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Twenty-minute neighbourhoods highlight the importance of well-connected and mixed-used neighbourhoods and communities with proximate access to employment, essential services, public transport, and open spaces. Shorter distances together with re-prioritised public spaces encourage more active transport choices, resulting in public health benefits and reduced environmental pollution. Higher liveability brought about by mixed-use developments enables people to have equitable access to local facilities, amenities, and employment opportunities, promoting vibrancy, social cohesion, and intergenerational connections. The attributes of 20-minute neighbourhoods also combine to create places, that are acknowledged as friendly for all ages, address changing needs across the life course, and provide better support for the ageing population. Furthermore, there are indications that 20-minute neighbourhoods may be more resilient against many of the negative impacts of stringent public health protocols such as those implemented in periods of lockdown during the Covid-19 pandemic. In this article, we evaluate and compare planning policies and practices aimed at establishing 20-minute neighbourhoods in Melbourne (Australia) and Scotland (the UK). Using case studies, we discuss similarities and differences involved in using place-based approaches of 20-minute neighbourhoods to address 21st-century challenges in key areas of health and wellbeing, equity, environmental sustainability, and community resilience.

A digital twin is a virtual representation of a physical object or process capable of collecting information from the real environment to represent, validate and simulate the physical twin’s present and future behavior. It is a key enabler of data-driven decision making, complex systems monitoring, product validation and simulation and object lifecycle management. As an emergent technology, its widespread implementation is increasing in several domains such as industrial, automotive, medicine, smart cities, etc. The objective of this systematic literature review is to present a comprehensive view on the DT technology and its implementation challenges and limits in the most relevant domains and applications in engineering and beyond.

We present findings from a geotechnical survey for a gravity-based Wave Energy Converter (WEC) to be installed in King Island, Tasmania. The goal of this work was to assess the deployment location for a 200 kW Oscillating Water Column (OWC) and to identify possible challenges for the foundation of the structure to make it Australia’s first operational offshore OWC for a remote offshore island. The proposed location for this OWC is the southeast coast of King Island, Tasmania, approximately in a depth of ~5.5 m LAT. The survey included sub-bottom profiling, sediment cores, surficial sediment strength by penetrometer drops, seabed imagery, as well as long-term deployment (>6 months) of pressure sondes and an acoustic wave current profiler (AWAC). Our findings demonstrate that the WEC can be installed in the proposed location with significant wave height Hs ~1–1.5 m and peak period Tp of 12–14 s, and that the site exhibits sufficient sand coverage and quasisteady bearing capacity. The period between the survey and prospective deployment is only one year, demonstrating the efficiency of the survey methods (in particular, the use of the penetrometer) and OWC design but also the suitability of the candidate site for this device design.

Particle number, particle mass, and CO2 concentrations were measured on the curb of a busy urban busway used entirely by a mix of diesel and CNG operated buses. With the passage of each bus, the ratio of particle number concentration and particle mass concentration to CO2 concentration in the diluted exhaust plume were used as measures of the particle number and mass emission factors, respectively. With all buses accelerating pastthe monitoring point, the results showed that the median particle mass emission from CNG buses was less than 9% of that from diesel buses. However, the median particle number emission from CNG buses was 6 times higher than the diesel buses, and the particles from the CNG buses were mainly in the nanoparticle size range. Using a thermodenuder to remove the volatile material from the sampled emissions showed that the majority of particles from the CNG buses, but not from the diesel buses, were volatile. Approximately, 82% of the particles from the CNG buses and 38% from the diesel buses were removed by heating the emissions to 300 degrees C.

One of the most encouraging sorts of renewable energy is ocean wave energy. In spite of a large number of investigations in this field during the last decade, wave energy technologies are recognised as neither mature nor broadly commercialised compared to other renewable energy technologies. In this paper, we develop and optimise Power Take-off (PTO) configurations of a well-known wave energy converter (WEC) called a point absorber. This WEC is a fully submerged buoy with three tethers, which was proposed and developed by Carnegie Clean Energy Company in Australia. Optimising the WEC’s PTO parameters is a challenging engineering problem due to the high dimensionality and complexity of the search space. This research compares the performance of five state-of-the-art metaheuristics (including Covariance Matrix Adaptation Evolution Strategy, Gray Wolf optimiser, Harris Hawks optimisation, and Grasshopper Optimisation Algorithm) based on the real wave scenario in Sydney sea state. The experimental achievements show that the Multiverse optimisation (MVO) algorithm performs better than the other metaheuristics applied in this work.

Transportation systems are one of the leading sectors that contribute to greenhouse gas emissions that lead to enhance global warming. The electrification of vehicles is a promising solution to this widespread problem; however, integrating electric vehicles (EVs) into existing grid systems on a large scale creates several problems, both for consumers and for utilities. Accelerated aging of expensive grid assets, such as power transformers, is one of the primary issues that these utilities are facing. This problem can be addressed with battery energy storage systems (BESS), which acts as buffer between demand and supply. Accordingly, this paper proposes a novel strategy for optimal sizing of BESS based on thermal loading of transformers. This paper also investigates issues associated with high penetration levels of rooftop photovoltaics (PVs), determining the synergy between EV charging load and BESS. The proposed solution is treated as an optimization problem, in which a new time of use (ToU) tariff is utilized as a demand response signal to reduce the accelerated aging of transformers. Extensive simulation results show that the size of BESS can be considerably reduced based on the proposed methodology, thereby avoiding accelerated aging of transformers without the need to augment existing grids.