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Modelling the Spatial Dependence of Multi-Species Point Patterns
No full textThe study of the spatial point patterns in ecology, such as the records of the observed locations of trees, shrubs, nests, burrows, or documented animal presence, relies on multivariate point process models. This study aims to compare the efficacy and applicability of two prominent multivariate point process models, the multivariate log Gaussian Cox process (MLGCP), and the saturated pairwise interaction Gibbs point process model (SPIGPP), highlighting their respective strengths and weaknesses when prior knowledge of the underlying mechanisms driving the patterns is lacking. Using synthetic and real datasets, we assessed both models based on their predictive accuracy of the empirical K function. Our analysis revealed that both MLGCP and SPIGPP effectively identify and capture mild to moderate clustering and regulations. MLGCP struggles to capture repulsive associations as they intensify. In contrast, SPIGPP can well estimate both the direction and magnitude of interactions even when the model is misspecified. Both models present unique advantages: MLGCP is particularly effective when there is a need to account for complex, unobserved heterogeneities that vary across space, while SPIGPP is suitable when interactions between points are the primary focus. The choice between these models should be guided by the specific needs of the research question and data characteristics.</p
A Data-Driven approach to Prognostics and Health Management of Aircraft Structures for Predictive Maintenance in Operations and Sustainment
No full textThis thesis makes significant research contributions towards the development of structural Prognostics and Health Management (PHM) methodologies with the development of diagnostics and prognostics algorithms for fleet aircraft sustainment and predictive maintenance operations. This research is an industry collaboration with the Australian Defence Science and Technology Group (DSTG), as well as interfacing with other Defence organisations, including the Capability Acquisition and Sustainment Group (CASG). Unlike prior research, this thesis introduces novel contributions that develop PHM in a direction towards condition-based maintenance at the fleet level to account for Configuration, Role and Operating Environment (CR&E) delta. This research has developed diagnostic and prognostic approaches that utilise on board aircraft sensors to detect and quantify structural non-linearities (e.g., control surface freeplay). This marks an important step in enabling effective in service sustainment that accounts for varying CR&E of aircraft. Furthermore, to support subsequent decision-making, the research implements Natural Language Processing (NLP) of unstructured textual maintenance records and tools for visualisation using Mixed Reality (MR) devices and software. This end to-end process flow provides a pathway for the realisation of improved efficiency, timely decision-making and task performance. This thesis presents novel methodologies and frameworks addressing key gaps in the literature on aircraft sustainment through advancements in Prognostics and Health Management (PHM). Current research in PHM lacks robust diagnostics and prognostics for non-linear structural degradation in aircraft, particularly in operational conditions. Additionally, conventional maintenance practices are limited by reliance on manual analysis of unstructured textual reports and insufficient integration of emerging technologies, such as Augmented Reality (AR) and digital twins, for effective damage evaluation and predictive maintenance. The thesis first develops a PHM framework for aircraft control surface freeplay analysis, introducing a two-phase process: supervised Machine Learning (ML) for diagnostic severity detection and Particle Filter (PF) based Remaining Useful Life (RUL) estimation. Results for diagnostics of nonlinearities (e.g., freeplay) achieve high accuracy on limited time-series data, while prognostics results demonstrate RUL predictions are possible with good confidence. Addressing limitations in existing literature, a synthetic dataset and numerical model is developed for freeplay degradation, enabling better understanding of the nonlinear damage failure modes. To complement numerical models, an experimental freeplay test rig with a remote sensing system is developed to monitor buffet-induced structural damage in aircraft structures. A three-step data analysis framework incorporating signal processing, feature extraction and predictive modelling demonstrates the effectiveness of neural networks and PF methods in diagnosing and predicting damage under realistic load conditions. Combined with surrogate datasets of real-world aircraft, these numerical and experimental approaches are verified for performance in diagnosing and predicting nonlinear damage in aircraft structures. The thesis further incorporates AR