmanned aerial vehicle was used to capture images of a small area covered by pinus pinea trees. Then, a digital surface model was generated with image matching. The elevation model representing the terrain surface, a ‘digital terrain model’,was extracted from the digital surface model using morphological filtering. Individual trees were extracted by analyzing elevation flow on the digital elevation model because the elevation reached the highest value on the tree peaks compared to the neighborhood elevation pixels. The quality of the results was assessed by comparison with reference data for correctness of the estimated number of trees. The tree heights were calculated and evaluated with ground truth dataset. The results showed 80% correctness and 90% completeness.

Statistical Characteristics of the Received Signal for Stochastic Surface Models

This paper describes the stochastic model of the scattered electromagnetic field.Unlike common_used functional_determined models the proposed is characterised by amplitude/phase fluctuation of the received signal.This paper derives the statistical characteristic of the input signal and describes algorithm for its estimation in post_processing and real_time processing modes.Achieved characteristics allow the mapping and estimation of the surface models more accurate,moreover,such processing increase space resolution of synthetic aperture radar.

Primary safe criterion of earth-brushing flight for flying vehicle over digital surface model

In modern terrain-following guidance it is an important index for flight vehicle to cruise about safely and normally. On the basis of a constructing method of digital surface model (DSM), the definition, classification and scale analysis of an isolated obstacle threatening flight safety of terrain-following guidance are made. When the interval of vertical-and cross-sections on DSM is 12. 5 m, the proportion of isolated obstacles to the data amount of DSM model to be loaded is optimal. The main factors influencing the lowest flying height in terrain-following guidance are analyzed, and a primary safe criterion of the lowest flying height over DSM model is proposed. According to their test errors, the lowest flying height over 1:10 000 DSM model can reach 40. 5 m^45. 0 m in terrain-following guidance. It is shown from the simulation results of a typical urban district that the proposed models and methods are reasonable and feasible.

A two scale nonlinear fractal sea surface model in a one dimensional deep sea

Using the theory of nonlinear interactions between long and short waves, a nonlinear fractal sea surface model is presented for a one dimensional deep sea. Numerical simulation results show that spectra intensity changes at different locations （in both the wave number domain and temporal-frequency domain）, and the system obeys the energy conservation principle. Finally, a method to limit the fractal parameters is also presented to ensure that the model system does not become ill-posed,

Design optimization of transonic compressor stage using CFD and response surface model

In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver(Numeca Fine). Data points for response evaluations were selected by improved distributed hypercube sampling (IHS) and the 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. To maximize the adiabatic efficiency, the genetic algorithm was applied to the response surface model to perform global optimization to achieve the optimum design of NASA Stage 35. An optimum leading edge line was found, which produced a new 3-D rotor blade combined with sweep and lean, and a new stator one with skew. It is concluded that the proposed strategy can provide a reliable method for design optimization of turbomachinery blades at reasonable computing cost.