Civil Engineering

TechTalk – Unlock the Hidden Value of Bridges’ Reserve Capacity in Toll Highway Operation

February 22 2024 (Thursday) 4:30-5:30pm
The extra reserve capacity exists widely in highway bridges due to the conservative design and construction. In a case study of a highway flyover in Singapore, the flyover still possesses at least an additional 30% loading capacity after twenty years of operation. This additional capacity, which was achieved by consuming extra raw materials and energy when the bridge was built years ago, is considered another kind of “waste” since it has never been used. To make use of it, the speaker introduced the additional loading capacity into the framework of operating profit optimization. The unused loading capacity enables a higher volume of vehicles and a higher proportion of heavy vehicles, thus further leading to the increase in toll profit.

TechTalk – Seawater Sea-sand Engineered Cementitious Composites (SS-ECC) for Marine and Coastal Infrastructures

January 25 2024 (Thursday) 4:30-5:30pm
Engineered/Strain-Hardening Cementitious Composites (ECC/SHCC) is an advanced fiber-reinforced concrete exhibiting multiple-cracking and strain-hardening under tension. We aimed to explore the feasibility of producing high-strength seawater sea-sand Engineered Cementitious Composites (SS-ECC) for marine and coastal applications facing the shortage of freshwater and river/manufactured sand. The effects of key composition parameters including the sea-sand size, the polyethylene fiber length, and the fiber volume dosage on the mechanical performance of SS-ECC were comprehensively investigated. The crack characteristics of SS-ECC were also assessed and modelled, which are critical for its applications with non-corrosive reinforcements. SS-ECC with tensile strength over 8 MPa, ultimate tensile strain of about 5%, and compressive strength over 130 MPa were achieved. Using seawater and sea-sand had almost no negative effects on the 28-day mechanical properties of high-strength ECC. Smaller sand size and higher fiber dosage of SS-ECC resulted in smaller crack widths under the same tensile strain. A five-dimensional representation was proposed to assess the overall performance of SS-ECC, by comprehensively considering both the crack characteristics and the mechanical properties. A probabilistic model was also proposed to describe the stochastic nature and evolution of crack width, and it can be used to estimate the critical tensile strain on SS-ECC for a given crack-width limit and cumulative probability. The findings and proposed methods can facilitate the design of SS-ECC in marine and coastal infrastructures.

TechTalk – HKU’s Contributions to Landslide Hazard Mitigation in Hong Kong

February 1 2024 (Thursday) 3:00-4:00pm
Hong Kong, renowned as one of the most densely populated territories globally, grapples with its hilly terrain and limited flat land, resulting in numerous buildings constructed on slopes or adjacent to large cut slopes. This situation poses a grave risk as landslides could tragically claim multiple lives. To address this critical issue, slope stabilization plays a crucial role in mitigating the landslide hazard. In this TechTalk, the pioneering work of Professor Peter Lumb on slope stability will be reviewed. The development and validation of soil nailing as an effective measure for slope stabilization will also be described.

TechTalk – Artificial Intelligence for Structural Design, Simulation and Health Monitoring

December 14 2023 (Thursday) 4:30-5:30pm
Structural engineering community require the experience of experts in design, simulation and structural health monitoring (SHM) of existing structures. Currently, the training process of structural engineers may take more than 10 years from undergraduate to expert. The economic design currently relies on the experience of engineers, which may not reach the optimized design outcome. In addition, high-fidelity simulation and SHM are still challenging and practical applications of the nonlinear structural simulation and SHM are mostly limited to researchers, instead of practical engineers. Conventional structural engineering widely adopts finite element solvers based on CPUs, which may be time consuming. The computing resources of GPU accelerators and GPU-based supercomputers cannot be fully utilized due to the lack of GPU-based simulation platforms.

The project develops deep-learning-based intelligent structural design, simulation and structural health monitoring platform. For structural design, dataset is collected for structural design input parameters and structural design drawings, the generative models are learned to generate preliminary structural design drawings of buildings and bridges. For structural simulation, physics-informed neural networks are developed to replicate the spatial discretization and temporal discretization of conventional finite element solvers. For SHM, the state-of-the-art neural operator is trained on finite element simulation dataset of vehicle-bridge interaction (VBI) system and fine-tuned on experimental dataset to infer the damage distribution field based on structural response field. The project can inspire the undergraduate and graduate students to learn more about the challenges and future developments of structural engineering.

