Mott MacDonald (Czechia)

The research presents a new computational system which allows researchers to examine piezoelectric plate structural stability and dynamic performance in landscape design projects that need to withstand wind loads and use energy-harvesting systems. The researchers create wind conditions for their research by using two atmospheric parameters which include the wind attack angle and the average wind speed to simulate outdoor conditions that affect piezoelectric plate performance. The plates are assumed to rest on viscoelastic–concrete auxetic foundations which provide landscape-integrated structures with improved damping abilities and unique deformation patterns. A power-law material model enables the creation of piezoelectric plate material properties which simulate functional gradients that exist throughout the thickness of the material. The research uses higher order shear deformation theory (HSDT) to establish a precise method for examining transverse shear effects which does not require shear correction factors. The electromechanical coupling mechanisms find their complete description through Maxwell's equations while Hamilton's principle serves as the basis for deriving the equations which govern motion because it ensures energy conservation. The harmonic differential quadrature method uses Chebyshev polynomial grid points to achieve spatial discretization of coupled partial differential equations which results in high numerical accuracy and efficient computational performance. The primary solution method uses Physics-informed deep neural networks (PIDNNs) as an Artificial intelligence technique to address the deficiencies which traditional numerical solvers experience during complex multi-physics simulations. The PIDNN framework enables prediction of stability boundaries and vibration characteristics plus electromechanical responses through its integration of governing physical laws into the loss function. The proposed method successfully analyzes smart piezoelectric plate systems which operate in wind-sensitive landscape design applications.

<p>This paper traces our evolution toward a 'forest-sensitive' design approach for footbridges through three case studies on Vancouver’s North Shore: the Casano-Loutet Pedestrian and Bicycle Overpass, Spirit Trail Lynn Creek Crossing, and Spirit Trail McCartney Creek Crossing. We document a shift in perspective from treating trees as obstacles to embracing them as design generators and that can positively shape infrastructure. Using empathetic digital tools—high-definition LiDAR scanning, realistic 3D point clouds, and advanced visualization—we could respond to forest complexity with greater intuition and precision than convetional methods allow. The resulting footbridge designs demonstrate an extrinsic elegance that follows from thoughtful contextual integration.</p>

Summary This study presents a comparison of integrated palynostratigraphy from two significant Triassic successions: the Bunter Sandstone storage complex in the Southern North Sea and the Sassendalen and Kapp Toscana groups on the Barents Shelf. Each study region serves distinct purposes—CO2 storage in the Southern North Sea and hydrocarbon exploration on the Barents Shelf—yet both require refined stratigraphic frameworks for effective resource development. For the Southern North Sea, analysis of 500 samples from 14 wells led to the establishment of a new palynozonation, addressing a critical gap in regional biostratigraphy and improving cross-border correlation between the UK and Dutch sectors. On the Barents Shelf, palynological and macrofossil data were integrated with sequence stratigraphy across 42 localities, refining chronostratigraphy and knowledge of the spatio-temporal distribution of reservoir sands. Our findings highlight how climate and environmental shifts influenced Triassic vegetation and sedimentation, with species turnover paralleling major marine transgressions and/or global climatic changes. The frameworks developed offer broader relevance, with potential applications to other Triassic successions, including those in the East Irish Sea Basin and Central and Northern North Sea.

Digital twins are a new paradigm for our time, offering the possibility of interconnected virtual representations of the real-world.The concept is very versatile, and has been adopted by multiple communities of practitice, policymakers, researchers and innovators.A significant part of the digital twin paradigm is about interconnecting digital objects, many of which have previously not been combined.As a result, members of the newly forming digital twin community are often talking at cross-purposes, because they have different starting points, assumptions and cultural practices.These differences are often due to the established philosophical world-view adopted within specific communities of practice.Therefore, in this paper we explore the philosophical context which underpins the concept of digital twins.As part of this effort we offer a set of philosophical principles for digital twins, which are intended to help facilitate their further development.Specifically, we argue that the philosophy of digital twins is fundamentally holistic.We further argue that digital twins are reconstructivist, meaning they aim to reconstruct the behaviour of a physical twin by assembling multiple "components", e.g.models, agents and data sets.Importantly, these digital twin components have the potential to capture emergent behaviours when they are dynamically assembled.Lastly, we discuss the following four questions (i) What is the distinction between a model and a digital twin?(ii) What previously unseen results can we expect from a digital twin?(iii) How can emergent behaviours be predicted?(iv) How can we assess the existence and uniqueness of digital twin outputs?

