Review of methods to predict solder joint reliability under thermo-mechanical cycling

Solder joints are often the cause of failure in electronic devices, failing due to cyclic creep induced ductile fatigue. This paper will review the modelling methods available to predict the lifetime of SnPb and SnAgCu solder joints under thermo-mechanical cycling conditions such as power cycling, accelerated thermal cycling and isothermal testing, the methods do not apply to other damage mechanisms such as vibration or drop-testing. Analytical methods such as recommended by the IPC are covered, which are simple to use but limited in capability. Finite element modelling methods are reviewed, along with the necessary constitutive laws and fatigue laws for solder, these offer the most accurate predictions at the current time. Research on state-of-the-art damage mechanics methods is also presented, although these have not undergone enough experimental validation to be recommended at present

Effects of particle plasticity characteristics on local interface stress in particle reinforced composite during uniaxial tension

For elastoplastic particle reinforced metal matrix composites, failure may originate from interface debonding between the particles and the matrix, both elastoplastic and matrix fracture near the interface. To calculate the stress and strain distribution in these regions, a single reinforcing particle axisymmetric unit cell model is used in this article. The nodes at the interface of the particle and the matrix are tied. The development of interfacial decohesion is not modelled. Finite element modelling is used, to reveal the effects of particle strain hardening rate, yield stress and elastic modulus on the interfacial traction vector (or stress vector), interface deformation and the stress distribution within the unit cell, when the composite is under uniaxial tension. The results show that the stress distribution and the interface deformation are sensitive to the strain hardening rate and the yield stress of the particle. With increasing particle strain hardening rate and yield stress, the interfacial traction vector and internal stress distribution vary in larger ranges, the maximum interfacial traction vector and the maximum internal stress both increase, while the interface deformation decreases. In contrast, the particle elastic modulus has little effect on the interfacial traction vector, internal stress and interface deformation.

A virtual inspection framework for precision manufacturing of aerofoil components

The finite element method plays an extremely important role in forging process design as it provides a valid means to quantify forging errors and thereby govern die shape modification to improve the dimensional accuracy of the component. However, this dependency on process simulation could raise significant problems and present a major drawback if the finite element simulation results were inaccurate. This paper presents a novel approach to assess the dimensional accuracy and shape quality of aeroengine blades formed from finite element hot-forging simulation. The proposed virtual inspection system uses conventional algorithms adopted by modern coordinate measurement processes as well as the latest free-form surface evaluation techniques to provide a robust framework for virtual forging error assessment. Established techniques for the physical registration of real components have been adapted to localise virtual models in relation to a nominal Design Coordinate System. Blades are then automatically analysed using a series of intelligent routines to generate measurement data and compute dimensional errors. The results of a comparison study indicate that the virtual inspection results and actual coordinate measurement data are highly comparable, validating the approach as an effective and accurate means to quantify forging error in a virtual environment. Consequently, this provides adequate justification for the implementation of the virtual inspection system in the virtual process design, modelling and validation of forged aeroengine blades in industry.

Gender Classification via Lips: Static and Dynamic Features

Automatic gender classification has many security and commercial applications. Various modalities have been investigated for gender classification with face-based classification being the most popular. In some real-world scenarios the face may be partially occluded. In these circumstances a classification based on individual parts of the face known as local features must be adopted. We investigate gender classification using lip movements. We show for the first time that important gender specific information can be obtained from the way in which a person moves their lips during speech. Furthermore our study indicates that the lip dynamics during speech provide greater gender discriminative information than simply lip appearance. We also show that the lip dynamics and appearance contain complementary gender information such that a model which captures both traits gives the highest overall classification result. We use Discrete Cosine Transform based features and Gaussian Mixture Modelling to model lip appearance and dynamics and employ the XM2VTS database for our experiments. Our experiments show that a model which captures lip dynamics along with appearance can improve gender classification rates by between 16-21% compared to models of only lip appearance.

