Feasibility of CANON process for treating nitrogenous wastewater containing heavy metals

The appearance of heavy metals in wastewater brings a major burden to wastewater treatment plants, due to the high toxicity to microorganisms. Several commonly used heavy metals, including Zn(II), Cd(II), Hg(II), and Pb(II) were adopted to clear the individual and joint toxicity to the completely autotrophic nitrogen removal over nitrite (CANON) process in six sequencing batch reactors. The obtained results suggested that the nitrogen removal performances were transiently inhibited, but rapidly recovered. The restoration period under the stress of Hg(II) and Pb(II) was shorter than that under Zn(II), Cd(II), and the joint heavy metals. During the long-term exposure, Cd(II) in 1mg L⁻¹ slightly inhibited the nitrogen removal, while Zn(II), Hg(II), Pb(II), and mixture showed a negligible impact on CANON process. The defense of extracellular polymeric substances (EPS), the good adaptability of functional bacteria, and the inducement of resistant genera by heavy metals all contributed to the robustness and stability of CANON process. Therefore, it is feasible to treat nitrogenous wastewater containing low heavy metals using CANON process. © 2020 Society of Chemical Industry     

基于多时间尺度和多源储能的综合能源系统能量协调优化调度

考虑源荷不确定性及储能设备配置对综合能源系统IES(integrated energy system)优化调度的影响,提出基于多时间尺度和多源储能的IES能量协调优化调度策略。该策略以系统运行经济最优、滚动控制时域内购能成本与储能惩罚成本之和最低以及设备输出功率调整量最小为目标,分别建立了日前、日内滚动和实时反馈3个时间尺度的优化调度模型。在日前考虑多种储能模式对IES经济性的影响;日内利用场景分析法描述滚动预测的不确定性来提高系统经济运行稳定性;再基于模型预测控制方法,构建日内与实时的反馈闭环优化,平抑由预测误差导致的系统功率波动。仿真结果表明:多源储能模式有助于提高IES的经济性;多时间尺度调度既可以保证IES运行的经济性,又能有效降低不确定性对系统实际运行的影响,减轻电网平抑功率波动负担。     

Influence of Y2O3 addition on the mechanical and oxidation behaviour of carbon fibre reinforced ZrB2/SiC composites

The influence of Y₂O₃ addition on the microstructure, thermo-mechanical properties and oxidation resistance of carbon fibre reinforced ZrB₂/SiC composites was investigated. Y₂O₃ reacted with oxide impurities present on the surface of ZrB₂ and SiC grains and formed a liquid phase, effectively lowering the sintering temperature and allowing to reach full density at 1900 °C. The presence of a carbon source (fibres) led to additional reactions which resulted in the formation of new secondary phases such as yttrium boro-carbides. Mechanical properties were significantly enhanced compared to the un-doped composite. Further tests at high temperatures resulted in strength increase up to 700 MPa at 1500 °C which was attributed to stress relaxation. Oxidation tests carried out at 1500 °C and 1650 °C in air showed that the presence of the Y-based secondary phases enhanced the growth of ZrO₂ grains, but offered limited protection to oxygen due to the lower availability of surficial SiO₂ formed from SiC.     

Processing of orthotropic and isotropic superhard B4C composites reinforced with reduced graphene oxide

A fabrication route based on aqueous colloidal processing plus transient liquid-phase assisted spark-plasma-sintering (SPS) with Ti-Al additives is described for the environmentally friendly obtention of superhard B₄C composites reinforced with reduced graphene oxide (rGO) having orthotropic and isotropic microstructures. It is shown that the former, which have coarse rGO platelets preferentially aligned perpendicular to the SPS pressing direction, can be prepared from mixtures of B₄C and Ti-Al particles with a source of thick, large rGO nanoplatelets by imposing smooth co-dispersion conditions to avoid platelet re-exfoliation and fragmentation. The latter, which have fine rGO platelets randomly oriented, can be fabricated from mixtures of B₄C and Ti-Al particles with a source of thin, small rGO nanoplatelets by applying intensive sonication to promote platelet re-exfoliation and fragmentation during co-dispersion. Finally, it is shown that these orthotropic and isotropic B₄C/rGO composites are equally superhard, and that, as expected, their microstructures interact differently with the cracks. Finally, this processing route is simple, and easily adaptable/extensible to make other ceramic/rGO composites with orthotropic and isotropic microstructures.     

Pressureless ultrafast sintering of near-net-shaped superhard isotropic B4C/rGO composites with Ti-Al additives

Superhard composites of B₄C reinforced with randomly-oriented reduced graphene oxide (rGO) nanoplatelets are manufactured by a near-net-shape fabrication route based on three successive steps. Firstly, aqueous colloidal processing is used for the environmentally-friendly preparation of a semi-concentrated multi-component slurry (B₄C as main component, Ti-Al as sintering additive, and rGO as toughening reinforcement), whose suitability for wet shaping is demonstrated by rheological measurements. Secondly, slip casting is used to produce robust green parts with shapes on demand and microstructures free of macro- and micro-defects. And thirdly, pressureless spark-plasma sintering (PSPS) is used for the ultrafast and energy-efficient densification of the green parts with shape retention. Measurements of shrinkage and hardness, as well as the microstructural observations, are used to identify suitable PSPS temperatures leading to obtaining isotropic B₄C/rGO composites that are superhard and almost twice as tough as the monolithic B₄C ceramics.     

