半柔性复合路面在重交通长大纵坡路段的应用

重点阐述半柔性复合路面技术在国道丹霍线(G304)本溪段重载长大纵坡试验路段的应用,对原路路况及改造方案、配合比设计、人员与设备要求、工程实施工艺等方面进行分析。     

State of charge estimation method based on the extended Kalman filter algorithm with consideration of time-varying battery parameters

In developing battery management systems, estimating state-of-charge (SOC) is important yet challenging. Compared with traditional SOC estimation methods (eg, the ampere-hour integration method), extended Kalman filter (EKF) algorithm does not depend on the initial value of SOC and has no accumulated error, which is suitable for the actual working condition of electric vehicles. EKF is a model-based algorithm; the accuracy of SOC estimated by this algorithm was greatly influenced by the accuracy of battery model and model parameters. The parameters of battery change with many factors and exhibit strong nonlinearity and time variance. Typical EKF algorithm approximates battery as a linear, time-invariant system; however, this approach introduces estimation errors. To minimize such errors, previous studies have focused on improving the accuracy of identifying battery parameters. Although studies on battery model with time-varying parameters have been carried out, few have studied the combination of time-varying battery parameters and EKF algorithm. A SOC estimation method that combines time-varying battery parameters with EKF algorithm is proposed to improve the accuracy of SOC estimation. Battery parameter data were obtained experimentally under different temperatures, SOC levels, and discharge rates. The results of parameter identification are made into a data table, and the battery parameters in the EKF system matrix are updated by looking up the data in the table. Simulation and experimental results shown that, average error of SOC estimated by the proposed algorithm is 2.39% under 0.9 C constant current discharge and 2.4% under 1.3 C, which is 1.91% and 2.35% lower than that of EKF algorithm with fixed battery parameters. Under intermittent discharge with constant current (1.1 C) and capacity (10%), the average error of SOC estimated by the proposed algorithm is 1.4%, which is 0.3% lower than that of EKF algorithm with fixed battery parameters. The average error of SOC estimated by the proposed algorithm under the New European Driving Cycle (NEDC) is 1.6%, which is 0.2% lower than that of EKF algorithm with fixed battery parameters. Relative to the EKF algorithm with fixed battery parameters, the proposed EFK algorithm with time-varying battery parameters yields higher accuracy.     

Highly efficient preparation of free all-trans-astaxanthin from Haematococcus pluvialis extract by a rapid biocatalytic method based on crude extracellular enzyme extract

A highly efficient, rapid, green and safe procedure for the preparation of free all-trans-astaxanthin from Haematococcus pluvialis algal extract, by a crude extracellular enzyme extract, was reported. The free all-trans-astaxanthin obtained by the biocatalysed method had fewer side products compared to the saponification procedure. Through single-factor experiments and a Box–Behnken design, it was possible to find the optimal biocatalytic conditions for the hydrolysis of 2 mg of H. pluvialis oil with 14.7 mg (protein content) of lyophilised crude extracellular enzyme extract obtained from Pseudomonas aeruginosa. The reaction was carried out in 30 min at pH 9.16 and 36 °C, in 5.5 mL total reaction volume, under nitrogen atmosphere and dark conditions. The hydrolysis ratio of the astaxanthin esters was 98.72%, and the production of free all-trans-astaxanthin was 82.83 μg per mg of H. pluvialis oil. The method herein reported was simpler than other enzymatic methods previously described and allowed saving of time and costs.     

Effect of Argon Blowing Rate on Multiphase Flow and Initial Solidification in a Slab Mold

Metallurgical and Materials Transactions B - The multiphase flow, heat transfer, and initial solidification behaviors in a 230 × 1300 mm2 continuous casting slab mold under different argon...     

A Marine‐Inspired Hybrid Sponge for Highly Efficient Uranium Extraction from Seawater

Marine sponges are used as biomonitors of heavy metals contamination in coastal environment as they process large amounts of water and have a high capacity for accumulating heavy metals. Here, inspired by the unique physical and physiological features of marine sponges, a surface engineered synthetic sponge for the highly efficient harvesting of uranium from natural seawater is developed. An ultrathin poly(imide dioxime) (PIDO)/alginate (Alg) interpenetrating polymer network hydrogel layer is uniformly wrapped around the skeleton of a melamine sponge (MS) substrate through a simple dipping–drying–crosslinking process, providing the hybrid MS@PIDO/Alg sponge with excellent uranium adsorption performance and sufficient mechanical strength to withstand the harsh conditions of practical applications. The maximum adsorption capacity reaches 910.98 mg‐U g‐gel^‐1 for the PIDO/Alg hydrogel layer and 291.51 mg‐U g‐sponge^‐1 for the whole hybrid MS@PIDO/Alg sponge in uranium‐spiked natural seawater. The adsorption capacity measured after 56 d of exposure in 5 tons of natural seawater is evaluated to be 5.84 mg‐U g‐gel^‐1 (1.87 mg‐U g‐sponge^‐1). This novel approach shows great promise for the mass production of high‐performance sponge adsorbent for uranium recovery from natural seawater and nuclear waste.     

