975 resultados para Engineers.


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Computational Fluid Dynamics (CFD) simulations are widely used in mechanical engineering. Although achieving a high level of confidence in numerical modelling is of crucial importance in the field of turbomachinery, verification and validation of CFD simulations are very tricky especially for complex flows encountered in radial turbines. Comprehensive studies of radial machines are available in the literature. Unfortunately, none of them include enough detailed geometric data to be properly reproduced and so cannot be considered for academic research and validation purposes. As a consequence, design improvements of such configurations are difficult. Moreover, it seems that well-developed analyses of radial turbines are used in commercial software but are not available in the open literature especially at high pressure ratios. It is the purpose of this paper to provide a fully open set of data to reproduce the exact geometry of the high pressure ratio single stage radial-inflow turbine used in the Sundstrand Power Systems T-100 Multipurpose Small Power Unit. First, preliminary one-dimensional meanline design and analysis are performed using the commercial software RITAL from Concepts-NREC in order to establish a complete reference test case available for turbomachinery code validation. The proposed design of the existing turbine is then carefully and successfully checked against the geometrical and experimental data partially published in the literature. Then, three-dimensional Reynolds-Averaged Navier-Stokes simulations are conducted by means of the Axcent-PushButton CFDR CFD software. The effect of the tip clearance gap is investigated in detail for a wide range of operating conditions. The results confirm that the 3D geometry is correctly reproduced. It also reveals that the turbine is shocked while designed to give a high-subsonic flow and highlight the importance of the diffuser.

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In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

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Refactoring is a common approach to producing better quality software. Its impact on many software quality properties, including reusability, maintainability and performance, has been studied and measured extensively. However, its impact on the information security of programs has received relatively little attention. In this work, we assess the impact of a number of the most common code-level refactoring rules on data security, using security metrics that are capable of measuring security from the viewpoint of potential information flow. The metrics are calculated for a given Java program using a static analysis tool we have developed to automatically analyse compiled Java bytecode. We ran our Java code analyser on various programs which were refactored according to each rule. New values of the metrics for the refactored programs then confirmed that the code changes had a measurable effect on information security.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

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Design and Anthropology challenges conventional thinking regarding the nature of design and creativity, in a way that acknowledges the improvisatory skills and perceptual acuity of people. Combining theoretical investigations and documentation of practice based experiments, it addresses methodological questions concerning the re-conceptualisation of the relation between design and use from both theoretical and practice-based positions. Concerned with what it means to draw 'users' into processes of designing and producing this book emphasises the creativity of design and the emergence of objects in social situations and collaborative endeavours. Organised around the themes of perception and the user-producer, skilled practices of designing and using, and the relation between people and things, the book contains the latest work of researchers from academia and industry, to enhance our understanding of ethnographic practice and develop a research agenda for the emergent field of design anthropology. Drawing together work from anthropologists, philosophers, designers, engineers, scholars of innovation and theatre practitioners, Design and Anthropology will appeal to anthropologists and to those working in the fields of design and innovation, and the philosophy of technology and engineering.

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Wheel-rail interaction is one of the most important research topics in railway engineering. It includes track vibration, track impact response and safety of the track. Track structure failures caused by impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. The wheel-rail impact forces occur because of imperfections on the wheels or rails such as wheel flats, irregular wheel profile, rail corrugation and differences in the height of rails connected at a welded joint. The vehicle speed and static wheel load are important factors of the track design, because they are related to the impact forces under wheel-rail defects. In this paper, a 3-Dimensional finite element model for the study of wheel flat impact is developed by use of the FEA software package ANSYS. The effects of the wheel flat to impact force on sleepers with various speeds and static wheel loads under a critical wheel flat size are investigated. It has found that both wheel-rail impact force and impact force on sleeper induced by wheel flat are varying nonlinearly by increasing the vehicle speed; both impact forces are nonlinearly and monotonically increasing by increasing the static wheel load. The relationships between both of impact forces induced by wheel flat and vehicles speed or static load are important to the track engineers to improve the design and maintenance methods in railway industry.

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Wheel–rail interaction is one of the most important research topics in railway engineering. It involves track impact response, track vibration and track safety. Track structure failures caused by wheel–rail impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. Wheel–rail impact forces occur because of imperfections in the wheels or rails such as wheel flats, irregular wheel profiles, rail corrugations and differences in the heights of rails connected at a welded joint. A wheel flat can cause a large dynamic impact force as well as a forced vibration with a high frequency, which can cause damage to the track structure. In the present work, a three-dimensional (3-D) finite element (FE) model for the impact analysis induced by the wheel flat is developed by use of the finite element analysis (FEA) software package ANSYS and validated by another validated simulation. The effect of wheel flats on impact forces is thoroughly investigated. It is found that the presence of a wheel flat will significantly increase the dynamic impact force on both rail and sleeper. The impact force will monotonically increase with the size of wheel flats. The relationships between the impact force and the wheel flat size are explored from this finite element analysis and they are important for track engineers to improve their understanding of the design and maintenance of the track system.

