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Integration of Electric Vehicles into Multi-energy Systems
No full textPenetration of multi‐energy systems (MESs) in power grids, mainly in the form of new disruptive technologies such as the co‐generation of heat and electricity systems, has increased in recent years. MESs are recognized as a successful method of promoting the energy efficiency and have been broadly used in contemporary metropolitan areas. An MES typically consists of multiple interconnected networks, including natural gas, transportation, and electricity distribution networks, which are integrated into an energy hub (EH). Due to the coupling components in the MES, different forms of energy can be converted, stored, and distributed using integrated energy converters and storage devices. The transport sector is one of the main energy consumers in EH, and an important source of carbon emissions indeed. This sector is accountable for over 20% of the emissions that can be removed using transport decarbonization strategies such as electrification. Electric mobility provides a great opportunity for sustainable transport when integrated with renewable resources, such as solar energy. Despite significant advantages, e‐mobility still has many challenges to be addressed. Charging electric vehicles (EVs) would greatly influence the demand for EH. That means an unavoidable interdependence between the energy and transport infrastructure in the MES when we go toward transport electrification. This chapter aims to review original research works about modeling, management, and intelligent controls of MES integrating EV routing and charging
The Subjective City: Towards a Reconceptualization of Urban Interiority
No full textInspired by the philosopher and psychoanalyst Félix Guattari’s essay Ecosophical Practices and the Restoration of the ‘Subjective City’ and his call for ‘the evolution of urban mentalities’, this chapter poses the question of interiority in the context of the urban environment. A selection of existing works that address a conjunction between interiority and urbanism are reviewed and considered in relation to how the author(s) position ‘interiority’ as a concept. This research reveals a consistent refrain in equating interiority as something associated with the individual and first-person subjectivity. Guattari’s use of ‘subjective’ in conjunction with ‘city’ refers not to the relation between individuals and urban space but to a way of conceptualizing the urban environment as a ‘mental ecology’. Guattari claims this is now the urgent task facing all creative practices associated with cities – urban planners and designers, architects, landscape architects (and I would add, interior designers) – as cities and, more broadly, the global biosphere confront unprecedented transformations due to population growth, environmental conditions etc. To address the challenge, Guattari says we require ‘new practices’, ‘new styles of living’ and the production of ‘this new subjectivity’. The invitation to reconceptualize urban interiority is extended here
The Future and Funding of Transnational Broadcasting and Soft Diplomacy in the Indo-Pacific
No full textThere is no more time to waste in ensuring ongoing funding for Australia’s transnational broadcast voice in the Indo-Pacific, focused on the new digital age. This book has acknowledged that many of the countries in the Indo-Pacific are under intense pressure from a range of actors, and has argued that Australia’s public broadcaster the ABC is best-placed to assist its neighbours, particulaly those which have under-developed local news and information eco-systems. While a recent boost to Australian public broadcast funding in the region, and further Australian government funding for development aid, has been welcomed, these funds are not guaranteed for the long term, and are tied to the generosity of the elected government of the day; this is certainly not enough to regain trust in the region, nor support the many and varied information needs of countries of the Indo-Pacific. It is time for Australia to broaden its view from supporting just its closest neighbours in the Pacific, to the wider Indo-Pacific. With climate change, the increasingly fraught relations between nations, and the complex political, security and media environment, Australia has an opportunity to increase transnational broadcast funding and ensure that this service is safe from future government or internal management cuts. If Australia is to meet the strategic ambitions for the region by China, or indeed the ambitions of other nations, it must take a long-term multi-generational vision to the region including securing widespread regional support through long-term funding for its trasnational broadcast and digital news services
The Role of Lawyers and Family Dispute Resolution Practitioners in Family Dispute Resolution Where There is Violence: Reflections on Practice
No full textAppropriate dispute resolution (‘ADR’) can be an effective and efficient way to resolve disputes through the use of processes such as mediation, which involves the use of a neutral impartial third party to facilitate conflict resolution. However, despite its advantages as an informal method of solving disputes, ADR has been criticised for providing ‘second-class justice’ to disputants due to inconsistencies in practice and legislation, and for failing to address power imbalances between parties. Power imbalances can be especially an important consideration in the family law jurisdiction where such imbalances arise due to family violence. Research underpinned by feminist theory has critiqued the strengths and shortcomings of mediation in family law disputes. This research explores the risk of using mediation where there are power imbalances, particularly where one party to the dispute is experiencing family violence.
