FEATURE SOLID MODELING TOOL SYSTEM:FSMTS

In conformity with the principle of Design for Manufacture,feature-based design strate- (?)es have been developed.As the“feature”is relevant to the“macro process plan”and“macro NC programs”,obviously,“feature”is beyond the power of conventional solid modellers.Neverthe- less,substantial breakthrough has not been made in the solid modeling field,except“feature at- taching”or“feature recognizing”methods have been taken on.In this paper,the theory, concepts,system architecture,and algorithm principles of solid modeling tool system have been represented.The practice of Feature Solid Modeling Tool System (FSMTS) developed at Huazhong University has proved that the tool may be a new foundation of Feature-Based Design.

Developing a modeling tool for flow profiling in irrigation distribution networks

Efforts are underway to rehabilitate the irrigation districts,such as in the Rio Grande Basin in Texas.Water distribution network models are needed to help prioritize and analyze various rehabilitation options,as well as to scientifically quantify irrigation water demands,usages,and losses,and to help manage gate automation.However,commercially available software packages were limited in applications due to their high cost and operational difficulty.This study aims to develop a modeling tool for modeling the water flow profile in irrigation distribution networks.The goal of developing the modeling tool was to make the modeling process simple,fast,reliable and accurate.On the basis of methodological study,the modeling tool has been developed for branching canal networks with the assumption of steady gradually varied flow.The flow profile calculation of the tool was verified from a single channel with 1%root mean squared error compared to the benchmark calculation and a branching network with 5%to 12%relative errors compared to check point measurement along the network.The developed modeling tool will be able to play an important role in water quantification for planning,analysis and development for modernization of irrigation systems.

Runoff Modeling in Ungauged Catchments Using Machine Learning Algorithm-Based Model Parameters Regionalization Methodology

Model parameters estimation is a pivotal issue for runoff modeling in ungauged catchments.The nonlinear relationship between model parameters and catchment descriptors is a major obstacle for parameter regionalization,which is the most widely used approach.Runoff modeling was studied in 38 catchments located in the Yellow–Huai–Hai River Basin(YHHRB).The values of the Nash–Sutcliffe efficiency coefficient(NSE),coefficient of determination(R2),and percent bias(PBIAS)indicated the acceptable performance of the soil and water assessment tool(SWAT)model in the YHHRB.Nine descriptors belonging to the categories of climate,soil,vegetation,and topography were used to express the catchment characteristics related to the hydrological processes.The quantitative relationships between the parameters of the SWAT model and the catchment descriptors were analyzed by six regression-based models,including linear regression(LR)equations,support vector regression(SVR),random forest(RF),k-nearest neighbor(kNN),decision tree(DT),and radial basis function(RBF).Each of the 38 catchments was assumed to be an ungauged catchment in turn.Then,the parameters in each target catchment were estimated by the constructed regression models based on the remaining 37 donor catchments.Furthermore,the similaritybased regionalization scheme was used for comparison with the regression-based approach.The results indicated that the runoff with the highest accuracy was modeled by the SVR-based scheme in ungauged catchments.Compared with the traditional LR-based approach,the accuracy of the runoff modeling in ungauged catchments was improved by the machine learning algorithms because of the outstanding capability to deal with nonlinear relationships.The performances of different approaches were similar in humid regions,while the advantages of the machine learning techniques were more evident in arid regions.When the study area contained nested catchments,the best result was calculated with the similarity-based parameter regionalization scheme because of the high catchment density and short spatial distance.The new findings could improve flood forecasting and water resources planning in regions that lack observed data.

Dynamics Analysis of a Parallel Mill-turn Tool Spindle Head Driven by Dual-linear Motors Using Extended Transfer Matrix Method

