Nonlinear modal analysis via non‐parametric machine learning tools

Modal analysis is an important tool in the structural dynamics community; it is widely utilised to understand and investigate the dynamical characteristics of linear structures. Many methods have been proposed in recent years regarding the extension to nonlinear analysis, such as nonlinear normal modes or the method of normal forms, with the main objective being to formulate a mathematical model of a nonlinear dynamical structure based on observations of input/output data from the dynamical system. In fact, for the majority of structures where the effect of nonlinearity becomes significant, nonlinear modal analysis is a necessity. The objective of the current paper is to demonstrate a machine learning approach to output‐only nonlinear modal decomposition using kernel independent component analysis and locally linear‐embedding analysis. The key element is to demonstrate a pattern recognition approach which exploits the idea of independence of principal components from the linear theory by learning the nonlinear manifold between the variables. In this work, the importance of output‐only modal analysis via “blind source” separation tools is highlighted as the excitation input/force is not needed and the method can be implemented directly via experimental data signals without worrying about the presence or not of specific nonlinearities in the structure.     

枪管结构对固有频率的影响

为了研究枪管结构对枪管固有频率的影响,针对枪管尤其是狙击枪管设计中约束长度、枪管外形、膛口装置以及膛线等不同结构,建立了相应的三维模型。采用以六面体为主的网格对枪管进行了网格划分,采用有限元方法对枪管进行了模态分析。计算获得了不同结构枪管的固有频率; 通过比较,得到了不同枪管结构对固有频率的影响。分析结果表明:枪管尾部螺纹长度越长,枪口振动幅度越低; 相同质量枪管,锥形外形枪管刚度最好; 加装膛口装置对枪管刚度和振动特性有不利影响。     

灾害孤岛潜势风险分群与降雨警戒值探讨

台湾本身地貌特性以及近年来强降雨事件发生频繁,促使山区地带发生复合式灾害,如崩塌、泥石流与山洪等,因此灾害孤岛效应有必要仿效泥石流以及洪水灾害,制定出参考警戒值以及警戒线,将有助于防灾决策、救难资源投入以及灾害风险判释。本文针对台湾发生过灾害孤岛效应的114个村进行分析,且着重于首次发生灾害的台风降雨事件。首先通过群集分析并依照各样本的6个灾因指标进行分类,群集结果显示可分为8个群,并再以象限分布描述各群的潜势相对风险。采用2004—2015年台风降雨事件的观测雨量数据,并利用距离反比权重法,得出各村的累积降雨量(R)与最大时雨量(I)。整合各群集样本雨量数据后,使用台湾水土保持局使用的RTI模式概念,计算出各群集之RTImin、RTI30、RTI50和RTI70,以绘制低风险区(0～30%)、中风险区(30～70%)和高风险区(70%～100%),其中着重探讨灾害孤岛事件的下限值RTImin,以便可得知最易发生灾害的群集。结果显示,各群的潜势风险反映RTImin的效果良好,如潜势风险越高则其RTImin值越低,即雨量驱动灾害发生的条件较低。群集中,第1与2群为低风险群、第3、5与6群为中风险群、第4、7与8群为高风险群,仅第5群无法透过RTImin验证潜势风险关系,故本文挑选的6项灾因指标,为辨别灾害孤岛效应潜势等级的重要因子。     

Simplification and applicability studies of a hydrogen-air detailed reaction mechanism

The research of hydrogen fuel internal combustion engine (HICE) had great significance facing the challenges of energy and environmental problems. Based on the detailed hydrogen-air reaction mechanism, the pre-mix model of CHEMKIN-Pro software was selected to simplify the detailed mechanism GRI-3.0. The most important elements and reactions was chose to construct framework mechanism firstly based on the sensitivity coefficient for H₂O and NO formation, and additional elements and reactions were added to framework mechanism for complementing the oxidation path of N2 and H₂. A simplified mechanism including 24-step elementary reaction was obtained and the laminar burning velocity calculated by this simplified mechanism matches well with the detailed mechanism in a wide range. This simplified mechanism was also applied in a CFD model which predicted the cylinder instantaneous pressure and NOx emission accurately within a large range of fuel air equivalent ratio. Showing that this mechanism has good applicability.     

Visually deficient working conditions and reduced work performance in office workers: Is it mediated by visual discomfort?

