绣针河下游地区三维地层建模

基于水源地实例,以钻孔资料为地层建模的数据来源,GMS软件为建模手段,介绍了建模过程,阐述了绣针河下游水源地的三维地层模型,以期为含水层水流、水质模拟建立基础。     

中密度纤维板热压过程的工艺仿真建模

针对中密度纤维板生产过程能耗高、成品性能不尽人意提出了中密度纤维板热压过程的工艺仿真建模方案。将热压过程的工艺参数作为优化的对象,分析不同参数对成品性能的影响。建立数学模型并在MATLAB仿真环境下仿真中密度纤维板热压生产过程。利用此模型制定合理的热压参数指导实际生产,计算结果较准确地预测出实验结果,验证热压过程仿真的实用性与准确性。     

基于神经网络的棉花质量检测系统的可行性分析

研究了气固两相流中固体质量的检测方法,针对棉花气力输送的非均匀性进行了分析,提出了应用神经网络进行棉花质量建模的分析方法,并分析了神经网络建模的过程,确定了系统的研究方案。     

蔬菜氮磷钾三元肥效模型的MonteCarlo建模法

应用"3414"设计的田间肥料试验结果,探讨蔬菜氮磷钾三元肥效模型的Monte Carlo建模法。莴苣试验结果表明,采用最小二乘法回归建模,NP、NK二元肥效模型属于非典型式,PK二元和NPK三元肥效模型属于典型式;而改用MonteCarlo建模法,NP、NK和PK二元肥效模型以及NPK三元肥效模型均属于典型式。采用最小二乘法回归建模,不同蔬菜作物建立的34个三元肥效模型的典型式出现机率为41.2%,而Monte Carlo建模法的典型式出现机率为91.2%,提高了2.2倍。Monte Carlo建模法是适当放弃数学上偏差平方和最小的最优性,使待估参数达到专业上最优而数学上较优,从而提高典型肥效模型的出现机率。对莴苣氮钾非典型肥效模型的推荐施肥表明,Monte Carlo法的结果明显优于产量频率分析法。因此,Monte Carlo建模法为建立蔬菜多元肥效模型和推荐施肥提供了一种有效方法。     

Effect of braid structure on yarn cross-sectional shape

The effect of braid construction parameters on yarn cross-sectional shape is presented in this paper. The location of the yarn within the braid unit cell is quantified by a compaction factor. A range of braided fabrics were produced and optically measured for actual yarn cross-sectional shape. A comparison of the theoretical and experimental values shows good correlation. Design curves can be produced with the developed model to allow selection of appropriate braid process parameter to create yarns with desired cross-sectional geometries.     

基于CAD/CAE的汽车车架仿真分析

车架是整个汽车的基体,其刚度、强度及动力性能等都会影响到振动舒适性、行驶平顺性和使用寿命。采用CAD/CAE软件,对车架结构进行有限元静力与动力仿真分析,从而达到设计的优化,为以后相应的产品开发提供了理论依据。     

Modeling soil metabolic processes using isotopologue pairs of position-specific C-labeled glucose and pyruvate

Most organic carbon (C) in soils eventually turns into CO₂ after passing through microbial metabolic pathways, while providing cells with energy and biosynthetic precursors. Therefore, detailed insight into these metabolic processes may help elucidate mechanisms of soil C cycling processes. Here, we describe a modeling approach to quantify the C flux through metabolic pathways by adding 1-¹³C and 2,3-¹³C pyruvate and 1-¹³C and U-¹³C glucose as metabolic tracers to intact soil microbial communities. The model calculates, assuming steady-state conditions and glucose as the only substrate, the reaction rates through glycolysis, Krebs cycle, pentose phosphate pathway, anaplerotic activity through pyruvate carboxylase, and various biosynthesis reactions. The model assumes a known and constant microbial proportional precursor demand, estimated from literature data. The model is parameterized with experimentally determined ratios of ¹³CO₂ production from pyruvate and glucose isotopologue pairs. Model sensitivity analysis shows that metabolic flux patterns are especially responsive to changes in experimentally determined ¹³CO₂ ratios from pyruvate and glucose. Calculated fluxes are far less sensitive to assumptions concerning microbial chemical and community composition. The calculated metabolic flux pattern for a young volcanic soil indicates significant pentose phosphate pathway activity in excess of pentose precursor demand and significant anaplerotic activity. These C flux patterns can be used to calculate C use efficiency, energy production and consumption for growth and maintenance purposes, substrate consumption, nitrogen demand, oxygen consumption, and microbial C isotope composition. The metabolic labeling and modeling methods may improve our ability to study the biochemistry and ecophysiology of intact and undisturbed soil microbial communities.     

Tracking the potato late blight pathogen in the atmosphere using unmanned aerial vehicles and Lagrangian modeling

A means for determining the aerial concentration, C (sporangia m⁻³), of plant pathogenic spores at various distances from a source of inoculum is needed to quantify the potential spread of a plant disease. Values of C for Phytophthora infestans sporangia released from an area source of diseased plants in a potato canopy was quantified in three ways: (1) by using Rotorods to sample the air just above the source, (2) by using unmanned aerial vehicles to sample the air at altitudes up to 90 m above the source and at downwind distances up to 500 m from the source, and (3) by using a Lagrangian stochastic simulation of sporangia flight trajectories to tie these two measurements together. Experiments were conducted using three potato crops over two years. Model predictions of time-average, crosswind-integrated concentrations were highly correlated (r = 0.9) with values of C measured using the unmanned aerial vehicles. The model describes the release and dispersal of sporangia from a potato canopy to a downwind distance of 500 m. Thus, it may have utility as a part of an area-wide decision support system by helping to predict risk of disease spread between neighboring or distant potato fields.     

Evaluation of a radiosity based light model for greenhouse cucumber canopies

Light distribution is a key factor of developmental and growth processes, and strongly depends on the foliage distribution which is affected, e.g., by the arrangement of the plants in the canopy. The precise simulation of the light distribution on organ level is an essential component for dynamical plant models which incorporate structural and physiological adaptions of plants to their environment. Combinations of static 3D plant models with 3D light models are used for analyzing the complex light distribution on leaf level in silico, but detailed measurements for evaluation of simulation results are almost non-existent. This study addressed the evaluation of a model on a high level of detail using individual leaf based light measurements in canopies of cucumber (Cucumis sativus L.). We combined a static 3D plant model derived from digitized plants on an individual organ scale with a mock-up of the surrounding canopy and a 3D radiosity based light distribution model. Variations of plant density and spacing were analyzed to cover a range of canopy architectures. An exclusion of components of the light environment by applying a shading encasement followed by a successive uncovering allowed investigating the scene under increasing levels of complexity. The combined 3D plant-light distribution approach allowed determining the interaction of the light directions and the canopy architecture as well as differences in the accuracy of the simulations. Depending on canopy architecture and shading treatment, the light distributions covered a range from exponentially shaped vertical gradients in encased treatments to nearly flat light profiles in nonencased conditions. In conclusion, simulations of leaf level PAR based on combinations of detailed 3D surfaced-based plant and light distribution models are suitable to derive light-induced physiological responses on organ level.