for Non-Destructive Evaluation (NDE) of damage hotspots, validated through a proof-of-concept using a decommissioned aircraft and digital twin models. This approach provides an alternative process to visual inspections of aircraft damage and demonstrates enhanced accuracy and efficiency in maintenance tasks, but also highlights the challenges in digital twin workflows for operational scalability. Lastly, the novel NLP framework is introduced to exploit unstructured maintenance and pilot reports, which are under-utilised and limited by labour-intensive manual analysis. This NLP framework uses statistical and ML techniques to provide a novel approach to identifying early lead indicators to aircraft major defects. The contributions made in this thesis collectively tackled the full, end-to-end process chain for data-driven predictive maintenance. From data generation with on-board monitoring sensors, to ML algorithms for lead indicator identification and damage progression modelling, this thesis extends the state-of-the-art for multiple PHM steps, through not only covering freeplay prognostics, but extending this into visualisation, not previously seen in literature. This thesis provides the necessary methodologies and frameworks to develop prognostics for aircraft control surface anomalies, NLP for automatic risk rating of fleet anomalies in underutilised unstructured maintenance reports and a Mixed Reality Non-Destructive Evaluation (MR-NDE) approach to aircraft sustainment. The outcomes of this thesis will support engineers and maintainers in the field to be more proactive in maintenance operations and help reduce overall costs through effective aircraft sustainment practices.</p
Swim Melbourne: Mapping places to swim in Melbourne
No full textThe 'Swim Melbourne' StoryMap explores swimmable places across Melbourne, uncovering stories and communities connected to these sites. The aim is to foster discussions of the experiences of swimming as an activity that creates deep connections to watery places, as well as creating challenges and moments for caution. The map reveals how the journey towards "swimmable cities" is an ongoing process - one that can enhance community and ecological resilience and support human and environmental health and wellbeing.</p
Sequenced co-design with stakeholder communities to support the development of spaces for mental health recovery and healing
No full textThis research reports on a sequenced co-design process to engage lived experience consumers, carers, healthcare professionals, sector advocates and government representatives in co-designing spatial and experiential inputs to a residential eating disorders facility. The stakeholder community was enabled to co-design a model of care and, building on this, shape the functional brief for the design of health spaces. The stakeholder community input provided architects and designers with a more expansive understanding of user needs regarding specific architectural qualities including psychological safety, flexibility, social connection, and sensory experiences. Our approach yields insights across three interlinked areas: capacity building in the stakeholder community to develop the design language to contribute to design discussions; co-design processes to question pre-existing design assumptions; and subsequently, the development of a more nuanced brief for health spaces. The research supports designers, architects, health organizations and health planners to meaningfully engage with future users of complex healthcare environments.</p
Structural Defect Detection and Severity Estimation Using High Resolution Image Processing
No full textIdentifying early signs of structural defects—such as cracks and corrosion—and determining their severity is crucial to preventing catastrophic failures, saving lives, and reducing financial losses. However, traditional visual inspection methods are labor-intensive and inefficient for large-scale infrastructure. Moreover, while direct measurement techniques (e.g., micrometer gauges and ultrasonic devices) offer quantitative assessments of defect severity, they are often time-consuming and impractical for field applications. A significant limitation also exists with many indirect Non-Destructive Testing and Evaluation (NDT & E) methods—such as Eddy Current Arrays, Guided Wave Ultrasound, Acoustic Emission, and Radiographic Testing—which rely on electrochemical or acoustic properties and typically require contact-based sensor placements, thereby reducing their feasibility in real-world deployments. This thesis addresses the problem of scalable, efficient, and non-contact detection and quantification of structural defects, with an emphasis on corrosion and cracking. In light of the limitations of conventional approaches, imaging-based NDT & E techniques, coupled with image processing algorithms, have emerged as promising alternatives for structural health monitoring. This research investigates the application of imaging-based NDT & E