偏高岭土对高强机制砂混凝土性能的影响

利用扫描电子显微镜(SEM)、压汞法(MIP)、快速氯离子迁移系数法(RCM)等手段,研究了偏高岭土(MK)掺量对高强机制砂混凝土抗压强度以及抗氯离子渗透性能的影响.研究发现: 掺入MK能够有效改善高强机制砂混凝土的力学性能和抗氯离子渗透性能:随MK掺量增加,抗压强度与抗氯离子渗透性能均呈先增大后减小的趋势,最佳MK掺量为8%,此时28 d抗压强度为98.5 MPa,较基准组增加13%,氯离子迁移系数为1.89×10^-12 m²/s,较基准组减小60%.微观结构试验表明适宜的偏高岭土掺量能够有效促进水泥水化;偏高岭土颗粒的晶核效应和微集料填充效应协同作用,使得机制砂混凝土的微观结构更加均匀密实,机制砂混凝土的多害孔、有害孔减少,少害孔增加,从而提高了机制砂混凝土抗压强度和抗氯离子渗透性能.     

景谷县森林蓄积量遥感估测及其动态变化分析

以云南省景谷县为研究区,基于Landsat5和Landsat8遥感数据,利用2012年和2017年两期全国森林资源连续清查实地调查数据,建立多元逐步回归和随机森林模型对景谷县森林蓄积量进行遥感估测对比研究。结果显示:综合建模精度来看,随机森林法在相同样地数量条件下具有更好的估测效果;从估测结果与林地保护利用规划和林地变更数据结果相比较,随机森林法估测值接近真实值,估测精度较高。     

茶树植保机械及减量施药技术研究进展

农药防治是茶树病虫害综合防治的重要组成部分,其在病虫害突发或爆发时具有快速高效的防治优势。茶树叶片表面具有亲水性,常量施药会造成茶叶农残超标、生态环境破坏等问题,实现茶树减量施药是减少茶叶农残的有效手段。系统综述了茶树生物特性、茶树病虫害预测诊断及防治方法、茶树植保机械及施药技术,强调提高茶树低容量喷雾的农药有效利用率是实现茶树减量施药的关键。针对目前茶园地面工况复杂及农药利用率低的问题,本文从低容量仿形喷雾机、茶树病虫害喷雾决策及智能终端等六个方面提出茶树病虫害施药技术及装备的研究建议,指出低量化、精准化及智能化是未来茶树植保喷雾机械及施药技术的发展方向。     

基于准静态同轴探头模型的土壤复介电测量方法

末端开路同轴探头法测量土壤复介电值用于表征土壤含水率具有准确、快捷的优点。针对目前土壤介电同轴探头集总测量模型没有充分考虑探头的参数以及土壤体积对测量结果影响等问题，基于电磁场理论，对末端开路同轴探头建立了准静态数学模型，适用于土壤的复介电常数准确测量。通过全波软件仿真和模型计算结果对比，以无水乙醇介电实测值和理论值对比，验证模型的准确性。采用本文介电测量模型对不同含水率的黄绵土进行测量计算，复介电常数实部与实测土壤含水率二阶多项式拟合决定系数大于0.965，表明本文所提土壤介电测量方法适用于土壤复介电常数和含水率的测量。     

基于距离相关系数和KNN回归模型的森林蓄积量估测研究

【目的】探究Landsat8 OLI数据和KNN算法在森林蓄积量估测中的潜力。【方法】以湖南省湘潭县为研究区,采用Landsat8 OLI数据和同时期的二类调查数据,通过距离相关系数筛选特征,分别采用线性回归模型(MLR)、K-近邻模型(KNN)、距离加权KNN模型(DW-KNN)和优化欧式KNN模型(FW-KNN)对森林蓄积量进行估测。使用十折交叉方法进行精度检验,对检验结果进行对比分析。【结果】3种KNN模型的估测结果均高于传统的线性模型,并且在3种KNN模型中,FW-KNN算法效果最好,决定系数达到0.69,为3种模型中最高;3种KNN模型中,本研究优化欧氏距离KNN模型的估测精度最高,其均方根误差为30.3%,相比于传统KNN模型的均方根误差降低了5.1%,相比于DW-KNN模型降低了3.3%。【结论】采用DW-KNN蓄积量估测结果明显优于其他两种模型,说明通过特征与蓄积量的相关性优化样本间的距离是一种可行的KNN优化方法。     

