2UPR-RPU过约束并联机构刚度性能评价

运用螺旋理论和应变能方法研究了具有2R1T三自由度的2UPR-RPU过约束并联机构的静弹性刚度性能,模型考虑了杆件和关节的柔度。首先,基于螺旋理论得到分支的约束螺旋系;其次,基于材料力学得到分支中杆件的应变能,通过映射分支约束螺旋系到铰空间得到关节的应变能,通过汇总杆件、关节的应变能和卡氏定理得到与约束螺旋系对应的分支紧凑刚度矩阵;最后,通过虚功原理得到机构的总体刚度矩阵。采用有限元商业软件建立了有限元模型,并与理论模型进行对比,验证了理论模型的正确性。定义弹性元件存储的应变能与总应变能之比作为应变能因子指标,给出了应变能因子指标在规则工作空间的四维切片分布图,从应变能的角度定量评价了各弹性元件对机构刚度性能的影响程度,给出了不同载荷作用下的全局应变能因子指标。本研究为定位对机构刚度性能影响最大的弹性元件提供了新的思路。     

垂直轴风力机翼型涡流噪声的数值分析

为了了解垂直轴风力机翼型涡流噪声特性,以LUT翼型为研究对象,首先利用Fluent进行流场分析,流场计算选用DES湍流模型,再结合Lighthill声类比方法计算翼型周围声场,将数值模拟计算得到的气动特性相关数据与该翼型的风洞试验结果作对比分析,同时分析了不同攻角对该翼型气动噪声特性的影响,最后研究了在攻角为8°时不同雷诺数对该翼型的声压级指向性特征影响.结果表明:数值计算所得气动数据与风动试验数据拟合良好,建立的仿真模型、网格质量和边界条件合理有效;随攻角增加,翼型涡脱落从尾缘向前缘推进,同时涡流脱落强度增大,气动噪声增强;随着雷诺数的增加,翼型四周声压级先增加后减小;雷诺数与声压级关联较大,控制叶片雷诺数有助于降低叶片噪声,为该翼型适用于低噪声垂直轴叶片提供理论基础.     

琼岛杨一年生播种苗生长节律研究

于2019年5月6日到12月25日对海南省琼岛杨Populus qiongdaoensis一年生播种苗的苗高、地径生长量进行定期观测,采用Logistic方程进行生长进程拟合,研究琼岛杨的苗期生长节律。结果表明,琼岛杨苗高和地径生长都呈现"慢—快—慢"的"S"形生长规律,且苗高、地径生长量与Logistic方程的回归相关性达到极显著水平,其相关系数分别达0.994和0.996。苗高生长速生期约119 d,占生长期的39.67%,占苗高年总生长量的63.77%;地径生长速生期约125 d,占生长期的45.42%,占地径年总生长量的66.15%。     

Finding suitable growth models for turbot (Scophthalmus maximus L.) in aquaculture 1 (length application)

Growth data of two different commercial turbot (Scophthalmus maximus) strains reared in recirculating aquaculture systems were analysed with the aim to determine the most suitable model for turbot. To assess the model performance three different criteria were used: (1) The mean percentage deviation between the estimated length and actual length; (2) the residual standard error with corresponding degrees of freedom and (3) the Akaike information criterion. The analyses were carried out for each strain separately, for sexes within strains and for a pooled data set containing both strains and sexes. We tested a pre‐selection of six models, containing three to four parameters. Models were of monomolecular shape or sigmoid shape with a flexible point of inflection including the special case of monomolecular shape in defined cases of their parameters. The 4‐parametric Schnute model achieved best fit in 62% of all cases and criteria tested, followed by the also 4‐parametric generalized Michaelis–Menten equation in 48% and the 4‐parametric Janoschek model (38%). The von Bertalanffy growth function achieved only 29%, Brody 24% and a new flexible function 19% best fit. In a 1–1000 day growth‐simulation sigmoid shaped curves were produced by the Schnute model in 71% of cases. The Janoschek and the Michaelis–Menten model each produced sigmoid curves in 57% of all cases. This indicates that a flexible 4‐parametric function reflects the growth curve of turbot the best and that this curve is rather sigmoid than monomolecular shaped.     

基于季节特征的土壤退墒模型建立与率定

利用河南省南阳市2011—2015年12个墒情站的土壤水分监测资料,分析研究了无增墒情况下土壤含水量消退规律,构建出基于不同季节(夏季、春秋季与冬季)的土壤含水量与衰减系数的数学模型,运用规划求解法率定模型参数,并利用2016—2017年资料对模型进行检验。结果表明,不同季节土壤水分衰竭系数模型分别为α=1.023(1-ω~2/4353)~(1/2)(夏季)、α=1.013(1-ω~2/7005)~(1/2)(春秋季)与α=1.008(1-ω~2/9303)~(1/2)(冬季),所建立的数学模型适用于南阳市相应季节壤土与粘壤土小麦、水稻与休闲地土壤旱情预测,但不适用于夏季与春秋季砂土特别是休闲地砂土土壤墒情预测。     

森林康养步道五感体验需求与潜在游客体验意愿分析

【目的/意义】通过探索五感体验需求对潜在游客体验意愿的驱动影响,以期能够准确理解与把握潜在游客的行为意向,为森林康养步道设计提供理论参考。【方法/过程】以潜在游客为研究对象,借助AMOS构建结构方程模型,并引入“认知程度”这一调节变量进行层级回归分析。【结果/结论】结果表明:五感体验需求对潜在游客选择体验森林康养步道的意愿具有正向显著影响;在森林康养步道中,对五感体验需求影响最大的为触觉体验需求,其次为嗅觉体验需求、视觉体验需求和听觉体验需求,影响最小的是味觉体验需求;潜在游客对森林康养的认知程度对于五感体验需求与体验意愿之间的关系具有正向调节作用。     

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.     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.     

Predicting the potential geographic distribution of Bactrocera bryoniae and Bactrocera neohumeralis(Diptera: Tephritidae) in China using MaxEnt ecological niche modeling

Bactrocera bryoniae and Bactrocera neohumeralis are highly destructive and major biosecurity/quarantine pests of fruit and vegetable in the tropical and subtropical regions in the South Pacific and Australia. Although these pests have not established in China, precautions must be taken due to their highly destructive nature. Thus, we predicted the potential geographic distribution of B. bryoniae and B. neohumeralis across the world and in particular China by ecological niche modeling of the Maximum Entropy(Max Ent) model with the occurrence records of these two species. Bactrocera bryoniae and B. neohumeralis exhibit similar potential geographic distribution ranges across the world and in China, and each species was predicted to be able to distribute to over 20% of the globe. Globally, the potential geographic distribution ranges for these two fruit fly species included southern Asia, the central and the southeast coast of Africa, southern North America, northern and central South America, and Australia. While within China, most of the southern Yangtze River area was found suitable for these species. Notably, southern China was considered to have the highest risk of B. bryoniae and B. neohumeralis invasions. Our study identifies the regions at high risk for potential establishment of B. bryoniae and B. neohumeralis in the world and in particular China, and informs the development of inspection and biosecurity/quarantine measures to prevent and control their invasions.