The hybrid dynamics of multi-rigid-body and multi-flexible-body system becomes the mainstream of multi-body dynamics.Currently there lacks a compact approach to model the hybrid dynamics,especially in modern machine tool application,due to the difficulty of solving the hybrid equations or the limitation of current software when dealing with the hybrid dynamics.The extended transfer matrix method（E-TMM）,which extends elements in three-dimensional space with higher matrixes,is proposed to simplify the modeling process of the hybrid dynamics.The E-TMM modeling approaches of 3 basic elements including 3D vibrant rigid body,joint and flexible body are studied in details.A parallel mill-turn tool spindle head unit driven by dual-linear motors is chosen as a plant to demonstrate the E-TMM modeling process.By using E-TMM,the spindle head unit is simplified as a topological network consisting of the three types of element,i.e.,3D vibrant rigid body,joint and flexible body,including 11 rigid bodies,14 joints and 1 3D-Timoshenko beam.Then the dynamic model of the system can be easily obtained by deducing the element-network by means of state vector transformation.The dynamic characteristics of the spindle head,such as natural frequencies,dynamic flexibility,etc.can be predicted by solving the obtained model.Experiment verification indicates that the E-TMM is valid with enough accuracy in the dynamic analysis of the parallel mill-turn tool spindle head.The E-TMM is capable of modeling the dynamics of machine tool structure with no requirements of deducing and solving the sophisticated differential equations.Moreover,the E-TMM provides a simple and elegant tool for hybrid dynamic analysis in future dynamic design of machine tools.

Conversion of Rapid Prototyping Models into Metallic Tools by Ceramic Moulding—an Indirect Rapid Tooling Process

A process to convert models made by rapid prototypi ng techniques like SL (stereolitography) and LOM (laminated object manufacturing) or by conventional techniques (silicones, resins, wax, etc.) into metallic mould s or tools has been developed. The main purpose of this technique is to rapidly obtain the first prototypes of parts, for plastics injection, forging or any oth er manufacturing process using the tools produced by casting a metal into a cera mic mould. Briefly, it can be said that the ceramic moulds are produced by mixing in variab le proportions, depending on the type of ceramics employed, strength and roughne ss desired, a ceramic mixture composed by alumina and/or zirconium silicates bon ded with silica coming from a liquid binder, based on ethyl silicate. A catalyst is added to the slurry in order to produce a sol-gel reaction. The liquid slur ry is poured into the box containing the mould to be reproduced. After a short p eriod of time, controlled by the amount of gelling agent, the ceramic mixture ac quires a rubber consistency. The pattern is removed from the ceramic mould, whic h is fired to stop the gelation reaction. After this stabilization the ceramic m ould is sintered at high temperatures in order to generate an inert mould wi th the desired strength in which almost all metallic alloys can be cast. The effect of ceramic materials (shape, granulometric distribution, chemical com position, etc.), processing parameters (proportion binder/ceramic/catalyst, sint ering conditions, etc.) and casting conditions (mould pre-heating temperature a nd pouring temperature) were studied in order to obtain metallic moulds or tools with tailored properties (high dimensional accuracy, low roughness and high mec hanical strength).

WEB-BASED VIRTUAL CNC MACHINE MODELING AND OPERATION

A CNC simulation system based on intemet for operation training of manufacturing facility and manufacturing process simulation is proposed. Firstly, the system framework and a rapid modeling method of CNC machine tool are studied under the virtual environment based on PolyTrans and CAD software. Then, a new method is proposed to enhance and expand the interactive ability of virtual reality modeling language（VRML） by attaining communication among VRML, JavaApplet, JavaScript and Html so as to realize the virtual operation for CNC machine tool. Moreover, the algorithm of material removed simulation based on VRML Z-map is presented. The advantages of this algorithm include less memory requirement and much higher computation. Lastly, the CNC milling machine is taken as an illustrative example for the prototype development in order to validate the feasibility of the proposed approach.

MODULE DEFINITION MODEL FOR MODULAR DESIGN AND MANUFACTU－RING OF HEAVY DUTY MACHINE TOOLS

The key techniques of modular design of heavy duty NC mathine tools are described. Amodule definition modelfor modular design and manufacturing of heavy duty NC machine tools isbulit and the essential composition of the module definition model (MDM) is discussed in detail. Itis composed of two models: the part definition model (PDM) and the module assembly model(MAM). The PDM and MAM are built and their structures are given. Using object-oriented know-ledge representation and based on these models, an intelligent support system of modular design forheavy duty NC machine tools is developed and implemented This system has been applied to thepractical use of Wuhan Heavy Duty Machine Tool Works

Quantification of Effects of Natural Geographical Factors and Land-scape Patterns on Non-point Source Pollution in Watershed Based on Geodetector:Burhatong River Basin,Northeast China as An Example

