Experimental Study on Consolidation Properties of Hydrate-Bearing Fine-Grained Sediments Collected from the Shenhu Area of the Northern South China Sea

Mechanical properties of hydrate-bearing fine-grained sediments are crucial to effectively mitigate environmental risks caused by artificial and natural decomposition of natural gas hydrates,and the decomposition can induce laterally confined deformation.To explore the effect of natural gas hydrates on laterally confined compression properties,consolidation tests are conducted on remolded hydrate-free and hydrate-bearing samples by using natural fine-grained sediments collected from the northern South China Sea as the host sediments,and empirical equations are developed based on the analyses of consolidation characteristics.The results show that vertical loading induces a reduction in void ratio,and the reduction increases with decreasing hydrate saturation when samples are subjected to the same vertical stress change.The compression index of samples is about 0.53 whether there is hydrate or not,but the yield stress of samples increases sharply with increasing hydrate saturation once beyond the critical value.The coefficient of volume compression and the coefficient of consolidation of hydrate-bearing samples both increase firstly and then decrease to a relative stable level with increasing vertical stress,and the transition occurs at 200 kPa.The average consolidation degree with elapsed time increases rapidly under low vertical stresses,slowly under median vertical stresses,and under high vertical stresses,the consolidation increases a little faster but still slower than those under low vertical stresses.

Heavy Metal Characteristics and Comprehensive Quality Index Evaluation of Soil-Crop System in 11 Cities of Yunnan Province, China

Yunnan province in China is a high background area of soil heavy metals, and agricultural planting and industrial and mining activities are relatively frequent, which aggravate soil heavy metal pollution. However, at present, there are few reports on the overall or large-scale soil-crop pollution and risk assessment of heavy metals in Yunnan Province. This study through 11 cities in Yunnan province of China farmland soil-crop systems of heavy metal lead, cadmium content, enrichment coefficient is analyzed, and using the method of potential ecological harm index, index of compressive quality to evaluate heavy metal pollution soil-crop system risk. Results showed that the average content of soil heavy metal Cd and Pb were 1.31 mg/kg, 64.17 mg/kg, which are higher than the background value of Yunnan province. The average contents of Pb and Cd in the edible parts of crops were 0.20 mg/kg, 0.08 mg/kg. The average content of heavy metals in crops in Diqing (Pb) and Nujiang (Cd) was 0.72 mg/kg and 0.148 mg/kg. The enrichment coefficients of heavy metals in edible parts of crops were the largest in Diqing (Pb) and Zhaotong (Cd). The average value of ecological risk index of Pb element in soil is 2.79, which indicates that the study area is in a slight ecological hazard, the average value of the ecological risk index of Cd in soil is 126.43. The average value of the comprehensive quality impact index (IICQ) is 4.27, which indicates that the study area is moderately polluted. In this study, the contents of heavy metals Cd and Pb in soils and crops in different administrative regions were determined, and the heavy metals Pb and Cd in soil-crop system of Yunnan province, China were evaluated, it is expected to have important scientific and theoretical significance for the safe use of cultivated land to export safe agricultural products and promote the sustainable development of agriculture in Yunnan Plateau.

基于可靠指标的桥梁结构稳定安全系数研究

桥梁相关规范规定,结构的第一类稳定安全系数不应小于4,但当第一类稳定安全系数取4时,能否保证结构在更可能出现的第二类失稳发生时的可靠指标达到目标可靠指标则值得研究。以钢筋混凝土受压构件为例,分别进行弹性和弹塑性稳定计算,取第一类稳定安全系数等于4,采用一次可靠度方法FORM得出第一类弹性失稳时的可靠指标,利用计算该可靠指标时的荷载效应和弹塑性临界荷载计算第二类弹塑性失稳时的可靠指标。结果表明:某些情况下,当第一类稳定安全系数取4时并不足以保证结构发生第二类失稳时的可靠指标达到目标可靠指标。文中还讨论了结构参数变化对结构第一类和第二类失稳时可靠指标及稳定安全系数的影响,得出第二类稳定安全系数和可靠指标的关系,并给出第二类稳定安全系数的取值建议。

Novel integration of extreme learning machine and improved Harris hawks optimization with particle swarm optimization-based mutation for predicting soil consolidation parameter

The study proposes an improved Harris hawks optimization(IHHO) algorithm by integrating the standard Harris hawks optimization(HHO) algorithm and mutation-based search mechanism for developing a high-performance machine learning solution for predicting soil compression index. HHO is a newly introduced meta-heuristic optimization algorithm(MOA) used to solve continuous search problems.Compared to the original HHO, the proposed IHHO can evade trapping in local optima, which in turn raises the search capabilities and enhances the search mechanism relying on mutation. Subsequently, a novel meta-heuristic-based soft computing technique called ELM-IHHO was established by integrating IHHO and extreme learning machine(ELM) to estimate soil compression index. A sum of 688 consolidation test data was collected for this purpose from an ongoing dedicated freight corridor railway project. To evaluate the generalization capability of the proposed ELM-IHHO model, a detailed comparison between ELM-IHHO and other well-established MOAs, such as particle swarm optimization,genetic algorithm, and biogeography-based optimization integrated with ELM, was performed. Based on the outcomes, the ELM-IHHO model exhibits superior performance over the other MOAs in predicting soil compression index.

