394 research outputs found

    Performance evaluation analysis of Ti-6Al-4V foam fan blades in aircraft engines: a numerical study

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    In the aerospace industry, the structures are subjected to significant loads and extreme conditions whilst being required to be lightweight and resilient. Metallic foams seem to meet these criteria. However, their usage in the aerospace applications are not as common as one would expect. To explore a potential application of foams, this study evaluates the performance of the foams of Ti-6Al-4V, a conventional material/alloy for aircraft engine fan blade applications performing numerical simulations. First, the mechanical properties of the Ti-6Al-4V alloy are calculated using the Mori–Tanaka mean-field homogenisation and finite element (FE) methods employing representative volume elements (RVE). Using those calculated material properties and the computer-aided design (CAD) model of a representative aircraft engine fan blade, the FE models are built. In these numerical models, the material properties and the rotational speed with the static aero-loads are selected as variables, whilst boundary conditions remain consistent to ensure a systematic investigation. Stress analysis and the prestressed modal analyses of the blades are performed, and the results are presented to discuss the impact of the void volume fraction of the alloy foams. This study reveals the complex nature of the mechanics of fan blades when made of foams

    Predicting Exploitation of Disclosed Software Vulnerabilities Using Open-source Data

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    Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that software vendors quickly provide patches once vulnerabilities are known and users quickly install those patches as soon as they are available. However, most vulnerabilities are never actually exploited. Since writing, testing, and installing software patches can involve considerable resources, it would be desirable to prioritize the remediation of vulnerabilities that are likely to be exploited. Several published research studies have reported moderate success in applying machine learning techniques to the task of predicting whether a vulnerability will be exploited. These approaches typically use features derived from vulnerability databases (such as the summary text describing the vulnerability) or social media posts that mention the vulnerability by name. However, these prior studies share multiple methodological shortcomings that inflate predictive power of these approaches. We replicate key portions of the prior work, compare their approaches, and show how selection of training and test data critically affect the estimated performance of predictive models. The results of this study point to important methodological considerations that should be taken into account so that results reflect real-world utility

    Modelling the effects of nanomaterial addition on the permeability of the compacted clay soil using machine learning based flow resistance analysis

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    Impermeable base layers that are made of materials with low permeability, such as clay soil, are necessary to prevent leachate in landfills from harming the environment. However, over time, the permeability of the clay soil changes. Therefore, to reduce and minimize the risk, the permeability-related characteristics of the base layers must be improved. Thus, this study aims to serve this purpose by experimentally investigating the effects of nanomaterial addition (aluminum oxide, iron oxide) into kaolin samples. The obtained samples are prepared by applying standard compaction, and the permeability of the soil sample is experimentally investigated by passing leachate from the reactors, in which these samples are placed. Therefore, Flow Resistance (FR) analysis is conducted and the obtained results show that the Al additives are more successful than the Fe additive in reducing leachate permeability. Besides, the concentration values of some polluting parameters (Chemical Oxygen Demand (COD), Total Kjeldahl Nitrogen (TKN), and Total Phosphorus (TP)) at the inlet and outlet of the reactors are analyzed. Three different models (Artificial Neural Networks (ANN), Multiple Linear Regression (MLR), Support Vector Machine (SVM)) are applied to the data obtained from the experimental study. The results have shown that polluting parameters produce high FR regression similarity rates (>75%), TKN, TP, and COD features are highly correlated with the FR value (>60%) and the most successful method is found to be the SVM model

    Low strain rate mechanical performance of balsa wood and carbon fibre-epoxy-balsa sandwich structures

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    The focus of this study is the experimental assessment of the mechanical behaviour of balsa wood and its sandwich structures, where balsa serves as the core, supported by carbon fibre-epoxy skin layers. A comprehensive characterisation is conducted on the mechanical behaviour of balsa wood and carbon fibre-epoxy balsa core sandwich structures subjected to a range of low strain rates. Initially, the study undertakes a consistent procedure for sample preparation. Subsequently, the characterisation of the manufactured composite structures is performed experimentally. A stereo microscope is employed for a detailed visual inspection of the internal structure of the balsa wood and the sandwich structures. Furthermore, the mechanical characterisation is carried out with three-point bending tests at a range of strain rates from 0.1 % to 6 % strain per minute. This research reveals key findings about balsa wood and its sandwich structures, highlighting their performance and their sensitivity even under low strain rates

    Characterisation and mechanical modelling of polyacrylonitrile-based nanocomposite membranes reinforced with silica nanoparticles

