电动汽车空调制热系统设计及研究

针对纯电动汽车空调系统制热功耗高且低温环境工况下制热效果差的问题,提出一种通过回收电机余热为乘客舱制热来减少制热功耗的空调系统.运用AMESim软件建立了电机余热循环系统模型并通过电机余热制热试验验证了该模型的准确性,建立了热泵空调制热系统模型并通过热泵空调制热试验验证了该模型的准确性,结合两个系统建立了带有电机余热回收的热泵空调系统仿真模型,分析了电机余热制热性能和电机余热辅助热泵空调制热性能.试验结果表明,电机余热单独制热在中等车速、环境温度高于10℃的工况下能够满足制热需求;电机余热辅助热泵空调制热能够有效提高制热效率,在电机转速为3000 r/min、压缩机转速为4000 r/min、环境温度为-5℃的工况下,等效制热能效比能够达到3.4,比同工况下热泵空调单独制热模式的能效比提高了约48％.该系统可以有效提高纯电动汽车的能源利用率,改善空调系统的制热性能.     

当我们来到模拟世界

想象一下,当你的曾祖父母还是少男少女之时,他们获得了一件开创性的新设备——全世界首个完全沉浸式的虚拟现实娱乐系统,不是你现在随处可见的那种蠢兮兮的VR眼镜.这种设备更像电影《黑客帝国》中出现的玩意——是一种时髦的魔力头带,塞满电极,以某种方式直接连上人类大脑的感知系统,用机器生成的新知觉取代了佩戴者的视觉、听觉、触觉、...     

液压蓄能式风力机组并网转速解耦优化控制

针对在风速、同步发电机负载变化情况下,液压蓄能式风力机组并网转速控制问题,提出一种新型并网转速控制方法——解耦广义预测优化控制方法（Decoupled Generalized Predictive Optimization Control, DGPOC）.首先,DGPOC利用基于广义预测的前馈解耦方法解除变量马达摆角和蓄能器比例阀开度之间的耦合关系,进而调节蓄能器比例阀,依靠蓄能器吸收波动流量,同步调节变量马达摆角实现恒转速控制,解决因风速、同步发电机负载变化引起的变量马达转速波动问题; 其次,将蓄能器比例阀的能量损耗作为性能约束项,加入到优化目标函数中,求取最优控制量,从而提高液压蓄能式风力机组风能利用率; 最后,利用建立的MATLAB-AMESim联合仿真实验平台验证DGPOC方法的有效性.实验结果表明： DGPOC方法不仅可以实现变量马达摆角和蓄能器比例阀开度两个变量的解耦,提升变量马达转速控制的快速性及鲁棒性,而且能够降低系统的能量损耗.     

刚性筏板下群桩基础共同作用实用分析方法

为了分析实际工程中大规模桩筏基础荷载分担及沉降特性,基于桩-土-筏相互作用理论提出了在竖向荷载作用下考虑土体弹塑性的刚性筏板下群桩基础共同作用的实用分析方法.桩-土-筏相互作用包括桩-土、桩-桩、筏-土和桩-筏相互作用,土体弹塑性考虑了土体模量的双曲线型变化特性.通过对不同尺寸条件下桩筏基础现场实测案例进行分析,介绍了计算过程中相应土体参数的取值方法,并基于基础沉降及桩-土荷载分担比实测和计算值对比结果,验证了该计算方法用于分析实际工程中大规模桩筏基础的合理性.同时基于某工程桩基优化分析,其计算结果表明:考虑筏板的荷载分担能显著降低桩基用量,桩数降为原设计1/3左右时,基础沉降并不会显著增加.     

Cu含量对2A14铝合金显微组织和腐蚀性能的影响

为了提升2A14铝合金耐局部腐蚀性能,采用扫描电镜(SEM)、点蚀测试、循环阳极极化曲线(Tafel)和电化学阻抗谱(EIS)等分析测试方法,研究了Cu含量对2A14铝合金锻件显微组织和腐蚀性能的影响.结果表明:随着Cu含量降低,诱导点蚀的Al2Cu和AlCuMgSi残余结晶相体积分数减小,点蚀坑密度显著降低,合金抗点蚀性能和电化学腐蚀性能大幅提高.     