In the context of family law, mediation is often seen as preferable to adversarial dispute resolution processes (such as litigation) as it incorporates parties’ voices and emotions as they seek to resolve issues in dispute and plan for effective future parenting. Mediation in family disputes permits recognition of the human and emotional dynamics during the breakdown of family relationships and the need for these to be dealt with professionally and skilfully while also paying attention to any power imbalances between the parties.
The form of ADR used in the family law field in Australia is referred to as family dispute resolution (FDR). FDR is led, or managed by, either family lawyers or FDR practitioners (FDRPs). Facilitation of FDR to assure parties’ voices are heard and included in the legal design of post-separation parenting agreements has the capacity to empower the vulnerable. Family lawyers and FDRPs assess risk, refer clients to specialist services and assist both parties to create a sustainable agreement.
This qualitative research project examines the practice of FDR through semi-structured interviews with family lawyers and FDRPs to explore their role in FDR. The research explores lawyers’ and FDRPs’ understandings of their practices and the ways that they have adapted their roles where the client was subjected to family violence. The research also explores the extent to which family lawyers have adapted their traditional role as spokespersons for their clients. Further, the project explores how family lawyers and FDRPs have acted effectively for their clients and the challenges they identified in achieving successful FDR, particularly in cases where parties were affected by a history of family violence.
The research findings will assist family lawyers and FDRPs to clarify and improve their practice working with clients experiencing family violence. The findings in this study demonstrate that family violence remains unacceptably widespread in Australia. Participants agreed that there is room for improvement to practice for both family lawyers and FDRPs and highlighted the need for a national practitioner risk assessment and management framework for identifying family violence. Further, the participants agreed that ongoing family violence education and training, and a collaborative case-based approach between family lawyers and FDRP’s will improve FDR practice, where there is family violence.</p
Textile Waste Management in Australia: Current Practices and Strategies for Reducing Environmental Impacts
No full textThe textile industry plays a crucial role in global economies, yet it faces significant environmental challenges, particularly concerning textile waste. This thesis undertakes an examination of sustainability challenges within Australia's textile industry, with a particular focus on textile waste management. The study aims to understand the current state of textile waste, develop a model to track textile flow from consumption to end-of-life stages, estimate textile consumption and waste generation, and evaluate associated environmental impacts, particularly in terms of carbon emissions. Through a comprehensive review of scholarly literature and empirical research, the study identifies critical insights, including insufficient data on textile consumption and waste, inadequacies in processing capacities, and the imperative for enhanced regulatory clarity concerning textile waste legislation. Material Flow Analysis serves as a methodological cornerstone to quantify waste streams, revealing significant volumes directed towards landfills despite recycling efforts. Furthermore, the study conducts a comparative analysis of energy demand and carbon footprints across diverse textile waste management systems in Australia, highlighting the potential of sustainable waste management practices to mitigate environmental impacts. The outcomes underscore the complexity of textile waste management and emphasize the necessity for collaborative efforts to address this exigent concern. This thesis constitutes an original academic contribution, furnishing insights gleaned from empirical research articles that not only deepen scholarly understanding but also offer actionable implications for policy formulation and industry practice aimed at fostering sustainability within the textile industry.</p
Animating Elderhood Datascapes of Ageing in Place
No full textEntirely built with AI tools, this video blends symbolic imagery and narration to explore curiosity, digital inclusion, and cognitive vitality in later life. The research reframes AI as a companion—adaptive, respectful, and human-centred—bridging generations and redefining how we age, learn, and stay connected.</p
Progressive Damage Analysis for Aerospace Composite Structures Subjected to Impact Loads
No full textAdvanced fibre-reinforced composite laminates are increasingly utilized in civil aircraft structures due to their high stiffness and strength-to-weight ratio. Carbon Fibre-Reinforced Polymers (CFRP) materials possess excellent in-plane mechanical characteristics but exhibit relatively high brittleness through the thickness. Consequently, internal damage such as fibre breakage, matrix-cracking, resin plastic deformation, and interlaminar delamination are commonly observed in layered composite structures subjected to out-of-plane impact loads. Identifying damage-tolerant designs in laminated composite materials subjected to low-velocity (LVI) or high-velocity impact (HVI) by foreign objects is challenging and complex to evaluate during the early design stages of new composite airframe structures.
