14 resultados para APPLIED LOAD


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A Newton–Raphson solution scheme with a stress point algorithm is presented for the implementation of an elastic–viscoplastic soilmodel in a finite element program. Viscoplastic strain rates are calculated using the stress and volumetric states of the soil. Sub-incrementsof time are defined for each iterative calculation of elastic–viscoplastic stress changes so that their sum adds up to the time incrementfor the load step. This carefully defined ‘iterative time’ ensures that the correct amount of viscoplastic straining is accumulated overthe applied load step. The algorithms and assumptions required to implement the solution scheme are provided. Verification of the solutionscheme is achieved by using it to analyze typical boundary value problems.

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The fatigue response of an epoxy matrix containing vasculature for the delivery of liquid healing agents is investigated. The release of a rapidly curing, two-part epoxy healing chemistry into the wake of a propagating crack reduces the rate of crack extension by shielding the crack tip from the full range of applied stress intensity factor. Crack propagation is studied for a variety of loading conditions, with the maximum applied stress intensity factor ranging from 62 to 84% of the quasi-static fracture toughness of the material. At the highest level of applied load, the rate of mechanical damage is so fast that the healing agents do not fully mix and polymerize, and the effect of healing is minimal. The self-healing response is most effective at impeding the slower propagating cracks, with complete crack arrest occurring at the lowest level of applied load, and reductions of 79–84% in the rate of crack extension at intermediate loads.

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Granular anchors are a relatively new concept in ground engineering with relatively little known regarding their load–displacement behaviour, failure modes, ultimate pullout capacity and also potential applications. A granular anchor consists of three main components: a base plate; tendon and compacted granular backfill. The tendon is used to transmit the applied load to the base plate which compresses the granular material to form the anchor. A study of the load–displacement response and ultimate pullout capacity of granular anchors constructed in intact lodgement till and made ground deposits is reported in this paper. Parallel tests were also performed on cast insitu concrete anchors which are traditionally used for anchoring purposes. A new method of analysis for the determination of the ultimate pullout capacity of granular anchors is presented and verified experimentally, with the dominant mode of failure controlled by the column length to diameter ratio. Granular anchors with L/D > 7 principally failed on bulging whereas short granular anchors failed on shaft resistance, with the latter mobilising similar pullout capacities as conventional concrete anchors.

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Ultrasonic welding process is a rapid manufacturing process used to weld thin layers of metal at low temperatures and low energy consumption. Experimental results have shown that ultrasonic welding is a combination of both surface (friction) and volume (plasticity) softening effects. In the presented work, a very first attempt has been made to simulate the ultrasonic welding of metals by taking into account both of these effects (surface and volume). A phenomenological material model has been proposed which incorporates these two effects (i.e. surface and volume). The thermal softening due to friction and ultrasonic (acoustic) softening has been included in the proposed material model. For surface effects a friction law with variable coefficient of friction dependent upon contact pressure, slip, temperature and number of cycles has been derived from experimental friction tests. Thermomechanical analyses of ultrasonic welding of aluminium alloy have been performed. The effects of ultrasonic welding process parameters, such as applied load, amplitude of ultrasonic vibration, and velocity of welding sonotrode on the friction work at the weld interface are being analyzed. The change in the friction work at the weld interface has been explained on the basis of softening (thermal and acoustic) of the specimen during the ultrasonic welding process. In the end, a comparison between experimental and simulated results has been presented showing a good agreement. © 2008 Elsevier Ltd. All rights reserved.

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Ultrasonic welding (consolidation) process is a rapid manufacturing process that is used to join thin layers of metal at low temperature and low energy consumption. Experimental results have shown that ultrasonic welding is a combination of both surface (friction) and volume (plasticity) softening effects. In the presented work, an attempt has been made to simulate the ultrasonic welding of metals by taking into account these effects (surface and volume). A phenomenological material model has been proposed, which incorporates these two effects (i.e., surface and volume). The thermal softening due to friction and ultrasonic (acoustic) softening has been included in the proposed material model. For surface effects, a friction law with variable coefficient of friction that is dependent on contact pressure, slip, temperature, and number of cycles has been derived from experimental friction tests. The results of the thermomechanical analyses of ultrasonic welding of aluminum alloy have been presented. The goal of this work is to study the effects of ultrasonic welding process parameters, such as applied load, amplitude of ultrasonic oscillation, and velocity of welding sonotrode on the friction work at the weld interface. The change in the friction work at the weld interface has been explained on the basis of softening (thermal and acoustic) of the specimen during the ultrasonic welding process. In the end, a comparison between experimental and simulated results has been presented, showing a good agreement. Copyright © 2009 by ASME.

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Considering that TBMs are nowadays used for long Trans-Alpine tunnels, the
understanding of rock breaking and chipping due to TBM cutter disks mechanism, for deep tunnelling operations, becomes very interesting. In this paper, the results from carried out laboratory tests that simulate the disk cutter action at the rock tunnel face by means of an indentation tool, acting on a rock
specimen with proper size, and the related three-dimensional and two-dimensional numerical modelling are proposed. The developed numerical models simulate the different test conditions (applied load, boundary conditions) allowing the analysis of the stresses distributions along possible breaking planes.
The influence of a confinement-free area on one side of the specimen, simulating the formation of a groove near the tool, is pointed out.
The obtained results from numerical modelling put in evidence a satisfactory agreement with the experimental observations.

