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The realism of ocean visual systems is a key challenge in developing maritime simulators within ocean engineering. Achieving high realism in turbulence simulation is crucial for enhancing the effectiveness of these simulators. Traditional spectrum-based methods lack realism and fail to generate turbulent interaction effects. To address this, an improved Hybrid Smoothed Particle Hydrodynamics method is proposed for simulating ocean scenes, incorporating advanced micropolar fluid model techniques to enhance detail realism. The proposed algorithm introduces a density constraint solver that directly adjusts particle distribution and couples it with a divergence-free velocity solver, aiming to construct a physical-based fluid simulation framework that enhances detail realism in ocean scene simulations. The results demonstrate that the proposed method effectively accelerates the convergence of constraint conditions, reduces simulation time, and improves overall incompressibility. Additionally, the introduced turbulence model addresses high-frequency detail loss caused by numerical dissipation in the Smoothed Particle Hydrodynamics method, enabling more complex navigation scenarios. This study provides theoretical and technical references for achieving realistic ocean scene simulations in maritime simulators. [ABSTRACT FROM AUTHOR]

Urban communities have long been pivotal in wealth creation and technological innovation. In the contemporary context, their modus operandi is intricately tied to a diverse array of critical infrastructure systems (CISs). These systems—encompassing utilities, transportation, communication, and more—are indispensable for daily life; however, historical lessons underscore that the ever-growing interdependence among modern CISs has sapped their robustness. Furthermore, this vulnerability is compounded by the intensifying natural hazards catalysed by climate change, leaving urban communities with eroded resilience. Against this backdrop, pilot studies have harnessed breakthroughs in artificial intelligence (AI) to chart a new course toward resilient urban communities. This paper illuminates AI-driven resilience by reviewing the latest research in key aspects including (1) the limitation of state-of-the-art resilience assessment frameworks; (2) emergency response as a novel blueprint featuring swift response following catastrophes; (3) efficient loss assessment of CISs using AI algorithms; and (4) machine-learning-enabled autonomous emergency response planning. The remaining challenges and hardships faced on the journey toward resilient urban communities are also discussed. The findings could contribute to the ongoing discourse on enhancing urban resilience in the face of increasingly frequent and destructive climate hazards. [ABSTRACT FROM AUTHOR]

In fire emergency management, a delayed execution will cause a significant number of casualties. Conventional fire drills typically only identify a certain percentage of evacuation bottlenecks after the building has been constructed, which is hard to improve. This paper proposes an innovative framework to validate fire emergency evacuation at the early design stage. According to the experience and knowledge of fire emergency evacuation design, the proposed framework also introduces a seamless two-way information channel to embed fire emergency evacuation simulations into a BIM-based design environment. Several critical factors for fire evacuation have been reviewed in relevant domain knowledge, which is used to build virtual characters to test in experimental scenarios. The results are analyzed to validate fire emergency evacuation factors, and the feedback knowledge is stored as a knowledge model for further applications. [ABSTRACT FROM AUTHOR]

The construction industry has increasingly adopted digital construction processes and technologies, fueled in part by governmental mandates aimed at modernizing construction workflows. While these advancements promise efficiency across different phases of a project, the efficacy of the digitally generated information often remains contingent on its alignment with the specific information exchange requirements of individual organizations. Current efforts to establish interoperable data schemas have made strides, yet challenges persist, particularly when tailoring information to meet the unique needs of organizations responsible for the operation and management of built assets. This paper dissects the outcomes of standard digital construction processes applied to a linear infrastructure project, highlighting observed shortcomings such as information overload and the difficulty of adapting the information for asset management needs. Building upon these findings, this paper introduces a framework aimed at streamlining the production of essential project information. This framework was developed through a series of expert workshops and subsequently tested on a separate infrastructure project, offering insights into its potential benefits and limitations. [ABSTRACT FROM AUTHOR]

Intelligent fault diagnosis (IFD) is essential for preventative maintenance (PM) in Industry 4.0. Data-driven approaches have been widely accepted for IFD in smart manufacturing, and various deep learning (DL) models have been developed for different datasets and scenarios. However, an automatic and unified DL framework for developing IFD applications is still required. Hence, this work proposes an efficient framework integrating popular convolutional neural networks (CNNs) for IFD based on time-series data by leveraging automated machine learning (AutoML) and image-like data fusion. After normalisation, uniaxial or triaxial signals are reconstructed into -channel pseudo-images to satisfy the input requirements for CNNs and achieve data-level fusion simultaneously. Then, the model training, hyperparameter optimisation, and evaluation can be taken automatically based on AutoML. Finally, the selected model can be deployed on a cloud server or an edge device (via tiny machine learning). The proposed framework and method were validated via two case studies, demonstrating the framework's availability for the automatic development of IFD applications and the effectiveness of the proposed data-level fusion method. [ABSTRACT FROM AUTHOR]

