78 resultados para Experiment container, ISS, FSL, FEM


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This paper presents the results of a real bridge field experiment in which damage was applied artificially to a steel truss bridge. The aim of this paper is to identify the dynamic parameters of this bridge using conventional techniques and investigate the effect of various damage conditions on those parameters. In the field experiment, acceleration measurements were recorded at a number of locations on the bridge deck. To excite the bridge, a two-axle van was driven across the bridge at constant speed. Dynamic parameters, such as the bridge mode shape, natural frequency and damping constant, are identified from the acceleration signals using existing techniques such as the fast Fourier transform, logarithmic decrement and frequency domain decomposition. The variation of these parameters under the influence of artificially applied damage conditions is investigated in order to evaluate their sensitivity to the bridge damage.

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Objective: We explored whether readers can understand key messages without having to read the full review, and if there were differences in understanding between various types of summary.
Design: A randomised experiment of review summaries which compared understanding of a key outcome.
Participants: Members of university staff (n = 36).
Setting: Universities on the island of Ireland.
Method: The Cochrane Review chosen examines the health impacts of the use of electric fans during heat waves. Participants were asked their expectation of the effect these would have on mortality. They were then randomly assigned a summary of the review (i.e. abstract, plain language summary, podcast or podcast transcription) and asked to spend a short time reading/listening to the summary. After this they were again asked about the effects of electric fans on mortality and to indicate if they would want to read the full Review.
Main outcome measure: Correct identification of a key review outcome.
Results: Just over half (53%) of the participants identified its key message on mortality after engaging with their summary. The figures were 33% for the abstract group, 50% for both the plain language and transcript groups and 78% for the podcast group.
Conclusions: The differences between the groups were not statistically significant but suggest that the audio summary might improve knowledge transfer compared to written summaries. These findings should be explored further using a larger sample size and with other reviews.

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The First World War hit Germany severely, particularly the agricultural sector, because the outbreak came unexpected and its duration exceeded all expectations. Many resources necessary for agricultural production were required by the war economy and led to shortages and shrinking supplies. Many agricultural laborers were drafted and the blockade imposed by the allies prevented Germany from a great deal of imports. As a consequence, the nutritional situation was devastating, particularly after 1916, and hit all groups of the German society. The period under observation provides one of most drastic natural experiments in the 20th century. This study uses anthropometric data from German soldiers who served in the Second World War to trace living standards between the 1900s and the 1920s. In contrast to other approaches, this paper is able to distinguish between social groups by occupation, religious denominatio\n, regional origin, and city size. The results suggest that although all social strata were hit by famine conditions, the height of farmers, urban citizens, Catholics, and especially individuals born in the highly integrated food-import regions along the coast and the banks of the Rhine declined most.

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This chapter explores the history of active citizenship education in English schools in relation to the more established tradition of service learning in the US.

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In order to carry out high-precision machining of aerospace structural components with large size, thin wall and complex surface, this paper proposes a novel parallel kinematic machine (PKM) and formulates its semi-analytical theoretical stiffness model considering gravitational effects that is verified by stiffness experiments. From the viewpoint of topology structure, the novel PKM consists of two substructures in terms of the redundant and overconstrained parallel mechanisms that are connected by two interlinked revolute joints. The theoretical stiffness model of the novel PKM is established based upon the virtual work principle and deformation superposition principle after mapping the stiffness models of substructures from joint space to operated space by Jacobian matrices and considering the deformation contributions of interlinked revolute joints to two substructures. Meanwhile, the component gravities are treated as external payloads exerting on the end reference point of the novel PKM resorting to static equivalence principle. This approach is proved by comparing the theoretical stiffness values with experimental stiffness values in the same configurations, which also indicates equivalent gravity can be employed to describe the actual distributed gravities in an acceptable accuracy manner. Finally, on the basis of the verified theoretical stiffness model, the stiffness distributions of the novel PKM are illustrated and the contributions of component gravities to the stiffness of the novel PKM are discussed.

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A digital directional modulation (DM) transmitter structure is proposed from a practical implementation point of view in this paper. This digital DM architecture is built with the help of several off-the-shelf physical layer wireless experiment platform hardware boards. When compared with previous analogue DM transmitter architectures, the digital means offers more precise and fast control on the updates of the array excitations. More importantly, it is an ideal physical arrangement to implement the most universal DM synthesis algorithm, i.e., the orthogonal vector approach. The practical issues in digital DM system calibrations are described and solved. The bit error rates (BERs) are measured via real-time data transmissions to illustrate the DM advantages, in terms of secrecy performance, over conventional non-DM beam-steering transmitters.

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As an emerging hole-machining methodology, helical milling process has become increasingly popular in aeromaterials manufacturing research, especially in areas of aircraft structural parts, dies, and molds manufacturing. Helical milling process is highly demanding due to its complex tool geometry and the progressive material failure on the workpiece. This paper outlines the development of a 3D finite element model for helical milling hole of titanium alloy Ti-6Al-4V using commercial FE code ABAQUS/Explicit. The proposed model simulates the helical milling hole process by taking into account the damage initiation and evolution in the workpiece material. A contact model at the interface between end-mill bit and workpiece has been established and the process parameters specified. Furthermore, a simulation procedure is proposed to simulate different cutting processes with the same failure parameters. With this finite element model, a series of FEAs for machined titanium alloy have been carried out and results compared with laboratory experimental data. The effects of machining parameters on helical milling have been elucidated, and the capability and advantage of FE simulation on helical milling process have been well presented.

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With the availability of a wide range of cloud Virtual Machines (VMs) it is difficult to determine which VMs can maximise the performance of an application. Benchmarking is commonly used to this end for capturing the performance of VMs. Most cloud benchmarking techniques are typically heavyweight - time consuming processes which have to benchmark the entire VM in order to obtain accurate benchmark data. Such benchmarks cannot be used in real-time on the cloud and incur extra costs even before an application is deployed.

In this paper, we present lightweight cloud benchmarking techniques that execute quickly and can be used in near real-time on the cloud. The exploration of lightweight benchmarking techniques are facilitated by the development of DocLite - Docker Container-based Lightweight Benchmarking. DocLite is built on the Docker container technology which allows a user-defined portion (such as memory size and the number of CPU cores) of the VM to be benchmarked. DocLite operates in two modes, in the first mode, containers are used to benchmark a small portion of the VM to generate performance ranks. In the second mode, historic benchmark data is used along with the first mode as a hybrid to generate VM ranks. The generated ranks are evaluated against three scientific high-performance computing applications. The proposed techniques are up to 91 times faster than a heavyweight technique which benchmarks the entire VM. It is observed that the first mode can generate ranks with over 90% and 86% accuracy for sequential and parallel execution of an application. The hybrid mode improves the correlation slightly but the first mode is sufficient for benchmarking cloud VMs.

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Response surface methodology was used to develop models to predict the effect of tomato cultivar, juice pH, blanching temperature and time on colour change of tomato juice after blanching. The juice from three tomato cultivars with adjusted pH levels ranging from 3.9 to 4.6 were blanched at temperatures from 60-100 °C for 1-5 min using the central composite design (CCD). The colour change was assessed by calculating the redness (a/b) and total colour change (∆E) after measuring the Hunter L, a and b values. Developed models for both redness and ∆E were significant (p<0.0001) with satisfactory coefficient of determination (R2 = 0.99 and 0.97) and low coefficient of variation (CV% = 1.89 and 7.23), respectively. Multilevel validation that was implemented revealed that the variation between the predicted and experimental values obtained for redness and ∆E were within the acceptable error range of 7.3 and 22.4%, respectively