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The aim of this paper is to investigate the mechanism of nanoscale fatigue using nano-impact and multiple-loading cycle nanoindentation tests, and compare it to previously reported findings of nanoscale fatigue using integrated stiffness and depth sensing approach. Two different film loading mechanism, loading history and indenter shapes are compared to comprehend the influence of test methodology on the nanoscale fatigue failure mechanisms of DLC film. An amorphous 100 nm thick DLC film was deposited on a 500 μm silicon substrate using sputtering of graphite target in pure argon atmosphere. Nano-impact and multiple-load cycle indentations were performed in the load range of 100 μN to 1000 μN and 0.1 mN to 100 mN, respectively. Both test types were conducted using conical and Berkovich indenters. Results indicate that for the case of conical indenter, the combination of nano-impact and multiple-loading cycle nanoindentation tests provide information on the life and failure mechanism of DLC film, which is comparable to the previously reported findings using the integrated stiffness and depth sensing approach. However, the comparison of results is sensitive to the applied load, loading mechanism, test-type and probe geometry. The loading mechanism and load history is therefore critical which also leads to two different definitions of film failure. The choice of exact test methodology, load and probe geometry should therefore be dictated by the in-service tribological conditions, and where necessary both test methodologies can be used to provide better insights of failure mechanism. Molecular dynamics (MD) simulations of the elastic response of nanoindentation is reported, which indicates that the elastic modulus of the film measured using MD simulation was higher than that experimentally measured. This difference is attributed to the factors related to the presence of material defects, crystal structure, residual stress, indenter geometry and loading/unloading rate differences between the MD and experimental results.

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Knowledge on the life span of the riveting dies used in the automotive industry is sparse. It is often the case that only when faulty products are produced are workers aware that their tool needs to be changed. This is of course costly both in terms of time and money. Responding to this challenge, this paper proposes a methodology which integrates wear and stress analysis to quantify the life of a riveting die. Experiments are carried out to measure the applied load required to split a rivet. The obtained results (i.e. force curves) are used to validate the wear mechanisms of the die observed using scanning electron microscopy. Sliding, impact, and adhesive wears are observed on the riveting die after a certain number of riveting cycles. The stress distribution on the die during riveting is simulated using a finite element (FE) approach. In order to confirm the accuracy of the FE model, the experimental force results are compared with the ones produced from FE simulation. The maximum and minimum von Mises' stresses generated from the FE model are input into a Goodman diagram and an S-N curve to compute the life of the riveting die. It is found that the riveting die is predicted to run for 4 980 000 cycles before failure.

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This paper investigates the mechanism of nanoscale fatigue of functionally graded TiN/TiNi films using nano-impact and multiple-loading-cycle nanoindentation tests. The functionally graded films were deposited on silicon substrate, in which TiNi films maintain shape memory and pseudo elastic behavior, while a modified TiN surface layer provides tribological and anti-corrosion properties. Nanomechanical tests were performed to comprehend the localized film performance and failure modes of the functionally graded film using NanoTestTM equipped with Berkovich and conical indenter between 100 μN to 500 mN loads. The loading mechanism and load history are critical to define film failure modes (i.e. backward depth deviation) including the shape memory effect of the functionally graded layer. The results are sensitive to the applied load, loading type (e.g. semi-static, dynamic) and probe geometry. Based on indentation force-depth profiles, depth-time data and post-test surface observations of films, it is concluded that the shape of the nanoindenter is critical in inducing the localized indentation stress and film failure, including shape recovery at the lower load range. Elastic-plastic finite element (FE) simulation during nanoindentation loading indicated that the location of subsurface maximum stress near the interface influences the backward depth deviation type of film failure. A standalone, molecular dynamics simulation was performed with the help of a long range potential energy function to simulate the tensile test of TiN nanowire with two different aspect ratios to investigate the theory of its failure mechanism.

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Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

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Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted for an idealised or ‘average’ patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population—effectively simulating a clinical trial. Specifically we hypothesise that an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or ‘average’ patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young’s modulus implant (View the MathML source) to one with a higher Young’s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis for an idealised of ‘average’ patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance–simulating a clinical trial–present a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.

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The finite element method in conjunction with the Soutis-Fleck model is used to predict the residual strength after impact of a carbon-fibre reinforced plastic wingbox subjected to a cantilever type loading. The maximum stress failure criterion further validates the Soutis-Fleck model predictions. The Soutis-Fleck model predicts that the wingbox fails at a tip load of 99.2 kN, approximately 5.5% less than the experimental observation

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While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

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Endometrial cancer risk has been directly associated with glycemic load. However, few studies have investigated this link, and the etiological role of specific dietary carbohydrate components remains unclear. Our aim was to investigate associations of carbohydrate intake, glycemic index, and glycemic load with endometrial cancer risk in the US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Recruitment took place in 1993-2001. Over a median of 9.0 years of follow-up through 2009, 386 women developed endometrial cancer among 36,115 considered in the analysis. Dietary intakes were assessed using a 124-item diet history questionnaire. Cox proportional hazards models were applied to calculate hazard ratios and 95% confidence intervals. Significant inverse associations were detected between endometrial cancer risk and total available carbohydrate intake (hazard ratio (HR) = 0.66, 95% confidence interval (CI): 0.49, 0.90), total sugars intake (HR = 0.71, 95% CI: 0.52, 0.96), and glycemic load (HR = 0.63, 95% CI: 0.46, 0.84) when women in the highest quartile of intake were compared with those in the lowest. These inverse associations were strongest among overweight and obese women. No associations with endometrial cancer risk were observed for glycemic index or dietary fiber. Our findings contrast with previous evidence and suggest that high carbohydrate intakes and glycemic loads are protective against endometrial cancer development. Further clarification of these associations is warranted.