Changes in natural geographic features and landscape patterns directly influence the hydrology and non-point source pollution processes in the watershed;however,to slow down non-point source pollution,it is necessary to distinguish their effects.But the non-point source pollution process is interactional as a result of multiple factors,and the collinearity between multiple independent variables limits our ability of reason diagnosis.Thus,taking the Burhatong River Basin,Northeast China as an example,the methods of hydrological simulation,geographic detectors,and redundancy analysis have been combined to determine the impact of natural geographic features and landscape patterns on non-point source pollution in the watershed.The Soil&Water Assessment Tool(SWAT)has been adopted to simulate the spatial and temporal distribution characteristics of total nitrogen and total phosphorus in the watershed.The results show that the proportions of agricultural land and forest area and the location-weighted landscape contrast index(LWLI)are the main indicators influencing the rivers total nitrogen and total phosphorus.The interaction of these indicators with natural geographic features and landscape configuration indicators also significantly influences the changes in total nitrogen(TN)and total phosphorus(TP).Natural geographical features and landscape patterns have different comprehensive effects on non-point source pollution in the dry and wet seasons.TN and TP loads are affected mainly by the change in landscape pattern,especially in the wet season.Although the ecological restoration program has improved forest coverage,the purification effect of increased forest coverage on the water quality in the watershed may be offset by the negative impact of increased forest fragmentation.The high concentration and complexity of farmland patches increase the risk of non-point source pollution spread to a certain extent.

Analysis of the Relationship between Landuse and Non-point Source Pollution in Ashi River Basin

Landuse is one of the most influential factors of non-point source pollution. Based on the three-year landuse data( 2000,2005 and 2008),Arc GIS and Fragstat were used to analyze the landuse type and the change of landscape pattern. The relationships between landuse and non-point source-total nitrogen( NPS-TN) and nonpoint source-total phosphorus( NPS-TP) were discussed with the methods of spatially statistical analysis,landscape pattern analysis and principal component analysis. The study results conveyed that agricultural land and forestland,which accounted for over 92% of the study area,were the major landuse type of Ashi River Basin.Meanwhile,the NPS pollution had close connections with landuse type and landscape pattern. When it comes to landuse type,the export risks of NPS-TN and NPS-TP were agricultural land > urban land > grassland > forestland. As for landscape pattern,NPS-TN and NPS-TP were positively related to SHDI and SHEI, while negatively connected with LPI,AI and COHESION. Therefore,the study could reach the conclusion that the more fragmented and complicated the landscape patterns were,the more serious the NPS pollution was.

Multi-view collaborative modeling method for complex system

It is hard to model a complex system by simply combining its partial characteristics.This paper presents a multi-view collaborative modeling method for complex system.Multi users,multi subjects,multi granularities and multi models in complex system modeling are unified to multi views.The principles and schemes for the decomposition of complex systems are introduced.According to the principle of separation of concerns,a complex system can be decomposed to a variety of model views.Collaborative modeling means that the views can be associated and integrated to form complete system model through their semantic.According to the form of representation,the models are generalizes to three kinds,i.e.,view models,semantic models and storage models,which provides a unified framework for conversion and mapping between the models.Under the guidance of the method,a tool for the modeling of warship C2 system is developed.Applications show that the tool can support collaborative modeling and design for C2 system outstandingly.

Suitability of common models to estimate hydrology and diffuse water pollution in North-eastern German lowland catchments with intensive agricultural land use

