Finite element modelling of metallic tubular crash structures with an explicit code

Numerous experimental studies have been carried out to investigate the collapse of tubular metallic crash structures under axial compression. Some simple theoretical models have been developed but these often assume one type of progressive collapse, which is not always representative of the real situation. Finite Element (FE) models, when further refined, have the potential to predict the actual collapse mode and how it influences the load-displacement and energy absorption characteristics. This paper describes an FE modelling investigation with the explicit code LS−DYNA. An automatic mesh generation programme written by the authors is used to set up shell and solid element tube models. Mesh specification issues and features relating to the contact and friction models are discussed in detail. The crush modes, load-deflection characteristics and energy absorption values found in the simulations are compared with a reasonable degree of correlation to those observed in a physical testing programme; however, improvements are still required.

Three-dimensional Finite Element modelling of laser shock peening process

Laser shock peening (LSP) is an innovative surface treatment technique for metal alloys, with the great improvement of their fatigue, corrosion and wear resistance performance. Finite element method has been widely applied to simulate the LSP to provide the theoretically predictive assessment and optimally parametric design. In the current work, 3-D numerical modelling approaches, combining the explicit dynamic analysis, static equilibrium analysis algorithms and different plasticity models for the high strain rate exceeding 106s-1, are further developed. To verify the proposed methods, 3-D static and dynamic FEA of AA7075-T7351 rods subject to two-sided laser shock peening are performed using the FEA package–ABAQUS. The dynamic and residual stress fields, shock wave propagation and surface deformation of the treated metal from different material modelling approaches have a good agreement.

Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Analytical solutions and finite element modelling of deep drawing process for cylindrical metal cups

Analytical modelling of deep drawing process is of value in preliminary process design to illustrate the influence of major variables including friction and strain hardening on punch loads, cup dimensions and process limits. In this study, analytical models including theoretical solution and a series of finite element models are developed to account for the influences of process parameters including friction coefficient, tooling geometry and material properties on deep drawing of metal cups. The accuracy of both the theoretical and finite element solutions is satisfactory compared with those from experimental work.

Mechanical behaviour of functionally graded carbon nanofibre/phenolic nanocomposites: numerical modelling and experimental validation

In this study, a finite element-based model was developed to investigate the mechanical behaviour of functionally graded carbon nanofibre (CNF)/phenolic nanocomposites. Four functionally graded nanocomposites (FGNs), a non-graded nanocomposite (NGN), and a pure phenolic with the same geometry and total carbon nanofibre content were designed and fabricated. Flexural tests were conducted to validate the proposed finite element model. Close agreement was obtained between experimental results and numerical predictions. The results showed that flexural modulus can be improved about 45% by controlling the CNF content across the thickness of the samples.

Experimental studies and modelling of the deformation behaviour of multiple nanolayers

Microcompression tests were performed on monolithic Cu and Fe thin films and a Cu/Fe multilayer that had each individual layer of 200 nm thick, to understand the mechanical behaviour of multiple nanolayers. The micron-sized pillars were prepared by focused-ion beam (FIB) technique and compressed with a flat punch in a nanoindenter. The flow curves of the monolithic Cu and Fe thin films and Cu/Fe multilayer were extracted from the microcompression tests. The monolithic Cu thin film bulges in the top region of the pillar, while the Fe thin film cracks due to its columnar grain structure. For the Cu/Fe multilayer, the ductile Cu layers accommodate the majority of plastic deformation upon compression, while cracking in the Fe layers leads to the failure of the multilayer. Finite element models of microcompression tests were also developed to provide insights into the deformation behaviours of the multilayer and monolithic thin films. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-scale simulation using a hybrid mass-spring system and finite element model

Ply-scale finite element (FE) models are widely used to predict the performance of a composite structure based on material properties of individual plies. When simulating damage, these models neglect microscopic fracture processes which may have a significant effect on how a crack progresses within and between plies of a multidirectional laminate. To overcome this resolution limitation a multi-scale modelling technique is employed to simulate the effect micro-scale damage events have on the macro-scale response of a structure. The current paper discusses the development and validation of a hybrid mass-spring system and finite element modelling technique for multi-scale analysis. The model developed here is limited to elastic deformations; however, it is the first key step towards an efficient multi-scale damage model well suited to simulation of fracture in fibre reinforced composite materials. Various load cases have been simulated using the model developed here which show excellent accuracy compared to analytical and FE results. Future work is discussed, including extension of the model to incorporate damage modelling.

