The concept of nitrogen (N) fertilizer optimization is central to achieving the dual objective of optimizing the crop yield while reducing the environmental impact in precision agriculture. Canopy nitrogen concentration (CNC) is a measure of crop N status that can be instrumental in mapping the crop N requirement in space and time to optimize N fertilizer application. Beyond the cropland, CNC information is vital in monitoring the ecosystem functioning through its linkage with carbon and nitrogen stocks. Remote sensing offers a rapid, non-destructive and cost-effective way of measuring the CNC status of the crops in contrast to the time-consuming, destructive and costly laboratory measurements. Therefore, based on the linkage between CNC and canopy reflectance, many remote sensing models have been proposed for CNC estimation. However, their mapping capability is greatly influenced by confounding factors such as biomass, canopy architecture, and soil background, which vary with growth stages, seasons and crop type, limiting their broader adoption and application. Therefore, this thesis proposes robust CNC remote sensing models that are deployable to cost-effective sensors. There are many multispectral CNC indices, but little is known about their robustness across a wide range of contrasting growth stages and seasons. Chapter 3 assesses the robustness of the eighteen widely used multispectral indices for CNC sensing with an aim of enhancing the current understanding of their performance. The results indicate that almost all the indices exhibit a similar level of correlation with CNC when applied at individual growth stages; however, the multispectral index vs. CNC relationship is growth-specific and varies significantly across the growth stages. Therefore, this unstable relationship leads to significant performance drops when evaluated against the pooled data. It is found that the majority of the CNC indices respond to CNC and biomass together with an even more consistent association with biomass than CNC. Furthermore, some growth stages exhibit a very high correlation (up to 0.90) between observed CNC and biomass which may further obscure the identification and development of robust CNC indices when only limited growth conditions are incorporated. Among the selected indices, only the photochemical reflectance index (PRI) exhibited a consistent, albeit low, association with CNC. Motivated by the limitations identified in Chapter 3, Chapter 4 implements an exhaustive search to optimize the 2-4 waveband based multispectral indices for CNC. This search incorporates a wide range of growth stages in seasons of two crop types, ryegrass (irrigated) and barley (rainfed). The results show that although the best waveband combination changes with season and crop type, the visible spectrum, especially the blue region, exhibited consistent sensitivity to CNC. The newly developed 4-waveband index (ND4) is a more skillful predictor with stronger linearity with CNC than its 2-waveband counterpart (ND2). In addition, ND4 effectively reduces the predictive loss when broader wavebands are used compared with ND2. Furthermore, the issue of biomass and canopy structure influence has been significantly reduced in both ND2 and ND4 compared with the pre-existing indices considered due to the use of a diverse data set in the index development process. Chapter 5 explores the full potential of the information-rich hyperspectral data by employing state-of-the-art statistical, machine learning (ML) and deep learning (DL) techniques to model CNC. Models to predict aboveground biomass (AGB) were also developed to characterize the canopy N status across the growth cycles using the ‘CNC dilution’ effect. These modelling approaches include partial least squares regression (PLSR), random forest (RF), 1D and 2D convolution neural networks (CNN), together with comparison against multispectral indices, ND4 and soil-adjusted vegetation index (SAVI) for CNC and AGB, respectively. The results indicate that 1D CNN is the best and its performance is followed by the PLSR model. These models are more robust and generalizable than their hyperspectral counterpart RF and 2D CNN. The multispectral ND4 index exhibits performance comparable to the PLSR in the test dataset but with lower generalizability. In general, the models underperform in low canopy cover for CNC and under the high biomass for AGB prediction. Furthermore, intercomparison among the spectral regions shows that the visible spectrum is a more informative input for the CNC models while the near-infrared (NIR) spectrum is for AGB models. The thesis provides an enhanced understanding of the robustness of multispectral indices for CNC estimation. The proposed multispectral indices in this thesis only employ 2-4 wavebands and are consistently sensitive to CNC across contrasting growth conditions. In addition, this research also investigates the potential and limitations of the hyperspectral models to estimate CNC and AGB.

