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Assessment of mining impact on groundwater is one of critical considerations for longwall extension and sustainability, however usually constrained by limited data availability, hydrogeological variation, and the complex coupled hydro-mechanical behaviour. This paper aims to determine the factors and mechanism of groundwater depressurisation and identify knowledge gaps and methodological limitations for improving groundwater impact assessment. Analysis of dewatering cases in Australian, Chinese, and US coalfields demonstrates that piezometric drawdown can further lead to surface hydrology degradation, while the hydraulic responses vary with longwall parameters and geological conditions. Statistical interpretation of 422 height of fracturing datasets indicates that the groundwater impact positively correlates to panel geometry and depth of cover, and more pronounced in panel interaction and top coal caving cases. In situ stress, rock competency, clay mineral infillings, fault, valley topography, and surface–subsurface water interaction are geological and hydrogeological factors influencing groundwater hydraulics and long-term recovery. The dewatering mechanism involves permeability enhancement and extensive flow through fracture networks, where interconnected fractures provide steep hydraulic gradients and smooth flow pathways draining the overlying water to goaf of lower heads. Future research should improve fracture network identification and interconnectivity quantification, accompanied by description of fluid flow dynamics in the high fracture frequency and large fracture aperture context. The paper recommends a research framework to address the knowledge gaps with continuous data collection and field-scale numerical modelling as key technical support. The paper consolidates the understanding of longwall mining impacting mine hydrology and provides viewpoints that facilitate an improved assessment of groundwater depressurisation.

Borehole breakout is a natural phenomenon in boreholes drilled in rock due to the induced stress concentration. Many researchers have attempted to correlate this phenomenon with in situ stress magnitudes. In this paper, a series of true triaxial tests on sandstone blocks (120 × 120 × 120 mm3) with different diameter pre-drilled holes have been carried out. Results confirmed that breakout geometries (angular span and depth) are dependent on the relative stress magnitudes. It is also noticed that a larger hole size (hole radius) yielded a wider angular span and deeper normalised depth (breakout depth/hole size), which indicates that hole size is an important parameter for breakout geometries. In addition, the analysis on previous experimental studies suggested that the relationship between two breakout geometries is not unique and is heavily influenced by the horizontal stress magnitudes. The analysis of the existing model also revealed the angular span may be narrowed with increasing horizontal stress ratio under a certain stress–strength condition. Both analyses indicate the breakout geometries are not only dependent on each other but also on the horizontal stress magnitudes. This leads to a tentative conclusion that breakout geometries may not be redundant factors and might be used for horizontal stress estimation.

The roughness of a rock joint gives rise to the phenomenon of dilatancy. Numerous studies have been conducted to examine their dilation behaviour partly due to its importance as a stabilising effect. While previous researchers have improved the understanding of dilation behaviour and identified important parameters affecting the magnitude of dilation during shear, there is still a lack of quantification of the method for predicting the dilation angle. This paper describes a systematic parametric study to investigate the effect of relative normal stress and geometric properties on the dilation of a saw-toothed rock joint by using a distinct element method code with Voronoi tessellation. The applicability of the numerical model was assessed by calibration with a series of standard laboratory tests. The simulation results indicate that the magnitude of relative normal stress plays the most important role among parameters and quantify how much those parameters affect the dilation behaviour during shear. The findings of this study, presented in a normalised relation, can be employed when dilation values need to be determined in rock engineering practice.

This paper presents a joint constitutive model that represents the shear behaviour of a large-scale opened rock joint. Evaluation of the degree of opening is made by considering the ratio between the joint wall aperture and the joint amplitude. Scale dependence of the surface roughness is investigated by approximating a natural joint profile to a fractal curve patterned in self-affinity. Developed scaling laws show the slopes of critical waviness and critical unevenness tend to flatten with increased sampling length. Geometrical examination of four 400-mm joint profiles agrees well with the suggested formulations involving multi-order asperities and fractal descriptors. Additionally, a fractal-based formulation is proposed to estimate the peak shear displacements of rock joints at varying scales, which shows a good correlation with experimental data taken from the literature. Parameters involved in the constitutive law can be acquired by inspecting roughness features of sampled rock joints. Thus, the model can be implemented in numerical software for the stability analysis of the rock mass with opened joints.