Various process-based models are extensively being used to analyze and forecast catchment hydrology and water quality. However, it is always important to select the appropriate hydrological and water quality modeling tools to predict and analyze the watershed and also consider their strengths and weaknesses. Different factors such as data availability, hydrological, hydraulic, and water quality processes and their desired level of complexity are crucial for selecting a plausible modeling tool. This review is focused on suitable model selection with a focus on desired hydrological, hydraulic and water quality processes(nitrogen fate and transport in surface, subsurface and groundwater bodies) by keeping in view the typical lowland catchments with intensive agricultural land use,higher groundwater tables, and decreased retention times due to the provision of artificial drainage. In this study, four different physically based, partially and fully distributed integrated water modeling tools, SWAT(soil and water assessment tool), SWIM(soil and water integrated model),HSPF(hydrological simulation program– FORTRAN) and a combination of tools from DHI(MIKE SHE coupled with MIKE 11 and ECO Lab), have been reviewed particularly for the Tollense River catchment located in North-eastern Germany. DHI combined tools and SWAT were more suitable for simulating the desired hydrological processes, but in the case of river hydraulics and water quality, the DHI family of tools has an edge due to their integrated coupling between MIKE SHE, MIKE 11 and ECO Lab. In case of SWAT, it needs to be coupled with another tool to model the hydraulics in the Tollense River as SWAT does not include backwater effects and provision of control structures. However, both SWAT and DHI tools are more data demanding in comparison to SWIM and HSPF. For studying nitrogen fate and transport in unsaturated, saturated, and river zone, HSPF was a better model to simulate the desired nitrogen transformation and transport processes. However, for nitrogen dynamics and transformations in shallow streams, ECO Lab had an edge due its flexibility for inclusion of user-desired water quality parameters and processes. In the case of SWIM, most of the input data and governing equations are similar to SWAT but it does not include water bodies(ponds and lakes), wetlands and drainage systems. In this review, only the processes that were needed to simulate the Tollense River catchment were considered, however the resulted model selection criteria can be generalized to other lowland catchments in Australia, North-western Europe and North America with similar complexity.

Evaluation and Hydrological Application of CMADS Reanalysis Precipitation Data against Four Satellite Precipitation Products in the Upper Huaihe River Basin, China

Satellite-and reanalysis-based precipitation products are important data source for precipitation, particularly in areas with a sparse gauge network. Here, five open-access precipitation products, including the newly released China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool(SWAT) model(CMADS)reanalysis dataset and four widely used bias-adjusted satellite precipitation products [SPPs;i.e., Tropical Rainfall Measuring Mission(TRMM) Multisatellite Precipitation Analysis 3B42 Version 7(TMPA 3B42V7), Climate Prediction Center(CPC) morphing technique satellite–gauge blended product(CMORPH-BLD), Climate Hazards Group Infrared Precipitation with Station Data(CHIRPS), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record(PERSIANN-CDR)], were assessed. These products were first compared with the gauge observed data collected for the upper Huaihe River basin, and then were used as forcing data for streamflow simulation by the Xin’anjiang(XAJ) hydrological model under two scenarios with different calibration procedures. The performance of CMADS precipitation product for the Chinese mainland was also assessed. The results show that:(1) for the statistical assessment, CMADS and CMORPH-BLD perform the best, followed by TMPA 3B42V7, CHIRPS, and PERSIANN-CDR, among which the correlation coefficient(CC) and rootmean-square error(RMSE) values of CMADS are optimal, although it exhibits certain significant negative relative bias(BIAS;-22.72%);(2) CMORPH-BLD performs the best in capturing and detecting rainfall events, while CMADS tends to underestimate heavy and torrential precipitation;(3) for streamflow simulation, the performance of using CMADS as input is very good, with the highest Nash–Sutcliffe efficiency(NSE) values(0.85 and 0.75 for calibration period and validation period, respectively);and(4) CMADS exhibits high accuracy in eastern China while with significant negative BIAS, and the performance declines from southeast to northwest. The statistical and hydrological evaluations show that CMADS and CMORPH-BLD have high potential for observing precipitation. As high negative BIAS values showed up in CMADS evaluation, further study on the error sources from original data and calibration algorithms is necessary. This study can serve as a reference for selecting precipitation products in datascarce regions with similar climates and topography in the Global Precipitation Measurement(GPM) era.

Evaluation of alternative surface runoff accounting procedures using SWAT model

For surface runoff estimation in the Soil and Water Assessment Tool(SWAT)model,the curve number(CN)procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition(SCSI)in field.From SWAT2005 and onward,an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration(SCSII).While improved runoff prediction with SCSII has been reported in several case studies,few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method.The objectives of the research were:(1)to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques;and(2)to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging(BMA).Applications of BMA provide an alternative approach to investigate the nature of structural uncertainty associated with both CN methods.Results showed that SCSII and BMA associated approaches exhibit improved performance in both discharge and total NO3 predictions compared to SCSI.In addition,the application of BMA has a positive effect on finding well performed solutions in the multi-dimensional parameter space,but the predictive uncertainty is not evidently reduced or enhanced.Therefore,we recommend additional future SWAT calibration/validation research with an emphasis on the impact of SCSII on the prediction of other pollutants.