IntroductionThe main purpose of this cross-sectional study was to investigate whether visual discomfort acts as a mediating factor between perceived visual ergonomic working conditions and self-rated visual performance among office workers who carry out administrative tasks and computer-based work at the Swedish Tax Agency.MethodsA questionnaire was sent to 94 office workers addressing: 1) perceived visual quality of the visual display units; 2) prevalence of eye symptoms; and 3) self-rated visual performance. Eighty-six persons (54 women (63%), 31 men (36%), and 1 of unspecified sex) answered the questionnaire. Multiple regression analysis investigated the association between visual ergonomic working conditions and visual performance, both with and without visual discomfort as a mediator.ResultsThe group mean of the Indexed survey questions indicated a reasonably good quality of visual ergonomic working conditions, a relative absence of eye symptoms, and acceptable self-rated visual performance. Results from multiple regression analysis showed a significant association between perceived visual ergonomic working conditions and self-rated visual performance (r² = 0.30, β = 0.327, p < 0.01). When visual discomfort was used as a mediator, the association between perceived visual ergonomic working conditions and self-rated visual performance remained the same (r² = 0.32, β = 0.315, p < 0.01).DiscussionIt was remarkable to discover that self-rated visual performance was independent of visual discomfort. Possible explanations include exposure factors not included in the current study, such as dry air and sensory irritation in the eyes, psychosocial stress, time spent performing near work activities, or time exposed to visually deficient working conditions.Relevance to industryThe strong connection between satisfaction with visual ergonomic working conditions and productivity in this study has implications for workplace profitability and staff satisfaction. If productivity is enhanced by better visual ergonomic working conditions, then managers of workplaces may be able to improve work outcomes by optimizing the physical work environment.     

Quasi-static compressive behaviour of aluminium cenosphere syntactic foams

In this paper, cenosphere particles embedded in AA2014 aluminium matrix are used to fabricate syntactic foam by stir casting method. The particle size is about 100?µm and foam density is about 1990?kg?m^?3. Compression tests at strain rate 0.001/s are performed on foam samples to characterise their mechanical properties which are then used in numerical analysis on commercial finite element analysis software ABAQUS/CAE with isotropic elastic-plastic material model. Experimental and numerical results show good conformity in deformation behaviour with elastic and plateau zones showing average deviations less than 5% and 20%, respectively. Foams showed high yield stress and energy absorption capabilities that can be useful in making blast and impact resistant structures.     

Numerical analysis of history-dependent hemivariational inequalities and applications to viscoelastic contact problems with normal penetration

In this paper numerical approximation of history-dependent hemivariational inequalities with constraint is considered, and corresponding Céa’s type inequality is derived for error estimate. For a viscoelastic contact problem with normal penetration, an optimal order error estimate is obtained for the linear element method. A numerical experiment for the contact problem is reported which provides numerical evidence of the convergence order predicted by the theoretical analysis.     

Vibration analysis and identification of breathing cracks in beams subjected to single or multiple moving mass using online sequential extreme learning machine

In this paper, a novel approach was presented to vibration analysis and identification of breathing cracks in Timoshenko beam under single or multiple moving mass. Dynamic strain energies (DSEs) and translational accelerations in beam structures under moving mass were used as forward problem and application of an emergent learning algorithm called the online sequential extreme learning machine algorithm as inverse problem to predict crack depths and locations. To demonstrate the potential of the proposed vibration analysis over existing ones, two validation studies have been done. To evaluate the proposed method to identify breathing cracks, two examples, namely, clamped–clamped beam and two span continuous beams have been studied. Also, the effect of the discrepancy in stiffness between the finite-element model and the actual tested dynamic system has been investigated. Another examination has been performed in which moving mass with different speeds are utilized. Also, the effect of multi mass passing through the beam has been studied. The obtained results indicated that the proposed method could identify the breathing cracks existence and severity in the beam under moving mass using DSE and accelerations, which may be noisy or noise free.     

Prediction of cooling efficiency of forced-air precooling systems based on optimized differential evolution and improved BP neural network

This paper proposes an approach to predict the efficiency of forced-air cooling of fresh apples that combines the optimized differential evolution (DE) algorithm and the back-propagation (BP) neural network algorithm. First, to balance population diversity and fast convergence, the individual mutation operation of the basic DE algorithm was optimized by dividing the entire population into two equal parts according to the fitness value of individuals, and DE-best-1 and DE-current-to-rand-1 are used as individual mutation operations for the superior- and inferior-part individuals, respectively. Moreover, the selection operation of basic DE was also changed by using a crowding scheme, which helps maintain population diversity and discover more regions containing the global optima. Second, an optimized DE-BP neural network model was established by using the optimized DE to determine the initial weights and thresholds of the BP neural network to avoid being trapped in local minima, following which the effect of input parameters on the network output was subjected to a comprehensive sensitivity analysis based on the trained neural network. The results show that the optimized DE-BP model accurately predicts the efficiency with which apples are cooled. Furthermore, the airflow velocity and total opening area have a significant negative correlation with the average apple temperature and a positive correlation with the cooling rate of the apples. Finally, the most important factor influencing the cooling efficiency of the pre-cooling system is the total opening area of the ventilated packaging.     

基于动态距离的模糊社区识别算法

社区识别技术是公共安全领域潜在危害行为预警预测和已发生危害行为追踪溯源的基础，针对传统社区识别算法将社区视作单一集合而无法描述社区主次成员的问题，提出一种基于动态距离的模糊社区识别算法。该算法将传统的单一社区结构划分为核心区域和边际区域，以边际区域来描述社区的模糊区间。该算法首先将网络设想为动态演变模型，网络中的任意节点均会与其他节点产生互动，互动将改变各节点间距离，距离也反过来影响互动。在阈值的界定下，受到多个社区吸引的节点被划分到边际区域，最终距离分布趋于稳定，各个社区结构得以显现。通过对比实验验证了CDFDD算法在社区识别上的有效性。