A pseudo-transient solution strategy for the analysis of delamination by means of interface elements

Recent efforts in the finite element modelling of delamination have concentrated on the development of cohesive interface elements. These are characterised by a bilinear constitutive law, where there is an initial high positive stiffness until a threshold stress level is reached, followed by a negative tangent stiffness representing softening (or damage evolution). Complete decohesion occurs when the amount of work done per unit area of crack surface is equal to a critical strain energy release rate. It is difficult to achieve a stable, oscillation-free solution beyond the onset of damage, using standard implicit quasi-static methods, unless a very refined mesh is used. In the present paper, a new solution strategy is proposed based on a pseudo-transient formulation and demonstrated through the modelling of a double cantilever beam undergoing Mode I delamination. A detailed analysis into the sensitivity of the user-defined parameters is also presented. Comparisons with other published solutions using a quasi-static formulation show that the pseudo-transient formulation gives improved accuracy and oscillation-free results with coarser meshes

An investigation of the changes in the natural frequency of a Pile affected by Scour

Scour around bridge foundations is one of the leading causes of bridge failure. Up until recently, the monitoring of this phenomenon was primarily based around using underwater instrumentation to monitor the progression of scour holes as they develop around foundation systems. Vibration-based damage detection techniques have been used to detect damage in bridge beams. The application of these vibration based methods to the detection of scour has come to the fore in research in recent years. This paper examines the effect that scour has on the frequency response of a driven pile foundation system, similar to those used to support road and rail bridges. The effect of scour on the vibration characteristics of the pile is examined using laboratory and field testing. It is clear that there is a very clear reduction in the natural frequency of the pile as the severity of scour increases. It is shown that by combining state-of-the-art geotechnical techniques with relatively simple finite element modelling approaches, it is possible to accurately predict the natural frequency of the pile for a given scour depth. Therefore, the paper proposes a method that would allow the estimation of scour depth for a given observed pile frequency.

Development of dynamic structural testing to current state-of-the-art hybrid testing

Even though computational power used for structural analysis is ever increasing, there is still a fundamental need for testing in structural engineering, either for validation of complex numerical models or to assess material behaviour. In addition to analysis of structures using scale models, many structural engineers are aware to some extent of cyclic and shake-table test methods, but less so of ‘hybrid testing’. The latter is a combination of physical testing (e.g. hydraulic
actuators) and computational modelling (e.g. finite element modelling). Over the past 40 years, hybrid testing of engineering structures has developed from concept through to maturity to become a reliable and accurate dynamic testing technique. The hybrid test method provides users with some additional benefits that standard dynamic testing methods do not, and the method is more cost-effective in comparison to shake-table testing. This article aims to provide the reader with a basic understanding of the hybrid test method, including its contextual development and potential as a dynamic testing technique.

K&C局部损伤混凝土材料模型在精细有限元模拟中的应用

This paper presents a study on concrete fracture and the associated mesh sensitivity using the finite element (FE) method with a local concrete model in both tension (Mode I) and compression.To enable the incorporation of dynamic loading, the FE model is developed using a transient dynamic analysis code LS-DYNA Explicit.A series of investigations have been conducted on typical fracture scenarios to evaluate the model performances and calibration of relevant parameters.The K&C damage model was adopted because it is a comprehensive local concrete model which allows the user to change the crack band width, fracture energy and rate dependency of the material.Compressive localisation modelling in numerical modelling is also discussed in detail in relation to localisation.An impact test specimen is modelled.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

Some concepts and models usefulninthe analysis of discrete life time data

This thesis entitled Reliability Modelling and Analysis in Discrete time Some Concepts and Models Useful in the Analysis of discrete life time data.The present study consists of five chapters. In Chapter II we take up the derivation of some general results useful in reliability modelling that involves two component mixtures. Expression for the failure rate, mean residual life and second moment of residual life of the mixture distributions in terms of the corresponding quantities in the component distributions are investigated. Some applications of these results are also pointed out. The role of the geometric,Waring and negative hypergeometric distributions as models of life lengths in the discrete time domain has been discussed already. While describing various reliability characteristics, it was found that they can be often considered as a class. The applicability of these models in single populations naturally extends to the case of populations composed of sub-populations making mixtures of these distributions worth investigating. Accordingly the general properties, various reliability characteristics and characterizations of these models are discussed in chapter III. Inference of parameters in mixture distribution is usually a difficult problem because the mass function of the mixture is a linear function of the component masses that makes manipulation of the likelihood equations, leastsquare function etc and the resulting computations.very difficult. We show that one of our characterizations help in inferring the parameters of the geometric mixture without involving computational hazards. As mentioned in the review of results in the previous sections, partial moments were not studied extensively in literature especially in the case of discrete distributions. Chapters IV and V deal with descending and ascending partial factorial moments. Apart from studying their properties, we prove characterizations of distributions by functional forms of partial moments and establish recurrence relations between successive moments for some well known families. It is further demonstrated that partial moments are equally efficient and convenient compared to many of the conventional tools to resolve practical problems in reliability modelling and analysis. The study concludes by indicating some new problems that surfaced during the course of the present investigation which could be the subject for a future work in this area.