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    In this study, neat polyacrylonitrile (PAN) and fumed silica (FS)-doped PAN membranes (0.1, 0.5 and 1 wt% doped PAN/FS) are prepared using the phase inversion method and are characterised extensively. According to the Fourier Transform Infrared (FTIR) spectroscopy analysis, the addition of FS to the neat PAN membrane and the added amount changed the stresses in the membrane structure. The Scanning Electron Microscope (SEM) results show that the addition of FS increased the porosity of the membrane. The water content of all fabricated membranes varied between 50% and 88.8%, their porosity ranged between 62.1% and 90%, and the average pore size ranged between 20.1 and 21.8 nm. While the neat PAN membrane’s pure water flux is 299.8 L/m2 h, it increased by 26% with the addition of 0.5 wt% FS. Furthermore, thermal gravimetric analysis (TGA) and differential thermal analysis (DTA) techniques are used to investigate the membranes’ thermal properties. Finally, the mechanical characterisation of manufactured membranes is performed experimentally with tensile testing under dry and wet conditions. To be able to provide further explanation to the explored mechanics of the membranes, numerical methods, namely the finite element method and Mori–Tanaka mean-field homogenisation are performed. The mechanical characterisation results show that FS reinforcement increases the membrane rigidity and wet membranes exhibit more compliant behaviour compared to dry membranes

    Gender Differences in Academic Efficacy across STEM Fields

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    Cultural processes can reduce self-selection into math and science fields, but it remains unclear how confidence in computer science develops, where women are currently the least represented in STEM (science, technology, engineering, and mathematics). Few studies evaluate both computer skills and self-assessments of skill. In this paper, we evaluate gender differences in efficacy across three STEM fields using a data set of middle schoolers, a particularly consequential period for academic pathways. Even though girls and boys do not significantly differ in terms of math grades and have similar levels of computer skill, the gender gap in computer efficacy is twice as large as the gap for math. We offer support for disaggregation of STEM fields, so the unique meaning making around computing can be addressed

    Halloysite nanotube-enhanced polyacrylonitrile ultrafiltration membranes: fabrication, characterization, and performance evaluation

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    This research focuses on the production and characterization of pristine polyacrylonitrile (PAN) as well as halloysite nanotube (HNT)-doped PAN ultrafiltration (UF) membranes via the phase inversion technique. Membranes containing 0.1, 0.5, and 1% wt HNT in 16% wt PAN are fabricated, and their chemical compositions are examined using Fourier transform infrared (FTIR) spectroscopy. Scanning electron microscopy (SEM) is utilized to characterize the membranes’ surface and cross-sectional morphologies. Atomic force microscopy (AFM) is employed to assess the roughness of the PAN/HNT membrane. Thermal characterization is conducted using thermal gravimetric analysis (TGA) and differential thermal analysis (DTA), while contact angle and water content measurements reveal the hydrophilic/hydrophobic properties. The pure water flux (PWF) performance of the porous UF water filtration membranes is evaluated at 3 bar, with porosity and mean pore size calculations. The iron (Fe), manganese (Mn), and total organic carbon (TOC) removal efficiencies of PAN/HNT membranes from dam water are examined, and the surfaces of fouled membranes are investigated by using SEM post-treatment. Mechanical characterization encompasses tensile testing, the Mori–Tanaka homogenization approach, and finite element analysis. The findings offer valuable insights into the impact of HNT doping on PAN membrane characteristics and performance, which will inform future membrane development initiatives

    Flutter mitigation of turbofan blades using viscoelastic patches

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    Flutter as a self-feeding aeroelastic instability presents one of the biggest challenges in aero-engine designsto improve its aerodynamic and structural performance. This work presents a detailed feasibility study ofusing different viscoelastic patches as Constrained Layer Damping (CLD) enhancement for an aero-enginefan blade to reduce potential flutter risks. The static and dynamic responses of the different materials andconfigurations (thicknesses, layers and locations) are evaluated on both cruise and take-off/landingconditions. It is found that a double bi-layer 3M® ISD110 is the optimal choice of material for the CLDtreatment for the fan blade. The study also shows that an optimal CLD treatment of 15 % total surface areaof the blade at the root demonstrated a 36 % reduction in resonance amplitudes across the first six modes

    Troubling stories of the end of occupy : feminist narratives of betrayal at occupy Glasgow

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    This article offers a feminist take on the question of why Occupy camps closed down, in the form of a narrative analysis of interviews from participants in Occupy Glasgow. In response to the emergence of an activist discourse emphasising the role of external forces in camp closure and the existence of a longer-term legacy in terms of individual and community politicisation, I build here on feminist interventions that point instead to serious internal problems within the camps and thus to a more limited legacy. Interrogating the plotting, characterisation and denouement of interviewee narratives, I show that feminist participants in Occupy Glasgow characterise the trajectory of the camp as a tragedy, attribute responsibility for the camp’s demise to co-campers and sometimes to themselves, and present the outcome of Occupy Glasgow as limited, and in some cases even traumatic. This raises serious questions about the culmination and outcomes of Occupy in Glasgow and more generally, and indicates the extent of the hard work remaining if future mobilisation against neoliberal austerity is to be more inclusive and sustainable. The article closes by considering the theoretical implications for the wider question of why movements come to an end
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