Modelling and predicting fatigue crack growth in structural adhesive joints

The present paper examines crack growth in a range of structural adhesive joints under cyclic-fatigue loadings. It is shown that cyclic-fatigue crack-growth in such materials can be modelled by a form of the Hartman and Schijve crack-growth equation which aims to give a unique and linear ‘master’ representation for the fatigue data points that have been experimentally obtained. This relationship is shown to capture the experimental data representing the effects of test conditions, such as the R-ratio (=σmin /σmax) present in the fatigue cycle and test temperature. It also captures the typical scatter often seen in such tests, especially at low values of the fatigue crack-growth rate. Furthermore, the methodology is shown to be applicable to, and to unify, the results from Mode I (opening tensile), Mode II (in-plane shear) and Mixed-Mode I/II fatigue tests. Finally, it is used to predict successfully the rate of fatigue crack-growth in two bonded-repair type joints where naturally-occurring disbonds have initiated and grown

Failure analysis and shock protection of external hard disk drive

Technology for processing and storage of data in portable external storage hard disks has increasingly improved over the years. Currently, terabytes of data can be stored in one portable external storage hard disk drive. Storing such amount of data on a single disk on itself is a risk. Several instances of data lost by big institutions and Multinational Corporation leading to several billions of Naira annually have been reported. As the technology for storing data is improving, there is an equal need to improve on data safety and reliability. It has been estimated that hardware structural failure contributes to over 40% of reported data loss annually worldwide.  This case study is aimed at failure analysis and shock protection of external hard disk drive. In order to achieve this aim, the hard disk components were assumed as a single block structure and mass-spring-damper system was used to analytically model its structural responses to free fall drop-impact shock and vibration. Secondly, the hard disk was also modeled as a beam element, which was again, subjected to impact of free fall from selected heights. The analytical results of these two mathematical models are comparable and within the limits. Then, Finite Element Analysis system was used to simulate the impact of stress on the structure of the hard disk before and after enclosing it in a padded casing. It was discovered that the padded casing absorbed shock and vibration from direct impact on the enclosed disk with a significant reduction of stress by 90%. Vibration and shock protection is recommended to be designed into all such delicate engineering components and systems to mitigate occurrence of failure. http://dx.doi.org/10.4314/njt.v35i4.2

Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation

In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables precise structural and functional measurements to be taken, e.g. from short-axis MR images of the left-ventricle. In this work we propose a recurrent fully-convolutional network (RFCN) that learns image representations from the full stack of 2D slices and has the ability to leverage inter-slice spatial dependences through internal memory units. RFCN combines anatomical detection and segmentation into a single architecture that is trained end-to-end thus significantly reducing computational time, simplifying the segmentation pipeline, and potentially enabling real-time applications. We report on an investigation of RFCN using two datasets, including the publicly available MICCAI 2009 Challenge dataset. Comparisons have been carried out between fully convolutional networks and deep restricted Boltzmann machines, including a recurrent version that leverages inter-slice spatial correlation. Our studies suggest that RFCN produces state-of-the-art results and can substantially improve the delineation of contours near the apex of the heart.Comment: MICCAI Workshop RAMBO 201

Fire Progression

Fires have grown up to 70% in recent years. Fire Progression is a Machine Learning research project wherein we are trying to predict the direction in which the fire might grow in future. We are using Machine Learning technique and features like surface temperature, air temperature, moisture, precipitation and other additional parameters to predict the progression

On the USAF ‘risk of failure’ approach and its applicability to composite repairs to metal airframes

The USAF report on the risk analysis of aging aircraft fleets notes that the operational life of individual airframes is seldom equal to the design life of the fleet and that the life of an aircraft fleet t ends to be determined more by its inherent operational capability and maintenance costs rather than by the number of flight hours specified at the design stage. As such this paper focuses on whether the USAF approach to risk assessment can be used for airf rames repaired with a composite patch/doubler. To this end the present paper describes a test program designed to study the effect of adhesively -bonded composite repairs to fatigue cracks that, prior to repair, have grown from small naturally -occurring mat erials discontinuities. This study reveals that crack growth in composite repairs conforms to the exponential growth equation used in the USAF approach to assessing the risk of failure. Furthermore, the exponent, ω, in the exponential growth law can be de termined from the crack growth history associated with the unrepaired specimens and the simple reduction in the stress due to the application of the composite patch/doubler, using the ‘cubic rule’ that was previously used to assess crack growth in the RAAF F/A -18 (Hornet) fleet

