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Hydraulics, Hydrology and Environmental Engineering (2023)
Book
Mathias, S. A. (2023). Hydraulics, Hydrology and Environmental Engineering. Springer. https://doi.org/10.1007/978-3-031-41973-7

This textbook provides an excellent resource for engineering and science students to develop basic, intermediate and advanced level skills in hydraulics, hydrology and environmental engineering. Topics include open channel flow, ocean waves, kinemati... Read More about Hydraulics, Hydrology and Environmental Engineering.

Cone Penetration Tests (CPTs) in layered soils: a Material Point approach (2023)
Presentation / Conference Contribution
Bird, R., Coombs, W., Augarde, C., Brown, M., Sharif, Y., Carter, G., Johnson, K., & Macdonald, C. (2023, June). Cone Penetration Tests (CPTs) in layered soils: a Material Point approach. Presented at 10th European Conference on Numerical Methods in Geotechnical Engineering, London

Cone Penetration Tests (CPTs) can be used to determine in-situ soil properties and represent a practical choice for site investigation offshore, especially for linear infrastructure, such as offshore wind export cables. Information gained from CPTs i... Read More about Cone Penetration Tests (CPTs) in layered soils: a Material Point approach.

Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption (2023)
Presentation / Conference Contribution
Barker, J., Bhowmik, N., Gaus, Y., & Breckon, T. (2023, February). Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption. Presented at VISAPP 2023: 18th International Conference on Computer Vision Theory and Applications, Lisbon, Portugal

Anomaly detection is the task of recognising novel samples which deviate significantly from pre-established normality. Abnormal classes are not present during training meaning that models must learn effective representations solely across normal clas... Read More about Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption.

A distributed renewable power system with hydrogen generation and storage for an island (2023)
Journal Article
Williams, L., & Wang, Y. (2024). A distributed renewable power system with hydrogen generation and storage for an island. Applied Energy, 358, Article 122500. https://doi.org/10.1016/j.apenergy.2023.122500

This study aimed to find a distributed renewable power system with hydrogen generation and storage to meet the current Isle of Rum's energy demands. Five different systems (Case 2–6) were evaluated compared to the current power system (Case 1), with... Read More about A distributed renewable power system with hydrogen generation and storage for an island.

On the development of a material point method compatible arc length solver for large deformation solid mechanics (2023)
Presentation / Conference Contribution
Gavin, N., Coombs, W., Brigham, J., & Augarde, C. (2023, April). On the development of a material point method compatible arc length solver for large deformation solid mechanics. Presented at UKACM 2023, Coventry, UK

The Material Point Method is a versatile technique, however, it may be unable to provide a valid solution if there is a snap-through or snap-back response in the equilibrium path. One approach of overcoming this issue is the use of path following tec... Read More about On the development of a material point method compatible arc length solver for large deformation solid mechanics.

An investigation into the methods for modelling pre-existing cracks in phase field problems (2023)
Presentation / Conference Contribution
Sims, B., Bird, R., Giani, S., & Coombs, W. (2023, April). An investigation into the methods for modelling pre-existing cracks in phase field problems. Presented at UKACM 2023, Warwick, UK

Phase field (PF) models are an increasingly popular method of numerically modelling fracture problems. While research has focused on the practical applications and computational efficiency of PF methods, little discussion exists around the merits of... Read More about An investigation into the methods for modelling pre-existing cracks in phase field problems.

An open-source Julia code for geotechnical MPM (2023)
Presentation / Conference Contribution
Gavin, N., Bird, R. E., Coombs, W. M., & Augarde, C. E. (2023, June). An open-source Julia code for geotechnical MPM. Presented at 10th European Conference on Numerical Methods in Geotechnical Engineering, London

There is considerable interest in the Material Point Method (MPM) in the computational geotechnics community since it can model problems involving large deformations, e.g. landslides, collapses etc. without being too far from the standard finite elem... Read More about An open-source Julia code for geotechnical MPM.

A ghost-stabilised material point method for large deformation geotechnical analysis (2023)
Presentation / Conference Contribution
Coombs, W. (2023, June). A ghost-stabilised material point method for large deformation geotechnical analysis. Presented at 10th European Conference on Numerical Methods in Geotechnical Engineering, London

The Material Point Method (MPM) is advertised as the method for large deformation analysis of geotechnical problems. However, the method suffers from several instabilities which are widely documented in the literature, such as: material points crossi... Read More about A ghost-stabilised material point method for large deformation geotechnical analysis.

Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks (2023)
Presentation / Conference Contribution
Higuera, G., & Kazemtabrizi, B. (2023, June). Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks. Presented at 27th International Conference on Electricity Distribution (CIRED 2023), Rome, Italy

This paper proposes a novel Active Network Management (ANM) framework for day-ahead operations planning of a medium-voltage active Distribution Network (DN) using a heuristic Network Reconfiguration (NR) algorithm with a Curtailment Minimisation Sche... Read More about Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks.

Techno-Economic-Environmental Analysis for Net-Zero Sustainable Residential Buildings (2023)
Presentation / Conference Contribution
Garg, A., Aujla, G., & Sun, H. (2023, October). Techno-Economic-Environmental Analysis for Net-Zero Sustainable Residential Buildings. Presented at IEEE PES ISGT Europe 2023, Grenoble, France

Carbon emissions are becoming a global concern responsible for climate change. The renewable energy sources (RESs) such as wind, solar, biomass are gaining importance to reduce emissions in the energy sector. However, these sources depend highly on v... Read More about Techno-Economic-Environmental Analysis for Net-Zero Sustainable Residential Buildings.

Assessing the techno-economic viability of a trigeneration system integrating ammonia-fuelled solid oxide fuel cell (2023)
Journal Article
Roy, D., Roy, S., Smallbone, A., & Roskilly, A. P. (2023). Assessing the techno-economic viability of a trigeneration system integrating ammonia-fuelled solid oxide fuel cell. Applied Energy, 357, Article 122463. https://doi.org/10.1016/j.apenergy.2023.122463

In recent years, ammonia has gained traction as a clean fuel alternative and a promising energy carrier. In this study, a trigeneration system fuelled by ammonia has been conceptualised, integrating a solid oxide fuel cell stack for power generation,... Read More about Assessing the techno-economic viability of a trigeneration system integrating ammonia-fuelled solid oxide fuel cell.

Adversarial attacking and defensing modulation recognition with deep learning in cognitive radio-enabled IoT (2023)
Journal Article
Zhang, Z., Ma, L., Liu, M., Chen, Y., & Zhao, N. (2024). Adversarial attacking and defensing modulation recognition with deep learning in cognitive radio-enabled IoT. IEEE Internet of Things Journal, 11(8), 14949-14962. https://doi.org/10.1109/JIOT.2023.3345937

Modulation recognition using deep learning (DL) can efficiently recognize modulated signals in cognitive radio-enabled Internet of Things (IoT). However, it is vulnerable to the attack of adversarial examples designed by attackers, leading to a decre... Read More about Adversarial attacking and defensing modulation recognition with deep learning in cognitive radio-enabled IoT.