As an organically interwoven system of people, government organizations and businesses, modern cities have become the engine that drives economic growth and technological revolution for each nation [[1]]. To catch up with these soaring functional demands, more CISs are expected to be constructed, which will further accelerate climate change, insomuch as 70% of the global greenhouse-gas (GHG) emissions emanate from the construction and operation of CISs [[5]]. Decarbonization of the Energy Sector Decarbonization of the energy sector is one of the most significant approaches to the fulfilment of the goal of net-zero emissions by 2050 [[17]], and DT has already been employed to steer a transformative path to renewable energy systems. [Extracted from the article]

In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a normal model and a deep learning algorithm as an anomaly detection tool. The method is divided into three main steps: (1) quality maintenance of the original AIS data, (2) extraction of normal ship trajectory clusters using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), in which a segmented improved Dynamic Time Warping (DTW) algorithm is used to measure the degree of trajectory similarity, (3) the clustering results are used as a normative model to train a Bi-directional Gated Recurrent Unit (BiGRU) recurrent neural network, which is used as a trajectory predictor to achieve real-time ship anomaly detection. Experiments were conducted using real AIS data from the port of Tianjin, China. The experimental results are manifold. Firstly, the data pre-processing process effectively improves the quality of raw AIS data. Secondly, the ship trajectory clustering model can accurately classify the traffic flow of different modes in the sea area. Moreover, the trajectory prediction result of the BiGRU model has the smallest error with the actual ship trajectory and has a better trajectory prediction performance compared with the Long Short-Term Memory Network model (LSTM) and Gated Recurrent Unit (GRU). In the final anomaly detection experiment, the detection accuracy and timeliness of the BiGRU model are also higher than LSTM and GRU. Therefore, the proposed method can achieve effective and timely detection of ship anomalous behaviors in terms of position, heading and speed during ship navigation, which provides insight to enhance the intelligence of marine traffic supervision and improve the safety of marine navigation. [ABSTRACT FROM AUTHOR]

Highway bridges in coastal areas are seriously affected by the marine environment, while most of the existing test methods for bridge-reinforced concrete beams considering both corrosion and fatigue factors are carried out in an alternating manner, which cannot reflect the actual service conditions of the bridge structure. This paper focuses on an experimental study of the coupled influence of reinforcement corrosion and fatigue loading in reinforced concrete T-shaped beams. A novel loading test device that can realize the corrosion–fatigue coupling effect is designed, and then six reinforced concrete T-shaped beams are fabricated and tested. For the corrosion–fatigue coupling test beams, the variation law of beam cracks, failure modes, steel strain development law, load-deflection relationship, and fatigue life are analyzed and compared with that of the simple fatigue test beams. The test results show that the cracks of the test beam develop continuously with the fatigue loading times under the corrosion–fatigue coupling environment. The fatigue failure modes are all brittle fractures of the main steel bars, which present the shape of uneven oblique section tearing. The new testing device and approach can provide direct insights into the interaction of reinforcement corrosion and cyclic loading on the fatigue behavior of T-shaped RC beams, which can be further used to understand the long-term performance of bridge structures under complex marine environments. [ABSTRACT FROM AUTHOR]

Knowledge management in construction health and safety is an intensive process involving different stakeholders. However, this domain's information is still fragmented and stored in various disordered formats that require systematic structure for reusing and sharing. This study aims to develop a domain ontology, HSM-Onto (Health and Safety Management-Ontology), to construct health and safety knowledge and improve health and safety management decision making. The HSM-Onto could implement the organization, storage and reuse of construction health and safety knowledge. It comprises two primary domain knowledge contexts, including construction project context and risk context. Based on the conducted analyses, the findings show that the HSM-Onto's health and safety knowledge sharing is effective and equips health and safety employees with sound recommendations for decision making. [ABSTRACT FROM AUTHOR]

