999 resultados para Weather simulations


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Nanoindentation is a useful technique for probing the mechanical properties of bone, and finite element (FE) modeling of the indentation allows inverse determination of elasto-plastic constitutive properties. However, FE simulations to date have assumed frictionless contact between indenter and bone. The aim of this study was to explore the effect of friction in simulations of bone nanoindentation. Two dimensional axisymmetric FE simulations were performed using a spheroconical indenter of tip radius 0.6m and angle 90°. The coefficient of friction between indenter and bone was varied between 0.0 (frictionless) and 0.3. Isotropic linear elasticity was used in all simulations, with bone elastic modulus E=13.56GPa and Poisson’s ratio =0.3. Plasticity was incorporated using both Drucker-Prager and von Mises yield surfaces. Friction had a modest effect on the predicted force-indentation curve for both von Mises and Drucker-Prager plasticity, reducing maximum indenter displacement by 10% and 20% respectively as friction coefficient was increased from zero to 0.3 (at a maximum indenter force of 5mN). However, friction has a much greater effect on predicted pile-up after indentation, reducing predicted pile-up from 0.27m to 0.11m with a von Mises model, and from 0.09m to 0.02m with Drucker-Prager plasticity. We conclude that it is important to include friction in nanoindentation simulations of bone.

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The iPlan treatment planning sys-tem uses a pencil beam algorithm, with density cor-rections, to predict the doses delivered by very small (stereotactic) radiotherapy fields. This study tests the accuracy of dose predictions made by iPlan, for small-field treatments delivered to a planar solid wa-ter phantom and to heterogeneous human tissue using the BrainLAB m3 micro-multileaf collimator.

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This research discusses some of the issues encountered while developing a set of WGEN parameters for Chile and advice for others interested in developing WGEN parameters for arid climates. The WGEN program is a commonly used and a valuable research tool; however, it has specific limitations in arid climates that need careful consideration. These limitations are analysed in the context of generating a set of WGEN parameters for Chile. Fourteen to 26 years of precipitation data are used to calculate precipitation parameters for 18 locations in Chile, and 3–8 years of temperature and solar radiation data are analysed to generate parameters for seven of these locations. Results indicate that weather generation parameters in arid regions are sensitive to erroneous or missing precipitation data. Research shows that the WGEN-estimated gamma distribution shape parameter (α) for daily precipitation in arid zones will tend to cluster around discrete values of 0 or 1, masking the high sensitivity of these parameters to additional data. Rather than focus on the length in years when assessing the adequacy of a data record for estimation of precipitation parameters, researchers should focus on the number of wet days in dry months in a data set. Analysis of the WGEN routines for the estimation of temperature and solar radiation parameters indicates that errors can occur when individual ‘months’ have fewer than two wet days in the data set. Recommendations are provided to improve methods for estimation of WGEN parameters in arid climates.

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Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.

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In this paper we discuss an advanced, 3D groundwater visualisation and animation system that allows scientists, government agencies and community groups to better understand the groundwater processes that effect community planning and decision-making. The system is unique in that it has been designed to optimise community engagement. Although it incorporates a powerful visualisation engine, this open-source system can be freely distributed and boasts a simple user interface allowing individuals to run and investigate the models on their own PCs and gain intimate knowledge of the groundwater systems. The initial version of the Groundwater Visualisation System (GVS v1.0), was developed from a coastal delta setting (Bundaberg, QLD), and then applied to a basalt catchment area (Obi Obi Creek, Maleny, QLD). Several major enhancements have been developed to produce higher quality visualisations, including display of more types of data, support for larger models and improved user interaction. The graphics and animation capabilities have also been enhanced, notably the display of boreholes, depth logs and time-series water level surfaces. The GVS software remains under continual development and improvement

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The heavy rain falls that we have been experiencing have had their impact on the public transport system, especially the ferries. September 2010 was the Brisbane area’s wettest on record, and early to mid October has shaped up much the same. So much so that the South East Queensland’s main water storages, the Wivenhoe and Somerset Dams, which are fed by the Stanley and Brisbane Rivers’ upper catchments, have filled to capacity. SEQ Water consequently released the floodgates on the Wivenhoe Dam for the first time in almost a decade, with bipartisan support of State and Local Governments.

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Nanoindentation is a useful technique for probing the mechanical properties of bone, and finite element (FE) modeling of the indentation allows inverse determination of elasto-plastic constitutive properties. However, all but one FE study to date have assumed frictionless contact between indenter and bone. The aim of this study was to explore the effect of friction in simulations of bone nanoindentation. Two dimensional axisymmetric FE simulations were performed using a spheroconical indenter of tip radius 0.6 m and angle 90°. The coefficient of friction between indenter and bone was varied between 0.0 (frictionless) and 0.3. Isotropic linear elasticity was used in all simulations, with bone elastic modulus E=13.56GPa and Poisson‟s ratio f 0.3. Plasticity was incorporated using both Drucker-Prager and von Mises yield surfaces. Friction had a modest effect on the predicted force-indentation curve for both von Mises and Drucker-Prager plasticity, reducing maximum indenter displacement by 10% and 20% respectively as friction coefficient was increased from zero to 0.3 (at a maximum indenter force of 5mN). However, friction has a much greater effect on predicted pile-up after indentation, reducing predicted pile-up from 0.27 to 0.11 m with a von Mises model, and from 0.09 to 0.02 m with Drucker-Prager plasticity. We conclude that it is potentially important to include friction in nanoindentation simulations of bone if pile-up is used to compare simulation results with experiment.

