Infrastructure Engineering - Research Publications
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ItemNo Preview AvailableA macro-element model for predicting the combined load behaviour of spudcan foundations in clay overlying sand(Thomas Telford Ltd., 2021-10-26)A macro-element model for predicting the load–displacement behaviour of a spudcan foundation in clay overlying sand when subjected to combined vertical, horizontal and moment loading is introduced. Observations from detailed drum centrifuge tests that measured the effect of the underlying sand layer on the foundation behaviour are combined with finite-element results and theoretical developments to derive the components of the model. The yield surface defined by the centrifuge test results suggests that as the spudcan nears the underlying sand layer, the absolute horizontal capacity remains relatively constant, while the vertical and moment capacities increase at approximately the same normalised rate. The model is demonstrated to accurately predict foundation behaviour by retrospectively simulating the experimental results. This macro-element model has the advantage that it can be integrated into the structural analyses of jack-up platforms required for site-specific assessments.
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ItemFeasibility and performance analysis of hybrid ground source heat pump systems in fourteen cities(PERGAMON-ELSEVIER SCIENCE LTD, 2021-11-01)Ground source heat pump systems (GSHP) for residential building heating, cooling, and hot water are highly energy efficient but capital intensive when sized for peak demands. The use of supplemental sources of energy with GSHP systems enables improved life-cycle economics through the reduction in the size and cost of the GSHP components. This paper investigates the life-cycle economics of hybrid solar-assisted ground source heat pump systems (SAGSHP) using simulations validated from field data. The economics and optimal sizing of SAGSHP systems for heating dominant climates in four locations in Australia and ten locations elsewhere are evaluated in order to explore the suitability and relative merits of SAGSHP systems in a range of heating dominant climates. In locations having high or moderate levels of solar irradiation, high electricity prices, and high or moderate gas prices, SAGSHP systems are shown to have the lowest life cycle cost amongst alternatives, with predicted savings of up to 30%.
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ItemPrivacy- and context-aware release of trajectory data(ACM, 2020-03)The availability of large-scale spatio-temporal datasets along with the advancements in analytical models and tools have created a unique opportunity to create valuable insights into managing key areas of society from transportation and urban planning to epidemiology and natural disasters management. This has encouraged the practice of releasing/publishing trajectory datasets among data owners. However, an ill-informed publication of such rich datasets may have serious privacy implications for individuals. Balancing privacy and utility, as a major goal in the data exchange process, is challenging due to the richness of spatio-temporal datasets. In this article, we focus on an individual's stops as the most sensitive part of the trajectory and aim to preserve them through spatio-temporal perturbation. We model a trajectory as a sequence of stops and moves and propose an efficient algorithm that either substitutes sensitive stop points of a trajectory with moves from the same trajectory or introduces a minimal detour if no safe Point of Interest (POI) can be found on the same route. This hinders the amount of unnecessary distortion, since the footprint of the original trajectory is preserved as much as possible. Our experiments shows that our method balances user privacy and data utility: It protects privacy through preventing an adversary from making inferences about sensitive stops while maintaining a high level of similarity to the original dataset.
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ItemNo Preview AvailablePerformance of a wheat yield prediction model and factors influencing the performance: A review and meta-analysis(ELSEVIER SCI LTD, 2021-12)CONTEXT: Process-based crop models provide ways to predict crop growth, evaluate environmental impacts on crops, test various crop management options, and guide crop breeding. They can be used to explore options for mitigating climate change impacts when combined with climate projections and explore mitigation of environmental impacts of production. The Agricultural Production Systems SIMulator (APSIM) is a widely adopted crop model that offers modules for simulation of various crops, soil processes, climate, and grazing within a modelling system that enables robust addition of new components. OBJECTIVE: This study uses APSIM Classic-Wheat as an example to examine yield prediction accuracy of biophysically based crop yield modelling and to analyse the factors influencing the model performance. METHODS: We analysed yield prediction results of APSIM Classic-Wheat from 76 published studies across thirteen countries on four continents. In addition, a meta-database of modelled and observed yields from 30 studies was established and used to identify factors that influence yield prediction uncertainty. RESULTS AND CONCLUSIONS: Our analysis indicates that, with site-specific calibration, APSIM predicts yield with a root mean squared error (RMSE) smaller than 1 t/ha and a normalised RMSE (NRMSE) of about 28%, across a wide range of environmental conditions for independent evaluation periods. The results show increasing errors in yield with limited modelling information and adverse environmental conditions. Using soil hydraulic parameters derived from site-specific measurements and/or tuning cultivar parameters improves yield prediction accuracy: RMSE decreases from 1.25 t/ha to 0.64 t/ha and NRMSE from 32% to 14%. Lower model accuracy was found where APSIM overestimates yield under high water deficit condition and when it underestimates yield under nitrogen limitation. APSIM severely over-predicts yield when some abiotic stresses such as heatwaves and frost affect the crop growth. SIGNIFICANCE: This paper uses APSIM-Wheat as an example to provide perspectives on crop model yield prediction performance under different conditions covering a wide spectrum of management practices, and environments. The findings deepen the understanding of model uncertainty associated with different calibration processes or under various stressed conditions. The results also indicate the need to improve the model's predictive skill by filling functional gaps in the wheat simulations and by assimilating external observations (e.g., biomass information estimated by remote sensing) to adjust the model simulation for stressed crops.