Bundling ecosystem services for detecting their interactions driven by large-scale vegetation restoration: enhanced services while depressed synergies

Ecosystem service (ES) bundles can facilitate comprehensive understanding of the spatial configurations and interactions of multiple ESs across large-scale landscapes. They are critical for informing policy and improving ecosystem management. The spatial dimension of ES bundles has been addressed in recent research but little work has considered the temporal changes of ES bundles. This paper uses a case study in the Loess Plateau, the core area of vegetation restoration in China, to explore changes in ES spatial distributions, bundle types and multiple ES interactions in a period of rapid vegetation restoration between 2000 and 2015. Measurable proxies, biophysical indicators and the InVEST model were used to quantify 10 ESs. We found that (1) most of the ESs were improved, especially provisioning services and carbon sequestration. (2) There is a steady tradeoff between provisioning services and most regulating services, while the impacts of vegetation restoration on agricultural production were small. (3) The synergies among ESs were weakened, implying the presence of subtle functional ES interdependencies. (4) Changes in the bundling patterns between 2000 and 2015 revealed heightened gaps among ESs due to the upsurge of carbon sequestration and deterioration of the baseflow regulation. This research provides a new perspective for understanding the interactions between multiple ESs with regional vegetation restoration activities. Ecological restoration programmes play an important role in enhancing ESs, but they may also lead to expanded gaps between ESs. Baseflow regulation could be included as a key indicator to support a comprehensive understanding of the impacts of restoration interventions. The ES bundle framework is able to capture changes over time of the ES interactions across a large-scale landscape and facilitates informed ES management

Grafting from versus Grafting to Approaches for the Functionalization of Graphene Nanoplatelets with Poly(methyl methacrylate)

Graphene nanoplatelets (GNP) were exfoliated using a nondestructive chemical reduction method and subsequently decorated with polymers using two different approaches: grafting from and grafting to. Poly(methyl methacrylate) (PMMA) with varying molecular weights was covalently attached to the GNP layers using both methods. The grafting ratios were higher (44.6% to 126.5%) for the grafting from approach compared to the grafting to approach (12.6% to 20.3%). The products were characterized using thermogravimetric analysis–mass spectrometry (TGA-MS), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), atomic force microscopy (AFM), and transmission electron microscopy (TEM). The grafting from products showed an increase in the grafting ratio and dispersibility in acetone with increasing monomer supply; on the other hand, due to steric effects, the grafting to products showed lower absolute grafting ratios and a decreasing trend with increasing polymer molecular weight. The excellent dispersibility of the grafting from functionalized graphene, 900 μg/mL in acetone, indicates an increased compatibility with the solvent and the potential to increase graphene reinforcement performance in nanocomposite applications

Grafting from versus grafting to approaches for the functionalisation of graphene nanoplatelets with poly(methyl methacrylate)

Graphene nanoplatelets (GNP) were exfoliated using a nondestructive chemical reduction method and subsequently decorated with polymers using two different approaches: grafting from and grafting to. Poly(methyl methacrylate) (PMMA) with varying molecular weights was covalently attached to the GNP layers using both methods. The grafting ratios were higher (44.6% to 126.5%) for the grafting from approach compared to the grafting to approach (12.6% to 20.3%). The products were characterized using thermogravimetric analysis–mass spectrometry (TGA-MS), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), atomic force microscopy (AFM), and transmission electron microscopy (TEM). The grafting from products showed an increase in the grafting ratio and dispersibility in acetone with increasing monomer supply; on the other hand, due to steric effects, the grafting to products showed lower absolute grafting ratios and a decreasing trend with increasing polymer molecular weight. The excellent dispersibility of the grafting from functionalized graphene, 900 μg/mL in acetone, indicates an increased compatibility with the solvent and the potential to increase graphene reinforcement performance in nanocomposite applications