Search Results (67)

Industrial environments are complex, making the monitoring of gauge meters challenging. This is especially true in confined spaces, underground, or at high altitudes. These difficulties underscore the need for intelligent solutions in the inspection and monitoring of plant assets, such as gauge meters. In this study, we plan to integrate unmanned ground vehicles and unmanned aerial vehicles to address the challenge, but the integration of these heterogeneous systems introduces additional complexities in terms of coordination, interoperability, and communication. Our goal is to develop a multi-domain robotic swarm system for industrial mapping and asset monitoring. We created an experimental setup to simulate industrial inspection tasks, involving the integration of a TurtleBot 2 and a QDrone 2. The TurtleBot 2 utilizes simultaneous localization and mapping (SLAM) technology, along with a LiDAR sensor, for mapping and navigation purposes. The QDrone 2 captures high-resolution images of meter gauges. We evaluated the system’s performance in both simulation and real-world environments. The system achieved accurate mapping, high localization, and landing precision, with 84% accuracy in detecting meter gauges. It also reached 87.5% accuracy in reading gauge indicators using the paddle OCR algorithm. The system navigated complex environments effectively, showcasing the potential for real-time collaboration between ground and aerial robotic platforms. Full article

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article

Urban tree planting on single-family-home lots represents a critical yet underexplored component of municipal greening strategies. This study examines residents’ perceptions of tree planting in Westpointe, a diverse neighborhood in Salt Lake City, Utah, as part of the city’s Reimagine Nature Public Lands Master Plan development effort. Through a mixed-methods approach combining qualitative interviews (n = 24) and a tree signup initiative extended to 86 residents, with 51 participating, this research explores the complex interplay of demographic, economic, social, and infrastructure factors influencing residents’ willingness to plant trees on single-family-home lots. The findings reveal significant variations based on gender, with women expressing more positive environmental and aesthetic motivations, while men focused on practical concerns including maintenance and property damage. Age emerged as another critical factor, with older adults (65+) expressing concerns about long-term maintenance capabilities, while younger families (25–44) demonstrated future-oriented thinking about shade and property values. Property characteristics, particularly yard size, significantly influenced receptiveness, with owners of larger yards (>5000 sq ft) showing greater willingness compared to those with smaller properties, who cited space constraints. Additional barriers, i.e., maintenance, financial, and knowledge barriers, included irrigation costs, lack of horticultural knowledge, pest concerns, and proximity to underground utilities. Geographic analysis revealed that Spanish-speaking social networks were particularly effective in promoting tree planting. The study contributes to urban forestry literature by providing nuanced insights into single-family homeowners’ tree-planting decisions and offers targeted recommendations for municipal programs. These include gender-specific outreach strategies, age-appropriate support services, sliding-scale subsidy programs based on property size, and comprehensive education initiatives. The findings inform evidence-based approaches to increase urban canopy coverage through private property plantings, ultimately supporting climate resilience and environmental justice goals in diverse urban neighborhoods. Full article

The digital transformation of the Architecture, Engineering and Construction sector is accelerating the adoption of digital platforms as critical enablers of data integration, stakeholder collaboration and process optimization. This paper presents a systematic review of 125 peer-reviewed journal articles (2015–2025), selected through a PRISMA-guided search using the Scopus database, with inclusion criteria focused on English-language academic literature on platform-enabled digitalization in the built environment. Studies were grouped into six thematic domains, i.e., artificial intelligence in construction, digital twin integration, lifecycle cost management, BIM-GIS for underground utilities, energy systems and public administration, based on a combination of literature precedent and domain relevance. Unlike existing reviews focused on single technologies or sectors, this work offers a cross-sectoral synthesis, highlighting shared challenges and opportunities across disciplines and lifecycle stages. It identifies the functional roles, enabling technologies and systemic barriers affecting digital platform adoption, such as fragmented data sources, limited interoperability between systems and siloed organizational processes. These barriers hinder the development of integrated and adaptive digital ecosystems capable of supporting real-time decision-making, participatory planning and sustainable infrastructure management. The study advocates for modular, human-centered platforms underpinned by standardized ontologies, explainable AI and participatory governance models. It also highlights the importance of emerging technologies, including large language models and federated learning, as well as context-specific platform strategies, especially for applications in the Global South. Full article

