Efficient modelling and optimisation of hybrid multilayered plates subject to ballistic impact

Among the key challenges present in the modelling and optimisation of composite structures against impact is the computational expense involved in setting up accurate simulations of the impact event and then performing the iterations required to optimise the designs. It is of more interest to find good designs given the limitations of the resources and time available rather than the best possible design. In this paper, low cost but sufficiently accurate finite element (FE) models were generated in LS Dyna for several experimentally characterised materials by semi-automating the modelling process and using existing material models. These models were then used by an optimisation algorithm to generate new hybrid offspring, leading to minimum weight and/or cost designs from a selection of isotropic metals, polymers and orthotropic fibre-reinforced laminates that countered a specified impact threat. Experimental validation of the optimal designs thus identified was then successfully carried out using a single stage gas gun. With sufficient computational hardware, the techniques developed in this pilot study can further utilise fine meshes, equations of state and sophisticated material models, so that optimal hybrid systems can be identified from a wide range of materials, designs and threats.

On the application of genetic algorithms for optimising composites against impact loading

A genetic algorithm (GA) was adopted to optimise the response of a composite laminate subject to impact. Two different impact scenarios are presented: low-velocity impact of a slender laminated strip and high-velocity impact of a rectangular plate by a spherical impactor. In these cases, the GA's objective was to, respectively, minimise the peak deflection and minimise penetration by varying the ply angles.

The GA was coupled to a commercial finite-element (FE) package LS DYNA to perform the impact analyses. A comparison with a commercial optimisation package, LS OPT, was also made. The results showed that the GA was a robust, capable optimisation tool that produced near optimal designs, and performed well with respect to LS OPT for the more complex high-velocity impact scenario tested.

A progressive failure model for composite laminates subjected to low velocity impact damage

This paper presents a 3-D failure model for predicting the dynamic material response of composite laminates under impact loading. The formulation is based on the Continuum Damage Mechanics (CDM) approach and enables the control of the energy dissipation associated with each failure mode regardless of mesh refinement and fracture plane orientation. Internal thermodynamically irreversible damage variables were defined in order to quantify damage concentration associated with each possible failure mode and predict the gradual stiffness reduction during the impact damage process. The material model has been implemented into LS-DYNA explicit finite element code within solid elements and it has proven to be capable of reproducing experimental results with good accuracy in terms of static/dynamic responses, absorbed energy and extent of damage.

Delamination threshold load for dynamic impact on plates

A criterion is derived for delamination onset in transversely isotropic laminated plates under small mass, high velocity impact. The resulting delamination threshold load is about 21% higher than the corresponding quasi-static threshold load. A closed form approximation for the peak impact load is then used to predict the delamination threshold velocity. The theory is validated for a range of test cases by comparison with 3D finite element simulation using LS-DYNA and a newly developed interface element to model delamination onset and growth. The predicted delamination threshold loads and velocities are in very good agreement with the finite element simulations. Good agreement is also shown in a comparison with published experimental results. In contrast to quasi-static impacts, delamination growth occurs under a rapidly decreasing load. Inclusion of finite thickness effects and a proper description of the contact stiffness are found to be vital for accurate prediction of the delamination threshold velocity

Modelling Static and Dynamic FRP-Concrete Bond Behaviour Using a Local Concrete Damage Model

This paper presents a study on the bond behaviour of FRP-concrete bonded joints under static and dynamic loadings, by developing a meso-scale finite element model using the K&C concrete damage model in LS-DYNA. A significant number of single shear experiments under static pull-off loading were modelled with an extensive parametric study covering key factors in the K&C model, including the crack band width, the compressive fracture energy and the shear dilatation factor. It is demonstrated that the developed model can satisfactorily simulate the static debonding behaviour, in terms of mesh objectivity, the load-carrying capacity and the local bond-slip behaviour, provided that proper consideration is given to the selection of crack band width and shear dilatation factor. A preliminary study of the effect of the dynamic loading rate on the debonding behaviour was also conducted by considering a dynamic increase factor (DIF) for the concrete strength as a function of strain rate. It is shown that a higher loading rate leads to a higher load-carrying capacity, a longer effective bond length, and a larger damaged area of concrete in the single shear loading scenario.

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.

