新疆公路三级区划中环境参数的提出

自然环境条件对公路工程的影响，主要体现在路线选取、路基强度和稳定性、路面稳定性和耐久性、公路主要自然病害(包括冻融、翻浆、雪害、风沙害、崩塌、滑坡和地震灾害等)、施工条件和养护运营环境等5个方面，分析自然条件和公路工程的关系，提出公路区划中地质地貌环境参数和水热状况环境参数。阐述了环境参数的提出过程，为新疆公路自然区划三级区的划分提供依据。     

基于48000载重吨教学实习船的动力学结构优化

本文以48000载重吨教学实习船为研究对象,采用通用有限元软件MSC.Patran/Nastran进行全船频响分析.全船有限元计算条件要求极高,而一般情况下又存在各种资料的限制或实验数据的缺失,因而会使得计算精度较低.本文介绍利用基本的设计资料的条件下,从模态参与系数角度结合模态振型提出一种新的动力学结构优化思路,并进行计算分析以验证该方法的可行性与准确性,为全船有限元振动分析提供新的研究思路.     

振冲法加固砂土地基工艺选择及施工参数控制

根据砂土的黏粒含量,振冲法可采用不加填料的振冲密实法或有填料的振冲置换法,选择合适的振冲施工工艺和确定合理的工艺参数,与地基加固效果和地基处理的工程投资密切相关。在振冲器的振动荷载作用下,由于饱和砂土的液化产生振密作用,根据孔隙水压力的增长模型,推导了饱和砂土的临界液化时间,并分析留振时间的影响因素。结合两个工程实例,探讨了振冲密实法和振冲置换法两种工艺的适应性及加固效果。根据砂土的类型和黏粒含量,将砂土地基分为3类,不同的砂土地基采用合适的振冲工艺,并得出施工参数的合理区间。     

基于基准有限元模型的箱梁TMD振动控制研究

针对高架桥梁结构引起的振动噪声问题,研究TMD控制箱梁结构振动的特性。为了获得精准的箱梁有限元模型,首先以铁路32 m简支箱梁桥为原型,按10:1的几何相似比设计制作简支箱梁缩尺试验模型,应用ANSYS软件建立初始动力有限元模型;对有限元模型模态分析与试验模型模态测试得到的自由模态信息进行误差分析,并采用基于灵敏度分析的模型修正技术对初始动力有限元模型弹性模量和密度进行修正,得到基准有限元模型,误差确认结果显示修正后的有限元模型更精准地反应箱梁的振动特性;进一步利用基准有限元模型,开展TMD控制简支箱梁桥振动的研究,研究结果表明TMD对于抑制桥梁竖向共振有很好的效果。     

燃机动力学建模中复杂结构处理方法研究

提出了三种以动力学相似为基础的转子动力学建模关键技术,并以某型燃气轮机建模为例,对该关键技术进行了验证。利用三种方法,对该燃气轮机的动力学特性进行研究,并与整机试验结果进行了对比。结果表明,动力学分析的准确程度主要由模型决定,本文所提出的三种建模关键技术能够反映结构的真实特性,可用于具有类似结构的双转子系统。     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

基于三点模型的柴油机热工参数预测

准确预测热工参数劣化趋势是对柴油机实施预测维修的前提。已有预测技术均视不同时段信息所具有的建模价值相等,忽略了近期信息比远期信息更能反映设备当前运行态势这一客观事实,导致预测模型难以准确描述柴油机热工参数的真实变化规律。针对该问题,提出一种基于三点模型的柴油机热工参数预测方法,并采用新陈代谢法同步更新建模数据,以提高建模数据的利用效率及预测精度。与灰色系统GM(1,1)模型预测精度的对比结果表明,三点模型能够有效处理不同时段信息在反映设备运行态势能力上的差异,得到更为准确的预测结果。     

基于粗糙-模糊软计算的船板线加热成形加工参数预报方法

提出一种基于粗糙-模糊软计算的建模方法,构造一种基于贴近方向修正的高精度模糊推理算法,通过有限元分析(FEA)建立板材线加热成形工艺信息系统,根据粗糙集软计算获取线加热成形的工艺规律,运用模糊推理实现加工参数的快速准确预报。粗糙-模糊建模适用于线加热成形过程的静态或动态模型的构建,为实现该工艺的智能建模与控制提供一种新的技术手段。     

基于响应面和遗传算法的柴油机瞬态过程喷油参数优化

基于台架试验数据,利用响应面法建立了某工程机械用柴油机瞬态过程喷油参数与性能的近似高精度模型,基于此模型采用遗传算法对瞬态过程喷油参数分别进行离线优化研究。结果表明:采用单目标优化确定的燃油消耗率(BSFC)、NO_x比排放量和颗粒质量(PM)比排放量的优化极限分别可达180.23g/(kW·h),8.92g/(kW·h)和0.011 8g/(kW·h),相对原机可降低多达4.5%,34.0%和37.3%。双目标优化的Pareto解集表明,相比于同时优化BSFC和NO_x比排放量,BSFC和PM比排放量更容易同时得到优化。采用权重因子适应度函数的三目标优化结果对应的BSFC,NO_x比排放量及PM比排放量分别为184.70g/(kW·h),12.62g/(kW·h)和0.012 2g/(kW·h),较原机分别降低2.1%,6.6%和35.3%。改进优化模型后,性能优化Pareto解集对应的BSFC和PM比排放量水平都非常接近其优化极限,但NO_x比排放量相对其优化极限仍然较高。     

Power network parameter estimation method based on data mining technology

The parameter values which actually change with the circumstances, weather and load level etc.produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition (SCADA) database as several types. The data processing technology was impliedto treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.