In the current context of tight constraints on land resources in major Chinese cities, the development of underground space in green spaces (USGSs) has become an important approach to exploit land use potential and alleviate the contradiction between human and land resources. Evaluating USGS development potential scientifically is crucial for project site selection and improving underground space utilization. However, most studies have focused on underground space as a whole, with limited attention to single land use types, and research on USGSs has mainly concentrated on planning and design. This study proposes a two-stage evaluation framework for urban green spaces, identifying suitable development areas while safeguarding ecological functions. The framework evaluates from “restrictiveness” and “suitability”: first extracting developable green spaces by restrictiveness evaluation and then assessing development potential by suitability evaluation. This approach overcomes traditional methods that disregard prerequisite relationships among factors. A case study in Binjiang District, Hangzhou, showed that small green spaces and connectivity were key limiting factors for the development of USGSs. The proposed framework could provide some degree of reference for future development potential evaluation of USGSs, and the results could provide actionable guidance for high-density built environments similar to Binjiang District. Full article

Carbon Capture and Storage (CCS) technology presents a practical solution for reducing industrial carbon dioxide (CO₂) emissions through underground anthropogenic CO₂ storage in depleted hydrocarbon reservoirs. The long-term storage efficiency faces several CO₂ leakage challenges that need to be addressed in the planning phase of the CCS project. Thus, effective risk assessment (RA) methodologies are crucial for ensuring safety, regulatory compliance, and public acceptance of CCS projects. This review examines RA parts and their corresponding technical and non-technical challenges. The analysis critically compares over 20 qualitative, semi-quantitative, quantitative, and hybrid RA techniques employed throughout GCS operations. Available quantitative RA tools do not deliver dependable results because they require technical data that become available late in the CCS project development process. Qualitative approaches work well for the initial screening of storage sites with limited data available, yet quantitative methods enable quantification of CO₂ leakage. For the first time, a comparative analysis of two integrated assessment tools is presented in this paper. The techniques achieve success based on high-quality data and analysis of existing technical and non-technical challenges which this paper examines. The comparative analysis outlines the limitations and advantages of every methodology studied and emphasizes the need for integrated hybrid frameworks to boost decision-making in the RA process. Future research should focus on creating or improving existing hybrid frameworks for late-stage RA while utilizing qualitative frameworks in the initial site screening stage to advance GSC’s safe and effective implementation. Full article

Utilizing underground space has become a means to address urban issues; however, heritage protection in underground development has become an unavoidable challenge. Whether to proceed with underground development in a heritage site requires a suitability study that considers various influencing factors to guide comprehensive protection planning. Therefore, conducting a suitability study for underground development in heritage sites is a critical issue that must be addressed before policy and planning decisions. Based on preliminary research, this study identifies and summarizes the influencing factors of underground heritage development suitability, innovatively constructs the “Underground Resource Development Suitability Index System of Cultural Heritage, URDSIS-CH”, and employs the “Dependency Analytic Process, DAP” method for evaluation. It explores spatial development issues arising from underground heritage development and clarifies the relationship mechanisms between relevant influencing factors. This study seeks to resolve the contradiction between underground space development and cultural heritage protection through technological and methodological approaches, providing insights for a more scientific approach to underground heritage preservation and utilization. Full article

With rapid urbanization, urban underground space (UUS) development has become crucial for sustainable urban growth. This paper systematically reviews geological suitability evaluation (GSE) methods for UUS, integrating theoretical frameworks, indicator systems, and assessment techniques. We establish a comprehensive evaluation framework based on environmental strategic assessment (ESA) principles, analyzing key geological factors, including rock/soil properties, hydrogeological conditions, geological hazards, and existing underground structures. The study compares weighting methods (AHP, EWM, CRITIC) and comprehensive evaluation models (FCE, TOPSIS, BNM), highlighting their advantages and application scenarios. A case study of Xiong’an New Area demonstrates how multi-layer UUS planning integrates geological constraints with sustainable development goals. The results show that combining 3D geological modeling with hybrid evaluation methods significantly improves decision-making accuracy. The review provides practical guidance for optimizing UUS utilization while addressing current challenges in indicator selection, weight rationalization, and heterogeneity management. Full article

The construction industry is undergoing a transformative shift through automation, with advancements in Generative AI (GenAI) and prompt engineering enhancing safety and efficiency, particularly in high-risk fields like underground construction, geotechnics, and mining. In underground construction, GenAI-powered prompts are revolutionizing practices by enabling a shift from reactive to predictive approaches, leading to advancements in design, project planning, and site management. This study explores the use of Google Gemini, a recent advancement in GenAI, for the prediction of rockburst intensity levels in underground construction. The Python programming language and the Google Gemini tool are combined with prompt engineering to generate prompts that incorporate essential variables related to rockburst. A comprehensive database of 93 documented rockburst cases is compiled. Subsequently, a systematic method is established that involves the categorization of intensity levels through data visualization and factor analysis in order to identify a reduced number of unobservable underlying factors. Furthermore, K-means clustering is utilized to identify data patterns. The gradient boosting classifier is then employed to predict the intensity levels of rockburst. The results demonstrate that GenAI and prompt engineering offers an effective approach for accurately predicting rockburst events, achieving an accuracy rate of 89 percent. Through predictive modeling with GenAI, construction engineering experts can proactively evaluate the likelihood of rockburst, allowing for improved risk management, optimized excavation strategies, and enhanced safety protocols. This approach enables the automation of complex analyses and provides a powerful tool for real-time decision-making and predictive insights, offering significant benefits to industries reliant on underground construction. However, despite the considerable potential of GenAI and prompt engineering in the construction sector, challenges related to output accuracy, the dynamic nature of projects, and the need for human oversight must be carefully addressed to ensure effective implementation. Full article