System for quasi‐continuous simultaneous measurement of oxygen diffusion rate and redox potential in soil

Oxygen diffusion rate (ODR) and redox potential (E_H) are quantitative indices representing oxygen availability and redox status in soils, which is valuable information for better understanding causes and effects of soil aeration. Because these indices are spatially and temporally highly variable, continuous measurements and adequate numbers of repetitions are essential for accurate in situ monitoring. Here, we present a new, fully automated recording system for in situ measurements where ODR and E_H are measured at the same platinum electrode. The conflict between electrode polarization for ODR and the resulting biased E_H readings is solved by reducing the polarization time and introducing a recovery interval between two consecutive measurement cycles. The shorter polarization time ensures accurate E_H readings. It also results in moderately overestimated ODR readings, but this can be corrected before data analysis. The recovery interval restricts temporal resolution of the E_H‐ODR data pairs to 8 h. We illustrate the use of the system with measurements in a field experiment in Zürich, Switzerland. ODR curves at different depths ran roughly parallel to the corresponding curves of O₂ concentration in soil air but ODR was much more sensitive to precipitation. Low ODR was a necessary but not a sufficient condition for declining E_H. E_H ran parallel to O₂ concentration in soil air rather than to ODR. The fully automated system allows for time series of replicate measurements in multifactorial field studies with reasonable labor requirements. It may be particularly suitable for studies examining the effects of soil tillage, compaction, and irrigation, where structure‐related soil properties such as porosity, gas permeability, and soil aeration play a dominant role.     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.     

作物叶面积测量的研究进展

对作物叶面积测量理论和方法进行梳理，综述了基于单叶叶面积、单株叶面积、群体叶面积3个维度进行叶面积测量的研究进展，提出作物叶面积测量的物理原理、数学建模原理、光学特征提取原理的理论分类，从精确度、有损和无损测量2个角度分析了叶面积测量的研究进展，并对叶面积测量技术发展趋势进行展望。     

车-液耦合响应下液罐车稳定性控制仿真

为了提高液罐车行驶安全性、减少液罐车侧翻、失稳所带来的危害,对于液罐车在转向或换道时车-液耦合动态响应对整车稳定性的影响进行了研究。联合液体纳维斯托克斯和流动控制方程,应用计算流体动力学软件ANSYS/Fluent建立并求解液体晃动模型,通过结合液体晃动模型和三自由度液罐车刚体模型获得液罐车车-液耦合动力学模型,分析有无控制策略情况下,液体晃动对液罐车横向稳定性的影响。仿真结果表明:提出的模糊差动制动控制策略能够有效提高车辆抗侧翻能力,减少罐车运输过程中交通事故的发生,对液罐车运输有指导意义。     

串联式混合动力拖拉机分动箱的设计与试验

设计的串联式混合动力分动箱由输入轴、中间轴、输出轴以及轴上齿轮和一对滑移齿轮组成。为减小分动箱体积,同时满足配套旋耕机较大耕深需求,在满足结构、强度、刚度等约束条件下,以分动箱总中心距和齿轮总体积最小为目标函数,建立了分动箱参数优化的数学模型。采用基于改进粒子群算法(PSO)的参数优化策略,优化结果表明,与基本粒子群算法相比,改进后的粒子群算法在收敛速度和收敛精度方面均有明显提高,改进后的齿轮总体积减小了2.9%,优化精度提高了1.5%。分动箱运动学仿真及试验结果表明,优化后的分动箱动力输出轴(PTO)动力性能符合要求,能够满足配套旋耕机的工作要求。