Comparison of analysis and experiment for gearbox noise

Low contact ratio spur gears were tested in the NASA gear-noise rig to study the noise radiated from the top of the gearbox. Experimental results were compared with a NASA acoustics code to validate the code for predicting transmission noise. The analytical code is based on the boundary element method (BEM) which models the gearbox top as a plate in an infinite baffle. Narrow band vibration spectra measured at 63 nodes on the gearbox top were used to produce input data for the BEM model. The BEM code predicted the total sound power based on the measured vibration. The measured sound power was obtained from an acoustic intensity scan taken near the surface of the gearbox at the same 63 nodes used for vibration measurement. Analytical and experimental results were compared at four different speeds for sound power at each of the narrow band frequencies over the range of 400 to 3200 Hz. Results are also compared for the sound power level at meshing frequency plus three sideband pairs and at selected gearbox resonant frequencies. The difference between predicted and measure sound power is typically less than 3 dB with the predicted value generally less than the measured value

Non-Newtonian and flow pulsatility effects in simulation models of a stented intracranial aneurysm

Permission to redistribute provided by publishers.Three models of different stent designs implanted in a cerebral aneurysm, originating from the Virtual Intracranial Stenting Challenge'07, are meshed and the flow characteristics simulated using commercial computational fluid dynamics (CFD) software in order to investigate the effects of non-Newtonian viscosity and pulsatile flow. Conventional mass inflow and wall shear stress (WSS) output are used as a means of comparing the cfd simulations. In addition, a WSS distribution is presented, which clearly discriminates in favour of the stent design identified by other groups. It is concluded that non-Newtonian and pulsatile effects are important to include in order to avoid underestimating wss, to understand dynamic flow effects, and to discriminate more effectively between stent designs. © Authors 2011

Characterisation of Soft Soil Microstructure Stabilised With Binary Blending Using Two Waste Fly Ashes

This paper represents an investigation on the microstructures of soil stabilised with binary blending using two different types of waste fly ashes. The microanalysis was conducted in order to realise the improvement in the strength of the stabilised soil. The soil used in this study was an intermediate plasticity silty clayey soil with medium organic matter content. FA1 was optimised in a previous study dependant on the unconfined compression strength (UCS) test conducted on specimens of soil treated with various percentages of FA1. The optimum percentage of FA1 was 12% of the dry weight of the soil. In this study, UCS test was conducted on specimens of soft soil treated with 12% of binder produced by binary blending of FA1 and FA2 with different proportions and the specimens were kept for curing at different periods (3, 7, 14, and 28 days) prior to being subjected to UCS testing. Scanning electronic microscopy (SEM) testing was employed to investigate the mechanism of strength improvement in the most remarkable soil-binder mixture. The results showed a significant development in stabilised soil strength. Moreover, the bond building sequences and subsequent changes in the microstructures of the stabilised soil due to the chemical reaction of the added fly ashes were observed

Soft Soil Stabilisation Using High Calcium Waste Material Ash

Civil engineering projects located in areas with soft soil present some of the most common problems in many parts of the world. Depending on the nature of the project, expensive solutions are sometimes used, which commonly involves the removal and replacement of the weak soils. Alternatively, ground improvement is now considered the best solution for such problems. Soil improvement can be achieved either by mechanical and/or chemical stabilisation. To reduce the use of cement and lime as the most traditional stabilizers applied to soft soils, sustainable waste materials have been increasingly used for soil stabilisation. This paper presents the results of a laboratory study on the stabilisation of silty clayey soil using a waste material fly ash (FA) with high calcium content produced from the incineration processes in domestic power stations. The FA used in this study has a high content of calcium oxide CaO and suitable content of silicon dioxide SiO2 (more than 25%). These cementitious and pozzolanic properties are responsible for the self-cementing characteristics of this fly ash. An intermediate plasticity silty clayey soil with medium organic matter content has been used in this study. The effect of FA on the physical and engineering properties on the selected soil such as the consistency limits, compaction characteristics (optimum moisture content and maximum dry density), and soil strength (unconfined compressive strength (UCS)), has been investigated. Different percentages of fly ash were added to the soft soil (1.5, 3, 6, 9, 12, and 15%) to produce different admixtures. Improvement levels were evaluated dependant on the UCS tests carried out on specimens at different periods of curing (zero, 7, 14, and 28 days). Results indicated that the maximum dry density decreased and the optimum moisture content increased with the increase of the FA content. In terms of the UCS tests, the results yielded the optimum value of the FA used in this study to be 12.0%, as this percentage decreased the index of plasticity (IP) significantly. The results of this study indicated that the use of this waste material could produce a significant cementitious reaction when added to the soil, and it could be used as a supplementary cementitious material