The Yinchuan Basin harbors significant geothermal resource potential and could be a clean energy source critical for transitioning to a low-carbon economy. However, the current research primarily focuses on the exploration and development of geothermal water in the sedimentary basins, with limited studies on the deep geothermal formation mechanisms and regional geothermal types. Although geophysical methods provide insights into the types and formation mechanisms of deep geothermal resources in the basin, there is still a lack of a connection between quantitative understanding and direct evidence. A series of algorithms based on thermal parameter characteristics can directly extract underground thermal features from raw geophysical signal data, offering a powerful tool for characterizing the structure and aggregation patterns of deep thermal sources. Therefore, this study employed a Bayesian thermal parameter inversion method based on interface information to obtain the spatial distribution of thermal conductivity, surface heat flow, and mantle heat parameters in the Ningxia Basin study area. Additionally, correlation analysis and global sensitivity analysis were conducted to further interpret the predicted results. A comprehensive analysis of the geophysical inversion results showed that the deep thermal anomalies in the basin are primarily controlled by fault activities and the lithospheres’ thermal structure, while shallow high-heat flow anomalies are closely related to convective circulation within faults and heat transfer from deep thermal sources. The established geothermal genesis mechanism and model of the Yinchuan Basin provide crucial support for sustainable regional geothermal development planning and the utilization of deep geothermal resources, contributing to energy security and emission reduction goals. Full article

Underground space is considered a critical urban resource that can significantly promote sustainable development under rational planning. This study, taking the Longgang region in SE China as an example, comprehensively considers the dual influences of geological environmental factors and socio-economic factors, incorporating socio-economic factors as key cost indicators. Following the principle of “stratification and classification”, a detailed assessment framework was developed to evaluate the suitability of underground space for development across various depths, and a systematic analysis of development suitability was conducted. Specifically, we employed a fuzzy comprehensive evaluation method to assess the suitability of underground space. During this process, an analytic hierarchy process (AHP) was used to determine the weights of geological environmental indicators, and the group judgment matrix approach was applied to assign weights to the socio-economic factors. The results indicated that, for shallow spaces, areas with high resource potential accounted for approximately 10.0% of the region, while areas with relatively high resource potential accounted for 28.5%. For medium-depth spaces, areas with high resource potential comprised 19.9% of the region, and areas with relatively high resource potential accounted for about 35.1%. These findings suggest that the study area demonstrated promising prospects for the development and utilization of underground space. The proposed approaches ensured that the evaluation results were both scientific and reasonable. By integrating the impact of socio-economic factors into suitability evaluation, the outputs provided more scientifically grounded guidance for urban planning. Full article

With the ongoing urbanization and densification of cities worldwide, the planning and utilization of urban underground space (UUS) have become crucial for developing urban underground infrastructure. Given the limited construction space within dense urban areas and the influence of declining groundwater levels, technologies such as open caissons and various vertical shaft methods have been introduced for UUS development. However, the dissemination of these technologies remains fragmented across different domains, lacking systematic summarization. A comprehensive, up-to-date overview of open caisson and vertical shaft technologies is essential for their effective application. In the manuscript, a systematic analysis of vertical shaft technologies, specifically focusing on their use in soft ground conditions, is conducted. The analysis is based on an extensive literature review and case study evaluation. It addresses the unique challenges posed by high compressibility, low bearing capacity, and groundwater sensitivity. Conventional shaft technologies and mechanized systems, including open caissons, drilled shafts, and the novel pressed-in ultra-deep assembled shafts (PIAUS), are evaluated systematically. Key aspects such as design principles, construction techniques, and stability in soft soils are discussed. The limitations of conventional methods in soft UUS are highlighted, while the advantages of advanced mechanized systems—such as rapid construction, reduced environmental impact, and improved safety—are emphasized. A detailed comparison of case studies demonstrates that PIAUS construction technology is particularly efficient in urban areas with confined spaces, dense building conditions, and ground conditions up to 200 MPa, with shaft diameters up to 12.8 m and depths of 115.2 m. Additionally, its suitability for rapid construction in soft and medium ground conditions is supported by undrained excavation with parallel excavation and liner sinking techniques. The PIAUS technology shows considerable potential for future projects, including shield construction shafts, ventilation shafts for tunnels, underground parking garages, and stormwater storage wells. This manuscript also highlights emerging mechanized methods in underground space development, their advantages, limitations, and areas for future research and improvement. Full article

