深海采矿转臂机构采矿姿态优化研究

针对海底地形不平坦特性,提出了一种变幅机构来自适应海底地形采矿姿态的采矿机构。综合考虑采矿机构采掘头距海底高度对采矿率影响,利用关键点法建立了节臂上的点到海底地形距离的数学模型。在此基础上,建立了以采矿率最高为目标的最优采矿姿态数学模型。以某实际地形为例,采用模拟退火遗传算法优化求解最优采矿姿态。根据其优化后结果可知,其最优采矿姿态与海底地形坡度变化一致,从而证明了采矿姿态模型的正确性。     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

浅析城市地下空间室内环境特点及设计思路:以西安赛格国际购物中心为例

随着中国城镇化进程的迅猛发展,城市规模不断扩大,人口不断增长,城市交通拥堵、环境污染、土地资源日益紧缺等问题日益凸显。城市地下空间作为城市资源的重要组成部分,适当的城市地下化发展可以在一定程度上缓解这些问题。文章简要叙述了目前我国城市地下空间开发利用的现状及城市地下空间的应用类型,分析了地下空间的恒温性、隔热性、湿度较大、环境封闭空气流通性差、天然光线不足、缺乏自然景观、没有外部形态等内部环境特点。以西安赛格国际购物中心为例,从自然采光、人工照明、植物水体和界面设计的角度概述了地下综合体室内设计的核心理念和关键步骤。最后提出了如下关于城市地下商业空间室内设计的优化思路：(1)空间布局明确,符合人的空间认知习惯;(2)通过扩大建筑入口和先进的技术手段,引入天然光;(3)运用照明模拟自然光;(4)引入自然元素,使室内外环境自然过渡,增加地下空间的活力,改善封闭感,缓解人的心理和生理障碍;(5)地下空间的各类尺度应符合人体尺度,避免产生不适感;(6)注重行动不便的人群,设置人性化的无障碍设施;(7)设计充足的休憩场所;(8)注重设计本土化,展现地域文化特色。