A hybrid generalised linear and Levenberg-Marquardt artificial neural network approach for downscaling future rainfall in North Western England

This paper describes a novel technique for downscaling daily rainfall which uses a combination of a generalised linear model (GLM) and artificial neural network (ANN) to downscale rainfall. A two-stage process is applied, an occurrence process which uses the GLM model and an amount process which uses an ANN model trained with a Levenberg–Marquardt approach. The GLM-ANN was compared with other three downscaling models, the traditional neural network (ANN), multiple linear regression (MLR) and Poisson regression (PR). The models are applied for downscaling daily rainfall at three locations in the North West of England during the winter and summer. Model performances with respect to reproduction of various statistics such as correlation coefficient, autocorrelation, root mean square errors (RMSE), standard deviation and the mean rainfall are examined. It is found that the GLM-ANN model performs better than the other three models in reproducing most daily rainfall statistics, with slight difficulties in predicting extremes rainfall event in summer. The GLM-ANN model is then used to project future rainfall at the three locations employing three different general circulation models (GCMs) for SRES scenarios A2 and B2. The study projects significant increases in mean daily rainfall at most locations for winter and decreases in summe

Application of the stochastic model for temporal rainfall disaggregation for hydrological studies in north western England

Assessment of climate change on any hydrological system requires higher temporal resolution at hourly or less in terms of time-scale. This paper implements the Bartlett-Lewis Rectangular Pulses (BLRP) model coupled with a proportional adjusting procedure to disaggregate daily rainfall to hourly rainfall in order to demonstrate the reliability of this method. Three stations in NorthWestern England have been selected that represent different climates in the region. Parameters estimation of the BLRP model has been performed under different levels of hourly rainfall aggregation for a combination of rainfall statistics. The Hyetos model, which applies BLRP, reproduced standard statistics such as mean, variance, Lag -1, autocorrelation as well as dry proportions. Moreover, the model was proven to have the capability to disaggregate the rainfall extremes. The fitted BLRP model could then be used to disaggregate future daily rainfall in order to investigate the climate change impact of different rainfall intensities

A laboratory study of high-performance cold mix asphalt mixtures reinforced with natural and synthetic fibres

This research aims to examine the impact of using natural and synthetic fibres as reinforcing materials, on the mechanical properties and water susceptibility of cold mix asphalt (CMA) including indirect tensile stiffness and resistance to rutting, cracking and moisture damage. Four different types of fibres were used: glass as a synthetic fibre, and hemp, jute and coir as natural fibres. Various samples of CMA, with and without fibres, were fabricated and tested. Traditional hot mix asphalt (HMA) was also used for comparison. The results indi cate a significant improvement in the indirect tensile stiffness modulus, for all fibre-reinforced CMA mixtures, over different curing times. The improved tensile behaviour represents a substantial contribution towards slowing crack propagation in bituminous mixtures, while scanning electron microscopy analysis confirmed the fibre shape and surface roughness characteristics. The improved performance of the reinforced mixtures with both natural and synthetic fibres, facilitated a substantially lower permanent deformation than traditional hot and cold mixtures at two different temperatures (45 °C and 60 °C). When using glass and hemp fibres as reinforcing materials, there was a significant improvement in CMA in terms of water sensitivity. Resistance to surface cracking was also improved when fibres were incorporated. Based on the test results, 0.35% fibre content by mass of dry aggregate and 14 mm fibre length are recommended to achieve the optimum performance output for indirect tensile stiffness. © 2018 Elsevier Lt