The UK net zero strategy aims to fully decarbonize the power system by 2035, anticipating a 40–60% increase in demand due to the growing electrification of the transport and heating sectors over the next thirteen years. This paper provides a detailed technical and economic analysis of the role of energy storage technologies and transmission lines in balancing the power system amidst large shares of intermittent renewable energy generation. The analysis is conducted using the cost-optimizing energy system modelling framework REMix, developed by the German Aerospace Center (DLR). The obtained results of multiple optimization scenarios indicate that achieving the lowest system cost, with a 73% share of electricity generated by renewable energy sources, is feasible only if planning rules in England and Wales are flexible enough to allow the construction of 53 GW of onshore wind capacity. This flexibility would enable the UK to become a net electricity exporter, assuming an electricity trading market with neighbouring countries. Depending on the scenario, 2.4–11.8 TWh of energy storage supplies an average of 11% of the electricity feed-in, with underground hydrogen storage representing more than 80% of that total capacity. In terms of storage converter capacity, the optimal mix ranges from 32 to 34 GW of lithium-ion batteries, 13 to 22 GW of adiabatic compressed air energy storage, 4 to 24 GW of underground hydrogen storage, and 6 GW of pumped hydro. Decarbonizing the UK power system by 2035 is estimated to cost $37–56 billion USD, with energy storage accounting for 38% of the total system cost. Transmission lines supply 10–17% of the total electricity feed-in, demonstrating that, when coupled with energy storage, it is possible to reduce the installed capacity of conventional power plants by increasing the utilization of remote renewable generation assets and avoiding curtailment during peak generation times. Full article

Underground cold storage gives rise to special challenges that require innovative solutions to ensure maximum energy efficiency. Conventional energy systems tend to be based on high energy use, so sustainable solutions are crucial. This study explores the novel idea of biomimetics and how it might be used in the planning and building of underground cold storage facilities as well as other infrastructure projects. Biomimetic strategies, inspired by termite mounds, gentoo penguin feathers, and beehive structures, are applied to minimize reliance on energy-intensive cooling systems. These natural models offer efficient thermal regulation, airflow optimization, and passive cooling mechanisms such as geothermal energy harvesting. The integration of naturally driven convection and ventilation ensures stable internal temperatures under varying conditions. Biomimicry was employed in Revit Architecture, coupled with structural optimization, to eliminate urban space’s limitations and further increase energy efficiency. The analytical work for this paper utilized a set of formulas that represent heat flow, thermal resistance, R-value, thermal transmittance, U-value, solar absorption, and G-value. The results pointed to very good insulation, with exterior walls having an R-value of 10.2 m²K/W and U-value of 0.98 W/m²K. Among the chosen 3-layer ETFE cushion with a U-value of 1.96 W/m²K, with a G-value of 0.50, showed good heat regulation and daylight management. Furthermore, bagasse-cement composites with a very low thermal conductivity of 0.10–0.30 W/m·K provided good insulation. This research proposes a scalable and sustainable approach in the design of underground cold storage by merging modelling based on Revit with thermal simulations. Biomimicry has been demonstrated to have the potential for changing subterranean infrastructure, conserving energy consumption, and creating eco-friendly construction practices. Full article

Safe path planning is essential for the autonomous operation of robotic roadheader in narrow underground tunnels, where limited perception and the robot’s geometric constraints present significant challenges. Traditional path planning methods often fail to address these issues. This paper proposes a collision prediction-integrated path planning method tailored for robotic roadheader in confined environments. The method comprises two components: collision prediction and path planning. A collision prediction model based on artificial potential fields is developed, considering the non-convex shape of the roadheader and enhancing scalability. By utilizing tunnel design information, a composite potential field model is created for both obstacles and the roadheader, enabling real-time collision forecasting. The A* algorithm is modified to incorporate the robot’s motion constraints, using a segmented weighted heuristic function based on collision predictions. Path smoothness is achieved through Bézier curve smoothing. Experimental results in both obstacle-free and obstacle-laden scenarios show that the proposed method outperforms traditional approaches in terms of computational efficiency, path length, and smoothness, ensuring safe, efficient navigation in narrow tunnels. Full article