techniques for detecting and quantifying structural defects. A custom desktop Multi-Spectral Imaging (MSI) system was developed to capture spectral data of steel specimens with artificially induced corrosion. Spectral unmixing techniques were applied to determine corrosion phase composition and severity. Additionally, a Terahertz imaging setup was employed for detecting corrosion under insulation, incorporating signal processing methods to estimate defect depth and coating thickness. In the final phase, a light weight Unmanned Aerial Vehicle (UAV) imaging platform was introduced, integrating deep learning based crack detection and transformer-based segmentation models. The findings highlight the potential of MSI for accurate corrosion phase identification, Terahertz imaging for sub-surface corrosion profiling, and UAV based imaging for scalable defect detection. By optimizing imaging systems and analytical methodologies, this work contributes a comprehensive imaging methodology for infrastructure health monitoring, industrial maintenance, and disaster risk mitigation.</p
Engineering Hybrid Halide Perovskites for Enhanced Stability: A Structural and Spectroscopic Study
No full textSemiconductors are the backbone of modern technology, driving innovations in medical devices to clean energy. Semiconductor devices based on silicon technology have been a major driving force behind the electronic revolution in the past few decades. Recently, a class of materials that has emerged as a promising candidate for many optoelectronic applications is organic lead halide perovskites. The remarkable surge in perovskite-related research is attributed to their high absorption coefficient, long charge carrier mobility, facile bandgap tuning, easy solution processability, high photoluminescence quantum yield, etc. However, organic lead halide perovskites possess stability issues under various environmental stressors such as temperature, moisture, and light. They suffer from temperature-dependent structural phase transitions, which can affect the optoelectronic properties of the compound. While under continuous light irradiation, perovskite shows halide segregation and metallic lead formation, which degrade the performance of the device. On the other hand, moisture-induced decomposition of perovskite materials can produce contaminated chemicals apart from the reduction of the device performance. Overcoming issues like structural phase transitions and degradation is crucial for future advancements. This thesis deals with the structural and spectroscopic investigations of composition- and additive-engineered organic lead halide perovskite materials. The results and discussions for the investigating systems, along with the introduction, methodology, and experimental techniques, are organized into seven chapters of the thesis. Chapter 1 is a brief introduction and motivation for the research work carried out in the thesis. Chapter 2 includes discussions on sample synthesis techniques and various experimental setups and protocols utilized for the investigations presented in the thesis. In Chapter 3, structural, optical, chemical, and electronic properties of A-site substituted MA1-xFAxPbBr3 (x= 0, 0.5, and 1) single crystals are presented. This chapter is divided into two sections. In the first section, detailed temperature-dependent structural characterization confirms the formation of cubic Pm3 ̅m symmetry at room temperature in all three compounds. At lower temperatures, all three compounds show phase transition to tetragonal to orthorhombic phases. Temperature-dependent Raman spectroscopy shows stronger interaction between MA+ cations and Br¯ anions in the low temperatures of the orthorhombic phase in MAPbBr3, while no such interactions were noticed in the other two compounds. Temperature-dependent photoluminescence study shows dual emission behavior of the compounds, while broad-band emission in the low temperature of MAPbBr3. Detailed study suggests that the dual emission behavior is due to the formation of direct-indirect state formation, while the broad-band emission is the result of the formation of the intrinsic self-trapped excitons. In the second section, a time-dependent XPS study was performed to understand the light stability of the compound under continuous exposure to high-energy X-rays. It was noticed that FA+ incorporation inhibits the metallic lead formation in perovskites. Chapter 4 discusses the results from X-site substituted MAPb(Cl1-xBrx)3 single crystals. This chapter is divided into two sections. In the first section, detailed temperature-dependent structural characterization confirms the formation of cubic Pm3 ̅m symmetry at room temperature in all three compounds. MAPbCl3 attains tetragonal and orthorhombic symmetry under changes in temperature. In the orthorhombic phase, below 160 K, a single orthorhombic Pnma symmetry cannot be fitted with small values of reliability parameters, indicating the presence of two orthorhombic