Arup (officially Arup Group Limited) is a British multinational professional services firm headquartered in London which provides engineering, architecture, design, planning, project management and consulting services for all aspects of the built environment. Founded by Sir Ove Arup in 1946, the firm has over 16,000 staff based in 96 offices across 35 countries around the world. Arup has participated in projects in over 160 countries.Arup is owned by trusts, the beneficiaries of which are Arup's past and present employees, who receive a share of the firm's operating profit each year.
Light pollution is an important issue that requires effective strategies to mitigate its negative effects while meeting the needs of the community. People’s perceptions of light pollution can influence their behaviour and attitudes towards lighting practices, thereby impacting the success of light pollution reduction effort and improvements in urban quality of life. However, people’s feelings about the lighted environment can be influenced by personal experiences, expectations, and cultural background, leading to different perceptions of lighting than what is actually present. To understand the perception of light pollution, a street survey was conducted in Hong Kong with 220 pedestrians across three site locations. The survey collected information on demographics and assessed perceptions of illuminance, colour temperature, uniformity, and glare, which formed the perceived lighting quality (PLQ) index. The results showed that there is no difference in the level of comfort between males and females or between younger and older participants under certain lighting conditions. However, individuals with lower education levels reported significantly lower comfort levels compared to those with higher education levels. The study also found a strong negative correlation between PLQ and perceived illuminance level. Additionally, both perceived colour temperature and glare level have a significant correlation with PLQ. Perceived illuminance has a weak correlation with perceived colour temperature and glare level, but perceived illuminance increases with perceived glare. Policymakers and lighting designers need to consider the perceptions of light pollution to develop effective strategies that meet the needs of the community.
The growing availability of big data and digital planning tools offers new ways to understand, analyse and design cities. Urban design pedagogy has accordingly adapted, embracing new analytical tools and methods to study the built form, including computer-aided design and parametric modelling. This paper investigates how procedurally modelled shape grammars can operationalise theoretical concepts of urban elements, patterns, morphological studies to inform design proposals. This investigation is based on an empirical study of an urban design studio conducted in Singapore where human-centric design principles were translated into computational logic for design synthesis. Through qualitative observations of the CGA modelling for urban design, the translation process and points of friction encountered are documented, offering new insights for urban design pedagogy and software development in the context of high-density Asian cities.
This paper presents an innovative Reduced-Order Model (ROM) for merging experimental and simulation data using Data Assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the Ensemble Kalman Filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost Singular Value Decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate (CR,ub) of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low Relative Root Mean Square Error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app1.
The built environment is vulnerable to climate-induced extreme events and natural disasters, which are repeatedly exposing communities to severe consequences and market disruptions. In response, the construction industry is developing resilient technologies for buildings, but the proposed solutions are often not cost-effective, rarely eco-friendly and typically fail to address multiple hazards present in many locations. These shortcomings stem from the absence of a clearly defined framework for quantifying holistic multi-hazard resilience. As a result, investment decisions are ill-informed and technical solutions are sub-optimal. This paper redresses this issue by proposing quantitative indicators and introducing the Resilience Readiness Levels to assess the resilience of buildings, considering multi-domain factors (physical, social, economic, environmental) in single or multi-hazard contexts (heat, seismic, wind, flood). The proposed resilience indices and calculation methods are based on a diverse set of scientific literature and real-world practices, and are demonstrated on Dutch and Italian urban blocks with different local hazards and building layouts. The results show that the multi-domain resilience approach can support informed early-stage building design and retrofit decision-making for single hazards, while aiding prioritization and intervention planning for improving building disaster preparedness in multihazard scenarios.
Drag embedment anchors are a key threat to buried subsea linear infrastructure, such as power/data cables and pipelines. For cables, selecting a burial depth is a compromise between protecting the cable from anchor strike and the increased cost of deeper installation. This paper provides an efficient large deformation, elastoplastic Material Point Method-based soil-structure interaction predictive tool for the estimation of anchor penetration based on Cone Penetration Test (CPT) site investigation data. The tool builds on earlier work by the authors supplemented by three key developments: modelling assemblies of rigid bodies (necessary for articulated anchors), a partitioned domain approach to enable accurate and efficient modelling of long anchor pulls, and an improved means of modelling rotational inertia. The numerical model is calibrated using CPT data and then used to predict the penetration behaviour of two different drag anchors across a range of relative density sands under drained conditions with validation against scaled geotechnical centrifuge physical tests. Numerical simulations both confirm assumptions in, and identify key issues with, the UK Carbon Trust's Cable Burial Risk Assessment (CBRA) approach for estimating anchor penetration. In particular, the results confirm that anchor penetration scales linearly with fluke length but also that the penetration of drag anchors is highly dependent on both the relative density of the sand and the full geometry of the anchor. The numerical model presented in this paper enables site-specific anchor-penetration assessment along cable routes and can be used to evaluate the performance of different anchor designs and sizes in varied soil conditions.
