热电厂热储系统的构建和优化研究

热电厂热储系统的构建,对于废弃能源存储和废水再利用有重要意义。以吉林省桦甸市热电厂为例,通过对研究区水文地质条件和温度参数概化,利用FEFLOW软件构建桦甸市热电厂地下水-热耦合模型,用实际观测资料进行识别和验正,初步构建热储系统模型。设置不同井间距和抽水量来优化热储模型,研究结果表明:200 m井间距热贯通严重,500 m和1 000 m热贯通影响小;1 500 m~3/d的流量比1 200 m~3/d的流量在提热期温度下降更快,但提热总量显著增加;各方案提热总量对比显示,优化储热方案为井间距离500 m,储热期注水量8 400 m~3/d,热提取期抽水量1 500 m~3/d,冷水抽注水井在储热期和热提取期水量均为1 200 m~3/d,提热总量为2.27×10~(11)J/d。     

建立在生命周期分析之上的城市机动车能源结构优化

针对我国城市能源供需矛盾日益恶化、环境污染日益严重的现状,优化城市机动车能源结构,缓解城市机动车对传统能源的使用压力,减少尾气排放,具有十分重要的意义.因此,本文以成都市为例,采用线性优化技术,通过确定各种车用能源生命周期内的能源消耗及排放、各种能源车辆的经济成本等,分析得到成都市整个城区范围内能耗最低、排放最小的各种能源机动车数量比例.结果表明,成都市各种能源机动车的数量比例随所选目标函数的不同而有所变化.为实现总能耗最小,各种能源机动车的比例按汽油、柴油、纯电动、电力/汽油混合动力、CNG单燃料、CNG/汽油双燃料、LPG单燃料、及LPG/汽油双燃料等划分应分别68.6%、11.4%、3.7%、6.1%、5.0%、5.0%、0.1%、0.1%.与机动车数量比例优化前相比,优化后总能源消耗量、石油消耗量分别平均减少了11.5%、13.8%.除PM₁₀及SO_x排放量有所增加外,其他气体的排放均有所减少,如CO₂、VOC、CO及NO_x的平均排放量分别减少了10.6%、13.5%、13.5%及16.5%.这是因为机动车能源结构优化后,纯电动汽车及混合燃油汽车的比例有所增加,由于这两类汽车都需要经常充电从而增加了电网的压力.而我国发电技术主要采用火力发电,发电过程将会产生大量的PM₁₀及SO_x.本研究的成果可用于环境决策者制定有效的交通能源政策,达到城市可持续发展的目的.     

不确定节点水量下水质监测点优化选址方法

针对供水管网水质监测点的优化选址问题,提出污染源位置识别准确度的概念,以水质监测点探测到的不同污染事件的时段区间冗余度最小化,和污染事件探测概率最大化为优化目标,结合一个案例管网,采用非支配排序遗传算法计算节点用水量变化条件下的监测点优化选址方案,算例结果显示节点用水量的不确定性不显著影响监测点的污染事件探测能力和可能性节点识别能力,但使监测点的污染源位置识别准确度降低.     

Isolation of a salt tolerant laccase secreting strain of Trichoderma sp. NFCCI-2745 and optimization of culture conditions and assessing its effectiveness in treating saline phenolic effluents

Most of the hazardous pollutants are phenolic in nature and persists in the environment. The ability of laccases to oxidize phenolic compounds and reduce molecular oxygen to water has led to intensive studies of these enzymes. Therefore the fungal strains with high laccase activity and substrate affinity that can tolerate harsh environmental conditions have a potential for biotechnological applications. Salt tolerant laccase secreting fungi can be utilized in treatment of saline and phenolic rich industrial effluents such as coir effluent and textile effluent that needed to be diluted several fold before microbial treatment. This is the first study describing the isolation and optimization of a salt tolerant strain of Trichoderma sp. potential for industrial applications. The fungus was identified based on morphological characteristics and was subsequently confirmed with molecular techniques and deposited at National Fungal Culture Collections of India （NFCCI） under the Accession No. Trichoderma viride NFCCI 2745. In contrast to other laccase secreting fungi, light conditions did not exert much influence on laccase production of this strain and salinity enhanced its laccase secretion. The fungus effectively removed the phenolic content of the textile effluent, coir-ret liquor and wood processing effluent within 96 hr of incubation. The tolerance of the fungus to high salinity and phenolic compounds makes this strain ideal for treating saline and phenolic rich industrial effluents.     

Entrepreneur environment management behavior evaluation method derived from environmental economy

Evaluation system can encourage and guide entrepreneurs, and impel them to perform well in environment management. An evaluation method based on advantage structure is established. It is used to analyze entrepreneur environment management behavior in China. Entrepreneur environment management behavior evaluation index system is constructed based on empirical research. Evaluation method of entrepreneurs is put forward, from the point of objective programming-theory to alert entrepreneurs concerned to think much of it, which means to take minimized objective function as comprehensive evaluation result and identify disadvantage structure pattern. Application research shows that overall behavior of Chinese entrepreneurs environmental management are good, specially, environment strategic behavior are best, environmental management behavior are second, cultural behavior ranks last. Application results show the efficiency and feasibility of this method.     

