超临界机组发生FAC的因素及相互关系分析

为了减轻因流动加速腐蚀(FAC)引起的锅炉结垢加速、汽水系统管道厚度减小甚至爆裂现象，对超临界机组发生流动加速腐蚀的机理及其主要影响因素进行了研究，并讨论了管壁内表面粗糙度、蒸汽含汽率、pH值、溶氧量对FAC的影响，以及温度与pH值、温度与流速、pH值与溶解氧量、溶解氧量与氢电导率等影响因素之间的相互作用关系，最后结合实际电厂的运行数据验证了分析结果。研究表明：减小工质流速、管壁粗糙度和氢电导率，增大给水的pH值和溶解氧含量可以使FAC的腐蚀速率减小，超临界加氧处理时pH值应在8.9～9.2之间，溶解氧量范围为45～100μg/L,氢电导率的期望值在0.1μS/cm以下。由于各影响因素之间的作用十分复杂，本文只给出了大致范围和趋势，并未给出准确数据。     

南水北调中线总干渠藻类的生态调度

南水北调中线总干渠无在线调蓄水库,对藻类生态调度过程中出现的问题开展生态调度实现策略和实施方式研究。主要实现策略包括:划定自身的调蓄区,隔离生态调度对下游的影响;采用高效的渠池运行方式,减少生态调度时蓄量的反复调整;综合考虑安全、快速、平稳等需求,设定生态调度实施进程和方式。具体实施方式包括:将总干渠划分为流速调控区、调蓄区和正常运行区,分别实施等体积、控制蓄量和闸前常水位方式运行;将生态调度过程划分为充水阶段和泄水阶段,基于流速调控目标值、持续时长和水位降幅约束条件,确定各阶段时长和各分区的闸门群调控方案等。基于2018年3月输水工况,采用明渠一维非恒定流模型,仿真总干渠上游15个渠池的藻类生态调度过程。结果表明,生态调度可在3.5 d内完成,各渠池的平均流速由0.48 m/s增至0.93 m/s,持续时间超过2 h。在整个生态调度过程中,水位变化平稳,水位变幅符合安全阈值要求,下游渠道的正常运行未受生态调度明显影响。     

农村综合能源系统多层协同优化运行方法

农村综合能源系统通过多种能源的协同互补,在满足农村用户多元化用能需求的同时,能有效提升能源利用效率和用能经济性。首先,在考虑适应农村典型场景的基础上,提出了一种三层协同自律的农村综合能源分层协同运行优化框架。然后,基于农村综合能源系统典型设备,建立了三层农村综合能源系统源-储-荷联合优化调度模型以及相应的优化调度流程。调度模型中冬季通过对沼气发电机组的余热回收与空气源热泵协同对用户供热;夏季对沼气发电机组余热进行回收,并通过溴化锂制冷机与空气源热泵联合对农村用户供冷。最后,对农村综合能源系统多层协同优化方法进行了算例分析,结果表明该优化方法提高了农村居民用能的经济性,验证了所提方法的有效性。     

A new method for extrapolating the load-displacement response of drilled shaft foundations for interpretation of side capacity

In this study, the side capacity of drilled shaft foundations is estimated from partially-mobilized load–displacement field data using a new method in the extrapolation of load–displacement response. A dataset of 138 bi-directional load tests is used to evaluate the degree of mobilization of unit side resistance. A total of 612 unit side-resistance curves obtained from measured strain gauge recordings are utilized in this study. The proposed extrapolation approach is based on a new technique, the Double Tangent method, characterizing the extent of mobilization for each unit side-resistance curve. Roughly, 12% of the dataset exhibits a fully-mobilized load–displacement response, with the remainder exhibiting varying degrees of a partially-mobilized response. Fully-mobilized records are further characterized using the Double Tangent method over different ranges of mobilization, resulting in four regression models based on predominant soil types. Each model is assessed statistically, and a global regression model is found suitable to predict maximum unit side resistance. The global model is further validated using two independent load test datasets, comparing measured values of unit side resistance against predicted values. The model is then used to predict maximum unit side resistance for all partially-mobilized data within the dataset, and the results are compared to two extrapolation techniques currently used in practice. The corresponding resistance-displacement response is extrapolated using a proposed asymptotic curve-fitting function for side resistance, and an example extrapolation is illustrated to showcase how the proposed method can be used in engineering practice.     