TechTalk – Environmental Geomechanics: Towards a Minimised Chemical Footprint in Geo-energy Engineering

November 23 2023 (Thursday) 4:30-5:30pm
Cracking is ubiquitous in a geomaterial when it is subject to an environmental perturbation. Controlling environmentally assisted subcritical crack growth is the key enabler to a safe and active geo-energy adaptation to Climate Change, particularly in the domain of e.g., unconventional shale hydrocarbon recovery, Carbon Capture Utilisation and Storage (CCUS) and enhanced geothermal systems (EGS). The aim of these applications is commonly to achieve an enhanced permeability and injectivity in the formation by the stimulation of hydraulic fracturing. In order to maximize the effectiveness of the technique and meanwhile limit the extent of chemical footprint, a sophisticated understanding of the feedback between the mechanics of a geomaterial and the surrounding environment it is subject to is required. In this talk, modelling approaches on the effect of chemical environment on subcritical cracking in a stressed geomaterial at multiple scales and an extension to an alternative non-destructive shear stimulation will be presented.

TechTalk – Waste to Wealth: Sustainable Land Reclamation Technologies

November 16 2023 (Thursday) 3:00-4:00pm
Land reclamation is one of the most effective solutions to address the severe problem of land shortage. By 2023, the total reclaimed area in Hong Kong is nearly equivalent to the whole area of Hong Kong Island. In Lantau Tomorrow Vision, there will be over 1700 hectares of new reclaimed land in the next 20-30 years, in which, the shortage of fill material will be a great challenge. Dredged marine deposits as a major solid waste are a potential fill material after stabilization. Chemically, waste ashes from industry were recycled, activated, and mixed with marine deposits to serve as fill material. The other biological method is also used, in which bacteria are adapted to induce calcium carbonate in marine deposits. The environmental impact and performance of the methods are evaluated. Without using cement, these green technologies could reduce carbon emissions, contributing to carbon neutrality, and promoting green and sustainable reclamation.

TechTalk – Wireless AI Perception: A New Sense for Machine Intelligence Beyond Vision

September 21 2023 (Thursday) 4:30-5:30pm
Can machines sense without cameras or sensors? Computer vision allows machines to “see,” but their perception capabilities based on cameras are fundamentally limited to a specific field of view and good lighting conditions – they cannot see through any occlusions or in the dark. In this talk, I will introduce Wireless AI Perception that opens a new sense for machine perception to decipher the physical world, even in absolute darkness and through walls and obstacles. To achieve this, Wireless AI leverages ambient wireless signals for sensing and turns any Wi-Fi devices from a pure communication medium into a ubiquitous all-in-one sensing platform. We will first introduce the concepts, principles, and grand challenges of Wi-Fi sensing, and then share our unique solution of Wireless AI, which has been commercialized and deployed as real-world products, such as motion sensing, sleep monitoring, fall detection, indoor tracking, just to name a few. We foresee that Wi-Fi Sensing will enter billions of devices and millions of homes, and today is just the beginning of this revolution.

TechTalk – Simulation, Optimization and Artificial Intelligence for On-demand Ride Service Operations

September 14, 2023 (Thursday) 4:30-5:30pm
On-demand ride services or ride-sourcing services, offered by transportation network companies like Uber, Lyft and Didi, have been experiencing fast development and steadily reshaping the way people travel in the past decade. Various mathematical models and optimization algorithms, including reinforcement learning approaches, have been developed in the literature to help ride-sourcing platforms design better operational strategies to achieve higher operational efficiency. However, due to cost and reliability issues (implementing an immature algorithm for real operations may result in system turbulence), it is commonly infeasible to validate these models and train/test these optimization algorithms within real-world ride sourcing platforms. Acting as a useful test bed, a simulation platform for ride-sourcing systems will thus be very important for both researchers and industrial practitioners to conduct algorithm training/testing or model validation through trails and errors. While previous studies have established a variety of simulators for their own tasks, it lacks a fair and public platform for comparing the models/algorithms proposed by different researchers. In addition, the existing simulators still face many challenges, ranging from their closeness to real environments of ride-sourcing systems, to the completeness of different tasks they can implement. To address the challenges, we propose a novel multi-functional and open-sourced simulation platform for ride-sourcing systems, which can simulate the behaviors and movements of various agents (including drivers and passengers) on a real transportation network. It provides a few accessible portals for users to train and test various optimization algorithms, especially reinforcement learning algorithms, for a variety of tasks, including on-demand matching, idle vehicle repositioning, and dynamic pricing. Evaluated by experiments based on real-world datasets, the simulator is demonstrated to be an efficient and effective test bed for various tasks related to on-demand ride service operations.

Young Scholar TechTalk – Blowing Bubbles in Membranes for More Efficient Freshwater Production

Global scarcity and contamination of freshwater pose a significant threat to sustainable development. To address this crisis, reverse osmosis (RO) technology has been playing a pivotal role in desalination and water reuse for freshwater production. The effectiveness of the RO membrane filtration is highly dependent on its surface functional rejection layer. My research focuses on shaping this rejection layer to be a voids-bearing structure, resembling blowing bubbles within the layer. This technique will result in a thinner rejection layer with a larger surface area, favoring water transport. On this basis, shaping branch bubbles to resemble a tree or coral can potentially achieve an exponential increase in water filtration efficiency, resulting in faster production of freshwater with significantly lower energy consumption.