A variance‐constrained approach to event‐triggered distributed extended Kalman filtering with multiple fading measurements

In this paper, a distributed extended Kalman filtering problem is studied for discrete‐time nonlinear systems with multiple fading measurements. To alleviate the network communication burden, the event‐triggered communication scheme is employed in both sensor‐to‐estimator channel and estimator‐to‐estimator channel. As such, the data transmission is executed only when the predefined event occurs. In addition, a set of independent random variables with known statistical properties is defined to represent the phenomenon of multiple fading measurements. The variance‐constrained approach is adopted to derive an upper bound for the estimation error covariance in consideration of the event‐triggered mechanism and truncated error by linearization. The filter gain for each node is then designed to minimize such an upper bound by recursively solving two Raccati‐like difference equations. By virtue of the stochastic stability theory, a sufficient condition is provided to guarantee the boundedness of the estimation error. Finally, a simulation example is presented to illustrate the feasibility and effectiveness of the proposed filtering algorithm.     

Airport Taxi Situation Awareness with a Macroscopic Distribution Network Analysis

This paper proposes a framework for airport taxi situation awareness to enhance the assessment of aircraft ground movements in complex airport surfaces. Through a macroscopic distribution network (MDN) of arrival and departure taxi processes in a spatial-temporal domain, we establish two sets of taxi situation indices (TSIs) from the perspectives of single aircraft and the whole network. These TSIs are characterized into five categories: aircraft taxi time indices (ATTIs), surface instantaneous flow indices (SIFIs), surface cumulative flow indices (SCFIs), aircraft queue length indices (AQLIs), and slot resource demand indices (SRDIs). The coverage of the TSIs system is discussed in detail based on the departure and arrival reference aircraft. A real-world case study of Shanghai Pudong airport demonstrates significant correlations among some of the proposed TSIs such as the ATTIs, SCFIs and AQLIs. We identify the most crucial influencing factors of the taxi process and propose two new metrics to assess the taxi situation at the aircraft and network levels, by establishing taxi situation assessment models instead of using two systems of multiple TSIs. The findings can provide significant references to decision makers regarding airport ground movements for the purposes of air traffic scheduling and congestion control in complex airports.

     

A Dual‐Gate MoS2 Photodetector Based on Interface Coupling Effect

2D transition metal dichalcogenides (TMDs) based photodetectors have shown great potential for the next generation optoelectronics. However, most of the reported MoS₂ photodetectors function under the photogating effect originated from the charge‐trap mechanism, which is difficult for quantitative control. Such devices generally suffer from a poor compromise between response speed and responsivity (R) and large dark current. Here, a dual‐gated (DG) MoS₂ phototransistor operating based on the interface coupling effect (ICE) is demonstrated. By simultaneously applying a negative top‐gate voltage (V_TG) and positive back‐gate voltage (V_BG) to the MoS₂ channel, the photogenerated holes can be effectively trapped in the depleted region under TG. An ultrahigh R of ≈10⁵ A W^?1 and detectivity (D*) of ≈10¹⁴ Jones are achieved in several devices with different thickness under P_in of 53 µW cm^?2 at V_TG = ?5 V. Moreover, the response time of the DG phototransistor can also be modulated based on the ICE. Based on these systematic measurements of MoS₂ DG phototransistors, the results show that the ICE plays an important role in the modulation of photoelectric performances. The results also pave the way for the future optoelectrical application of 2D TMDs materials and prompt for further investigation in the DG structured phototransistors.     

协同催化水解羰基硫和二硫化碳的低温催化剂的研究进展

钢厂副产煤气是钢铁企业产生的二次能源,但是由于其中含有化学稳定性高的COS和CS2,二次利用困难,部分钢铁企业会将其直接高空排放,这样不仅造成了能源浪费,还造成了环境污染.因此,研究者们开发了多种技术用于脱除COS和CS2,其中水解法脱除废气中的COS和CS2是应用较为广泛的脱硫技术.然而,目前水解催化剂的使用温度相对较高,而钢厂副产煤气具有温度低、热值低、二氧化碳及氧含量高等特点.因此,近十年来研究者们研发了多种低温水解催化剂,用于COS和CS2的单独催化水解,甚至两种气体的协同催化水解.这些催化剂的成功研发不仅使得水解催化剂的使用温度大幅度降低,而且保持了其较高的水解效率.COS和CS2单独低温水解催化剂主要包括金属氧化物基催化剂、活性炭基催化剂以及类水滑石基催化剂.其中,金属氧化物基水解催化剂主要以γ-Al2 O3和TiO2为载体,并且以TiO2作为载体能更好地抑制水解催化剂中毒;活性炭基水解催化剂可通过调控其活性成分与含量以及提高活性炭载体自身品质来增强其低温水解性能;而类水滑石基水解催化剂则是通过调整其层板金属的组成、制备方法及条件使得其具有优异的低温水解性能.此外,由于活性炭具有特殊的物理化学特性,COS和CS2的协同水解催化剂主要是以活性炭基低温水解催化剂为主.本文归纳了COS和CS2低温水解催化剂的研究进展,分别对COS和CS2的单独水解催化剂和协同水解催化剂及其催化水解机理进行了介绍,分析了低温水解催化剂研发所面临的问题并提出未来可尝试的研究方向,以期开发更多COS和CS2协同水解的低温催化剂,更重要的是,为今后钢铁行业副产煤气中COS和CS2协同水解低温催化剂的研究方向及工业化应用提供参考.