Ultra-High Strength Concrete (UHSC) is now being widely adopted in the construction industry due to the very high compressive strength, high elastic modulus, excellent durability characteristics etc. In the macroscopic scale, UHSC is considered as a homogenous and isotropic material when designing concrete structures. However, in reality UHSC is a highly heterogeneous material consisting of different length scales of heterogeneities known as multiscales of concrete. These multiscales of concrete can be identified as macroscale, mesoscale, microscale, nanoscale, and atomic scale. Mechanical and durability characteristics and the nonlinear behaviour of UHSC in the macroscale depend on the characteristics of the constituents in these multiscales. Modelling these individual scales and developing a connectivity between the scales are essential in exploring how the phases in each scale are contributing to the macroscopic behaviour of UHSC. Even though previous researchers have focused on individual scales of UHSC, a comprehensive study examining all the multiscales present in UHSC and developing a framework to link these scales to explore the contribution from each scale to the macroscopic behaviour is lacking. This research tries to address the question of how to model UHSC in different scales and how the intrinsic material properties of constituent phases in the different spatial scales contribute to the overall macroscopic behaviour. The main aim of this investigation is to create a comprehensive multiscale modelling framework to model UHSC in various length scales, and to bridge the gap between these scales and upscale and predict the macroscopic behaviour of UHSC using constituent properties at nano, micro and meso scales. In this research, mesoscale, microscale, and nanoscale of concrete are modelled using advanced modelling techniques such as finite element representative element modelling (FE-RVE) and finite element mesoscale modelling. An experimental programme is carried out to investigate the material parameters of the constituents at different scales using macro scale experiments and nanoindentation to characterize the nano and micro properties. The properties from nanoindentation results were used to evaluate the different phases and their homogenized elastic and strength parameters using statistical deconvolution, finite element limit analysis, Linear Comparison Composite (LCC) method, and an inverse analysis algorithm. Proposed framework is capable of homogenizing the elastic and strength parameters and linking the micro and nanoscale properties to the FE-RVE models so that the material properties can be upscaled from nanoscale to the macroscale. Finally, the homogenized mechanical properties are compared with the experimental properties of UHSC at the macroscale and the results concluded that the proposed multiscale and homogenization framework is able to predict the macro properties using nano and microscopic properties. Mesoscale modelling of concrete to explore the fracture and damage propagation behaviour of UHSC investigated in this thesis as the first component. Aggregate scanning and synthetic aggregate generation methodologies using spherical harmonics and other algorithms are presented and the behaviour of UHSC under uniaxial compression is investigated using mesoscale modelling. Experimental procedure followed to characterize UHSC microstructure and the nanoindentation tests performed to obtain the micromechanical properties of UHSC are presented subsequently. Also, the hydration simulation of UHSC is examined and compared with the High Strength Concrete (HSC). Finally, the elastic modulus and compressive strength homogenization for UHSC using the continuum micromechanics based analytical models and numerical FE-RVE modelling is presented. It can be concluded that the modelling of UHSC in different spatial scales can identify the critical phases which contribute to the enhanced mechanical properties in the macroscale and the developed multiscale modelling framework can successfully upscale and predict the mechanical properties of UHSC using the micromechanical properties of constituents in different spatial scales. This will also help to accurately model structures at macro-scale.

The initiation phase of capital projects is critical as this is where the highest number of options exist for modifying the project with minimal expenditure. Government and large organisations frequently involved in major capital projects have extensive procedures for this phase. However, organisations with an operational focus (like major container terminal stevedores) that only occasionally undertake capital projects face the dilemma of the trade-off between project planning and operations management. The reviewed literature shows a lack of consistent organisational practice in creating a project-strategy link during the initiation phase for these organisations. The existing research gaps indicate the need to investigate further the role and influence of the executive sponsor and how project success is defined and perceived by the project team during the project initiation phase. In addition, the need to undertake a qualitative research methodology, including interviews, is determined for investigating the project initiation phase. The research investigates the project initiation phase to foster in-depth understanding and fulfil the identified research gaps. The research examines the Australian container stevedoring industry as a case study to develop evidence-based recommendations to improve the project initiation phase and provide a project initiation framework that fits the business context and needs. The research intends to answer the question: “What are factors that influence the project initiation phase within the Australian Stevedoring industry?”. In addition to an extensive literature review, a living research investigation of real projects initiated by a stevedoring company operating in Australia has been observed; the researcher spent six months as a participant-observer and witnessed the initiation of twelve capital projects, recorded more than ten thousand words of written observations, and conducted 34 semi-structured interviews. The collected data were qualitatively analysed using a four-step coding method. The findings from the overall analysis indicated that the project initiation phase in the case Australian stevedoring company is not optimised and suffered from many issues at the initiation phases. It is further found that the existing project management frameworks fail to integrate with the organisation’s culture, which poses an adverse impact on the project initiation. Some of these identified key elements of organisational culture observed were lack of workplace trust, high individualism, ineffective interdepartmental communication, and the lack of resources. All these factors posed a hindrance in following a structured project management framework. The findings also suggested that the industry operational considerations such as engineering and safety complexity and the productivity-driven environment impact the decisions made during the project initiation phase. Based on the overall findings, the research suggests that the case organisation must implement a unique project initiation framework to meet the needs and the context of the operationally-focused industry. It is further recommended that the suggested framework be customised and utilised for other similar industries to dictate the success of the project initiation phase.

