Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

Additional deepwater sampling of prey fish in Lake Michigan annual bottom trawl survey reveals new insights for depth distribution dynamics

Beginning in 2013, sites at the 128-m bottom depth contour were added to the sampling design of the annual Lake Michigan bottom trawl survey for prey fish, which has been conducted by the U.S. Geological Survey Great Lakes Science Center (GLSC) each fall since 1973, to better assess fish depth distributions in a changing ecosystem. The standard sampling design included bottom depths from 9 to 110 m, although the GLSC also sporadically conducted bottom trawl tows at the 128-m bottom depth contour during 1973–1988. Enactment of this new sampling design in 2013 revealed that mean biomass density of deepwater sculpins (Myoxocephalus thompsonii) at the 128-m depth exceeded the sum of mean biomass densities at shallower depths, indicating that the bulk of the deepwater sculpin population is residing in waters deeper than 110 m. Thus, our findings supported the hypothesis that the depth distribution of the deepwater sculpin population had shifted to deeper waters beginning in 2007, thereby explaining, at least in part, the marked decline in deepwater sculpin abundance since 2006 based on the standard sampling design. In contrast, our results did not support the hypothesis that the slimy sculpin (Cottus cognatus) population had shifted to deeper waters sometime after 2000. A portion of the burbot (Lota lota) population may have also shifted in depth distribution to waters deeper than 110 m after 2007, based on our results. Our findings have served as an impetus to further expand the range of depths sampled in our bottom trawl survey.     

Evaluation of back-calculated elastic moduli of unreinforced and geocell-reinforced unbound granular material from full-scale field tests

This paper presents a field-scale experimental track over a poor subgrade with an unreinforced section and a geocell-reinforced section subjected to in-situ performance tests. Plate load tests and Benkelman beam tests were carried out distributed in several unreinforced and reinforced layers. The objective was to: (1) examine the variability of the elastic modulus of unbound granular material (UGM) due the influence of its thickness and the presence of poor subgrade in its base, (2) evaluate the modulus improvement factor (MIF) generated by the geocell reinforcement in the UGM and (3) verify the most appropriate condition to apply the MIF to transport infrastructure design. The results showed that there is a significant influence of the thickness of the UGM layer on its elastic modulus when the layer is supported directly over a soft subgrade. The MIF values obtained in field suggest that its determination is mostly related to the UGM maximum elastic modulus rather than its decreased values (by virtue of poor subgrade or reduced thicknesses), and that the analytical formulation presented for MIF calculation has good predictive capability to be applied to pavement design.     

High performance H2 sensor based on rGO-wrapped SnO2–Pd porous hollow spheres

Hydrogen (H₂) sensors based on metal oxide semiconductors (MOS) are promising for many applications such as a rocket propellant, industrial gas and the safety of storage. However, poor selectivity at low analyte concentrations, and independent response on high humidity limit the practical applications. Herein, we designed rGO-wrapped SnO₂–Pd porous hollow spheres composite (SnO₂–Pd@rGO) for high performance H₂ sensor. The porous hollow structure was from the carbon sphere template. The rGO wrapping was via self-assembly of GO on SnO₂-based spheres with subsequent thermal reduction in H₂ ambient. This sensor exhibited excellently selective H₂ sensing performances at 390 °C, linear response over a broad concentration range (0.1–1000 ppm) with recovery time of only 3 s, a high response of ～8 to 0.1 ppm H₂ in a minute, and acceptable stability under high humidity conditions (e. g. 80%). The calculated detection limit of 16.5 ppb opened up the possibility of trace H₂ monitoring. Furthermore, this sensor demonstrated certain response to H₂ at the minimum concentration of 50 ppm at 130 °C. These performances mainly benefited from the special hollow porous structure with abundant heterojunctions, the catalysis of the doped-PdO_x, the relative hydrophobic surface from rGO, and the deoxygenation after H₂ reduction.     

矿用直线振动筛结构故障分析

针对煤矿选煤厂直线振动筛工作过程中出现的结构故障问题,采用有限元仿真与现场测试结合的方法对振动筛出现故障的原因进行了分析研究。介绍了振动筛的主要结构及常见故障,并以某矿选煤厂发生大梁断裂的振动筛为例,对该振动筛进行三维建模和有限元模态分析,分析结果表明:随着模态阶次的增加,振型的变化逐渐由移动转为结构本身的扭曲变形。在该振动筛空载工作状态下,选用本质安全型便携式测振记录仪进行振动测试并处理测试信号,得到该振动筛的工作频率。结合模态分析结果和实际测试结果,判断出空载时频繁运行振动筛是造成其大梁断裂的主要原因。根据故障原因给出维护建议:应当尽量避免振动筛在空载或物料较少的状态下长时间运行;在振动筛投入使用前,应预先了解振动筛的工作状态及可能存在的薄弱环节,尽可能避免结构故障,保证振动筛可靠运行。     

Free vibration behavior of a thermally post-buckled FG Timoshenko beam under large deflection using a tangent stiffness-based method

For thermally postbuckled configurations, the free vibration behavior of functionally graded (FG) Timoshenko beams are investigated. The postbuckling configurations are obtained through a geometrically nonlinear static problem. The free vibration problem around the postbuckled configuration is formulated using its tangent stiffness. The energy based governing equations are solved following the Ritz method. The elements of the tangent stiffness matrix are obtained using the Ritz coefficients. The results are shown to exhibit the effects of FG material, material profile parameter, and length-thickness ratio. The comparative results are presented for both the cases of the physical neutral surface and the geometrical neutral surface.     

双光束激光焊匙孔动态特征分析

文中研究了高功率单光束激光焊与双光束激光焊过程中匙孔动态特征的差别. 结果表明，单光束激光焊及双光束激光焊接过程中匙孔均处于从产生到湮灭的剧烈波动的过程，不同于单光束激光焊匙孔的形成、长大、维持、缩小、湮灭过程，双光束激光焊的匙孔还存在分离长大及合并缩小的过程；在相同的焊接参数及焊缝具有相同熔深的条件下，双光束激光焊匙孔的波动频率约为单光束激光焊的2/3，单光束激光焊匙孔的开口面积均值约为双光束激光焊匙孔开口面积的1/2，开口面积的波动变异系数约为单光束激光的2倍，即双光束激光焊过程中匙孔较单光束激光焊的具有较高稳定性.     

用宽带超表面产生阵列贝塞尔光束

通过在空间光调制器（SLM）上加载相位图或通过光刻加工微型圆锥状结构可以产生贝塞尔光束阵列。然而，典型空间光调制器具有比波长大一个数量级的像素尺寸，这限制了相位梯度的可用范围，用光刻法加工的微型锥透镜的顶端不是标准的圆锥，这影响了贝塞尔光束的质量。为了克服这些缺点，将复杂的相位图加载到电介质超表面上，设计了一种可以产生阵列贝塞尔光束（在波长700 nm处，NA=0.3）的超表面器件。该器件可以宽波段工作，其单元结构在波长580~800 nm范围内的偏振转换效率均超过57%。利用时域有限差分算法（FDTD）对该器件（厚度为380 nm，直径仅为40 μm）进行了仿真，所产生的阵列光束都垂直于超表面器件。所提出的阵列贝塞尔光束发生器具有纳米级别的厚度和几十微米的直径，这对于未来的集成光学领域具有很大的应用前景。