Semiconductor Fe-doped SrTiO3-δ perovskite electrolyte for low-temperature solid oxide fuel cell (LT-SOFC) operating below 520 °C

High-temperature operation of solid oxide fuel cells causes several degradation and material issues. Lowering the operating temperature results in reduced fuel cell performance primarily due to the limited ionic conductivity of the electrolyte. Here we introduce the Fe-doped SrTiO_3-δ (SFT) pure perovskite material as an electrolyte, which shows good ionic conduction even at lower temperatures, but has low electronic conduction avoiding short-circuiting. Fuel cell fabricated using this electrolyte exhibits a maximum power density of 540 mW/cm² at 520 °C with Ni-NCAL electrodes. It was found that the Fe-doping into the SrTiO_3-δ facilitates the creation of oxygen vacancies enhancing ionic conductivity and transport of oxygen ions. Such high performance can be attributed to band-bending at the interface of electrolyte/electrode, which suppresses electron flow, but enhances ionic flow.     

Risk modelling of a hydrogen gasholder using Fuzzy Bayesian Network (FBN)

Gasholder is one of the principal types of storage for gaseous hydrogen. It plays an important role in the hydrogen production. Nonetheless, hydrogen leakage in gasholders may lead to great hazard and dire consequences such as fire and explosion. Therefore, safety analysis is vital for preventing such potential accidents. Root causes of hydrogen leakage and possible consequences were obtained using Bow-Tie analysis (BT). Then, to relax the limitation of BT in modelling uncertainties and conditional dependency, a Bayesian Network (BN) model for gasholder leakage was established by converting BT to BN (BTBN). In the meantime, in order to cope with the uncertainty of the failure data, the fuzzy logic based on expert judgment was applied. Unlike the traditional FTA, the proposed approach can be used for backward inference (i.e. accident tracing) of systems, which is particularly important to find the most critical causes of accident scenarios Based on the results of the study, the main influencing factors to the hydrogen gasholder leakage were human factor, that is, operation error, inspection not specified, inspection not performed and delay of inspection. The events missle (due to domino), lightning, vehicle collision, downstream compressor failure were the second level critical events in the failure of gasholder.     

Performance analysis of empirical models for predicting rock mass deformation modulus using regression and Bayesian methods

Deformation modulus of rock mass is one of the input parameters to most rock engineering designs and constructions. The field tests for determination of deformation modulus are cumbersome, expensive and time-consuming. This has prompted the development of various regression equations to estimate deformation modulus from results of rock mass classifications, with rock mass rating (RMR) being one of the frequently used classifications. The regression equations are of different types ranging from linear to nonlinear functions like power and exponential. Bayesian method has recently been developed to incorporate regression equations into a Bayesian framework to provide better estimates of geotechnical properties. The question of whether Bayesian method improves the estimation of geotechnical properties in all circumstances remains open. Therefore, a comparative study was conducted to assess the performances of regression and Bayesian methods when they are used to characterize deformation modulus from the same set of RMR data obtained from two project sites. The study also investigated the performance of different types of regression equations in estimation of the deformation modulus. Statistics, probability distributions and prediction indicators were used to assess the performances of regression and Bayesian methods and different types of regression equations. It was found that power and exponential types of regression equations provide a better estimate than linear regression equations. In addition, it was discovered that the ability of the Bayesian method to provide better estimates of deformation modulus than regression method depends on the quality and quantity of input data as well as the type of the regression equation.     

煤矿地面轨道运输矿车自动避障技术研究

介绍了煤矿地面轨道运输矿车自动避障技术。首先介绍了基于雷达的矿车前方障碍物检测技术及其相关算法,然后详细介绍了基于机器视觉的矿车前方障碍物检测系统和常用的图像处理方法以及相关的算法,最后介绍了雷达和机器视觉融合的障碍物检测技术在煤矿地面轨道运输矿车自动避障过程中的应用。     

Ca对Mg-Gd-Y-Zn-Zr合金热变形行为及热加工性能的影响

利用Gleeble3500热模拟试验机研究了Ca对Mg-Gd-Y-Zn-Zr合金在变形温度573～723 K,应变速率0.001～1 s-1的热变形行为及热加工性能的影响。结果表明:Ca增大了合金的流变应力及变形激活能,扩宽了加工安全区及最佳加工区范围,但降低了最大功率耗散因子及动态再结晶程度。结合激光共聚焦显微镜分析了合金热压缩后组织,验证了热加工图的准确性,并制定了合理的热加工工艺,Mg-Gd-Y-Zn-Zr合金的最佳加工区域为:应变速率0.001～0.01 s~(-1),温度623～723 K。根据最佳加工工艺参数获得了表面质量良好,无变形缺陷的等温锻造合金。