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.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

废菌渣活性炭的制备及对废水中硝基苯的吸附

以废菌渣为原料制备活性炭，采用能量-色散光谱（EDS）和傅里叶变换红外光谱仪（FTIR）进行表征，结果表明：活性炭表面具有多种官能团，有利于提高对硝基苯的吸附。并研究了活性炭吸附硝基苯的影响因素（pH、初始浓度、吸附时间、投加量）、吸附等温线及热力学。结果表明：在常温中性pH条件下，初始浓度为50mg/L，活性炭用量为0.15g时硝基苯去除率可达98%，出水水质满足《污水综合排放标准》（GB 8978－1996）中对硝基苯浓度低于2.0mg/L的要求。活性炭对硝基苯的吸附具有较快的吸附速率，即1min接近平衡。该吸附行为是自发放热反应，可以用Freundlich模型很好地拟合。废菌渣活性炭对硝基苯的吸附主要是疏水作用和氧化钼活化共同作用的结果。因此，以农业废弃物-废菌渣制备得到的废菌渣活性炭具有良好的经济实用性，可用于废水处理中，实现以废治废的目的。     

Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a sensor, it does not share its waking schedule to its neighbors and cache any waking schedules of other sensors. Hence, the energy consumption for time synchronization, location information and waking schedule shared will be reduced significantly. The saving energy can be used for improving data collection rate. Simulation shows our scheme is efficient to improve packets generation rate in rechargeable wireless sensor networks.     

渣油催化临氢热转化钼铁双金属催化剂的研究

Replacement of precious single metal catalysts with cost-effective, highly-dispersed composite catalysts for catalytic hydrothermal conversion of residue holds tremendous promise for the residue upgrading technologies. Organic metals were added to the feed as the oil-soluble precursors, and transformed into the catalytic active phases in this work. Physical properties and structures of the composite catalysts had been investigated by X-ray fluorescence spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, scanning electron microscope and transmission electron microscopy. The composite catalysts were found to be highly efficient in the catalytic hydrothermal conversion of both model compound and residue. Increased metal dispersion and synergistic effects of two metals played indispensable roles in such catalytic system. Results showed that under the test conditions in the article, the catalyst had the best catalytic performance when the mass ratio of molybdenum to iron was 1.5.     

净水水处理剂中有害杂质在水中残留物分析与风险评估

与欧盟和美国标准相比,我国硫酸铝和硫酸铵标准缺少对水处理剂中有害杂质镍、锑、硒、银、吡啶、氰化物、六价铬的检测;次氯酸钠缺少对水处理剂中有害杂质汞、铬、镉、铁、镍、锑、硒、银、六价铬的检测。结合某市2019年上半年13个水厂出厂水和原水的检测数据,剔除了5项始终低于检出限的有害杂质指标,以及2项出厂水浓度低于原水浓度的有害杂质指标。建议该市硫酸铝和硫酸铵的检测项目可以在原有国标基础上增加锑、硒;次氯酸钠可以增加汞、锑、硒。     

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength and stress have an odd or an even set size. The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa. The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study. The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample. In general, the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.