phases. MAPbCl1.5Br1.5 maintains cubic Pm3 ̅m symmetry till 120 K, while MAPbBr3 attains its tetragonal I4/mcm symmetry and orthorhombic Pnma symmetry respectively. Temperature-dependent Raman spectroscopy shows much stronger interaction between MA+ cations and Cl¯ anions in the low temperatures of the orthorhombic phase in MAPbCl3 compared to MAPbBr3, while no such interactions were noticed in the mixed compound. Temperature-dependent photoluminescence study shows light-induced halide segregation in the mixed compound, while broad-band emission in the low temperature of MAPbBr3 and higher temperatures of MAPbCl3 was observed. Detailed study suggests that the broad-band emission is the result of intrinsic self-trapped excitons formation. The formation of double unit cells in the low temperatures of MAPbCl3 stabilizes the lattice fluctuation, while smaller sizes of Cl¯ ions make compact unit cells at the higher temperature with stronger MA+–Cl¯ interaction, which gives rise to the broad-band emission. In the second section, an XPS study was performed to understand the light stability of the compound under continuous exposure to high-energy X-rays. All three compounds show light-induced Pb0 formation under continuous X-ray irradiation. In Chapter 5, five single crystals of dual-site compositionally engineered perovskite MA1-xFAxPb(I0.95Br0.05)3 (0 ≤ x ≤ 1) compounds are presented. Structural study confirms the presence of cubic and tetragonal phases in MAPb(I0.95Br0.05)3, while hexagonal and cubic phases in MA0.25FA0.75Pb(I0.95Br0.05)3 and FAPb(I0.95Br0.05)3. Complete cubic structure is found in MA0.75FA0.25Pb(I0.95Br0.05)3 and MA0.5FA0.5Pb(I0.95Br0.05)3 compounds. UV-visible spectroscopy suggests that FA-rich compounds with hexagonal phases are partially photoinactive. All the compounds show excellent light stability without halide segregation. Time-dependent photoluminescence suggests enhancement in intensity over time, which is due to the Pb-interstitial defects occupied by the superoxide molecules. FA-rich compounds show excellent stability under continuous X-ray exposure. In Chapter 6, two ionic liquids 2-chloro-1-methypyridinium iodide (CNMP) and 1,4-dimethylpyridinium iodide (DMPI) were used as additives with different concentrations in the precursor solution of MA0.4FA0.6PbI2.8Br0.2 perovskite and thin films were fabricated. Time-dependent XPS study was performed to understand the stability of the perovskite layer. It was found that DMPI-added thin films with concentrations of 1 mg/ml and 1.5 mg/ml show excellent X-ray high-energy beam stability under 30 minutes of continuous exposure. A time-dependent photoluminescence study shows that DMPI-added films with concentrations of 1 mg/ml and 1.5 mg/ml maintain the intensity of photoluminescence, suggesting defect passivation in the thin films. Scanning electron microscopy also suggests that the DMPI additive enhances the film morphology. The thin films were kept under continuous light exposure at room temperature and high temperature, and in both cases, the thin film without the DMPI additive changed its color from black to yellow, while DMPI added thin film maintained its black color. XRD study suggests the formation of PbI2 in the bare film without DMPI additive. Further, photodetectors were fabricated with or without DMPI-added perovskite precursor solution. A summary and future scopes are discussed in Chapter 7.</p
<i>Landscape</i>
No full textThis work was exhibited under the pseudonym Antoinette J. CitizenLandscape is an interactive installation where Citizen recreated the first level of the original Nintendo Super Mario Bros game. Every element is at the scale of the visitor. On the walls are question mark boxes that you can press to recreate the sounds from the game.The work has been exhibited at:2009 Shape of Things to Come, The Block, Australia 2010 Ceci N'est Pas Un Casino!, Casino Luxembourg, Luxembourg2010 Ceci N'est Pas Un Casino!, Villa Merkel, Germany</p
Agentic Architecture: Synthesising Complexity for Regenerative Futures
No full textResearch Background: This work sits at the intersection of architectural design, AI, and systemic urbanism, addressing the urgent need for design methodologies that respond to planetary-scale complexity. It builds on and critiques traditions in computational design, ecological urbanism, and high-resolution material systems, referencing thinkers such as Luciana Parisi (Contagious Architecture), Mario Carpo (The Second Digital Turn), who identifies this work as emblematic of the second digital turn—a paradigm defined by algorithmic authorship, mass-customisation, and non-standard material logics. Carpo positions it as a key exemplar of the shift from parametric formalism to computational design ecologies that embed information directly into material and tectonic systems and Benjamin Bratton (The Stack), and Albert-László Barabási (network science). The project extends ongoing discourse around AI-augmented design cognition beyond automation or