声屏障参数简易计算方法的探讨

声屏障作为从传播途径解决噪声问题的一种有效措施,得到了越来越多的应用。本文简单介绍了声屏障设计的一般步骤和设置所需考虑的周边环境条件的一般原则;同时还介绍了一种简易声屏障参数计算方法,通过声屏障衰减理论和工程实践验证,证明了计算方法的可行性,为声屏障工程应用提供借鉴。     

Parametric study along with selection of optimal solutions in dry wire cut machining of cemented tungsten carbide (WC-Co)

This work deals with parametric study of dry wire EDM (WEDM) process of cemented tungsten carbide. Experiments have been conducted using air as dielectric medium to investigate effects of pulse on time, pulse off time, gap set voltage, discharge current and wire tension on cutting velocity (CV) surface roughness (SR) and oversize (OS). Firstly, a series of exploratory experiments were carried out to identify appropriate gas and its pressure. Afterward, preliminary experiments were conducted to investigate effects of process parameters on dry WEDM characteristics and find appropriate ranges for each factor. Then a central composite rotatable method was employed to design experiments based on response surface methodology (RSM). Empirical models were developed to create relationships between process factors and responses by considering to analysis of variances (ANOVA). To increase the predictability of the process, intelligent models have been developed based on back-propagation neural network (BPNN) and accuracy of these models was compared with mathematical models based on root mean square error (RMSE) and prediction error percent (PEP). In order to select optimal solutions in the cases of single-objective and multi-objectives optimization problems, optimization includes two main approaches. First approach was based on mathematical model and desirability function. Also second approach was designed based on neural network and particle swarm optimization. These approaches were applied in both cases of single-objective and multi-objectives optimization problems and their results were compared with together. Results indicated that selection of air at inlet pressure of 1.5 bar is really appropriate for conducting experiments of next stages. Also, the BPNN creates more accurate prediction rather than mathematical model. Moreover, the BPNN-PSO approach was more efficient in optimization of process rather than mathematical model-desirability function in respect with validation tests.     

Developing China's roadmap for air quality improvement: A review on technology development and future prospects

Air pollution control policies in China have been experiencing profound changes, highlighting a strategic transformation from total pollutant emission control to air quality improvement, along with the shifting targets starting from acid rain and NO_x emissions to PM_2.5 pollution, and then the emerging O₃ challenges. The marvelous achievements have been made with the dramatic decrease of SO₂ emission and fundamental improvement of PM_2.5 concentration. Despite these achievements, China has proposed Beautiful China target through 2035 and the goal of 2030 carbon peak and 2060 carbon neutrality, which impose stricter requirements on air quality and synergistic mitigation with Greenhouse Gas (GHG) emissions. Against this background, an integrated multi-objective and multi-benefit roadmap is required to provide decision support for China's long-term air quality improvement strategy. This paper systematically reviews the technical system for developing the air quality improvement roadmap, which was integrated from the research output of China's National Key R&D Program for Research on Atmospheric Pollution Factors and Control Technologies (hereafter Special NKP), covering mid- and long-term air quality target setting techniques, quantitative analysis techniques for emission reduction targets corresponding to air quality targets, and pathway optimization techniques for realizing reduction targets. The experience and lessons derived from the reviews have implications for the reformation of China's air quality improvement roadmap in facing challenges of synergistic mitigation of PM_2.5 and O₃, and the coupling with climate change mitigation.     

GSK-XGBoost模型在井底风温预测中的应用*

为防治矿井热害,针对矿井井底风温在预测过程中精度较低的问题,提出1种网格搜索法结合K折交叉验证优化XGBoost的预测模型。通过分析确定影响井底风温的主要因素,使用网格搜索算法结合K折交叉验证,进行迭代缩小搜索范围并调参,选取最优参数配置,实现对XGBoost模型的优化,得到预测结果并与其他模型进行比较。研究结果表明:初始参数经优化后,当最大回归树深度为3且学习速率为0.1时,XGBoost回归模型性能最佳,与随机森林模型、BP神经网络模型、T-S模糊神经网络模型相比,平均相对误差分别降低了2.12%,0.88%,0.3%,均方根误差分别降低了0.66,0.24,0.11 ℃。     

基于遗传算法和场域模型的多障碍物房间人员疏散研究*

为提高多障碍物房间的人员疏散效率,利用场域元胞自动机模型并融合经典遗传算法,对2出口和4出口的多障碍物房间进行布局优化和疏散仿真研究。研究结果表明:利用遗传算法可快速寻找最优座椅布局,连排座椅设置在远离出口侧可有效减轻行人疏散时的拥堵程度;经过遗传算法优化后的座椅布局可协调疏散人群到达出口的时间,从而缓解出口通行压力,提高整体疏散效率,保障行人在大型多障碍物房间内的疏散安全。