The complexity arises from the numerous parameters defining laminate configurations (e.g., material properties, layup configuration, ply thickness, and fibre architecture) and impact scenarios (e.g., impactor geometry, material, mass, energy, or velocity). Conducting physical tests for every possible configuration during the design phase is time-consuming and prohibitively expensive. In addition, numerical and analytical methods are not fully reliable in predicting failure, durability, or damage propagation in fully assembled composite structures. As a result, extensive laboratory testing is still required to certify the performance and impact behaviour of laminated composite structures. This study aims to develop a robust and efficient simulation methodology for predicting damage and energy absorption in composite structures under various dynamic loads, focusing on two selected material architectures: layered unidirectional and triaxial-braided composites.
This research builds on existing literature by introducing a high-fidelity meso-scale modelling framework that emphasizes both intralaminar and interlaminar mechanical behaviours in selected material fibre-architectures. The objective is to establish physics-based guidelines for defining numerical model parameters based on constitutive experimental properties, thereby minimizing the need for extensive calibration and correlation phase. A series of closed-form expressions, derived from evaluated material mechanical properties and fibre-architectures, are introduced to define Finite Element Analysis (FEA) numerical fracture initiation and propagation parameters, which are crucial for the selected material structures under varying impact loads.
The developed methodology includes innovative numerical techniques to characterize the elastic response and post-failure fracture mechanics evolution of selected composite materials. Constitutive intralaminar and interlaminar fracture mechanisms observed in the chosen material architectures are analysed and modelled separately using structured cohesive interface elements. A series of intralaminar single-element numerical analyses and fracture toughness mechanical specimen models are provided to investigate and characterize damage nucleation and evolution across the selected material structures. A set of literature benchmark analyses is included to verify the developed numerical modelling framework. A fibre-aligned shell-cohesive modelling approach is introduced to replicate the mechanical behaviour of layered unidirectional composites under various loading conditions. Conversely, a solid-cohesive meso-scale modelling technique is presented for analysing the intertwined fibre architecture characteristic of textile triaxial-braided composites. A series of MATLAB tools are proposed to automatically reconstruct the designed meso-scale mesh topology based on selected mesh sizes and composite panel geometries.
An extensive experimental study is conducted to assess the low-velocity and high-velocity impact performance of selected composite material architectures. The study specifically addresses material sensitivity to Barely Visible Impact Damages (BVID) and ballistic impact loads with velocities ranging from 5 m/s to 450 m/s. A detailed analysis of contact force evolution and residual damage morphology through post-mortem panel analysis and X-ray CT-scans is provided to validate the developed numerical model results. A scientific photogrammetry environment is designed to capture 3D high-speed displacement and deformation fields of the back-face panel when impacted by a high-velocity axial-symmetric metallic projectiles. The investigated material architectures are compared under selected dynamic loads to evaluate their overall impact performance and assess their damage tolerance mechanical properties.
