Experimental characterisation of rate-dependent compression behaviour of fibre reinforced composites

Fibre reinforced polymers (FRP) materials are being increasingly used for aerospace and automotive structural applications. One of the critical loading conditions for such applications is impact, consequently, understanding of the composite behavior under such loads becomes critical for structural design. The analysis and design process for achieving impact-resistant composite structures requires rate-dependent constitutive models, which, in turn, requires material properties of the composite over a range of strain rates. It is, therefore, the objective of the research to investigate the strain rate-dependent behavior of fiber reinforced composites under compressive loads for a wide range of fiber orientations. Quasi-static (≈ 1e-3 s-1) and high loading (≈ 200 s-1) rates are considered for the experimental study. Accordingly, two different test setups are utilized, a screw-driven universal testing machine for quasi-static tests and a Split Hopkinson Pressure Bar (SHPB) system for dynamic tests. The stress-strain response of the composite is reported for the different fiber orientations and the strain rates, revealing the rate-dependent characteristics of the carbon fiber reinforced composite. From the test results, it is observed that, the dependency of the fracture strength on the loading rate is significant. The results are summarised in terms of the failure envelope in the transverse compression-in-plane shear σ22-σ12 plane for the two strain rates

A Wedge-DCB Test Methodology to Characterise High Rate Mode-I Interlaminar Fracture Properties of Fibre Composites

A combined numerical-experimental methodology is presented to measure dynamic Mode-I fracture properties of fiber reinforced composites. A modified wedge-DCB test using a Split-Hopkinson Bar technique along with cohesive zone modelling is utilised for this purpose. Three different comparison metrics, namely, strain-displacement response, crack propagation history and crack opening history are employed in order to extract unique values for the cohesive fracture properties of the delaminating interface. More importantly, the complexity of dealing with the frictional effects between the wedge and the DCB specimen is effectively circumvented by utilising right acquisition techniques combined with an inverse numerical modelling procedure. The proposed methodology is applied to extract the high rate interlaminar fracture properties of carbon fiber reinforced epoxy composites and it is further shown that a high level of confidence in the calibrated data can be established by adopting the proposed methodology

On the Rate-dependent Plasticity Modelling of Unidirectional Fibre-reinforced Polymeric Matrix Composites

Three different approaches to plasticity are investigated to model the experimentally-observed non-linear behaviour of unidirectional fibre-reinforced polymeric matrix materials. The first and simplest approach consists on assuming independent one-dimensional rate-dependent plasticity on in-plane (12) and through-thickness longitudinal (13) shear components of the Cauchy stress tensor. The second, employs a 3D extension of the plane stress Hill'48 anisotropic plastic surface. The third and the last is formulated as a quadratic yield function inspired by Puck's fracture initiation criterion. It searches for a plastic localisation plane in which a certain combination of normal and shear stresses is maximum. Numerical simulations are conducted to analyse the off-axis compression behaviour of carbon fibre reinforced epoxy composite under varying loading rates. The afore-mentioned three different approaches are explored with an aim to predict the experimentally-observed non-linear response of such composites. The model parameters are determined using a deterministic inverse modelling strategy employing an iterative domain reduction optimisation technique. As far as the experiments are concerned, the quasi-static and medium rate tests were carried out in universal testing machines, while the experiments at high rate were conducted in a Split Hopkinson Pressure Bar system. The effectiveness in terms of accuracy and robustness of the three approaches are discussed

Vigorous Module Based Data Management

Data is important in today’s life and it must be saved using less amount of memory. Data is important in day to day life for many purposes, like Government activities, any organization needs their own database, hospitals, schools etc. It is necessary to save data into database as per the user’s query generation with less memory conjunction. One of the novel techniques we have developed for saving data into database by using file similarity algorithm. This technique is used to split the text file into number of paragraphs and save these paragraphs using appropriate reference number. These reference numbers are stored in database, whenever same paragraph will appeared in another text file it will check database and then save the other references of that file which are new for that file. This technique requires less memory and data can be stored in appropriate manner

DL-Lite: Tractable Description Logics for Ontologies: A Survey

Description Logic, called DL-Lite, specially used to capture essential ontology languages, and keeping low difficulty of logic. Here logic means computing subsumption between concepts, and checking satisfiability of the whole knowledge base, as well as answer complex queries over the set of instances maintained in secondary storage. DL-Lite the usual DL logical tasks are polynomial in the amount of the TBox, and query answering is polynomial in the amount of the ABox (i.e., in data difficulty). To the best of knowledge, this is the first result of polynomial data difficulty for query answering over DL knowledge bases. A distinguished visage of logic is to allow for a partitions between TBox and ABox logic during query evaluation: the part of the process requiring TBox logic is self-determining of the ABox, and the some part of the process requiring access to the ABox which can be carried out by an SQL engine, thus taking benefit of the query optimization strategies provided by current DBMSs