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This study uses dosimetry film measurements and Monte Carlo simulations to investigate the accuracy of type-a (pencil-beam) dose calculations for predicting the radiation doses delivered during stereotactic radiotherapy treatments of the brain. It is shown that when evaluating doses in a water phantom, the type-a algorithm provides dose predictions which are accurate to within clinically relevant criteria, gamma(3%,3mm), but these predictions are nonetheless subtly different from the results of evaluating doses from the same fields using radiochromic film and Monte Carlo simulations. An analysis of a clinical meningioma treatment suggests that when predicting stereotactic radiotherapy doses to the brain, the inaccuracies of the type-a algorithm can be exacerbated by inadequate evaluation of the effects of nearby bone or air, resulting in dose differences of up to 10% for individual fields. The results of this study indicate the possible advantage of using Monte Carlo calculations, as well as measurements with high-spatial resolution media, to verify type-a predictions of dose delivered in cranial treatments.

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This paper presents channel measurements and weather data collection experiments conducted in a rural environment for an innovative Multi-User-Single-Antenna (MUSA) MIMO-OFDM technology, proposed for rural areas. MUSA MIMO-OFDM uplink channels are established by placing six user terminals (UT) around one access point (AP). Generated terrain profiles and relative received power plots are presented based on the experimental data. According to the relative received signal, MUSA-MIMO-OFDM uplink channels experience temporal fading. Moreover, the correlation between the relative received power and weather variables are presented. Results show that all weather variables exhibit a negative average correlation with received power. Wind speed records the highest average negative correlation coefficient of -0.35. Local maxima of negative correlation, ranging from 0.49 to 0.78, between the weather variables and relative received signals were registered between 5-6 a.m. The highest measured correlation (-0.78) of this time of the day was exhibited by wind speed. These results show the extend of time variation effects experienced by MUSA-MIMO-OFDM channels deployed in rural environments.

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A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

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Background Apart from helmets, little is known about the effectiveness of motorcycle protective clothing in reducing injuries in crashes. The study aimed to quantify the association between usage of motorcycle clothing and injury in crashes. Methods and findings Cross-sectional analytic study. Crashed motorcyclists (n = 212, 71% of identified eligible cases) were recruited through hospitals and motorcycle repair services. Data was obtained through structured face-to-face interviews. The main outcome was hospitalization and motorcycle crash-related injury. Poisson regression was used to estimate relative risk (RR) and 95% confidence intervals for injury adjusting for potential confounders. Results Motorcyclists were significantly less likely to be admitted to hospital if they crashed wearing motorcycle jackets (RR = 0.79, 95% CI: 0.69–0.91), pants (RR = 0.49, 95% CI: 0.25–0.94), or gloves (RR = 0.41, 95% CI: 0.26–0.66). When garments included fitted body armour there was a significantly reduced risk of injury to the upper body (RR = 0.77, 95% CI: 0.66–0.89), hands and wrists (RR = 0.55, 95% CI: 0.38–0.81), legs (RR = 0.60, 95% CI: 0.40–0.90), feet and ankles (RR = 0.54, 95% CI: 0.35–0.83). Non-motorcycle boots were also associated with a reduced risk of injury compared to shoes or joggers (RR = 0.46, 95% CI: 0.28–0.75). No association between use of body armour and risk of fracture injuries was detected. A substantial proportion of motorcycle designed gloves (25.7%), jackets (29.7%) and pants (28.1%) were assessed to have failed due to material damage in the crash. Conclusions Motorcycle protective clothing is associated with reduced risk and severity of crash related injury and hospitalization, particularly when fitted with body armour. The proportion of clothing items that failed under crash conditions indicates a need for improved quality control. While mandating usage of protective clothing is not recommended, consideration could be given to providing incentives for usage of protective clothing, such as tax exemptions for safety gear, health insurance premium reductions and rebates.

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Quantum dot - plasmon waveguide systems are of interest for the active control of plasmon propagation, and consequently, the development of active nanophotonic devices such as nano-sized optical transistors. This paper is concerned with how varying aspect ratio of the waveguide crosssection affects the quantum dot - plasmon coupling. We compare a stripe waveguide with an equivalent nanowire, illustrating that both waveguides have a similar coupling strength to a nearby quantum dot for small waveguide cross-section, thereby indicating that stripe lithographic waveguides have strong potential use in quantum dot –plasmon waveguide systems. We also demonstrate that changing the aspect ratio of both stripe and wire waveguides can increase the spontaneous emission rate of the quantum dot into the plasmon mode, by up to a factor of five. The results of this paper will contribute to the optimisation of quantum dot - plasmon waveguide systems and help pave the way for the development of active nanophotonics devices.