This research advances the understanding of impact behaviour in composite structures by offering a robust simulation methodology that reduces reliance on experimental calibration and correlation techniques. A close overlook of fracture mechanisms and damage tolerant mechanical properties for selected material architectures is provided and compared with the computed numerical solutions. The findings significantly advance the development of progressive damage numerical models, offering valuable insights for virtual testing and supporting the building block certification process used in aerospace engineering design.</p
Energy Analytics: Application of Machine Learning to Electricity Data Analytics
No full textFossil fuel usage results in consequences that harm the environment, economy, and human life, among which climate change is the most important one. Renewable energy resources and electrification of conventional systems are potential ways to replace fossil fuel usage. A smart grid is an infrastructure that facilitates the transition to more environmentally friendly energy sources. Smart meters provide large-scale data that raises the need for analysis. Such analysis is crucial to maintaining and planning to build more efficient smart grids. Traditional methods for analysing time series data recorded by smart meters are not flexible and do not generalise well to unseen cases. Deep learning techniques have proved to be useful in analysing such complex data and providing insights for smart grid planners and operators. The aim of this thesis is to explore the effectiveness of deep learning techniques in analysing energy data.
The thesis develops a new tool to forecast energy generation from photovoltaic (PV) cells. Solar energy is one of the main forms of renewable energy resources which is captured by PV cells. Since PV generation heavily depends on heavily uncertain variables, like weather conditions, the PV power generation problem is a challenging problem. The stochastic nature of the input features introduces uncertainty that makes power generated from PV cells less dispatchable compared to conventional generation methods. Therefore, to make PV generation better dispatchable, an accurate forecast is required. We propose a deep learning-based forecaster, that combines the power of convolutional and recurrent neural networks, that outperforms state-of-the-art methods.
The second research addressed here is to identify electric vehicles (EVs) from smart meter recordings. The electrification of transport systems will help decarbonize the transport systems. However, charging EVs imposes overhead on the grid that can cause voltage fluctuations. Therefore, EV identification has a significant application in the management of the local grid by energy distributors. The major issue is that the number of EV users is much lower than non-EV users which raise the imbalance issue for the dataset. Inspired by anomaly detection ideas, we propose a novel EV identification technique based on deep learning that takes an unsupervised approach and outperforms baselines. By doing so, we do not need to manipulate the input data. Instead, we rely on the abundance of the non-EV part of the input data.
Finally, the thesis develops deep learning techniques for fault/anomaly detection in multi-sensor systems. The major issue associated with this problem is the lack of labeled time series which raises the need for unsupervised learning. The other challenge is the multivariate nature of such data and the correlation information that exists between several sensors. Often, energy data come in the form of multivariate time series with significant inter correlations. Taking this correlation into account is a major challenge that impacts the performance of anomaly detectors. We propose a deep learning that considers the correlation between different sensor time series explicitly. Our method models both temporal and spatial correlations between different time series. We prove empirically the effectiveness of our model.</p
Mapping cross-national conceptions of essential energy to advance housing energy justice – Urban tour photos - Obuda
No full textThe project entailed qualitative research from focus groups and urban tours. The study leveraged the cross-national collaboration of the WELLBASED project. WELLBASED was a European Union Horizon 2020 project that was trialling energy poverty interventions between 2021 and 2025 across six cities: Leeds (UK), Valencia (Spain), Heerlen (Netherlands), Edirne (Turkey), Obuda (Hungary) and Jelgava (Latvia). The study captured and compared the WELLBASED professionals’ perceptions of essential energy.This dataset contains the photos of the urban tour in Obuda, Hungary, in the summer of 2023.</p
Mapping cross-national conceptions of essential energy to advance housing energy justice –Comic
No full textThe project entailed qualitative research from focus groups and urban tours. The study leveraged the cross-national collaboration of the WELLBASED project. WELLBASED was a European Union Horizon 2020 project that was trialling energy poverty interventions between 2021 and 2025 across six cities: Leeds (UK), Valencia (Spain), Heerlen (Netherlands), Edirne (Turkey), Obuda (Hungary) and Jelgava (Latvia). The study captured and compared the WELLBASED professionals’ perceptions of essential energy.This dataset contains varied versions of a Comic that was produced as part of this project.</p