BURA Community:

Enhancing out-of-plane seismic resistance of masonry walls with fiber-reinforced overlays: tests, modeling, and fragility analysis

2026-06-21T02:00:31Z

Title: Enhancing out-of-plane seismic resistance of masonry walls with fiber-reinforced overlays: tests, modeling, and fragility analysis Authors: Wen, T-H; Yuen, TYP; Zhou, X Abstract: This study investigates the out-of-plane seismic performance and fragility of masonry walls retrofitted with basalt fiber grid (BFG), carbon fiber–reinforced polymer (CFRP), glass fiber–reinforced polymer (GFRP), and ultra-high-performance concrete (UHPC). Large-scale masonry wall specimens were tested under lateral loading to examine strength, deformation capacity, and failure mechanisms. This study focuses on the pure out-of-plane response of masonry walls, without considering in-plane forces or deformations. All retrofitted walls significantly outperformed the unreinforced masonry (URM) wall, which failed at 11.34 kN. Peak strengths reached 40.79 kN (GFRP), 30.92 kN (UHPC), 24.88 kN (BFG), and 21.39 kN (CFRP), with varying ductility and crack patterns. Discrete finite element models, calibrated against experimental results, were employed to perform incremental dynamic analysis and derive seismic fragility curves. Results show that retrofitting markedly reduced failure probabilities, raising median spectral acceleration thresholds by factors of 3–7 compared with URM. Among the methods, GFRP achieved the most favorable fragility performance, exhibiting both high capacity and low drift exceedance. These findings demonstrate that retrofit material choice and configuration are critical for improving seismic resilience and reducing collapse risk in masonry structures.

End-of-life Management of Electric Vehicle Batteries

2026-06-20T02:00:40Z

Title: End-of-life Management of Electric Vehicle Batteries Authors: Shafique, M Abstract: Net-Zero aims have led to an increase in the market share of UK electric vehicles (EVs) to 20.4% in 2025 - up from 16.9% in 2024. It is estimated that by 2035, 150,000 tonnes of battery packs will reach end of life (EOL) annually that will need to be processed. Unless this waste flow is managed, many of the environmental gains of the transition to EVs will be lost. Government and the automotive industry should take a holistic approach to EOL EV battery management: focusing on regulations, producer responsibilities, financial incentives, infrastructure development, domestic processing capacity, research and development (R&D), and supply chain security. A comprehensive strategy is necessary to build a circular economy for batteries and avoid environmental damage from waste overflow and international shipping for processing.

Effects of ultrafine glass powder on the reliability analysis and life prediction of cement mortar under multi-concentration sulfate attack

2026-06-18T02:00:33Z

Title: Effects of ultrafine glass powder on the reliability analysis and life prediction of cement mortar under multi-concentration sulfate attack Authors: Sun, Y; Li, Z; Hou, D; Zhao, Y; Wang, J; Zhou, X Abstract: In this paper, the influence mechanism of ultrafine glass powder (UGP) on the sulfate resistance of cement mortar is studied by replacing cement with different of equal quality amounts. The reliability analysis of UGP-modified cement mortar in sulfate environment is systematically discussed by mass change analysis, scanning electron microscope (SEM), X-ray diffraction (XRD) and nanoindentation, etc. The results show that the proper amount of UGP can significantly improve the sulfate resistance of cement mortar, and the effect is the best when the content of UGP is 10%. Compared with the undoped UGP group, the flexural strength and compressive strength increased by 11.34%, 8.62% and 6.63%, 6.85% respectively after 120 days of erosion in 5% and 10% sodium sulfate solutions, and the mass loss was the smallest. A two-parameter Weibull distribution model via relative dynamic elastic modulus is developed to predict the reliability life of UGP-modified cement mortar. The results show that 10% UGP content can significantly prolong the service life of cement mortar in sulfate environment. UGP effectively consumes Ca(OH)₂ through pozzolanic reaction, which promotes the formation of C-S-H gel and reduces the formation of expansion products such as gypsum (CaSO₄·2 H₂O) and ettringite (AFt), as well as optimizes pore structure and enhances material compactness and microscopic mechanical properties. Description: Data availability: Data will be made available on request.

Machine learning approaches to understand the uptake and elimination of anthropogenic stressors in animal health

2026-06-18T14:37:31Z

Title: Machine learning approaches to understand the uptake and elimination of anthropogenic stressors in animal health Authors: Uhlhorn, Jasmin Abstract: The detection of pharmaceuticals in aquatic ecosystems raises questions about their potential effects on non-target organisms. However, environmental concentrations do not directly reflect the internal body burden of organisms. As part of this work, an investigation of contaminants of emerging concern in a coastal ecosystem as well as in marine biota highlighted this, with internal and surface water concentrations differing substantially. The gap may be linked to both environmental conditions and compound-specific uptake and elimination processes, which affect their bioaccumulation potential. Laboratory-based studies to understand compound-dependent uptake and elimination kinetics have traditionally focused on fish. In line with the 3Rs principle and regulatory efforts to move away from vertebrate testing, and to broaden taxonomic coverage, this work aimed to assess the potential of the invertebrate model species Daphnia magna to be used in mixture-based exposures as a high-throughput alternative. This necessitated the development and validation of a broad targeted analytical method for the determination of multi-class pharmaceuticals in D. magna, which had not previously been developed. This work successfully developed a method applicable across multiple pharmaceutical classes, capable of quantifying more than 50 compounds to acceptance criteria defined by ICH method validation guidelines. Mixture toxicokinetic exposures were performed, ranging from a single compound to simultaneous exposure of up to 50 compounds, and toxicokinetic profiles were successfully derived for 49 pharmaceuticals. Pharmaceuticals generally exhibited low bioconcentration potential with the majority of compounds having bioconcentration factors (BCFs) of <60 L kg-1 dry weight (dw), yet values ranged from 2 to >10,000 L kg-1 dw. The broad range highlights the importance of considering internal exposure when assessing hazard and subsequent risk. The generated toxicokinetic data was applied to machine learning models alongside published fish BCF data. The models achieved good performance for fish but showed limited predictive ability for D. magna. Mechanistic evaluation confirmed that models identified established properties and relationships that are linked to bioaccumulation and membrane permeability (logP, TPSA), demonstrating their ability to capture relevant processes when sufficient representative data is available. Overall, this work highlighted the potential of mixture-based approaches in the non-vertebrate organism D. magna to enable higher-throughput bioconcentration assessment. Utilising this high-throughput testing could rapidly generate ecotoxicity data to fulfil regulatory requirements and enable in silico modelling approaches to potentially replace animal testing in the future. Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London