There is still a great deal of opportunity for research on contextual interactive immersion in virtual heritage environments. The general failure of virtual environment technology to create engaging and educational experiences may be attributable not just to deficiencies in technology or in visual fidelity, but also to a lack of contextual and performative-based interaction, such as that found in games. This thesis will suggest improvements will result from more research on the below issues: 1. Place versus Cyberspace: What creates a sensation of place (as a cultural site) in a virtual environment in contradistinction to a sensation of a virtual environment as a collection of objects and spaces? 2. Cultural Presence versus Social Presence and Presence: Which factors help immerse people spatially and thematically into a cultural learning experience? 3. Realism versus Interpretation: Does an attempt to perfect fidelity to sources and to realism improve or hinder the cultural learning experience? 4. Education versus Entertainment: Does an attempt to make the experience engaging improve or hinder the cultural learning experience? This doctoral thesis outlines a theoretical definition of place, culture, and presence that may become a matrix for virtual environment design as well as a discussion of the advantages and disadvantages of appropriating game-style interaction to enhance engagement. A virtual environment was built using Adobe Atmosphere to test whether cultural understanding and engagement can be linked to the type of interaction offered. The thesis also includes a survey of evaluation mechanisms that may be specifically suitable for virtual heritage environments. In its review of appropriate methodology, the thesis suggests new terms and criteria to assess the contextual appropriateness of various evaluation methods, and provides seven schematic examples of game-style plot devices that lend themselves to evaluation. The test-bed is the evaluation of a virtual archaeology project in Palenqué Mexico using theories of cultural immersion as well as computer game technology and techniques. The case study of Palenqué involved five types of evaluation specifically chosen to assess cultural awareness and understanding gained from different forms of interaction in a virtual heritage environment.

Flood is one of the most devastating natural hazards, as it often causes fatalities and damages to infrastructure. To develop strategies for flood risk mitigation, flood inundation models are often used to provide useful information for assessments of potential impacts of floods. Two-dimensional (2D) hydrodynamic models are commonly used for flood inundation simulations. However, they can be computationally intensive when used to simulate many flood events, for example for uncertainty analysis, or to simulate very large floodplains. To improve computational efficiency, data-driven models based on machine learning techniques and conceptual models based on simplified water-filling concepts have been developed. Data-driven models appear as black-box models and are yet to be used by many practitioners with confidence. Simplified conceptual models are generally not designed to simulate the temporal propagation of floods and are often only applied to estimate maximum/final flood extent and floodwater levels. In Australia, 2D hydrodynamic models have been established for many important catchments. There is potential to build on these existing models and develop methods to speed up flood inundation simulations. In this MPhil thesis, a new modelling method, LoHy+, is proposed based on existing 2D hydrodynamic models, to produce an efficient simulation of flood extent and depth with time. The method first develops a low-fidelity 2D hydrodynamic model (LFM) with coarse mesh based on an existing high-fidelity 2D hydrodynamic model (HFM). The aim of the LFM is to produce reasonably accurate simulation of water levels within the main river channels while tolerating poorer simulation elsewhere in the floodplain. Next, the method develops a Mapping Module by using training data to establish relationships between water levels in both river channels and across the floodplain generated using the HFM and water levels in the river channels generated using this LFM. In subsequent applications, the LFM is run first, and the Mapping Module is applied to estimate flood inundation within the entire model domain. The implementation of the LoHy+ is demonstrated using a real-world catchment located in the southern Murray Darling Basin, Australia. A fully calibrated HF MIKE21 FM hydrodynamic model is available for the catchment. The performance of the LoHy+ method is evaluated against simulation from the high-fidelity hydrodynamic model. There is a good agreement between results from the LoHy+ method and the original high-fidelity 2D hydrodynamic model. The new method is much more efficient and can simulate the spatiotemporal evolution of flood inundation with reasonable accuracy. It is potentially a useful tool for applications that require many model runs or long simulation durations.

