Effect of phosphogypsum on saline-alkalinity and aggregate stability of bauxite residue

A column experiment was conducted to investigate the effect of phosphogypsum (PG) on the saline- alkalinity, and aggregate stability of bauxite residue. Results showed that: with increasing leaching time, the concentrations of saline-alkali ions decreased while the concentration increased in bauxite residue leachate; compared with CK (control group) treatment, pH, electric conductivity (EC), exchangeable sodium percentage (ESP), sodium absorption ratio (SAR), and exchangeable Na⁺ content of bauxite residue were reduced following PG treatment; average particle sizes in aggregates following CK and PG treatments were determined to be 155 and 193 nm, respectively. SR-μCT test results also confirmed that bauxite residue following PG treatment acquired larger aggregates and larger pore diameter. These results indicate that the PG treatment could significantly modulate the saline-alkalinity, and simultaneously enhance aggregate stability of bauxite residue, which provides a facile approach to reclaim bauxite residue disposal areas.     

碳酸性侵蚀与AAR作用下纳米混凝土的耐久性

地铁混凝土处于地下空间,容易受到地下水的碳酸性侵蚀；碱集料反应 (AAR)是一种严重的混凝土耐久性问题,既难以发现又难以修补,由两者共同作用引起的混凝土耐久性降低严重影响地铁隧道的正常使用.为研究纳米材料对地铁混凝土在碳酸性侵蚀和AAR共同作用下耐久性的影响,在普通混凝土中掺入适量纳米SiO₂和纳米Fe₂O₃,利用自行研制的碳酸性侵蚀试验箱进行试验,采用碳酸性侵蚀深度、膨胀率和声速作为测试指标来评价纳米混凝土在碳酸性侵蚀和AAR共同作用下的耐久性.试验结果表明:掺入纳米颗粒后,混凝土的膨胀率和侵蚀深度有了明显降低,而声速有了明显提升,说明纳米混凝土的耐久性优于普通混凝土；在182 d龄期时,掺量为2%的纳米SiO₂混凝土耐久性改善最明显,侵蚀深度和膨胀率最小,声速最大且声速下降幅度最小；其次是掺量为1%的纳米Fe₂O₃混凝土.由于纳米颗粒特殊的物理化学性质,改善了混凝土内部的微观结构和孔溶液的化学组成,使碳酸性侵蚀和碱集料反应共同作用下混凝土的耐久性得到了提高.     

钢渣复合取代矿粉、砂和石用作混凝土掺合料与骨料及其性能分析

用风淬渣粉取代矿粉、电炉渣砂取代混合砂、电炉渣石取代碎石制备混凝土，分析了混凝土的内照射指数、外照射指数、f-CaO含量、沸煮膨胀值、比表面积、密度、含水率、容重、含泥量、泥块含量、坍落度、抗压强度及其化学组成、矿物组成与微观形貌，研究了钢渣的安全性与稳定性及风淬渣粉取代矿粉、电炉渣砂取代混合砂、电炉渣石取代碎石与钢渣复合取代矿粉、砂和石对混凝土性能的影响。结果表明，风淬渣粉、电炉渣砂和电炉渣石的安全性与稳定性满足国标要求，可用于混凝土。当风淬渣粉取代20wt%矿粉、电炉渣砂取代10wt%混合砂和电炉渣石取代20wt%碎石时，混凝土的性能最优。钢渣复合取代矿粉、砂和石的比例合适，可改善混凝土的界面结构密实度，尤其能提高混凝土养护后期的强度。     

混菌矿化增强再生粗骨料的物理力学性能

为克服单一微生物培养成本高且矿化鲁棒性不足的缺陷，提出了一种混菌矿化增强再生粗骨料物理力学性能的方法.通过筛选矿化效率较高的好氧嗜碱混菌，考察了混菌矿化对再生粗骨料物理力学性能和混凝土抗压强度的影响.结果表明：相同增强时间下，混菌比纯菌呈现出更优异的矿化增强效果；随着混菌矿化增强时间的延长，再生粗骨料吸水率和压碎指标呈现出先减小后增大的趋势，最优增强时间为15 d；采用矿化增强再生粗骨料制备的再生混凝土抗压强度提高幅度达到22.1%.     