Predictions of the mechanical properties of unidirectional fibre composites by supervised machine learning

We present an application of data analytics and supervised machine learning to allow accurate predictions of the macroscopic stiffness and yield strength of a unidirectional composite loaded in the transverse plane. Predictions are obtained from the analysis of an image of the material microstructure, as well as knowledge of the constitutive models for fibres and matrix, without performing physically-based calculations. The computational framework is based on evaluating the 2-point correlation function of the images of 1800 microstructures, followed by dimensionality reduction via principal component analysis. Finite element (FE) simulations are performed on 1800 corresponding statistical volume elements (SVEs) representing cylindrical fibres in a continuous matrix, loaded in the transverse plane. A supervised machine learning (ML) exercise is performed, employing a gradient-boosted tree regression model with 10-fold cross-validation strategy. The model obtained is able to accurately predict the homogenized properties of arbitrary microstructures

Determination of Ground Water Associated with Lignite Mining in Arid Climate,

Ground water and surface water create a range of problems in lignite mining utilizing surface mining methods. In order to create a safe and economic mining environment, it is essential to carry out mining after dewatering the rock mass surrounding the lignite mines by advance dewatering techniques. This paper briefly describes the ground water regimes including pressure gradients associated with various lignite deposits together with the practical examples of some important lignite deposits in the world. An effective method of controlling ground water in multi-aquifer environment in lignite deposits is to carry out rock mass dewatering using borehole pumps. This approach will help reducing the inflow rates of ground water to the mining excavation and also increase the effective strength of the overburden strata, thus, increasing the slope stability of the mining excavations. The main theme of this paper is to present a case history analysis of Thar lignite deposit in Sindh, Pakistan which has lignite reserves of some 193 billion tonnes. The paper presents a proposed method of dewatering the Thar prospect together with an assessment of the quality of aquifer water which can be used to improve the quality of life of people inhabiting in the Thar Desert area of Sindh, Pakistan. Water samples from three aquifers were collected from nine different locations and were analyzed in the laboratory for evaluating their physical and chemical characteristics. The test results indicated that the aquifer water can be classified as (sodium+ potassium) -chloride type water with a TDS range of 1000 to 20,000 mg/L. Consequently, this ground water is classified as brackish (saline water) requiring treatment before it can be utilised for domestic or industrial consumptions. It should be noted that this ground water does not contain heavy metals and toxic metals including arsenic, mercury and lead or cyanide. However, results indicate that groundwater from a few locations contained traces of silver (<4oppb) Owithozinc0<0.1ppm

The effect of 2 mMol glutamine supplementation on HSP70 and TNF-α release by LPS stimulated blood from healthy children.

OBJECTIVE: Glutamine has been shown to promote heat shock protein 70 (HSP70) release both within experimental in vitro models of sepsis (2-10 mM) and in adults post trauma (0.5 g/kg), although the efficacy varies and is dependent on the model used. The effect of glutamine supplementation on HSP70 release in children is less clear. Therefore, the aim of this study was to investigate the effect of 2 mM glutamine added to incubation media on HSP70 and inflammatory mediator release in an in vitro model of paediatric sepsis using whole blood from healthy paediatric volunteers. METHODS: An in vitro whole blood endotoxin stimulation model using 1 μg/ml lipopolysaccharide (LPS) over a 24 h time period was used to investigate the effects of 2 mM glutamine on HSP70 and inflammatory mediator release in healthy children. RESULTS: The addition of 2 mM glutamine to the incubation media significantly increased HSP70 release over time (p < 0.05). This was associated with an early pro-inflammatory effect on TNF-α release at 4 h (p < 0.005) which was not seen at 24 h. There was a non significant trend towards higher levels of IL-6 and IL-10 following the addition of 2 mM glutamine, which appears to differ from the response reported in adult and animal models. CONCLUSION: Glutamine supplementation of incubation media promotes HSP70 and early TNF- α release in an in vitro model using blood samples from healthy children.This is the author accepted manuscript. The final version is available via Elsevier at http://dx.doi.org/10.1016/j.clnu.2014.12.00

Emerging sensor-cloud technology for pervasive services and applications

This is an Editorial article for the Special Issue on "Emerging Sensor-Cloud Technology for Pervasive Services and Applications" of the International Journal of Distributed Sensor Networks