Tropical cyclone surface wind and wave fields are investigated and defined using composite datasets from buoys, scatterometers and altimeters and the physics of wave evolution in tropical cyclones are explored using a series of numerical experiments with the WAVEWATCH III spectral wave model. The complete database consists of 24 years of global scatterometer observations, 30 years of global altimeter observations, and over 30 years of North American buoy measurements. The analysis of these combined datasets provides the most comprehensive investigation of the structure of the tropical cyclone wind and wave fields ever undertaken. The size of the database allowed us to investigate the effect of the velocity of forward movement and the central pressure of the tropical cyclone on the wind and wave field structure. The results confirmed the left-right asymmetry of wind and wave fields with the maximum wind speed and wave height to the right of the tropical cyclone (north hemisphere). Due to the extended fetch to the right of the moving tropical cyclone, the data also shows the asymmetry in the wave field is greater than the wind field. The observed wind inflow angle is shown to vary both radially and azimuthally within the tropical cyclone, with the maximum inflow angle in the right rear quadrant. The extensive in situ buoy database confirms previous studies, indicating that the one-dimensional spectra are generally unimodal. The directional spectra are directionally skewed, consisting of remotely generated waves radiating out from the storm's centre and locally generated wind sea. The model generated spectra are consistent with the observed buoy data and are shown to be largely governed by nonlinear wave-wave interactions resulting in a cascade of energy from the wind-sea to the remotely generated spectral peak. The critical role of nonlinear processes explains why one-dimensional tropical cyclone spectra have characteristics very similar to fetch-limited waves, even though the generation system is far more complex. The results also provide strong validation of the critical role nonlinear interactions play in wind-wave evolution.

Internal erosion is responsible for nearly half of dam failures globally and considered a major risk to safety and security of water management structures. Suffusion as one of the main mechanisms of internal erosion is defined as relocation or migration of fine particles within pre-existing pores of internally unstable soils caused by seepage forces. This research is focused on suffusion and the impact of influential parameters on internal stability potential of gap-graded granular material. Several experimental research works have been carried out so far to study suffusion, influential parameters, and its impact on the mechanical behaviour of soils. However, due to the macro-scale nature of experimental studies, micro-scale interactions between soil particles is not well investigated. In fact, macro-scale observations in physical experiments is dictated by micro-scale interactions inside granular packing such as particle displacements, contact forces, connectivity status of particles with their neighbours and pore size distribution. These micro-scale interactions are investigated by micromechanics and discrete element method (DEM) is an efficient numerical modelling tool in providing micro-scale properties of the packing of granular material. DEM has been widely used to evaluate microstructure of granular material under the impact of various influential parameters. The influence of external loadings, particle shape (i.e. spherical particles and angular particles selected from predefined library of different shapes) and qualitative relative density have been investigated in previous DEM studies. This PhD work aims to quantify internal stability status of the gap-graded granular packings under the impact of several controlling parameters. Controlling parameters investigated in this research are fine content (FC), gap-ratio (GR, size ratio between the smallest coarse particle and the largest fine particle), relative density (Dr), stress path and real soil fabric. To find the research gap, previous experimental and numerical modelling studies is reviewed first. Due to the lack of standardized method for sample production with target relative density in DEM, a new procedure based on variation of inter-particle coefficient of friction is developed. Then, packings with FC between 10% to 50%, GR between 2 to 10, and Dr in range of Dr,min to 100% are generated in DEM to assess the impact of these controlling parameters on contribution of fine particles to stress transferring mechanism and internal stability status of packings. Analysis of stress reduction factor (defined as the ratio of effective stress transmitted by fine fraction to the effective stress carried by the packing) shows that contribution of fine fraction to stress transferring mechanism of packings with GR = 4, FC = 25% and 35% improves with Dr suggesting that these packings can be classified as transitional. However, transitional zone starts at higher FC as GR increases beyond GR = 4. Variation of strong contact types under the impact of controlling parameters reveal that stress transferring mechanism is mainly dominated by strong fine-coarse and fine-fine contacts as transitional zone starts and when the packing is internally stable, respectively. In addition, DEM modelling