This study focused on studying the V-shaped rock failure around borehole walls and reproducing borehole breakout using numerical simulations. Discrete element method (DEM) is adopted, and a two-dimensional particle flow code (PFC2D) model is built based on Tenino sandstone. The simulations are conducted by applying different maximum horizontal stress values under the same minimum horizontal stress condition, and the results are compared with the true-triaxial breakout experiments on the same rock properties and loading conditions. Due to the absence of vertical stress in 2D simulations, the obtained angular spans are generally larger than the experimental values. On the other hand, the breakout depths are found to be significantly smaller than the experimental results since the failed particles within the breakout zone remained to withstand internal loads and constrain the damage zone. In order to better simulate the rock detachment process during breakout formation, a particle removal algorithm using the strain energy release concept is developed and embedded into the model. With the implementation of the algorithm, the breakout propagation process in the vicinity of the borehole shows a good agreement with the experimental observations, suggesting that the effective removal of failed particles is essential for accurately simulating borehole breakout. The results from this study can provide new insights into the V-shaped breakout formation mechanism and strain energy changes during borehole breakout initiation and propagation.

Simulating fire spread and identifying potential propagation pathways in the Wildland–Urban Interface (WUI) are critical for wildfire prevention, emergency preparedness, and firefighting—especially in the wake of catastrophic events such as the 2025 Los Angeles wildfire, the 2019–2020 Australian bushfires, and the 2023 wildfires in Greece. Despite growing awareness of wildfire risks near urban boundaries, lightweight, high-resolution 3D simulation tools remain limited, hindering scenario-based planning and rapid response. To address this gap, we present a voxel-based 3D wildfire propagation simulator developed in Python. The simulator integrates LiDAR-derived voxel models of urban environments, GIS-informed fuel characterizations, and high-performance parallelism via the Taichi framework. Fire dynamics are modeled across 3D voxel grids using a hybrid of physics-based and empirical approaches, incorporating key parameters such as wind speed, fuel type, and moisture content. Critical processes—including inter-voxel heat transfer, crown fire spread, and surface fireline intensity—are captured to simulate realistic fire behavior. Simulation results are exported in standard 3D formats for immersive visualization in platforms such as Blender and Unity. A case study using LiDAR data from Newcastle, Australia demonstrates the tool’s real-world applicability. Designed for modularity and extensibility, the simulator supports model replacement, parameter tuning, and integration with diverse spatial datasets. It also serves as a scalable framework for high-fidelity modeling of inter-voxel mass and energy transfer in complex urban environments, enhancing decision-support capabilities. Additionally, the tool generates synthetic fire spread data, enabling the training of generative AI models and integration with broader urban and environmental simulation platforms.

Providing information to emergency responders and citizens is one of the most critical aspects during bushfire events. In many cases ground-based infrastructure might be malfunctioning or destroyed and satellite communication might appear the only option. This paper concentrates on the use of the QZSS satellites to provide short messages early warning. The paper provides a preliminary overview of the initial investigations, development and testing of an emergency management system for preparedness and response to extreme bushfire events in Australia. We examine how emergency modelling data can be used to assist a central command centre in generating location-based information during a crisis.

