大方坯连铸动态轻压下技术应用研究

攀钢全连铸工程新建的大方坯连铸机采用了奥钢联SMART／ASTC动态轻压下技术。自大方坯连铸机投产以来,以重轨钢、硬线等典型钢种为代表开展了应用大方坯连铸轻压下技术的试验研究。通过不断优化调整轻压下工艺制度,取得了改善铸坯中心偏析、疏松和缩孔的显著效果。结果表明,铸坯表面无清理率达到100％,中心疏松≤1．0级,中心偏析≤1．0级,中心缩孔≤0．5级,中心碳偏析指数≤1．05,无其他内部质量缺陷,为攀钢生产高速铁路用钢轨提供了合格铸坯。     

Environmental factors controlling phytoplankton dynamics in a large floodplain river with emphasis on cyanobacteria

Harmful algal blooms are occurring in large river ecosystems and at the mouth of large rivers with increasing frequency. In lentic systems, the chemical and physical conditions that promote harmful algal blooms are somewhat predictable but tracking prevalence and conditions that promote harmful algal blooms in lotic systems is much more difficult. We captured two of the most extreme discharge years within the last 20 years occurring in the Upper Mississippi River, allowing a natural experiment that evaluated how major shifts in discharge drive environmental variation and associated shifts in phytoplankton. Statistical models describing significant environmental covariates for phytoplankton assemblages and specific taxa were developed and used to identify management‐relevant numeric breakpoints at which environmental variables may promote the growth of specific phytoplankton and/or cyanobacteria. Our analyses supported that potentially toxin‐producing cyanobacteria dominate under high phosphorus concentration, low nitrogen concentration, low nitrogen‐to‐phosphorus ratio, low turbulence, low flushing, adequate light and warm temperatures. Cyanobacteria dominated in 2009 when low discharge and low flushing likely led to optimal growth environments for Dolichospermum, Aphanizomenon and Microcystis. Rarely will a single factor lead to the dominance, but multiple positive factors working in concert can lead to cyanobacteria proliferation in large rivers. Certain isolated backwaters with high phosphorus, low nitrogen, warm water temperatures and low potential for flushing could benefit from increased connection to channel inputs to reduce cyanobacterial dominance. Numerous examples of this type of habitat currently exist in the Upper Mississippi River and could benefit from reconnection to channel habitats.     

A wavelet-based autoregressive fuzzy model for forecasting algal blooms

This paper proposes fuzzy models for forecasting the complex behavior of algal blooms. The models are developed through the integration of autoregressive models, the Takagi-Sugeno fuzzy model, and discrete wavelet transform algorithms. The premise parts of the proposed models are determined using the subtractive clustering technique and the consequent parts are optimized using weighted least squares. To train and validate the proposed fuzzy models, a large number of data sets were collected from Daecheong reservoir in Geum River in the Republic of Korea. The data include both water quality and hydrological variables. Total nitrogen, total phosphorous, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, pH, air temperature, water temperature and outflow water were evaluated as input signals while chlorophyll-a was used as an output. It is demonstrated from the simulation that the proposed fuzzy models are effective in forecasting algal blooms.     

微囊藻毒素的检测和脱除方法综述

近年来,由于富营养化,全球有害蓝藻水华的发生率持续上升,形成水华的蓝藻会释放出多种毒素,微囊藻毒素是有害蓝藻产生的常见毒素,具有肝毒性、肾毒性、神经毒性、生殖毒性等多种毒性,严重威胁人类和生态系统健康。微囊藻毒素在水中非常稳定,难以通过传统水处理工艺去除。因此,寻求经济有效的微囊藻毒素检测和脱除方法至关重要。本文综述了定量检测和去除微囊藻毒素的方法,包括物理法、化学法和生物法,并分析总结了这三类方法用于检测和脱除微囊藻毒素的优势与局限性,总结了不同方法脱除微囊藻毒素的机理,重点介绍了绿色高效的光催化降解微囊藻毒素的脱除方法,最后,基于当前的研究结果,对未来微囊藻毒素脱除研究方向进行了展望,为解决环境中微囊藻毒素的污染问题提供思路。     

轧制规程对初轧切损的影响

在包钢初轧厂１１５０ｍｍ初轧机上,进行了不同轧制规程轧制Ｂ８．４ｔ沸腾钢锭生产２５０ｍｍ×２５０ｍｍ方坯的试验,以确定最小的切尾长度．用铣床对试件尾部纵向断面做了解剖,测定了试件尾部的内部缺陷尺寸和合适的切尾量．结果表明：改进轧制方式对降低钢锭切尾损失是高度显著性因素,其显著性水平α＝０．００５．改进轧制方式可提高方坯收得率１．２４％以上．     

Validation of 2015 Lake Erie MODIS image spectral decomposition using visible derivative spectroscopy and field campaign data

Timely identification of color-producing agents (CPAs) in Lake Erie is a challenging, but vital aspect of monitoring harmful algal blooms (HABs). In particular, HABs that include large amounts of cyanobacteria (CyanoHABs) can be toxic to humans, posing a threat to drinking water, in addition to recreational and economic use of Lake Erie. The optical signal of Lake Erie is complex (Becker et al., 2009; Moore et al., 2017), typically comprised of phytoplankton, cyanobacteria, colored dissolved organic matter (CDOM), detritus, and terrigenous inorganic particles, varying in composition both spatially and temporally. The Kent State University (KSU) spectral decomposition method effectively partitions CPAs using a varimax-rotated, principal component analysis (VPCA) of visible reflectance spectra measured using lab, field or satellite instruments (Ali et al., 2013; Ortiz et al., 2017, 2013). We analyze 2015 imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and field samples collected during the early 2015 cyanoHAB season. We identified four primary CPA spectral signatures, and the spatial distribution of each identified CPA, in the reflectance spectra datasets of both the MODIS and lab-measured water samples. The KSU spectral decomposition method results in mixtures of specific pigments, pigment degradation products, and minerals that describe the optically complex water. We found very good agreement between the KSU VPCA spectral decomposition results and in situ measurements, indicating that this method may be a powerful tool for rapid CyanoHAB monitoring and assessment in large lakes using instruments that provide moderate resolution imagery (0.3 to 1 km²).     

Spatial and temporal variability of inherent and apparent optical properties in western Lake Erie: Implications for water quality remote sensing

Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP and AOP observations have been temporally limited and have not assessed statistical differences between IOPs over spatial and temporal gradients. The objective of this study is to assess trends in IOPs over variable spatial and temporal scales. Large spatio-temporal variability in IOPs was observed between 2015 and 2016 likely due to the difference in the extent and duration of mid-summer cyanobacteria blooms. Differences in the seasonal trends of the specific phytoplankton absorption coefficient between 2015 and 2016 suggest differing algal assemblages between the years. Other IOP variables, including chromophoric, dissolved organic matter (CDOM) and beam attenuation spectral slopes, suggest variability is influenced by river discharge and sediment re-suspension. The datasets presented in this study show how these IOPs and AOPs change over a season and between years, and are useful in advancing the applicability and robustness of remote sensing methods to retrieve water quality information in western Lake Erie.