Influence of expanded polystyrene size on deformation characteristics of light weight soil

Deformation characteristics of light weight soil with different EPS (expanded polystyrene) sizes were investigated by consolidation tests.The results show that the confined stress-strain relation curve is in S shape,which has a good homologous relation with e-p curve and e-lgp curve,and three types of curves reflect obvious structural characteristics of light weight soil.When cement mixed ratio and EPS volume ratio are the same for different specimens,structural strength decreases with the increase of EPS size,but compressibility indexes basically keep unchanged within the structural strength.The settlement of light weight soil can be divided into instantaneous settlement and primary consolidation settlement.It has no obvious rheology property,and 90% of total consolidation deformation can be finished in 1 min.Settlement-time relation of light weight soil can be predicted by the hyperbolic model.S-lgt curve of light weight soil is not in anti-S shape.It is proved that there is no secondary consolidation section,so consolidation coefficient cannot be obtained by time logarithm method.Structural strength and unit price decrease with the increase of EPS size,but the reducing rate of the structural strength is lower than that of the unit price,so the cost of mixed soil can be reduced by increasing the EPS size.The EPS beads with 3-5 mm in diameter are suggested to be used in the construction process,and the prescription of mixed soil can be optimized.

A Survey of Bitmap Index Compression Algorithms for Big Data

With the growing popularity of Internet applications and the widespread use of mobile Internet, Internet traffic has maintained rapid growth over the past two decades. Internet Traffic Archival Systems（ITAS） for packets or flow records have become more and more widely used in network monitoring, network troubleshooting, and user behavior and experience analysis. Among the three key technologies in ITAS, we focus on bitmap index compression algorithm and give a detailed survey in this paper. The current state-of-the-art bitmap index encoding schemes include： BBC, WAH, PLWAH, EWAH, PWAH, CONCISE, COMPAX, VLC, DF-WAH, and VAL-WAH. Based on differences in segmentation, chunking, merge compress, and Near Identical（NI） features, we provide a thorough categorization of the state-of-the-art bitmap index compression algorithms. We also propose some new bitmap index encoding algorithms, such as SECOMPAX, ICX, MASC, and PLWAH＋, and present the state diagrams for their encoding algorithms. We then evaluate their CPU and GPU implementations with a real Internet trace from CAIDA. Finally, we summarize and discuss the future direction of bitmap index compression algorithms. Beyond the application in network security and network forensic, bitmap index compression with faster bitwise-logical operations and reduced search space is widely used in analysis in genome data, geographical information system, graph databases, image retrieval, Internet of things, etc. It is expected that bitmap index compression will thrive and be prosperous again in Big Data era since 1980s.

Selection of regression models for predicting strength and deformability properties of rocks using GA

Recently,many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties.Although statistical analysis is a common method for developing regression models,but still selection of suitable transformation of the independent variables in a regression model is diffcult.In this paper,a genetic algorithm(GA)has been employed as a heuristic search method for selection of best transformation of the independent variables(some index properties of rocks)in regression models for prediction of uniaxial compressive strength(UCS)and modulus of elasticity(E).Firstly,multiple linear regression(MLR)analysis was performed on a data set to establish predictive models.Then,two GA models were developed in which root mean squared error(RMSE)was defned as ftness function.Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.

Determination of blast-induced ground vibration equations for rocks using mechanical and geological properties

In the recent decades, effects of blast loads on natural and man-made structures have gained considerable attention due to increase in threat from various man-made activities. Site-specific empirical relationships for calculation of blast-induced vibration parameters like peak particle velocity （PPV） and peak particle displacement （PPD） are commonly used for estimation of blast loads in design. However, these relation- ships are not able to consider the variation in rock parameters and uncertainty of in situ conditions. In this paper, a total of 1089 published blast data of various researchers in different rock sites have been collected and used to propose generalized empirical model for PPV by considering the effects of rock parameters like unit weight, rock quality designation （ROD）, geological strength index （GSI）, and uniaxial compressive strength （UCS）. The proposed PPV model has a good correlation coefficient and hence it can be directly used in prediction of blast-induced vibrations in rocks. Standard errors and coefficient of correlations of the predicted blast-induced vibration parameters are obtained with respect to the observed field data. The proposed empirical model for PPV has also been compared with the empirical models available for blast vibrations predictions given by other researchers and found to be in good agreement with specific cases.

Theoretical Study and Analysis on Properties of Filter Aids

Pressure filtration and filter aids should be adopted in filtration of high-viscosity molten chemical fiber containing foreign materials and gel particles. Theoretical analysis and argumentations on manners of assisted filtration and specific requirements of filter aids are performed. Measurement and comparison on properties of several filter aids are also carried out, conclusions and suggestions are put forward.

右江高阶地胀缩土成因初探

研究胀缩土的成因，为地表建筑物防灾减灾，有一定的现实意义。根据胀缩土的工程地质特征，平面和垂向分布规律，右江高阶地胀缩土为冲洪积成因。

Ginix: Generalized Inverted Index for Keyword Search

Keyword search has become a ubiquitous method for users to access text data in the face of information explosion. Inverted lists are usually used to index underlying documents to retrieve documents according to a set of keywords efficiently. Since inverted lists are usually large, many compression techniques have been proposed to reduce the storage space and disk I/O time. However, these techniques usually perform decompression operations on the fly, which increases the CPU time. This paper presents a more efficient index structure, the Generalized INverted IndeX （Ginix）, which merges consecutive IDs in inverted lists into intervals to save storage space. With this index structure, more efficient algorithms can be devised to perform basic keyword search operations, i.e., the union and the intersection operations, by taking the advantage of intervals. Specifically, these algorithms do not require conversions from interval lists back to ID lists. As a result, keyword search using Ginix can be more efficient than those using traditional inverted indices. The performance of Ginix is also improved by reordering the documents in datasets using two scalable algorithms. Experiments on the performance and scalability of Ginix on real datasets show that Ginix not only requires less storage space, but also improves the keyword search performance, compared with traditional inverted indexes.