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Clustering of multivariate data is a commonly used technique in ecology, and many approaches to clustering are available. The results from a clustering algorithm are uncertain, but few clustering approaches explicitly acknowledge this uncertainty. One exception is Bayesian mixture modelling, which treats all results probabilistically, and allows comparison of multiple plausible classifications of the same data set. We used this method, implemented in the AutoClass program, to classify catchments (watersheds) in the Murray Darling Basin (MDB), Australia, based on their physiographic characteristics (e.g. slope, rainfall, lithology). The most likely classification found nine classes of catchments. Members of each class were aggregated geographically within the MDB. Rainfall and slope were the two most important variables that defined classes. The second-most likely classification was very similar to the first, but had one fewer class. Increasing the nominal uncertainty of continuous data resulted in a most likely classification with five classes, which were again aggregated geographically. Membership probabilities suggested that a small number of cases could be members of either of two classes. Such cases were located on the edges of groups of catchments that belonged to one class, with a group belonging to the second-most likely class adjacent. A comparison of the Bayesian approach to a distance-based deterministic method showed that the Bayesian mixture model produced solutions that were more spatially cohesive and intuitively appealing. The probabilistic presentation of results from the Bayesian classification allows richer interpretation, including decisions on how to treat cases that are intermediate between two or more classes, and whether to consider more than one classification. The explicit consideration and presentation of uncertainty makes this approach useful for ecological investigations, where both data and expectations are often highly uncertain.

Simulation of contact pressure in sheet metal trimming/blanking process

In the car body stamping process, trim/blank die cutting edges are subjected to very high tribological loads that result in loss of tool material from both the punch and die cutting edges. According to Archard’s wear model, normal contact force and sliding distance directly affects the wear. Therefore, knowledge of the acting forces on local contact areas has a pivotal role towards the prediction of tool wear. This paper presents a finite element modelling approach to determining the contact pressure distribution on the tool cutting edges during a trimming/blanking process. Characteristic areas on sheared edge profile, variation of punch force and high contact pressures affected areas have also been analysed.

Residual thermal stresses in a Fe3Al/Al2O3 gradient coating system

To combine the merits of both metals and ceramics into one material, many researchers have been studying the deposition of alumina coating using plasma spray on metal substrates. However, as the coatings are deposited at a high temperature, residual thermal stresses develop due to the mismatch of thermal expansion coefficients of the coating and substrate and these are responsible for the initiation and expansion of cracks, which induce the possible failure of the entire material. In this paper, the residual thermal-structural analysis of a Fe3Al/Al2O3 gradient coating on carbon steel substrate is performed using finite element modelling to simulate the plasma spray. The residual thermal stress fields are obtained and analyzed on the basis of temperature fields in gradient coatings during fabrication. The distribution of residual thermal stresses including radial, axial and shear stresses shows stress concentration at the interface between the coatings and substrate. The mismatch between steel substrate and composite coating is still the dominant factor for the residual stresses

Analysis of springback variation in sheet metal forming

This thesis investigated how the variation in inputs, such as material and processing conditions affected the shape defect phenomenon (springback) for sheet metal forming processes. Using a stochastic Finite Element modelling tool, it was found that the material type and fluctuations in material properties significantly influenced the variation in springback.

Sheared edge quality in the trimming of sheet metals

Examines the sheared edge quality of different automotive sheet metals resulting from the trimming process using experimental tooling and finite element modelling. The significant differences in burr, sliver and edge profile formation have been explained in terms of the strain distribution and tensile properties of the materials.

Effect of pore size on mechanical properties of titanium foams

In the study, both experimental work and numerical modeling are performed to investigate the pore size effects on the mechanical properties and deformation behaviours of titanium foams. Cylindrical titanium foam samples with different pore sizes are fabricated through powder metallurgy. Scanning electron microscope (SEM) is used to determine the pore size, pore distribution and the ratios of the length to width of pores. Compressive tests are carried out to determine the mechanical properties of the titanium foams with different pore sizes. Finally, finite element modeling is attempted to simulate the deformation behaviour and the mechanical properties of the titanium foams. Results indicate that titanium foams with different pore sizes have different geometrical characteristics, which lead to different deformation behaviours of cell walls during compression, resulting in different mechanical properties of titanium foams.