outcome is resulted in a framework based on intergranular matrix phase diagrams to predict internal stability of the gap-graded granular soils. To investigate the impact of stress path on the roles that fine particles play in stress transferring mechanism, axial compression and extension stress paths are applied to multiple gap-graded packings. Packings with GR = 4 and FC = 10% and 15% at Dr = 100% and FC = 25% at Dr = 50% (internally unstable), FC = 25% and 35% at Dr = 100% and 50%, respectively, (transitional) and FC = 35% at Dr = 100% (internally stable) are considered here. DEM findings show a very similar impact of axial compression and extension on variation of micro-scale and macro-scale parameters. In this study, stress reduction factor, proportion of active (directly involved in force network), semi-active (provide a secondary support to the soil primary structure) and in-active (unstressed) fine particles and Z (coordination number) are considered as micro-scale and e (void ratio) as macro-scale parameters. In fact, stress reduction factor, proportion of active fine particles and Z decrease, but e increases when packings with FC = 25% and 35% at Dr = 100% undergo through axial stress paths. Although, the reverse trend is achieved for the variation of these micro- and macro-scale parameters with axial strain for the same packings at Dr = 50%, the impact of axial compression and extension stress paths is more noticeable for the packing with FC = 35% at Dr = 50%. In addition, it is interesting to note that both micro-scale and macro-scale parameters in packings with FC = 25 and 35% at Dr = 50% and 100% show a converging trend under axial extension, but they fully converge under axial compression at large strains. Proportion of semi-active and in-active fine particles increases and decreases, respectively, at large strains for packings with FC = 25 and 35% at Dr = 50%. Therefore, it is expected to observe initiation of suffusion under larger hydraulic gradient at large strains in comparison to isotropic compression for this packing. To study the impact of real soil fabric on contact network and contribution of fine particles to stress transferring mechanism, internally unstable gap-graded soil sample is scanned by micro computed tomography (micro-CT) and transferred to DEM. To enhance quality of micro-CT scans, various image filters are used, but anisotropic diffusion and non-local mean filters demonstrate an outstanding performance. DEM outputs suggest a crucial impact of coefficient of friction on porosity and coordination number of coarse particles. Findings of this study provides a better understanding of suffusion, erodibility potential of fine particles and microstructural changes in packing of granular gap-graded material under the impact of controlling parameters. Outcome of this research helps in describing underlying phenomenon of observations in physical erosion experiments. Finally, results of this study can be used in revising standard methods and guidelines which are based on empirical observations and do not consider micro-scale interactions between particles.

The Southern Ocean is the birthplace of the fiercest waves on the Earth that play a fundamental role in the global climate by regulating momentum, heat, and gas exchanges between the atmosphere and the ocean. At high latitudes, waves interact with Antarctic sea ice, another crucial player of the Earth's climate, modulating its expansion in winter and retreat in summer, hence affecting the global albedo. Despite the importance of waves for the climate system, global wave models are considerably biased in the Southern Ocean, due to the scarcity of observations in these remote waters. This study presents a unique data set of simultaneous observations of winds, surface currents, and ocean waves acquired underway during the Antarctic Circumnavigation Expedition (ACE) that went around the Southern Ocean from December 2016 to March 2017 (Austral summer). Discrepancies in the estimation of surface current velocities are demonstrated from a comparison of the data set against satellite observations and model predictions. It is discussed how these observations underpin the setup, calibration, and validation of the WaveWatch-III wave model over a domain covering the entire Southern Hemisphere. The calibrated model is then evaluated for the accuracy of wave predictions in the Southern Ocean. The wave heights and periods are well predicted by the model although, a slight overestimation of wave heights is present. This study shows that large biases of wave predictions at high latitudes are linked to the ice cover around Antarctica. It is also demonstrated that accounting for surface current has limited contribution in the reduction of wave prediction biases in the Southern Ocean. The observations are also used to thoroughly assess the performance of global wave models, namely the CAWCR hindcast and the ECMWF ERA-5 reanalysis, in this region. The CAWCR hindcast notably overestimates wave heights in the Southern Ocean however, the biases are shown to be considerably reduced in the ERA-5 analysis that benefits from data assimilation. The effects of data assimilation on wave predictions in the Southern Ocean are fully assessed by comparing the MFWAMv4 wave model's performance with and without data assimilation. Results show improved model performance due to assimilation of remotely sensed observations.

