概率设计与干涉理论

在确定了零件可靠度的基础上,就可以进行产品(系统)可靠度预测、可靠度分配、以及零件概率设计等工作。本文仅介绍零件的概率设计及其基础理论——干涉理论,重点介绍了正态强度与应力干涉下可靠度的计算。     

应力-强度相关性干涉下的随机安全系数与零件可靠性设计

为解决机械零件可靠度计算中的应力-强度相关性干涉问题,根据两者负相关结构,运用Copula函数的相关性理论,基于零件可靠性计算的相关性干涉模型,建立了应力-强度相关性干涉下的随机安全系数—可靠度计算模型,并给出机械零件的平均安全系数可靠度计算方法.以受拉零件为代表,借助于相关性干涉的联结方程,给出了应力-强度相关性干涉下静强度可靠性设计的通用型求解方法和步骤,通过算例,说明了该模型的有效性、准确性.     

不稳定变应力下零件的等效可靠度

在不稳定变应力下,由于影响零件可靠性的因素十分复杂,因此对不稳定变应力下零件可靠度的计算迄今尚无统一的定论方法。笔者将疲劳损伤累积法则、等效应力的概念和应力-强度干涉模型联系起来,导出了一种不稳定应力下零件等效可靠度的算法,可供工程设计应用。     

应力—强度干涉模型的可靠度计算方法的研究

静态应力－强度系统的可靠度仅与应力和强度的干涉有关,应力－强度干涉模型在概率法和可靠性预测中,有非常重要的作用。对应力－强度干涉模型的4种重要的可靠度计算方法进行了介绍、分析和比较,并对各自的特点、应用场合作了说明。     

用改进的蒙特卡洛法求应力-强度系统的可靠度界

静态应力-强度系统的可靠度仅与应力和强度的干涉有关。应用概率统计的基本原理,在对干涉区间上应力和强度进行一定分析的基础上,提出了采用改进的蒙特卡洛模拟计算法求出系统可靠度界的新方法。计算结果表明：该算法与传统的蒙特卡洛法相比较,具有更高的精度,且计算简单,是计算应力-强度系统可靠度的一种行之有效的方法。     

单向相关下的机械零件动态可靠性分析

对于载荷与强度存在相关性的情形,应用传统的应力-强度干涉模型具有一定的局限性。为评估零件在应力与强度单向相关下的动态可靠度,利用Gamma过程来描述随机载荷作用,基于经典的Miner累积损伤理论,推导随着载荷作用而产生的强度不断降低的强度退化模型。结合应力-强度干涉模型,进而建立零件的动态可靠度模型。最后通过算例验证模型的有效性,结果表明,该模型能够有效用于零件在单向相关下的动态可靠性评估。     

用高斯积分法计算机械零件的可靠度

采用高斯积分法求解应力－－强度干涉模型,给出了几种常用的应力与强度分布时的可靠度计算公式。     

基于模糊状态判据的应力——强度干涉理论

用模糊状态判据考虑零件状态的模糊性，提出了基于模糊状态判据的应力一强度干涉理论，给出了模糊随机可靠度的定义和计算公式。     

应力-强度干涉模型在系统失效概率分析中的应用及相关问题

研究一般串联、并联及K／N表决系统（不要求系统中各零件失效事件是相互独立的）的失效概率建模与失效概率预测。通过详细考察、深入分析应力-强度干涉理论、方法及其在零件失效概率和系统失效概率计算中的建模过程，介绍“系统级”的应力-强度干涉模型及其在系统失效概率分析中的应用，并给出应用实例及其与实验观测结果的比较。与传统的先计算零件失效概率，再在各零件失效相互独立的（不真实）假设条件下建立串联、并联、表决等系统失效概率模型的方法不同，文中提出应用“系统级”的应力-强度干涉分析直接建立系统失效概率模型的方法。为应用应力-强度干涉模型预测系统失效概率，首先详细分析传统的零件失效干涉分析过程中发生的系统可靠性信息损失问题。分析表明，零件失效概率的不确定性与载荷分散程度有关，在传统的应用应力-强度干涉模型计算零件失效概率过程中遗失的失效相关性信息对系统失效概率估算是十分重要的。在此基础上，指出无法通过传统的零件可靠度参数构建一般系统（具有失效相关性的非独立失效系统）可靠性模型的原因。最后，建立能根据系统低阶失效数据预测高阶失效概率的参数化模型。     

多种失效模式下的机械零件动态可靠性模型

考虑共因失效和随机载荷作用次数对可靠性的影响,建立了零件在多种失效模式下的动态可靠性模型。指出共因失效同样存在于零部件的失效中,运用应力-强度干涉模型和顺序统计量理论建立了多种失效模式下载荷多次作用时的零件可靠性模型以及零件动态可靠性模型。以齿轮的可靠度计算为例,研究了零件可靠度和失效率随时间的变化规律。研究表明,当零件强度不退化或退化不明显时,零件的可靠度随时间逐渐降低,失效率曲线具有浴盆曲线前两个阶段的特征。     

