Adrian Wing‐Keung Law

Nanyang Technological University

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E. Eric Adams

Massachusetts Institute of Technology

Kun Zhou

Nanyang Technological University

Hieu Trung Kieu

Nanyang Technological University

Anthony G. Fane

UNSW Sydney

Dharma K.K. Sree

Nanyang Technological University

Bing Zhao

Changsha University of Science and Technology

Adrian C. H. Lai

Nanyang Technological University

Dongdong Shao

Northeastern University

Zhenhua Huang

Xiamen University of Technology

Nian‐Sheng Cheng

Zhejiang University

Cooperative Institutions

Nanyang Technological University

150

Chinese Academy of Sciences

National University of Singapore

Shanghai Jiao Tong University

University of Hong Kong

Dalian University of Technology

Wuhan University

Tsinghua University

Massachusetts Institute of Technology

University of Chinese Academy of Sciences

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Factors affecting the performance of a submerged hollow fiber bundle

Journal of Membrane Science (2006)

A. Yeo Adrian Wing‐Keung Law Anthony G. Fane

Flow resistance

10.1016/j.memsci.2006.03.029

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Citations (101)

Spreading and Deposition of Turbidity Currents: Application to Open-Water Sediment Disposal

Journal of Waterway Port Coastal and Ocean Engineering (2020)

Jenn Wei Er Adrian Wing‐Keung Law E. Eric Adams

A new two-phase box model is developed in this study for the prediction of a spatially varying turbidity current with sediments on a horizontal bottom. The turbidity current is segmented into small subvolumes to account for the spatial variation with nonuniform spreading, while a two-phase formulation computes the differential settling of the suspended sediments inside the turbidity current, which form deposits onto the seabed. In addition, the new model is capable of simulating the transition from constant flux to fixed volume propagation, which is typical for both natural submarine landslides and engineered barged sediment disposal. The computation is terminated when most of the total sediment volume is deposited, yielding the final deposition pattern. Following the model development, a detailed experimental study was carried out in the laboratory to validate the model predictions by releasing large but finite amounts of sediments through a rectangular opening on the water surface. The agreement between the model predictions and experimental measurements was found to be satisfactory. Finally, this model is integrated into the Barged Sediments Disposal Model (BSDM) software for the assessment of open-water barged sediment disposal. A practical application of the integrated BSDM is demonstrated using a field study reported in the literature.

Turbidity current

Turbidity

Deposition

Settling

Seabed

10.1061/(asce)ww.1943-5460.0000556

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Citations (7)

Boundary interactions of horizontal brine discharges

CRC Press eBooks (2022)

Dong Shao Adrian Wing‐Keung Law

A horizontal outfall near the seabed is occasionally adopted in engineering practice for the submerged discharge of dense jets. Upon exiting the nozzle, the horizontal dense jet would curve toward and impinge on the seabed due to the negative buoyancy. The boundary interactions between the discharge and the seabed would intensify if the offset between the outfall and the seabed, or the bed proximity, reduces. Quantitative assessment of the boundary impingement and attachment of the offset dense jet is studied experimentally using Particle Image Velocimetry (PIV) and Planar Laser Induced Fluorescence (PLIF). Boundary-influenced and free horizontal offset dense jets were investigated by varying the discharge densimetric Froude number, Fr, as well as the bed proximity parameter z0/LM. Various relationships of the impingement characteristics were established through the analysis of the experimental results.

Brine

10.1201/9780429100307-26

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Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling

arXiv (Cornell University) (2024)

Meng Yan Minghao Han Adrian Wing‐Keung Law Xunyuan Yin

In this paper, we propose a physics-informed learning-based Koopman modeling approach and present a Koopman-based self-tuning moving horizon estimation design for a class of nonlinear systems. Specifically, we train Koopman operators and two neural networks - the state lifting network and the noise characterization network - using both data and available physical information. The two neural networks account for the nonlinear lifting functions for Koopman modeling and describing system noise distributions, respectively. Accordingly, a stochastic linear Koopman model is established in the lifted space to forecast the dynamic behavior of the nonlinear system. Based on the Koopman model, a self-tuning linear moving horizon estimation (MHE) scheme is developed. The weighting matrices of the MHE design are updated using the pre-trained noise characterization network at each sampling instant. The proposed estimation scheme is computationally efficient because only convex optimization is involved during online implementation, and updating the weighting matrices of the MHE scheme does not require re-training the neural networks. We verify the effectiveness and evaluate the performance of the proposed method via the application to a simulated chemical process.

10.48550/arxiv.2408.03653

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Modeling of quasi-constant volume gravity currents due to open-water sediment disposal

Bulletin of the American Physical Society (2016)

Jenn Wei Er Adrian Wing‐Keung Law E. Eric Adams

Constant (computer programming)

Open water

Source

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Implications of enhancing critical flux of particulates by AC fields in RO desalination and reclamation

Desalination (2008)

Y.P. Zhang Tzyy Haur Chong Anthony G. Fane Adrian Wing‐Keung Law H.G.L. Coster

Biofouling

Membrane Fouling

10.1016/j.desal.2007.02.043

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Citations (15)

3D Printing of Mixed Matrix Films Based on Metal–Organic Frameworks and Thermoplastic Polyamide 12 by Selective Laser Sintering for Water Applications

ACS Applied Materials & Interfaces (2019)

Rui Li Shangqin Yuan Wang Zhang Han Zheng Wei Zhu

The fabrication of metal–organic framework (MOF)-based macro-materials is considered as a promising strategy toward the practical applications of powdered MOF crystals. In this study, selective laser sintering (SLS), an advanced three-dimensional (3D) powder printing technique, has been employed to fabricate MOF–polymer mixed matrix films (MMFs) by using thermoplastic polyamide 12 (PA12) powder as the matrix material and five types of MOFs including ZIF-67, NH2-MIL-101(Al), MOF-801, HKUST-1, and ZIF-8 crystals as the fillers. A three-layer HKUST-1-PA12 complex with a grid pattern is fabricated to demonstrate the printability of 3D MOF–polymer structure. Single-layer MMFs with grid patterns are printed by using the five types of MOF fillers with different mass loadings to study their free-standing characteristic, thickness, specific surface area, hydrophilia, water permeate flux, and mechanical stability. The methylene blue (MB) adsorption tests are conducted using the NH2-MIL-101(Al)-PA12 MMFs with different grid patterns to exemplify the applications of the MMFs for water purification. It is confirmed that the MOF components retain their high maximum adsorption capacity, and the printed MMFs can be conveniently regenerated for cyclic utilization. This work provides an insight into the utilization of advanced 3D printing technology to manufacture macro-MOF–polymer materials for practical applications.

Selective laser sintering

Matrix (chemical analysis)

10.1021/acsami.9b11840

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Citations (88)

Re-entrainment around a low-rise industrial building: 2D versus 3D wind tunnel study

Atmospheric Environment (2004)

Adrian Wing‐Keung Law E.C.C. Choi Rex E. Britter

Entrainment (biomusicology)

Low-rise

Air entrainment

10.1016/j.atmosenv.2004.03.059