optimisation, toward generative systems aware of material, ecological, and societal entanglements. Research Contribution: Agentic Architecture: Synthesising Complexity for Regenerative Futures is a multi-channel video installation exhibited at the 2025 Venice Architecture Biennale (curated by Carlo Ratti). The work presents an original AI-driven tectonic system—AI Timber—combining ancient dry-joint logic with AI combinatorics, enabling adaptive, prefabricated, high-density urban infrastructures. It introduces a novel workflow linking n-dimensional voxelised data, multimodal generative AI, and generative algorithmic systems, including simulations of electromagnetic fields, site-adaptive Multi-Agent Systems, and field-based logics. While not explicitly robotic in this iteration, the work establishes a computational substrate that naturally connects to robotic assembly in future developments. The project consolidates two decades of research in discrete design, simulation, and systemic urban strategies into a speculative but technically grounded prototype for planetary urbanism. Research Significance: This work was directly invited by the curator to participate in the main international exhibition at the Venice Biennale—one of the most prestigious platforms in architecture—positioning it among the top global contributions in the field. Supported by RMIT, AIARCH, and RACE HPC, the work synthesises a suite of methods and ideas developed over years of research, which have also informed prior keynote engagements at forums such as CogX, TU Munich, and the Ecocity Summit. This work has attracted interest from global design-tech actors and urban innovation networks, highlighting its potential for wider impact and translational research collaborations. Its strategic and aesthetic originality, combined with its methodological depth, exemplifies high-impact design research and reflects RMIT’s global leadership in AI-driven architecture.</p
Restricting community treatment orders to people with non-affective psychosis is needed to reduce use and improve subsequent outcomes: Queensland-wide cohort study
No full textBackground The use of community treatment orders (CTOs) has increased in many jurisdictions despite very limited evidence for their efficacy. In this context, it is important to investigate any differences in outcome by subgroup. Aims To investigate the variables associated with CTO placement and the impact of CTOs on admissions and bed-days over the following 12 months, including differences by diagnosis. Method Cases and controls from a complete jurisdiction, the state of Queensland, Australia, were analysed. Administrative health data were matched by age, sex and time of hospital discharge (index date) with two controls per case subject to a CTO. Multivariate analyses were used to examine factors associated with CTOs, as well as the impact on admissions and bed-days over the 12 months after CTO placement. Registration: Australian and New Zealand Clinical Trials Registry (ACTRN12624000152527). Results We identified 10 872 cases and 21 710 controls from January 2018 to December 2022 (total n = 32 582). CTO use was more likely in First Nations people (adjusted odds ratio = 1.14; 95% CI: 1.06–1.23), people from culturally diverse backgrounds (adjusted odds ratio = 1.45; 95% CI: 1.33–1.59) and those with a preferred language other than English (adjusted odds ratio = 1.21; 95% CI: 1.02–1.44). When all diagnostic groups were considered, there were no differences in subsequent admissions or bed-days between cases and controls. However, both re-admissions and bed-days were significantly reduced for CTO cases compared with controls in analyses restricted to non-affective psychoses (e.g. adjusted odds ratio = 0.77, 95% CI: 0.71–0.84 for re-admission). Conclusions Queenslanders from culturally or linguistically diverse backgrounds and First Nations peoples are more likely to be placed on CTOs. Targeting CTO use to people with non-affective psychosis would both address rising CTO rates and mean that people placed on these orders derive possible benefit. This has implications for both clinical practice and policy.</p
Teaching Tracker Tools
No full textThe Teaching Tracker Tools website is a research-backed, interactive platform designed to support classroom observation and teacher development a powerful example of a creative educational tool for mentoring. This dynamic set of tools for collecting observations of teaching and learning in the classroom is built on research on classroom observations and feedback. The researchers invite you to use these tools to enhance teacher professional learning, for pre-service and in-service teaching. This site contains a range of Teaching Tracker Tools (T3) and the Collaborative Approach to Teaching Observations (CATO) post-observation discussion questions. Together these are designed to capture a range of elements of classroom teaching and learning, and foster discussions that lead to improvements in teaching and learning.</p