基于音频特征的工程车辆工况识别研究

高效率地使用工程车辆是工程项目管理中节约成本的有效方法，无人监管环境下工程车辆的工况识别，是实现工程车辆高效率使用的有效手段。目前以GPS等技术为核心的车辆智能管理系统未对工程车辆进行工况识别，提出一种基于GRU循环神经网络的工程车辆工况识别方法，通过对工程车辆在不同工况下产生的音频信号进行分析，从中提取Mel倒谱系数作为主要特征，构建GRU循环神经网络模型进行训练和识别。实验结果表明，该方法可以实现对工程车辆工况的有效识别。     

Sequential alignment attention model for scene text recognition

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state-of-the-art solutions usually depend on the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. Unfortunately, there often exists severe misalignment between feature areas and text labels in real-world scenarios. To address this problem, this paper proposes a sequential alignment attention model to enhance the alignment between input images and output character sequences. In this model, an attention gated recurrent unit (AGRU) is first devised to distinguish the text and background regions, and further extract the localized features focusing on sequential text regions. Furthermore, CTC guided decoding strategy is integrated into the popular attention-based decoder, which not only helps to boost the convergence of the training but also enhances the well-aligned sequence recognition. Extensive experiments on various benchmarks, including the IIIT5k, SVT, and ICDAR datasets, show that our method substantially outperforms the state-of-the-art methods.     

Benchmark value determination of energy efficiency indexes for coal-fired power units based on data mining methods

The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values.     

Revisiting CO2 emissions convergence in G18 countries

This study revisits whether CO₂ emissions converge in G18 countries over the period of 1950–2013. To work on this empirical analysis, we employ a more powerful quantile unit root test with per capita CO₂ emissions. While conventional unit root tests fail to reject convergence in CO₂ emissions in these G18 countries, quantile unit root test results demonstrate CO₂ emissions converged in 5 of these G18 countries (i.e., Australia, Brazil, Canada, Germany, and India). Our empirical results have important policy implications for the governments of G18 countries to direct efficient and effective energy policies to reduce the CO₂ emissions.     

基于英飞凌TC275的整车控制器CCP协议底层驱动开发

针对以英飞凌TC275单片机为平台的整车控制器,进行控制器局域网络标定协议(controller area network calibration protocol,CCP)底层驱动程序的开发。依据CCP的需求开发了英飞凌TC275的控制器局域网络(controller area network,CAN)模块、系统定时器(system timer,STM)模块和FLASH模块的底层驱动程序,实现CCP标定系统的通信连接、数据上传、数据下载、数据存储等功能。为验证系统的性能,进行整车控制器的实际测试,测试结果表明:所开发的基于TC275单片机的CCP底层驱动程序能够实现CCP的功能要求。     

Exergy analysis of the diesel pre-reforming solid oxide fuel cell system with anode off-gas recycling in the SchIBZ project. Part I: Modeling and validation

Solid oxide fuel cell (SOFC) systems with anode off-gas recirculation (AGR) and diesel pre-reforming are advantageous because they can operate with the current fuel infrastructure. In the SchIBZ-project, the prototype of such a SOFC system for maritime applications has already been commissioned. In this first paper, we model the system devices to conduct an exergy analysis of this real SOFC plant and validate them with experimental values from experiments in laboratory scale. The results of our simulation agree well with the experimental values. The calculations with the validated results may be closer to the real thermodynamic behavior of such system components than previous literature.