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Secure communications in wireless sensor networks operating under adversarial conditions require providing pairwise (symmetric) keys to sensor nodes. In large scale deployment scenarios, there is no prior knowledge of post deployment network configuration since nodes may be randomly scattered over a hostile territory. Thus, shared keys must be distributed before deployment to provide each node a key-chain. For large sensor networks it is infeasible to store a unique key for all other nodes in the key-chain of a sensor node. Consequently, for secure communication either two nodes have a key in common in their key-chains and they have a wireless link between them, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path have a key in common. Length of the key-path is the key factor for efficiency of the design. This paper presents novel deterministic and hybrid approaches based on Combinatorial Design for deciding how many and which keys to assign to each key-chain before the sensor network deployment. In particular, Balanced Incomplete Block Designs (BIBD) and Generalized Quadrangles (GQ) are mapped to obtain efficient key distribution schemes. Performance and security properties of the proposed schemes are studied both analytically and computationally. Comparison to related work shows that the combinatorial approach produces better connectivity with smaller key-chain sizes.

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This paper is based on an Australian Learning & Teaching Council (ALTC) funded evaluation in 13 universities across Australia and New Zealand of the use of Engineers Without Borders (EWB) projects in first-year engineering courses. All of the partner institutions have implemented this innovation differently and comparison of these implementations affords us the opportunity to assemble "a body of carefully gathered data that provides evidence of which approaches work for which students in which learning environments". This study used a mixed-methods data collection approach and a realist analysis. Data was collected by program logic analysis with course co-ordinators, observation of classes, focus groups with students, exit survey of students and interviews with staff as well as scrutiny of relevant course and curriculum documents. Course designers and co-ordinators gave us a range of reasons for using the projects, most of which alluded to their presumed capacity to deliver experience in and learning of higher order thinking skills in areas such as sustainability, ethics, teamwork and communication. For some students, however, the nature of the projects decreased their interest in issues such as ethical development, sustainability and how to work in teams. We also found that the projects provoked different responses from students depending on the nature of the courses in which they were embedded (general introduction, design, communication, or problem-solving courses) and their mode of delivery (lecture, workshop or online).

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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

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Here mixed convection boundary layer flow of a viscous fluid along a heated vertical semi-infinite plate is investigated in a non-absorbing medium. The relationship between convection and thermal radiation is established via boundary condition of second kind on the thermally radiating vertical surface. The governing boundary layer equations are transformed into dimensionless parabolic partial differential equations with the help of appropriate transformations and the resultant system is solved numerically by applying straightforward finite difference method along with Gaussian elimination technique. It is worthy to note that Prandlt number, Pr, is taken to be small (<< 1) which is appropriate for liquid metals. Moreover, the numerical results are demonstrated graphically by showing the effects of important physical parameters, namely, the modified Richardson number (or mixed convection parameter), Ri*, and surface radiation parameter, R, in terms of local skin friction and local Nusselt number coefficients.

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An investigation of the effect of nano particles on natural convection of water based nanofluids contained in an open rectangular cavity is carried out numerically. The flow pattern and heat transfer characteristics are studied for different values of volume fraction in the range 0   0.2 , Rayleigh number in the range 9 1 Ra 10 and the nano particles with different thermo physical properties. It was found that for low Rayleigh numbers, heat transfer exhibits a decreasing trend for increasing values of volume fraction of oxide nanofluids, whereas for higher values of Rayleigh numbers, an increasing trend of heat transfer was observed due to increase in the volume fraction of nanofluids.

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Natural convection thermal boundary layer adjacent to the heated inclined wall of a right angled triangle with an adiabatic fin attached to that surface is investigated by numerical simulations. The finite volume based unsteady numerical model is adopted for the simulation. It is revealed from the numerical results that the development of the boundary layer along the inclined surface is characterized by three distinct stages, i.e. a start-up stage, a transitional stage and a steady stage. These three stages can be clearly identified from the numerical simulations. Moreover, in presence of adiabatic fin, the thermal boundary layer adjacent to the inclined wall breaks initially. However, it is reattached with the downstream boundary layer next to the fin. More attention has been given to the boundary layer development near the fin area.

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The advanced programmatic risk analysis and management model (APRAM) is one of the recently developed methods that can be used for risk analysis and management purposes considering schedule, cost, and quality risks simultaneously. However, this model considers those failure risks that occur only over the design and construction phases of a project’s life cycle. While it can be sufficient for some projects for which the required cost during the operating life is much less than the budget required over the construction period, it should be modified in relation to infrastructure projects because the associated costs during the operating life cycle are significant. In this paper, a modified APRAM is proposed, which can consider potential risks that might occur over the entire life cycle of the project, including technical and managerial failure risks. Therefore, the modified model can be used as an efficient decision-support tool for construction managers in the housing industry in which various alternatives might be technically available. The modified method is demonstrated by using a real building project, and this demonstration shows that it can be employed efficiently by construction managers. The Delphi method was applied in order to figure out the failure events and their associated probabilities. The results show that although the initial cost of a cold-formed steel structural system is higher than a conventional construction system, the former’s failure cost is much lower than the latter’s

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The Bouncing Back Project, which began after the Queensland flood event in January 2011, has organically grown through a number of reiterations as per the diagram above. In the August 2011 it resulted in the physical construction of an Emergency Shelter [designed by GreenLeaf Engineers] in Sydney at the Customs House in Circular Quay and a conference paper publication at the AASA conference. To date this research has progressed without any research grant funding and has resulted in significant media interest. During the construction of the Emergency Shelter we collected a wide range of multimedia data which is being compilled into a documentary focusing on the architecture students’ experience throughout the iterations of Bouncing Back.