With the development of bridge structures towards being light weight and having a large span , the overall flexibility, and, hence, wind sensitivity, of the bridge increases. Flutter is one of the pivotal factors considered in the design and operation stage for long-span cable-stayed bridges due to its devastating impact, often intrigued by relatively low instability caused by wind speed. This paper presents a reliability theory-based numerical analysis on bridge flutter stability and its influence law of key parameters using a real bridge, the Xiangshan Harbor highway cable-stayed bridge in China. The analysis starts with creating a full scale of finite element model for the bridge in service to calculate the flutter derivative and time-dominated combining rational function in order to obtain the critical-flutter wind speed, and then the aerodynamic self-excited forces on the bridge and flutter time-history response are calculated to identify the flutter critical wind speed. Further, the influence of key parameters for flutter reliability, including the stiffness of the main girder, wire breaking rate, damping ratio and cable breakage location are analyzed comprehensively to achieve the change law of critical flutter wind speed with these parameters. Considering the uncertainty of the actual parameters, these parameters are taken as random variables, and the reliability index and failure probability of bridge flutter are calculated according to their probability distribution and the Latin hypercube sampling method. On this basis, a few suggestions are put forward for flutter risk-control during the service of this cable-stayed bridge, which can further enhance the design theory for long-span flexible bridges. [ABSTRACT FROM AUTHOR]

The evolution of the construction industry is associated with the continuous implementation of new technologies. Building Information Modelling (BIM) has revolutionised the collaboration and data sharing processes in the architecture, engineering, and construction (AEC) industry. However, it needs to be supported by new technologies that can embrace digital construction by transforming the construction industry into a dynamic environment. There is a lack of understanding of the cutting-edge technologies that have emerged to help with the digital transformation of the construction industry. There is a need to understand all these technologies and how they can be leveraged holistically towards future BIM innovations. Therefore, this article conducts a literature review to evaluate how targeted cutting-edge technologies can be utilised to release the full potential of BIM from a technical perspective. A bibliometric analysis focusing on the co-occurrence of keywords related to various technologies, their links with BIM, and their related research themes was conducted based on the Web of Science (WoS) database holdings from 2010 to 2019. The findings demonstrate that one type of technology can help with solving a specific issue. However, using one technology alone does not solve an issue entirely. The current technology has been utilised independently and not as a coherent system. Thus, a weak information integration and management approach can restrict the leveraging of a smart BIM environment. This paper is not meant to be exclusive. Many new technologies, concepts, and ideas can be added to help realise BIM potentials that are not covered in this study. Furthermore, the analysis was based on the dataset retrieved from WoS and only included the literature in English. Based on those findings, the authors indicated a technology fusion to support BIM development. [ABSTRACT FROM AUTHOR]

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets. [ABSTRACT FROM AUTHOR]

An analytical model is presented for solving the longitudinal complex impedance of a large-diameter floating pile in viscoelastic surrounding soil with radial heterogeneity and viscous-type damping, taking the effect of three-dimensional wave propagation of soil and lateral inertia of the pile shaft into account. The corresponding analytical solution for longitudinal impedance is also derived and validated via comparisons with existing solutions. The influences of the pile length, Poisson's ratio of the pile shaft and the viscous damping coefficient, as well as the degree and radius of disturbed surrounding soil, on the longitudinal impedance of the pile shaft are examined by performing parametric analyses. It is demonstrated that the proposed analytical model and solution are suitable for the longitudinal vibration problem of a large-diameter pile and radially inhomogeneous surrounding soil, especially when the pile slenderness is low. In addition, the present solution can be easily degenerated to describe the longitudinal vibration problem relating to a large-diameter floating pile in radially homogenous soil or a pile with fixed-end supports. [ABSTRACT FROM AUTHOR]