Destructive and non-destructive evaluation of concrete for optimum sand to aggregate volume ratio

Aggregates are the biggest contributor to concrete volume and are a crucial parameter in dictating its mechanical properties. As such, a detailed experimental investigation was carried out to evaluate the effect of sand-to-aggregate volume ratio (s/a) on the mechanical properties of concrete utilizing both destructive and non-destructive testing (employing UPV (ultrasonic pulse velocity) measurements). For investigation, standard cylindrical concrete samples were made with different s/a (0.36, 0.40, 0.44, 0.48, 0.52, and 0.56), cement content (340 and 450 kg/m³), water-to-cement ratio (0.45 and 0.50), and maximum aggregate size (12 and 19 mm). The effect of these design parameters on the 7, 14, and 28 d compressive strength, tensile strength, elastic modulus, and UPV of concrete were assessed. The careful analysis demonstrates that aggregate proportions and size need to be optimized for formulating mix designs; optimum ratios of s/a were found to be 0.40 and 0.44 for the maximum aggregate size of 12 and 19 mm, respectively, irrespective of the W/C (water-to-cement) and cement content.     

Topography‐Induced Cell Self‐Organization from Simple to Complex Aggregates

Self‐organization is a fundamental and indispensable process in a living system. To understand cell behavior in vivo such as tumorigenesis, 3D cellular aggregates, instead of 2D cellular sheets, have been employed as a vivid in vitro model for self‐organization. However, most focus on the macroscale wetting and fusion of cellular aggregates. In this study, it is reported that self‐organization of cells from simple to complex aggregates can be induced by multiscale topography through confined templates at the macroscale and cell interactions at the nanoscale. On the one hand, macroscale templates are beneficial for the organization of individual cells into simple and complex cellular aggregates with various shapes. On the other hand, the realization of these macro‐organizations also depends on cell interactions at the nanoscale, as demonstrated by the intimate contact between nanoscale pseudopodia stretched by adjacent frontier cells, much like holding hands and by the variation in the intermolecular interactions based on E‐cadherin. Therefore, these findings may be very meaningful for clarifying the organizational mechanism of tumor development, tissue engineering and regenerative medicine.     

全尾砂和废石联合胶结充填体最佳配比及应用

针对红岭铅锌矿分级充填骨料来源不足、地表废石堆积污染环境的情况,提出将该矿选厂产生的全尾砂和地表废石作为充填骨料的联合胶结充填方案。分别测试了全尾砂和地表废石的物理化学性质,验证了碎石和全尾砂作为联合充填骨料的可行性。通过充填配比试验,分析了不同配比全尾砂废石充填体强度特性,得出了最佳充填配比。结果表明,充填试块的强度随灰砂比减小而减小,随养护龄期增加呈增大趋势,随充填料浆质量浓度增大而增大,最佳配比为: 胶结充填灰砂比1∶8、普通充填灰砂比1∶12,全尾砂∶废石配比4∶6,质量浓度78%。根据研究结果,在红岭铅锌矿进行了全尾砂废石充填技术工业应用,证实该技术可行。     

An investigation on the recycling of hydrated cement from concrete demolition waste

Construction and demolition waste (CDW) recycling is generally limited to the use of the coarser fraction as aggregate for new concrete. The recovery of fine aggregates requires a cleaning by removing the hydrated cement waste (HCW). In this paper, the possibility to use HCW extracted from CDW as alternative component for the production of new clinker is explored.A pure HCW sample was prepared and used in partial replacement of natural materials in raw admixtures for new clinker production. At a replacement degree of 30%, a new Portland clinker containing almost 50% of C₃S could be produced with a huge spare in the release of CO₂ (about 1/3 less). At higher HCW dosage a non-Portland clinker containing almost 80% of C₂S has been obtained: its use as supplementary cementing material in blended cements revealed satisfying long term performances.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

A new systematic firefly algorithm for forecasting the durability of reinforced recycled aggregate concrete

This study presents a new systematic algorithm to optimize the durability of reinforced recycled aggregate concrete. The proposed algorithm integrates machine learning with a new version of the firefly algorithm called chaotic based firefly algorithm (CFA) to evolve a rational and efficient predictive model. The CFA optimizer is augmented with chaotic maps and Lévy flight to improve the firefly performance in forecasting the chloride penetrability of strengthened recycled aggregate concrete (RAC). A comprehensive and credible database of distinctive chloride migration coefficient results is used to establish the developed algorithm. A dataset composite of nine effective parameters, including concrete components and fundamental characteristics of recycled aggregate (RA), is used as input to predict the migration coefficient of strengthened RAC as output. k-fold cross validation algorithm is utilized to validate the hybrid algorithm. Three numerical benchmark analyses are applied to prove the superiority and applicability of the CFA algorithm in predicting chloride penetrability. Results show that the developed CFA approach significantly outperforms the firefly algorithm on almost tested functions and demonstrates powerful prediction. In addition, the proposed strategy can be an active tool to recognize the contradictions in the experimental results and can be especially beneficial for assessing the chloride resistance of RAC.