Effects of Optimized Operating Parameters on Combustion Characteristics and NO_x Emissions of a Burner based on Orthogonal Analysis

To optimize the structure of the burner,improve the combustion performance,and reduce the emission of NO_x,a self-circulating low NO_x combustion technology was used to design a new type of flue gas self-circulating low NO_x burner.Based on previous research on the numerical model of combustion and the composition of mixed gas on combustion and NO_x emissions,the effect of various factors on the ejection coefficient of the flue gas self-circulating structure was analyzed using the orthogonal test method,and the burner operating parameters,such as preheating temperature and excess air coefficient,were deeply studied through the three-dimensional finite element numerical model in this paper.The results show that the diameter ratio of the nozzle and the length of the cylindrical section of the flue gas self-circulating structure have great influence on its ejection and mixing ability.The optimal ejection coefficient was 0.4829.Overall,the amount of NO_x emissions greatly increased from 6.23×10~(-6) (volume fraction) at the preheating temperature 973 K to 3.5×10~(-3) at preheating temperature 1573 K.When the excess air coefficient decreased from 1.2 to 1,the maximum combustion temperature decreased from 2036.3 K to 1954.22 K,and the NO_x emissions decreased from 352.29×10~(-6) to 159.73×10~(-6).     

基于UML的CMP控制系统设计与实现

CMP(Chemical Mechanical Polishing)设备是半导体集成电路(IC)制造中的关键设备,CMP设备控制软件的开发是CMP设备研发的关键技术之一。在分析三工位CMP设备控制系统需求的基础上,对控制系统中的3个工位的模块构建等问题进行了探讨,给出了控制软件的设计方法。在对CMP系统功能架构进行详细分析的基础上,利用UML对系统控制结构进行了分析设计,并用例模型、结构模型和行为模型等对系统进行了可视化建模,然后用Rational Rose 2003的正向工程实现模型到C++代码的转换,最后在此基础上用Visual C++进行系统开发和实现。     

预应力作用下雷达框架结构的动力特性

针对雷达框架结构经常在预应力作用下的特点,从模态分析的角度对预应力的作用机理进行理论推导,并结合工程实践进行分析,得出预应力是通过改变框架结构的刚度矩阵影响结构的固有特性的结论.     

pH响应型可降解纳米容器的制备及防腐性能

为了合成快速响应的纳米容器,实现缓蚀剂靶向释放,更好地解决油气田管道金属进一步腐蚀的状况,采用修饰的St?ber法,改变无机和有机硅源的摩尔比合成了不同亚胺嵌入的有机硅纳米颗粒(S-SNPs)并负载缓蚀剂MBT得到了智能缓蚀剂MBT@S-SNPs,并研究其智能防腐性能.研究结果表明,S-SNPs在中性环境下稳定,而在酸...     

酚醛基碳气凝胶的常压制备及电化学应用

本研究利用线性酚醛树脂体系,以溶胶-凝胶法在常压条件下制得有机气凝胶,并进一步碳化制备出碳气凝胶.研究发现,该碳气凝胶经过KOH活化后,具有微/介/大孔的分级孔结构,且比表面高达2091.87 m2·g-1.对材料进行电化学性能研究发现,其在1 A·g-1电流密度下,比电容为282.3 F·g-1.在600 W·kg-...     

单臂液压机组合机架的三维建模

在构造单臂液压机预应力组合机架三维实体模型基础上,合理处理机架预紧、接触、摩擦等边界条件,建立了组合机架的三维弹性接触分析模型.为组合机架的整体受力状态及变形评价提供了依据.     

伪码测距中码跟踪环的FPGA实现

码跟踪环的设计是伪码/载波相位联合测距系统的一个关键环节.分析了伪码跟踪环路的结构,利用查表法、二阶环路分别对NCO和环路滤波器等关键部分进行了设计,并给出了相应的电路结构.系统仿真与FPAG片上测试结果表明,实现了伪码准确、实时跟踪,跟踪到的伪码相位误差小于载波相位的周期长,设计的跟踪环具有一定工程应用价值.     

Cryptomining Malware Detection Based on Edge Computing-Oriented Multi-Modal Features Deep Learning

In recent years, with the increase in the price of cryptocurrencies, the number of malicious cryptomining software has increased significantly. With their powerful spreading ability, cryptomining malware can unknowingly occupy our resources, harm our interests, and damage more legitimate assets. However, although current traditional rule-based malware detection methods have a low false alarm rate, they have a relatively low detection rate when faced with a large volume of emerging malware. Even ...     

ABAQUS软件在高进水塔动力分析中的应用

结合进水塔工程实例,利用大型商业有限元分析软件ABAQUS完成了进水塔的动力分析,着重研究了进水塔结构的自振特性和地震响应,验证了进水塔的强度要求,分析了进水塔结构的抗倾覆及抗滑移稳定性。在计算结果的基础上并提出了设计修改意见,为工程设计提供了依据。     

A Unified Shared-Private Network with Denoising for Dialogue State Tracking

Dialogue state tracking(DST)leverages dialogue information to predict dialogues states which are generally represented as slot-value pairs.However,previous work usually has limitations to efficiently predict values due to the lack of a powerful strategy for generating values from both the dialogue history and the predefined values.By predicting values from the predefined value set,previous discriminative DST methods are difficult to handle unknown values.Previous generative DST methods determine values based on mentions in the dialogue history,which makes it difficult for them to handle uncovered and non-pointable mentions.Besides,existing generative DST methods usually ignore the unlabeled instances and suffer from the label noise problem,which limits the generation of mentions and eventually hurts performance.In this paper,we propose a unified shared-private network(USPN) to generate values from both the dialogue history and the predefined values through a unified strategy.Specifically,USPN uses an encoder to construct a complete generative space for each slot and to discern shared information between slots through a shared-private architecture.Then,our model predicts values from the generative space through a shared-private decoder.We further utilize reinforcement learning to alleviate the label noise problem by learning indirect supervision from semantic relations between conversational words and predefined slot-value pairs.Experimental results on three public datasets show the effectiveness of USPN by outperforming state-of-the-art baselines in both supervised and unsupervised DST tasks.