Australian public policy references to building information modelling (BIM), a 3D digital attributable object based built environment representation capability, continue to evolve. Whilst BIM is heralded as a means to lift productivity in the architecture, construction and engineering industry, developments are converging with other emerging narratives. The shifting intent has meant different objectives, opportunities and challenges are presented, particularly for broad and socially orientated applications that involve BIM. However, public policy responses remain unresolved, whether to reconcile or leverage these Big Picture perspectives or overcome prevailing limitations. As a result, directions for public procurement of infrastructure projects in view of BIM remain unclear. In progressing policy orientated debates, the current thesis presents constructive-interpretivist research to develop public procurement policy options aimed at capitalising on the opportunity afforded by BIM for infrastructure projects. From the abductive conceptual study, unique theoretical informational systems-based perspectives and concepts are developed to interpret BIM and its place in context. BIM systems (technology, modelling and model) are distinguished from other forms and features of informational systems. An idealised frame for policy development is proposed, setting the relativity of BIM systems at scale and evolutionary economics-based orders of rules. Application of the theoretical perspectives is presented and validated through a deductive case study of nested “systems”. Focusing on the roads sector between early 2017-2018, the resulting constructed narrative vertically profiles Australian organisational, project, industry and government positions and policies in view of BIM. Comparative qualitative analyses expose policy distinctions and coordination risks in terms of “BIM”, BIM systems, pre-BIM states and other systems characteristics. Predicted transformational implications draw from the consistent omission or narrow referencing of “rules” relating to BIM and the roads sector. However, outcomes highlight that despite indicative embryonic features, the underlying pre-text of analogous BIM characteristics (including functionality) is also qualified. Even before getting to BIM, the necessity and value propositions for consolidated or integrated and granular detailing and performance about the built environment is underdeveloped. Responding to the identified issues and risks, the research qualifies the demand for BIM to assist decision makers understand the extent and investment of proposed policy changes in response to BIM. The point of BIM is reset to engender scaled productivity towards “digital infrastructure” and reconcile business as usual presumptions and the creative-destructive implications of change. The recommended policy options target multi-stakeholder interventions and mechanisms that range from the development of strategic internal positioning on BIM for the road agency and extend through to a proposed intergovernmental agreement that advances capability in the Australian built environment sector. In preparation for BIM rather than “BIM” per se, the public policy options are developed as a first pass step for the future development of more comprehensive, longer term programs. From the theoretical perspectives, this includes acknowledging data or digital based approaches as a necessary but qualified step towards predicted future directions predicated on informational systems outcomes.