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ItemExperimental and Analytical Investigation of a RC Wall with a Gabion Cushion Subjected to Boulder Impact(PERGAMON-ELSEVIER SCIENCE LTD, 2021-05-31)An experimental investigation involving the use of a full-scale pendulum device to deliver solid object impact on a reinforced concrete (RC) barrier specimen that was fitted with a layer of gabion cushion is reported in this paper. The deflection behaviour of the stem wall of the RC barrier including the tensile strains developed in the longitudinal reinforcement was of interests. Results recorded from the tests are compared with results from control experiments which were without the protection of any cushion materials. The introduction of a layer of cushion is shown to be able to have the contact force reduced by more than 95% and deflection demand reduced by about 70%. An analytical procedure employing the Hunt and Crossley contact model, Swiss code model and two-degrees-of-freedom (2DOF) system modelling technique is presented for calculating the flexural response behaviour of the cushioned barrier and validated by comparison with experimental measurements. An important outcome from the study is a simple hand calculation procedure featuring the use of a closed form expression along with a design chart which is illustrated by a worked example, to facilitate uptake in design practices.
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ItemA multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments(ELSEVIER SCI LTD, 2021-11-01)Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NOX, NH4 and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.
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ItemNo Preview AvailableCover Image, Volume 8, Issue 2(Wiley, 2021-03)Abstract The cover image is based on the Focus Article Healthy waterways and ecologically sustainable cities in Beijing‐Tianjin‐Hebei urban agglomeration (northern China): Challenges and future directions by Giri Kattel et al., https://doi.org/10.1002/wat2.1500. image
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ItemNo Preview AvailableNeural factoid geospatial question answering(UNIV MAINE, 2021)Existing question answering systems struggle to answer factoid questions when geospatial information is involved. This is because most systems cannot accurately detect the geospatial semantic elements from the natural language questions, or capture the semantic relationships between those elements. In this paper, we propose a geospatial semantic encoding schema and a semantic graph representation which captures the semantic relations and dependencies in geospatial questions. We demonstrate that our proposed graph representation approach aids in the translation from natural language to a formal, executable expression in a query language. To decrease the need for people to provide explanatory information as part of their question and make the translation fully automatic, we treat the semantic encoding of the question as a sequential tagging task, and the graph generation of the query as a semantic dependency parsing task. We apply neural network approaches to automatically encode the geospatial questions into spatial semantic graph representations. Compared with current template-based approaches, our method generalises to a broader range of questions, including those with complex syntax and semantics. Our proposed approach achieves better results on GeoData201 than existing methods.
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ItemNo Preview AvailableThe semantics of place-related questions(UNIV MAINE, 2021)The trend to equip information systems with question-answering capabilities raises the design problem of deciding which questions a system should be able to answer. Typical solutions build on mining human conversations or logs from similar systems for question patterns. For the case of questions about geographic places, we present a complementary approach, showing how to derive possible questions from an ontology of spatial information and a classification of place facets. We argue that such an approach reduces the inherent and substantial data bias of current solutions. At a more general level, we provide a novel understanding of spatial questions and their role in designing and using spatial information systems.
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ItemNo Preview AvailableUnderstanding the Characteristics of Pedestrians when Passing Obstacles of Different Sizes: An Experimental Study(Forschungszentrum Julich, Zentralbibliothek, 2021-10-03)The aim of this study is to understand the collective movements of individuals and to observe how individuals interact within a physical environment in a crowd dynamic, which has drawn the attention of many researchers. We conducted an experimental study to observe interactions in the collective motions of people and to identify characteristics of pedestrians when passing obstacles of different sizes (bar-shaped, 1.2 m, 2.4 m, 3.6 m and 4.8 m), going through one narrow exit and employing three different flow rates in walking and running conditions. According to the results of our study, there were no differences in collision-avoidance behaviour of pedestrians when walking or running. The pedestrians reacted early to the obstacles and changed the direction in which they were walking by quickly turning to the left or to the right. In terms of the speed of the pedestrians, the average velocity was significantly affected while performing these tasks, decreasing as the size of the obstacle increased; therefore, the size of obstacles will affect flow and speed levels. Travel time was shorter when participants were in the medium-flow rate experiments. In terms of the distance of each individual’s travel, our data showed that there was no significant difference in all the flow rate experiments for both speed levels. Our results also show that when the pedestrians crossed an obstacle, the lateral distance averaged from 0.3 m to 0.7 m, depending on the flow rate and speed level. We then explored how the body sways behaved while avoiding obstacles. It is observed that the average sway of the body was less in the high-speed conditions compared to the low-speed conditions – except for the HF & 4.8 m experiment. These results are expected to provide an insight into the characteristics of the behaviour of pedestrians when avoiding objects, and this could help enhance agent-based models.