热轧低碳DC04钢表面色差产生机理及控制

针对钢铁企业生产中热轧低碳DC04钢出现的色差问题,通过对现场取样分析,明确了造成热轧带钢表面色差缺陷的主要原因是中部和边部的氧化铁皮的厚度和结构存在差异.为解决这一问题,利用高温差热分析仪(TGA)和场发射电子探针(EPMA),模拟研究了在连续冷却过程中氧化铁皮微观结构的转变规律.结果表明,先共析Fe3O4优先在原始的Fe3O4层处形核生长,随着温度的降低,开始生成片层状的共析组织Fe3O4+α-Fe,但当冷却速率达到25℃/min时,共析反应被阻止.依据实验结果在生产现场进行工业试制,通过合理的设定卷取温度和冷却速率有效地控制氧化铁皮微观组织结构和厚度,基本消除了表面色差缺陷.     

New testing methodology for the quantification of rock crushability: Compressive crushing value (CCV)

Crushing is a size reduction process that plays a key role in both mineral processing and crushing-screening plant design. Investigations on rock crushability have become an important issue in mining operations and the manufacture of industrial crusher equipment. The main objective of this research is to quantify the crushability of hard rocks based on their mineralogical and mechanical properties. For this purpose, the mineralogical, physical, and mechanical properties of various hard rocks were determined. A new compressive crushing value (CCV) testing methodology was proposed. The results obtained from CCV tests were compared with those from mineralogical inspections, rock strength as well as mechanical aggregate tests. Strong correlations were found between CCV and several rock and aggregate properties such as uniaxial compressive strength (UCS), the brittleness index (S₂₀), and aggregate impact value (AIV). Furthermore, the relationship between the mineralogical properties of the rocks and their CCVs were established. It is concluded that the proposed testing methodology is simple and highly repeatable and could be utilized as a pre-design tool in the design stage of the crushing process for rock quarries.     

Simulating FAS-induced apoptosis by using P systems

In contrast to differential equations, P systems are an unconventional model of computation which takes into consideration the discrete character of the quantity of components and the inherent randomness that exists in biological phenomena. The key feature of P systems is their compartmentalised structure which represents the heterogeneity of the structural organisation of the cells, and where one can take into account the role played by membranes in the functioning of the system, for example signalling at the cell surface, selective uptake of substances from the media, diffusion across different compartments, etc. We show here that P systems can be a reliable tool for Systems Biology and could even outperform in some cases the current simulation techniques based on differential equations. We will also use a strategy based on the well known Gillespie algorithm but running on more than one compartment called Multi-compartmental Gillespie Algorithm.     

Genetic background of phenotypic variation

A noteworthy feature of the living world is its bewildering variability. A key issue in several biological disciplines is the achievement of an understanding of the hereditary basis of this variability. Two opposing, but not necessarily irreconcilable conceptions attempt to explain the underlying mechanism. The gene function paradigm postulates that phenotypic variance is generated by the polymorphism in the coding sequences of genes. However, comparisons of a great number of homologous gene and protein sequences have revealed that they predominantly remained functionally conserved even across distantly related phylogenic taxa. Alternatively, the gene regulation paradigm assumes that differences in the cis-regulatory region of genes do account for phenotype variation within species. An extension of this latter concept is that phenotypic variability is generated by the polymorphism in the overall gene expression profiles of gene networks. In other words, the activity of a particular gene is a system property determined both by the cis-regulatory sequences of the given genes and by the other genes of a gene network, whose expressions vary among individuals, too. Novel proponents of gene function paradigm claim that functional genetic variance within the coding sequences of regulatory genes is critical for the generation of morphological polymorphism. Note, however, that these developmental genes play direct regulatory roles in the control of gene expression.