Impact-resistant design of reinforced concrete (RC) structures has a prominent role in mitigating hazards caused by extreme events. An example of such a structure is the RC barrier that serves as a protective measure in mountainous areas to protect lives and built infrastructure. Impact actions can be divided into localised and global actions. Local actions are controlled by the amount of impact force generated at the point of contact, and it is referred herein as contact force. The magnitude of contact force can be much higher than the quasi-static force, which can cause permanent damage to the structure. Gabion cushion layers are commonly used to protect localised damage in RC passive defence measures. Gabions are expensive and require extensive maintenance. Other structural concrete elements exposed directly to collision hazards or an abrasive environment are still required to design to withstand the contact forces developed during projected impact scenarios. Localised damage in the form of denting, spalling and punching failure are primarily resulted in RC members subjected to low-velocity impact actions. Predicting localised damage by impact action is more complex than global effects as the prediction depends on the determination of highly transient forces and stresses. These impact forces are highly influenced by the material behaviour and structural dynamic behaviour of colliding objects, which have not been incorporated in the expressions stipulated in contemporary codes of practices. Due to the complex nature of the impact, a significant amount of studies in the literature to date on localised damage are based on empirical data obtained from experimentation or numerical simulations. The major limitation with the empirical modelling is uncertainties over the scope of applicability as the derived relationships employ a specific range of impact events. Models developed based on theories also have limitations, but they are more transparent and can be amended to suit the conditions of impact, thereby has the merit of generality. Because of that, theoretical models consisting of closed-form expressions and are executable on MATLAB and Excel are proposed in this research project to determine the localised failure of RC structures. The recent development of the Hunt and Crossley theoretical model for accurately predicting the impact force has been reported for windborne debris and hail impact. The main drawback of this methodology is that the determination of model parameters requires calibration against impact experimentations using spherical impactors. In this research, an inexpensive experimental procedure based on the use of compression testing of cylindrical specimens of impactor and target objects is proposed to determine the model parameters. The innovation presented in this study waives away the need for costly and time-consuming impact experimentations and preparation of spherical samples. The accuracy of the proposed methodology to predict the impact force has been validated against impact experimentations and finite element simulations for impact by granite on concrete surfaces. This deterministic methodology can be capitalised for predicting damage to concrete. Denting and spalling of concrete on the impact surface is caused by the stress developed in the vicinity of the contact region. This study elaborates the adaptation of an analytical model derived from the fundamental theories of solid mechanics for the determination of transient effective stress contours. The accuracy of the simulated stress contours has been verified employing FE simulations which were previously validated against experimental measurements. The calculated stress contours at the instance of peak impact force and hardness of the target that is subjected to strike are to be employed to estimate the degree of damage in the proposed procedure. This theoretically based model to predict the occurrence of denting and spalling has been verified with large-scale experimentations on RC barrier specimens using solid steel and rock impactors. A deterministic analytical model has been developed to predict the occurrence of punching failure in RC based on conventional “free-body diagram” analysis. The proposed model accounts for the transient actions of impact (impact force and inertia force) generated within the shear plug in combination with material resistant forces. Given that the impact force can be predicted using the previously developed deterministic methodology, a numerical procedure that can be implemented on MATLAB or Excel to calculate the inertial resistance is introduced. The proposed punching shear failure predictive model has been verified by pendulum style impact experimentations on RC wall specimens. Further validations are incorporated employing drop test results on RC beam specimens reported in the literature. Predictive models presented in this thesis to determine the local response behaviour of RC are beneficial in the design of RC structures that are constructed in the proximity of collision hazards. Worked examples and step-by-step procedures are illustrated individually in the corresponding chapters of the thesis. In order to facilitate the uptake of the proposed methodology for industrial applications, complete design guidelines combining the deterministic approaches investigated in this research project with detailed calculation steps are presented towards the end of the thesis.

As the environmental problems have attracted more and more attention over the recent years, the cement production in concrete industry has become a global concern. In the concrete construction industry, ordinary Portland cement (OPC), as an important binder in concrete, is identified to be the major cause of energy cost and carbon emissions Thus to reduce the environmental impact caused by the cement production, sustainable concrete with the use of less cement has become a necessity. Supplementary cementitious materials (SCMs) have been developed to be used as admixtures in concrete. Fly ash (FA) which is one of the most commonly used SCMs is a waste material from the combustion of coal in electricity stations. It has a large storage over the world and continues to be produced over time. However, the most significant problem of concrete with FA, especially large amount of FA, is the slow early age strength development. A comprehensive literature review on different properties of FA concrete are first provided including