Behavioral differences in violence: the case of intra-group differences of paramilitaries and guerrillas in Colombia

In most studies on civil wars, determinants of conflict have been hitherto explored assuming that actors involved were either unitary or stable. However, if this intra-group homogeneity assumption does not hold, empirical econometric estimates may be biased. We use Fixed Effects Finite Mixture Model (FE-FMM) approach to address this issue that provides a representation of heterogeneity when data originate from different latent classes and the affiliation is unknown. It allows to identify sub-populations within a population as well as the determinants of their behaviors. By combining various data sources for the period 2000-2005, we apply this methodology to the Colombian conflict. Our results highlight a behavioral heterogeneity in guerrilla’s armed groups and their distinct economic correlates. By contrast paramilitaries behave as a rather homogenous group.

Consistent Dirichlet Boundary Conditions for Numerical Solution of Moving Boundary Problems

We consider the imposition of Dirichlet boundary conditions in the finite element modelling of moving boundary problems in one and two dimensions for which the total mass is prescribed. A modification of the standard linear finite element test space allows the boundary conditions to be imposed strongly whilst simultaneously conserving a discrete mass. The validity of the technique is assessed for a specific moving mesh finite element method, although the approach is more general. Numerical comparisons are carried out for mass-conserving solutions of the porous medium equation with Dirichlet boundary conditions and for a moving boundary problem with a source term and time-varying mass.

Intelligent agents and distributed models for cooperative task support

Purpose – To describe some research done, as part of an EPSRC funded project, to assist engineers working together on collaborative tasks. Design/methodology/approach – Distributed finite state modelling and agent techniques are used successfully in a new hybrid self-organising decision making system applied to collaborative work support. For the particular application, analysis of the tasks involved has been performed and these tasks are modelled. The system then employs a novel generic agent model, where task and domain knowledge are isolated from the support system, which provides relevant information to the engineers. Findings – The method is applied in the despatch of transmission commands within the control room of The National Grid Company Plc (NGC) – tasks are completed significantly faster when the system is utilised. Research limitations/implications – The paper describes a generic approach and it would be interesting to investigate how well it works in other applications. Practical implications – Although only one application has been studied, the methodology could equally be applied to a general class of cooperative work environments. Originality/value – One key part of the work is the novel generic agent model that enables the task and domain knowledge, which are application specific, to be isolated from the support system, and hence allows the method to be applied in other domains.

Probability density estimation with tunable kernels using orthogonal forward regression

A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimation process determines a tunable kernel, namely, its center vector and diagonal covariance matrix, by minimizing a leave-one-out test criterion. The kernel mixing weights of the constructed sparse density estimate are finally updated using the multiplicative nonnegative quadratic programming algorithm to ensure the nonnegative and unity constraints, and this weight-updating process additionally has the desired ability to further reduce the model size. The proposed tunable-kernel model has advantages, in terms of model generalization capability and model sparsity, over the standard fixed-kernel model that restricts kernel centers to the training data points and employs a single common kernel variance for every kernel. On the other hand, it does not optimize all the model parameters together and thus avoids the problems of high-dimensional ill-conditioned nonlinear optimization associated with the conventional finite mixture model. Several examples are included to demonstrate the ability of the proposed novel tunable-kernel model to effectively construct a very compact density estimate accurately.

An agent based approach to distributed task modeling for co-operative task support

This paper describes the design and implementation of an agent based network for the support of collaborative switching tasks within the control room environment of the National Grid Company plc. This work includes aspects from several research disciplines, including operational analysis, human computer interaction, finite state modelling techniques, intelligent agents and computer supported co-operative work. Aspects of these procedures have been used in the analysis of collaborative tasks to produce distributed local models for all involved users. These models have been used as the basis for the production of local finite state automata. These automata have then been embedded within an agent network together with behavioural information extracted from the task and user analysis phase. The resulting support system is capable of task and communication management within the transmission despatch environment.