In the search for lightweight and sustainable engineering approaches, enhancing the surface wear resistance of structural materials, such as 6061-T6 aluminum alloy, has become increasingly important. This study investigates the effect of coverage rates on the tribological properties of shot-peened 6061-T6 alloy, aiming to improve its usage in industries where weight reduction and durability are important, such as aerospace, automotive, railway, and renewable energy systems. A shot peening process was applied at four different coverage rates of 100%, 200%, 500%, and 1500% for comprehensive evaluation. A series of experimental analyses were conducted, including microhardness tests, ball-on-plate wear tests, residual stress measurements, and surface roughness evaluations. Furthermore, microstructural analysis was performed to investigate subsurface deformation, and scanning electron microscopy (SEM) was carried out to identify the wear mechanisms of the worn surfaces in detail. The results demonstrated a clear trend of gradual improvement in wear resistance with increasing shot peen coverage. The sample treated at a 1500% coverage rate exhibited 1.34 times higher hardness and 19 times higher wear resistance compared to the untreated sample. This study highlights that shot peening is an effective and feasible surface engineering method for enhancing the wear performance of 6061-T6 alloy. The findings offer valuable contributions for the development of lightweight and wear-resistant components considering sustainable material design.

Wind energy plays a major role in decarbonisation of the electricity sector and supports achieving net-zero greenhouse gas emissions. Over the last decade, the wind energy deployments have grown steadily, accounting for more than one fourth of the annual electricity generation in countries like the United Kingdom, Denmark, and Germany. However, as the share of wind energy increases, system operators face challenges in managing excessive wind generation due to its nondispatchable nature. Currently, the most common practice is wind energy curtailment in which wind farm operators receive constraint payments to reduce their renewable energy production. This practice not only leads to wastage of large volumes of renewable energy, but also the associated financial cost is reflected to rate payers in the form of increased electricity bills. On-site energy storage technologies come to the forefront as a technology option to minimise wind energy curtailment and to harness wind energy in a more efficient way. To that end, this paper, first, systematically evaluates different energy storage options for wind energy farms. Second, a depth analysis of curtailment and constraint payments of major wind energy farms in Scotland are presented. Third, using actual wind and market datasets, a techno-economic analysis is conducted to examine the relationship between on-site energy storage size and the amount of curtailment. The results show that, similar to recent deployments, lithium-ion technology is best suited for on-site storage. As case studies, Whitelee and Gordon bush wind farms in Scotland are chosen. The most suitable storage capacities for 20 years payback period is calculated as follows: (i) the storage size for the Gordonbush wind farm is 100 MWh and almost 19% of total curtailment can be avoided and (ii) the storage size for the Whitlee farm is 125 MWh which can reduce the curtailment by 20.2%. The outcomes of this study will shed light into analysing curtailment reduction potential of future wind farms including floating islands, seaports, and other floating systems.

Background While psychological symptoms are common among older adults, Mental Health Literacy (MHL) is low. This situation may show significant differences in MHL levels and psychological symptom severity among risk groups. However, this is not sufficiently clear. Therefore, this study aimed to examine psychological symptom risk levels and MHL among older adults in Türkiye, and to identify demographic, clinical, and MHL-related factors associated with variation in continuous Global Severity Index (GSI) scores within the high-risk and very-high-risk groups. Methods A cross-sectional design was used. The study was completed with 985 older adults aged between 65 and 89 years. Data were collected via the Participant Information Form, MHL Scale, and Symptom Checklist–90–Revised (SCL-90-R). Univariate and multivariate linear regression analyses were conducted to identify predictors of high-risk psychological symptoms, with multicollinearity checked via VIF values. Results Based on GSI scores obtained from the SCL-90-R scale, 42.6% of participants were in the normal risk group, 39.6% in the high-risk group, and 17.8% in the very high-risk group. In Model 1, multivariate regression analyses revealed that low MHL, being aged 65–74, female gender, low education level, and a history of mental disorder were significant predictors of high-risk GSI. In Model 2, the absence of a physical chronic disease was additionally found to be a significant predictor. Together, these variables explained 31–34% of the variance in GSI risk. Conclusions These results suggest that MHL, along with key demographic and clinical factors, plays a significant role in predicting high-risk GSI among older adults.