Predicting the rutting behaviour of natural fibre-reinforced cold mix asphalt using the finite element method

This paper describes the development of a three-dimensional (3-D), finite element model (FEM) of flexible pavements made with cold mix asphalt (CMA), which has itself been reinforced with two different natural fibres: jute and coir. A 3-D finite element model was employed to predict the viscoelastic response of flexible CMA pavements when subjected to multiple axle loads, different bituminous material properties, tire speeds and temperatures. The analysis was conducted by the finite element computer package ABAQUS/STANDARD. The pavements were subject to cyclic and static loading conditions to test for permanent deformation (rutting). The accuracy of the developed model was validated by comparing the predicted results with those measured in the lab. Reinforced and unreinforced CMA mixture models were simulated in this research. The results indicate that the CMA mixtures reinforced with natural fibres, are effective in mitigating permanent deformation (rutting). These reinforcing materials can extend the service life of flexible pavements. © 2018 Elsevier Lt

Application of the UKCP09 WG Outputs to Assess Performance of Combined Sewers System in a Changing Climate

In many parts of the world old sewer systems have been designed without consideration for change in climate, so probabilities and risks of sewer surcharge and flooding are elevated due to increase in extreme rainfall events as a consequence of global warming. The current paper is aiming to assess how the climate change on interannual to multidecadal timescale (2020s, 2050s, 2080s) will affect design standards of waste water networks due to the presumed increase in rainfall intensity and frequency in the Northwest of England area (selected site). Design storms have been analysed for future rainfall obtained from the UK Climate Projection version 2009 (UKCP09) weather generator, which was applied to the existing urban drainage system to check the level of service in winter and summer seasons. Two emission scenarios (SRES) have been adopted to simulate the greenhouse gas concentration; high scenario (A1FI) and low scenario (B1). Results indicate that the impact of increase in the deign storm of the system in winter lead to a potential of increase flood volume from manholes and intern basements at risk of flooding with the worst condition associated with 24 hours storm in 2080s. Moreover, when this design storm depth increased by only 15%, the corresponding flood volume increase by 40%, this indicates that the relation between the cause of flooding and its consequences is non-linear. Summer season has an opposite picture and flood volume is projected to decrease with the increase in the storm duration causing low risk. Considering climate change in this study caused most of urban drainage models runs to be very slow with some interruption in the simulation due to the inflation in some parameters, so cautious should be taken

Investigation on experimental techniques to detect, locate and quantify gear noise in helicopter transmissions

A robotic system to automate the detection, location, and quantification of gear noise using acoustic intensity measurement techniques has been successfully developed. Major system components fabricated under this grant include an instrumentation robot arm, a robot digital control unit and system software. A commercial, desktop computer, spectrum analyzer and two microphone probe complete the equipment required for the Robotic Acoustic Intensity Measurement System (RAIMS). Large-scale acoustic studies of gear noise in helicopter transmissions cannot be performed accurately and reliably using presently available instrumentation and techniques. Operator safety is a major concern in certain gear noise studies due to the operating environment. The man-hours needed to document a noise field in situ is another shortcoming of present techniques. RAIMS was designed to reduce the labor and hazard in collecting data and to improve the accuracy and repeatability of characterizing the acoustic field by automating the measurement process. Using RAIMS a system operator can remotely control the instrumentation robot to scan surface areas and volumes generating acoustic intensity information using the two microphone technique. Acoustic intensity studies requiring hours of scan time can be performed automatically without operator assistance. During a scan sequence, the acoustic intensity probe is positioned by the robot and acoustic intensity data is collected, processed, and stored