mechanical properties, setting time, heat of hydration, workability, self-compacting concrete, shrinkage and creep, several major durability properties (chloride ingress, sulfate attack, carbonation, alkali-silica reaction) and microstructure. Thus the general properties of FA concrete could be better understood. The hydration and strength properties of FA concrete are further investigated for concrete with the incorporation of FA from different regions. The FA were sourced from both Indonesia and Australia including Gladstone, Port Augusta and Bayswater. It was found that the main difference of the FA in different regions is the particle size distribution and the differences in chemical composition. Higher fineness of FA particles leads to higher hydration rate and strength. The degree of hydration and chemically bound water (WB) is linearly correlated with the compressive strength. To improve the early age strength of the overall high volume fly ash (HVFA) concrete mixes, The HVFA concrete mixes were optimized by improving the aggregate grading, reducing the water to binder (w/b) ratio and adjusting the paste to void volume ratio (Vp/Vv). It was found that the concrete mainly fail in pastes rather than aggregate. Thus, the early age strength of HVFA pastes by the adding of admixtures was especially determined. The admixtures used to improve the compressive strength of HVFA pastes were nano-CSH crystals, calcium formate (CF), and hydrated lime (HL). The underlying mechanism of how theses admixtures work in the pastes was investigated by hydration and microstructural testing approaches. It was found that the adding of single nano-CSH crystals, CF or HL could improve the compressive strength of HVFA pastes due to different mechanisms. However, the addition of combined CF and HL decreased the strength mainly due to cracks and pores caused by rapid hydration. As the adiabatic temperature rise is an important parameter that could significantly affect the properties of concrete, the adiabatic temperature rises of OPC and FA concrete were modelled from the heat of hydration curves. The accuracy of the modelling was successfully improved by the adjustment of hydration parameters. Finally, machine learning (ML), as a statistical tool, was used in this research to predict the compressive strength of HVFA composites with the addition of different admixtures. The accuracy of the model could be further improved by increasing the data sets.

Concrete as a building material has been utilised in human civilisation for centuries. Featuring both strength and durability, concrete structures have prolonged life span when carefully designed, constructed and maintained. Modern concretes employ a variety of ingredients to achieve different material and structural performance requirements. One of the major concerns in construction of concrete members is the cracking that takes place during construction or with 1-7 days after the concrete placement. This period is referred to as “early age”. Cracking tendency of early age concrete is governed by a race between the strength gain over time and the in-situ stresses experienced by the member. Concrete members are restrained by its hardening internally or by the adjacent existing members. During early ages, it is understood, when strength of the member is surpassed by the stress, which happens primarily due to temperature development, cracking is likely to happen. Among the identified factors, thermal deformation is considered as one of the major effects that the concrete experiences. As stated earlier, concrete expands due to heat accumulation due to chemical exothermic reaction, known as cement hydration and contracts when rate of reaction slows down. If the concrete member is left unrestrained, the member will not experience any stresses and, therefore, the concrete will have little to no cracking risk. However, dilatation of concrete elements is almost always restrained, to some degree, due to member geometry resulting in differential dilation due to thermal gradient, internal steel elements or restrained externally due to the presence of adjacent structural members. In this research, the author focussed on the stress and strength evolution based on thermal effects experienced by early age concrete members. The primary aim of this project is to establish a reliable and simple method that describes the temperature induced stress development of early age concrete. In fulfilling the aim of this research, the key contributions of the thesis comprise of four models proposed to assist designers with various early-age thermal stress issues with concrete elements. They are: A spreadsheet-based temperature field model (Model A) for early age concrete is presented. The model can calculate temperature profiles at locations within a hydrating concrete block. The model is based on the concept of effective thickness and revised heat compensation technique. The model has proven to be able to estimate the peak temperatures at the core and the surface of the slab to a reasonable accuracy. Following the development of Model A, a simplified predictive thermal stress model (Model B) is proposed. This model is validated by comparison with output from FEM which calculates the thermal stress of early age concrete as well as thermal recordings from in-situ measurement. Model B is able to predict the stress profile within a concrete member and the critical location of tensile stress which corresponds to be the point with largest temperature difference to the thermal core. To assist the use of Model B, a neural network (NN) model (Model C) for the prediction of the adiabatic temperature rise (ATR) of concrete mixes is developed. The model is trained with 14 sets of ATR parameters derived from the Triple Parameter Equation (TPE)expression. The parameters are determined through a gradient descent algorithm. The result suggests that the TPE represents the ATR of concrete mix with good accuracy. Lastly, to promote the use of steel fibres (SF) in improving the flexural strength of concrete and as a solution to early-age cracking, a simplified prediction model (Model D) which is able to estimate the effect of SF in flexural strength of concrete beam was proposed. Addition of steel fibres (SF) can improve the ductility, flexural and tensile strength properties of concrete. The model is based on a combination of classical bending stress model and probability distribution of the area of SF within the section.