This paper presents a case history of one-dimensional time-domain nonlinear site response analysis for a major infrastructure project in the San José area, USA. The subsurface material of the study site consists of Holocene alluvial deposits with interbedded and crosscut clays and silts, sands, and gravels. Two levels of design earthquakes were considered herein associated with the return periods of 225 and 975 years. For each design level, site response analyses were performed to propagate a suite of eleven pairs of horizontal input ground motions at the reference soil horizon (a depth of about 75 m or 240 ft; VS30 of about 490 m/s or 1600 ft/s) through a site-specific ground model. The site-specific ground model also accounts for strain rate effects on clay layers. A series of sensitivity evaluations were also completed for verifying and enhancing understanding of dynamic response of the study site. The site response analysis results show the site exhibits high nonlinearity, especially in clay layers, de-amplifying short-to-intermediate period content (0.01 to 1 s) while amplifying long period content. Also, a comparison of surface response spectra from the site response analysis versus ground motion models is presented herein highlighting the design implications of conducting site response analyses at soft sites, where high nonlinearity is anticipated.

Originally implemented in 1995 to communicate bathing water quality to the public, Auckland Council's water quality management program provided an assessment based on retrospective water quality sampling. Safeswim (www.safeswim.org.nz) was deployed in 2017 to overcome limitations related to sampling data availability and to maximize the use of water monitoring data by integrating such data with real-time modeling, artificial intelligence, big-data analytics, visualization, and information dissemination. Safeswim is shaped around a single, central data platform Moata that gives Safeswim its capacity for managing and analyzing large, diverse datasets while running multiple models to provide Aucklanders with information updated in 15-min intervals. The platform has facilitated Safeswim's greatly increased reliability and prediction performance over five years on from its first implementation, to close to 90% overall accuracy, and as a result has grown into a reliable and efficient public decision support system for the Auckland Council. The success of Safeswim in Auckland has led other communities around the world to consider and are inspired to implement similar programs.

Adding new unit operations to drinking water treatment systems requires consideration of not only efficacy for its design purpose but also costs, water quality characteristics, impact on overall regulatory compliance, and impact of other treatment unit operations. Here, pilot study results for ion exchange (IX) and granular activated carbon (GAC) are presented for a utility with both per- and polyfluoroalkyl substances (PFAS) and volatile organic contaminant removal needs. Specifically, the impact of upstream air stripping and phosphate addition on PFAS treatment performance was evaluated. Modeling was used to fit the IX and GAC pilot data and predict performance under different scenarios. GAC performance was generally consistent for treating water before or after the air stripper, but the addition of phosphate prior to air-stripping resulted in a loss of 15%-25% capacity for some PFAS on IX media, demonstrating the need to consider the entire treatment train before implementing PFAS removal unit operations.

Abstract With over 21 million cubic metres of material (equivalent to 8,400 Olympic swimming pools) earmarked to be excavated and moved across the 90 km of the northern section of the High Speed Two Phase One route, an accurate understanding of the material types for the re-use of materials in earthworks is a prerequisite for the efficient delivery of construction and optimal use of materials. Such an understanding is not only important to ensure the earthworks meet the technical standards but also to minimising the carbon footprint associated with the re-use of materials during construction. Conventional methods for assessing the suitability for reuse of excavated material focus on a statistical review of ground investigation data against the Specification of Earthworks (SCEW) Series 0600 supported by 2D long sections. However, this does not always give a clear indication of the spatial distribution of materials in 3D across the length and breadth of the assets and therefore the proportions generated once practicalities of separating material are considered. This restricts the opportunity to refine the mass haul strategy and potentially leaves significant residual risks to be managed during construction. This can have significant cost, environmental and carbon implications, particularly if additional material needs to be imported or sent to landfill. This paper will outline a digital evaluation approach adopted by the Integrated Project Team (IPT) on N1N2 utilising a 3D ground model and asset design models to unlock the optimisation of the mass haul strategy. The cost savings, risk reduction and sustainability benefits will be detailed through a series of case studies across the N1 and N2 contracts on the northern section of the Phase one route. The technique is expected to continue to bring benefits through detailed design and construction, but the benefits also extend beyond HS2 to infrastructure projects where a mass haul strategy is required.

Most coastal infrastructure is designed according to an acceptable risk of a specific event (e.g., the 100-year flood). However, there are challenges with establishing risk-based design conditions for problems that depend on multiple forcing conditions, such as compound flooding. For compound flooding, the flood extent will depend on both storm surge and precipitation, and there may be multiple combinations of these variables that result in the same flood extent. Traditionally, this problem might be addressed by making a conservative assumption in one of these variables and performing an extremal analysis on the other; however, this process is fraught with uncertainty, and the results of this method do not offer any true statistical representation of risk. This paper explores a simple methodology for establishing joint extremal probabilities between environmental variables that may be correlated, such as precipitation and storm surge, which are both associated with tropical storms.