Assessment of the impact speed and angle conditions for the EN1317 barrier tests

Roadside safety barriers designs are tested with passenger cars in Europe using standard EN1317 in which the impact angle for normal, high and very high containment level tests is 20°. In comparison to EN1317, the US standard MASH has higher impact angles for cars and pickups (25°) and different vehicle masses. Studies in Europe (RISER) and the US have shown values for the 90th percentile impact angle of 30°–34°. Thus, the limited evidence available suggests that the 20° angle applied in EN 1317 may be too low.
The first goal of this paper is to use the US NCHRP database (Project NCHRP 17–22) to assess the distribution of impact angle and collision speed in recent ROR accidents. Second, based on the findings of the statistical analysis and on analysis of impact angles and speeds in the literature, an LS-DYNA finite element analysis was carried out to evaluate the normal containment level of concrete barriers in non-standard collisions. The FE model was validated against a crash test of a portable concrete barrier carried out at the UK Transport Research Laboratory (TRL).
The accident data analysis for run-off road accidents indicates that a substantial proportion of accidents have an impact angle in excess of 20°. The baseline LS-DYNA model showed good comparison with experimental acceleration severity index (ASI) data and the parametric analysis indicates a very significant influence of impact angle on ASI. Accordingly, a review of European run-off road accidents and the configuration of EN 1317 should be performed.

LS 4825: A blue supergiant on the far side of the galaxy

We present high-resolution spectroscopic observations of LS 4825, a V = 12 B-type star in the Galactic center direction. On the basis of its stellar and interstellar spectra, we infer that it is likely to be a young supergiant at a distance of 21 +/- 5 kpc, and hence lying on the far side of the 'Galaxy. Adopting this hypothesis, a differential abundance analysis shows LS 4825 to have a chemical composition that is consistent with local B-type supergiants. These observations therefore represent the first detailed investigation of a star on the far side of the Galactic center. We trace multiple interstellar components in Ca II K and Na I D spectra, with velocities -206 less than or equal to v(lst) less than or equal to +93 km s(-1). We consider the likely origin of this gas and find that some components appear to trace matter lying close to the Galactic center. We discuss the possible use of such sight lines in furthering our understanding both of the nature of gas around the Galactic center and of the abundance gradient of the Galaxy.

Adaptive Bacteria Colony Picking in Unstructured Environments Using Intensity Histogram and Unascertained LS-SVM Classifier

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

LS-ADT: Lightweight and Scalable Anomaly Detection for Cloud Datacentres

Cloud data centres are implemented as large-scale clusters with demanding requirements for service performance, availability and cost of operation. As a result of scale and complexity, data centres typically exhibit large numbers of system anomalies resulting from operator error, resource over/under provisioning, hardware or software failures and security issus anomalies are inherently difficult to identify and resolve promptly via human inspection. Therefore, it is vital in a cloud system to have automatic system monitoring that detects potential anomalies and identifies their source. In this paper we present a lightweight anomaly detection tool for Cloud data centres which combines extended log analysis and rigorous correlation of system metrics, implemented by an efficient correlation algorithm which does not require training or complex infrastructure set up. The LADT algorithm is based on the premise that there is a strong correlation between node level and VM level metrics in a cloud system. This correlation will drop significantly in the event of any performance anomaly at the node-level and a continuous drop in the correlation can indicate the presence of a true anomaly in the node. The log analysis of LADT assists in determining whether the correlation drop could be caused by naturally occurring cloud management activity such as VM migration, creation, suspension, termination or resizing. In this way, any potential anomaly alerts are reasoned about to prevent false positives that could be caused by the cloud operator’s activity. We demonstrate LADT with log analysis in a Cloud environment to show how the log analysis is combined with the correlation of systems metrics to achieve accurate anomaly detection.

Parametric scans of HB and LS-RPA regimes employing Petawatt laser

By contrast to the Target Normal Sheath acceleration (TNSA) mechanism [1], Radiation Pressure Acceleration (RPA) is currently attracting a substantial amount of experimental [2,3] and theoretical [4-6] attention worldwide due to its superior scaling in terms of ion energy and laser-ion conversion efficiency. Employing Vulcan Petawatt lasers of the Rutherford Appleton Laboratory, UK, both the Hole-boring (HB) and the Light-Sail (LS) regimes of the RPA have been extensively explored. When the target thickness is of the order of hole-boring velocity times the laser pulse duration, highly collimated plasma jets of near solid density are ejected from the foil, lasting up to ns after the laser interaction. By changing the linear polarisation of the laser to circular, improved homogeneity in the jet's spatial density profile is achieved which suggests more uniform and sustained radiation pressure drive on target ions. By decreasing the target areal density or increasing irradiance on the target, the LS regime of the RPA is accessed where relatively high flux (~ 1012 particles/MeV/Sr) of ions are accelerated to ~ 10 MeV/nucleon energies in a narrow energy bandwidth. The ion energy scaling obtained from the parametric scans agrees well with theoretical estimation based on RPA mechanism and the narrow bandwidth feature in the ion spectra is studied by 2D particle-in-simulations.