Concurrent optimization of structural topology and infill properties with a CBF-based level set method

In this paper, a parametric level-set-based topology optimization framework is proposed to concurrently optimize the structural topology at the macroscale and the effective infill properties at the micro/meso scale. The concurrent optimization is achieved by a computational framework combining a new parametric level set approach with mathematical programming. Within the proposed framework, both the structural boundary evolution and the effective infill property optimization can be driven by mathematical programming, which is more advantageous compared with the conventional partial differential equation-driven level set approach. Moreover, the proposed approach will be more efficient in handling nonlinear problems with multiple constraints. Instead of using radial basis functions (RBF), in this paper, we propose to construct a new type of cardinal basis functions (CBF) for the level set function parameterization. The proposed CBF parameterization ensures an explicit impose of the lower and upper bounds of the design variables. This overcomes the intrinsic disadvantage of the conventional RBF-based parametric level set method, where the lower and upper bounds of the design variables oftentimes have to be set by trial and error. A variational distance regularization method is utilized in this research to regularize the level set function to be a desired distanceregularized shape. With the distance information embedded in the level set model, the wrapping boundary layer and the interior infill region can be naturally defined. The isotropic infill achieved via the mesoscale topology optimization is conformally fit into the wrapping boundary layer using the shape-preserving conformal mapping method, which leads to a hierarchical physical structure with optimized overall topology and effective infill properties. The proposed method is expected to provide a timely solution to the increasing demand for multiscale and multifunctional structure design.

     

The ‘corpuscle’ stereological problem—re-evaluation using slab fragment volumes and application to the correction of DNA histograms from sections of spherical nuclei

A new category of stereological size distribution unfolding models is introduced. It is based on the use of the volumes of particle slab fragments, in addition to their profile dimensions. When spheres are cut by a slab of known (constant) thickness, an estimation of discrete sphere sizes from section data is then possible, as only one parent sphere solution exists for any slab fragment, given the latter's projection size and volume. The unfolding algorithm consists in sequentially testing a set of equations: only one of the solutions satisfies various constraints on bounds. A precise determination of the section thickness is required. Truncation parameters, instead of being troublesome inputs as in classical unfolding models, become valuable outputs. This model offers the first stereologically valid solution to the important problem of correcting DNA-amount histograms obtained from sectioned spherical nuclei. Under the (biologically reasonable) assumption that the nuclear volume is proportional to the DNA amount, it is possible to estimate the DNA concentration and, subsequently, compute discrete slab fragment volumes from corresponding DNA values. An application to Feulgen-stained rat liver sections is shown. Measurements of hepatocytic nuclear-profile areas and integrated optical densities are obtained by automated image analysis (IBAS), and the model is used to unfold the section-obtained DNA histogram. A maximum likelihood fitting of the final distribution with chi functions allows a parametric estimation of ploidy frequencies. This model can only be used for acceptably spherically shaped particles.     

Modelling the effects of machine breakdowns in the generalized cell formation problem

Machines are key elements in manufacturing systems and their breakdowns can dramatically affect system performance measures. This paper proposes a new multi-objective pure integer linear programming approach for the cell formation problem with alternative process routings and machine reliability consideration. The model minimizes total cost and maximizes system reliability simultaneously. Traditional reliability evaluation approaches attempt to model the reliability of the manufacturing system as a function of its elements. These approaches have some negative aspects; therefore, instead of modeling the system reliability as an explicit objective function, we use an approach to model the effects of the machine unreliability in terms of cost and time-based effects. Using the ?-constraint method as an optimization tool for multi-objective programming, a numerical example is solved to demonstrate the capability of the proposed model in evaluating various effects of the reliability consideration.     

基于马尔可夫链的混合动力汽车模型预测控制

采用模型预测控制的思路,选取加速踏板位置不变、指数衰减、按马尔可夫链随机分布三种不同的车辆未来转矩需求预测模型,运用动态规划算法进行转矩分配的优化,并与基于规则的混合动力控制策略进行对比。仿真结果表明,马尔可夫链模型预测控制在混合动力车辆能量分配上具有优化潜力。最后提出了模型预测控制应用于混合动力汽车能量分配的进一步研究方向。     

A new approach for the analysis solution of dynamic systems containing fractional derivative

Fractional derivative models, which are used to describe the viscoelastic behavior of material, have received considerable attention. Thus it is necessary to put forward the analysis solutions of dynamic systems containing a fractional derivative. Although previously reported such kind of fractional calculus-based constitutive models, it only handles the particularity of rational number in part, has great limitation by reason of only handling with particular rational number field. Simultaneously, the former study has great unreliability by reason of using the complementary error function which can’t ensure uniform real number. In this paper, a new approach is proposed for an analytical scheme for dynamic system of a spring-mass-damper system of single-degree of freedom under general forcing conditions, whose damping is described by a fractional derivative of the order 0< α< 1 which can be both irrational number and rational number. The new approach combines the fractional Green’s function and Laplace transform of fractional derivative. Analytical examples of dynamic system under general forcing conditions obtained by means of this approach verify the feasibility very well with much higher reliability and universality.     