The traditional way of designing energy pile system is mostly single domain/objective oriented, which lacks of means to coherently consider different while relevant factors across domains. The cost for life cycle design, construction and maintenance, return of investment, CO2 emission related sustainable requirements, and so on also need to be considered, in a systematic manner, along with the main functional design objective for loading capacity and robustness. This paper presents a novel multi-objective holistic approach for energy pile system design using ontology based multi-domain knowledge orchestration, which can holistically provide the designers with across domain factors regarding financial, safety, and environmental impact, for smart and holistic consideration during the early design stage. A prototypical ontology-based decision tool has been developed, aiming at the holistic optimization for energy pile system by combining ontology and Semantic Web Rule Language rules. A case study was performed to illustrate the details on how to apply knowledge query to provide a series of design alternatives autonomously by taking different design parameters into account. The method has demonstrated its practicability and scientific feasibility, it also shows the potential to be adopted and extended for other domains when dealing with multi-objective holistic design making. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of the freefall of lifeboat motion simulation in a ship life-saving simulation training system, a mathematical model using the strip theory and Kane's method is established for the freefall of the lifeboat into the water from a ship. With the boat moving on a skid, the model of the ship's maneuvering mathematical group (MMG) is used to model the motion of the ship in the waves. Based on the formula of elasticity and friction theory, the forces of the skid acting on the boat are calculated. When the boat enters the water, according to the analytical solution theory of slamming, the slamming force of water entry is solved. The simulation experiments are carried out by the established model. The results of the numerical simulation are compared with the calculation results of the hydrodynamics software Star CCM+ at water entry under initial condition A in the paper. The position and velocity of the center of gravity of the boat, the angle, and velocity and acceleration of pitch calculated by the two methods are in good agreement. There is a little difference between the values of translation acceleration calculated by the two methods, which is acceptable. This shows that our numerical algorithm has good accuracy. A qualitative analysis is performed to find the safe point of water entry under the condition of different wave heights and two situations of a ship encountering waves. Finally, the model is applied to the ship life-saving training system. The model can meet the system requirements and improve the accuracy of the simulation. [ABSTRACT FROM AUTHOR]

Based on the theory of wave propagation in three-dimensional (3D) continuum, a new analytical approach for the longitudinal vibration characteristics of a floating pile in layered soils with radial heterogeneity is developed by employing a viscous-type damping model. Firstly, an analytical solution for the longitudinal complex impedance at the pile head is deduced by employing the Laplace transform and complex stiffness technique with the compatibility conditions of the pile and radially inhomogeneous surrounding soil. Secondly, a semi-analytical solution in the time domain is further acquired by using the inverse Fourier transform method. Furthermore, the corresponding analytical solutions are validated through contrasts with previous solutions. Finally, parametric analyses are underway to investigate the effect of radial heterogeneity of surrounding soils on longitudinal vibration characteristics of floating piles. It is indicated that the proposed approach and corresponding solutions can provide a more wide-ranging application than the simple harmonic vibration for longitudinal vibration analysis of a floating pile in soils. [ABSTRACT FROM AUTHOR]

It is a challenging work to simulate wind and waves in virtual scenes of marine simulators. In this paper, a divergence-free position based fluid (DFPBF) framework is introduced for ocean wave modeling in marine simulators. We introduce a set of constant density constraints and divergence-free velocity constraints to enforce incompressibility. By adjusting the position distribution of fluid particles, the particle density is forced to be constant. Constraining the divergence-free velocity field can keep the density change rate at zero. When correcting the position and velocity of particles, we introduced a relaxation correction scheme to accelerate the convergence of the framework. The simulation results show that as the scene scale expands and the number of fluid particles increases, this acceleration effect will be more significant. Secondly, we propose a novel particle-based three-dimensional stochastic fluctuating wind field. The Perlin noise is introduced to disturb the constant horizontal wind field to form a stochastic wind field. On this basis, a stochastic fluctuating wind field simulation framework is proposed. By adjusting the pulse period and pulse width, users can flexibly control the fluid turnover under the action of the wind field. This wind field framework can be easily integrated into the DFPBF model. Based on this wind field model, we simulated some typical wind wave scenarios, including interaction scenarios with lighthouse and lifebuoy, and verified the effectiveness of the wind field model. [ABSTRACT FROM AUTHOR]

The realistic simulation of ocean scenes is of great significance in many scientific fields. We propose an improved Smoothed Particle Hydrodynamics (SPH) framework to simulate the ocean scenes. The improved SPH combines nonlinear constant density constraints and divergence-free velocity field constraint. Density constraints adjust the particle distribution on position layer, so that the density is constrained to a constant state. The addition of the divergence-free velocity field constraint significantly accelerates the convergence of constant density constraint and further reduces the density change. The simulation results show that the improved SPH has high solution efficiency, large time steps, and strong stability. Then, we introduce a unified boundary handling model to simulate coupling scenes. The model samples the boundary geometry as particles by means of single layer nonuniform sampling. The contribution of the boundary particles is taken into account when the physical quantities of fluid particles are computed. The unified model can handle various types of complex geometry adaptively. When rendering the ocean, we propose an improved anisotropic screen space fluid method, which alleviates the discontinuity problem near the boundary and maintains the anisotropy of particles. The research provides a theoretical reference for the highly believable maritime scene simulation in marine simulators. [ABSTRACT FROM AUTHOR]