基于连续密度变量的结构支撑布局优化设计

支撑布局的优化设计是决定结构设计质量与力学品质的关键因素 ,论文提出了用拓扑优化技术进行支撑布局优化设计的一种方法。为了实现结构动力学性能优化 ,采用拓扑优化方法中的虚拟密度技术 ,将支撑单元布局这一离散变量问题转化为连续变量优化问题。该方法以虚拟密度作为设计变量 ,基于单元刚度矩阵与设计变量的指数对应关系 ,建立了结构固有频率对设计变量的灵敏度计算格式 ,实现了动力学优化。论文给出了支撑布局拓扑优化的实例 ,这些问题对于检验论文中所使用的拓扑优化方法的可行性和结果的可信度有很大帮助 ,同样对于这种方法的推广应用也有很大指导意义。计算结果表明 ,拓扑优化方法不仅能够解决结构布局优化设计问题 ,而且在模型建立合理的情况下 ,也能够有效地对支撑布局进行动力学优化     

Closed-Form Modeling and Analysis of an XY Flexure-Based Nano-Manipulator

Flexure-based mechanisms are widely utilized in nano manipulations. The closed-form statics and dynamics modeling is difficult due to the complex topologies, the inevitable compliance of levers, the Hertzian contact interface, etc. This paper presents the closed-form modeling of an XY nano-manipulator consisting of statically indeterminate symmetric(SIS) structures using leaf and circular flexure hinges. Theoretical analysis reveals that the lever's compliance, the contact stiffness, and the load mass have significant influence on the static and dynamic performances of the system.Experiments are conducted to verify the effectiveness of the established models. If no piezoelectric actuator(PEA) is installed, the influence of the contact stiffness can be eliminated. Experimental results show that the estimation error on the output stiffness and first natural frequency can reach 2% and 1.7%, respectively. If PEAs are installed, the contact stiffness shows up in the models. As no effective method is currently available to measure or estimate the contact stiffness, it is impossible to precisely estimate the performance of the overall system. In this case, the established closed-form models can be utilized to calculate the bounds of the performance. The established closed-form models are widely applicable in the design and optimization of planar flexure-based mechanisms.     

Detailed Analysis of Oil Transport in the Piston Assembly of a Gasoline Engine

More realistic and useful models of piston ring lubrication can only be achieved if there is a better understanding of the complex mechanisms by which oil flows in this region of the engine. The volume of oil in the piston assembly and its residence time in this high-temperature environment are crucial in determining the quantity and quality of oil available to lubricate the piston rings. Typically models of piston ring pack lubrication focus upon the oil flowing through the piston ring/cylinder interface. However, a number of additional oil flow paths and interactions with gas blow-by have been observed in the piston assembly. This paper presents a model that includes a number of such mechanisms and evaluates their influence on the lubrication of a piston ring pack from a typical automotive gasoline engine. The results indicate that such additional mechanisms are needed to give improved predictions of oil transport they highlight the relative importance of several of these mechanisms and help guide future research.     

基于免疫算法的多变量控制系统PID参数优化方法研究

提出一种基于免疫算法的多变量控制系统PID参数优化方法。首先对免疫算法的步骤和实现过程进行了介绍;接着采用了一种新的、适合多变量系统特点的控制系统性能指标,即用阶跃响应曲线超出期望变化区域的面积的大小来衡量控制系统的优劣。该指标被用于构造免疫算法的适应度函数。论文最后将上述方法用于火电机组负荷控制系统优化,取得了良好的效果。     

Synthetical efficiency-based optimization for the power distribution of power-split hybrid electric vehicles

Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviates from the scheduled driving cycle, the effect of optimal results will be declined greatly. Therefore, the instantaneous optimization strategy carried out on-line is studied in this paper. The power split path and the transmission efficiency are analyzed based on a special power-split scheme and the efficiency models of the power transmitting components are established. The synthetical efficiency optimization model is established for enhancing the transmission efficiency and the fuel economy. The identification of the synthetical efficiency as the optimization objective and the constrain group are discussed emphatically. The optimization is calculated by the adaptive simulated annealing （ASA） algorithm and realized on-line by the radial basis function （RBF）-based similar models. The optimization for power distribution of the hybrid vehicle in an actual driving condition is carried out and the road test results are presented. The test results indicate that the synthetical efficiency optimization method can enhance the transmission efficiency and the fuel economy of the power-split hybrid electric vehicle （HEV） observably. Compared to the rules-based strategy the optimization strategy is optimal and achieves the approximate global optimization solution for the power distribution. The synthetical efficiency optimization solved by ASA algorithm can give attentions to both optimization quality and calculation efficiency, thus it has good application foreground for the power distribution of power-split HEV.