Search Results (39)

Accurate recognition of Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) signals is crucial for mitigating positioning errors and improving the positioning performance of Ultra-Wideband (UWB) localization systems. Current NLOS identification methods are limited to the specific measurement environments and fail to exhibit effective cross-domain adaptability, being unable to generalize to unseen environments. To address these challenges, we propose a novel NLOS identification strategy based on a Domain-Adversarial Neural Network (DANN). Firstly, aiming at the problem that traditional feature extraction methods fail to capture the deep nonlinear characteristics of Channel Impulse Response (CIR) data, we develop a CNN-DAE-MLP-Attention (CDM) hybrid model for high-quality channel feature extraction, which takes both raw CIR data and handcrafted channel features into account. Secondly, we integrate the CDM model into the DANN framework by replacing its original shallow feature extraction module to further propose the CDMD algorithm; by combining the robust feature representation capability of CDM with the excellent domain adaptation capability of DANN, the proposed CDMD algorithm achieves enhanced performance in cross-domain LOS/NLOS identification. Finally, the effectiveness of the proposed algorithm is verified using measured data from different scenarios. Results demonstrate that the proposed algorithm possesses strong generalization ability. For cross-domain NLOS recognition from underground parking garage to corridor and underground parking garage to lobby, the proposed method achieves accuracies of 77.00% and 72.84%, respectively. Moreover, the results indicate that only a limited number of target-domain samples are sufficient for the model to achieve accurate cross-domain transfer. Full article

With the rapid development of underground spaces and demand for infrastructure-independent autonomous positioning in post-disaster rescue, Pedestrian Dead Reckoning (PDR) has become a key research focus. However, traditional PDR suffers from cumulative heading drift, inadequate 3D positioning performance, and poor anti-magnetic interference capabilities, failing to meet the high-precision positioning requirements of rescuers in underground and multistory buildings. To address these issues, this paper proposes an adaptive 3D-PDR method fusing inertial, geomagnetic, and barometric (3D-IMB-APDR). Sensor data are optimized via FFT dominant frequency extraction and Butterworth zero-phase filtering, with magnetic interference compensated by geomagnetic ellipse fitting. A segmental heading correction with a multi-criteria dynamic geomagnetic reliability model suppresses heading drift. A barometer-based coarse estimation and inertial fine correction architecture is adopted, where a lightweight CNN-BiLSTM network extracts inertial features for step height, and AEKF fuses multi-source data to achieve accurate vertical height estimation and precise 3D positioning. Validated in sports fields, underground parking garages, and staircases, the method outperforms four comparative methods, reducing positional RMSE by 65.77–98.23%, with endpoint errors of 1.40 m, 2.56 m, and 0.32 m, respectively. Relying solely on chest-worn sensors, it provides a reliable 3D autonomous positioning solution for rescuers in post-disaster rescue and underground engineering. Full article

In contemporary multi-family housing construction, the structural grid is often influenced or conditionally determined by the dimensional logic of underground parking garages. When transferred to above-ground storeys, it directly defines façade frontage, building depth, and possibilities for apartment organisation. Previous research has mostly examined housing typology, dimensional standards, and structural systems as separate domains, while the influence of parking-derived structural grids has not been systematically analysed within a unified framework. This paper applies an analytical-comparative approach, comparing typical structural grids derived from parking modules with the minimum façade frontages required for different apartment types. The method includes identifying characteristic grid dimensions, defining minimum façade frontages based on normatively prescribed room widths, calculating deviations between required and available dimensions, and analysing individual and combined apartment units according to the criterion of minimal positive deviation, within the Serbian regulatory framework. The results show that the structural grid is a relevant factor in apartment organisation and typological structure. Certain grids enable more rational layouts with minimal spatial adjustments, while others generate dimensional surplus, excessive depth, or typological constraints. The study establishes a link between parking modules, structural grids, and apartment organisation, and proposes an analytical framework for evaluating their dimensional compatibility in multi-family housing design. Full article

Underground parking garages in high-density megacities are high-risk environments where strong confinement and large fire loads pose severe safety threats. In this study, an evaluation model is proposed based on the entropy weight method combined with dynamic traffic conditions to determine the regional fire service accessibility index $C_j$. Taking Shenzhen, a megacity in China, as the study area, POI data were used to identify 510 fire stations as supply points and 3378 underground parking garages as demand points, yielding 165,522 samples across 49 evaluation scenarios. The results show that the overall average travel time, distance, and velocity are 388.17 s, 2217.95 m, and 5.84 m/s. $C_j$ fluctuates between 0.572 and 0.813, demonstrating clear time-of-day differences. The overall average $C_j$ for all 49 scenarios is 0.697, corresponding to Grade “C”, representing the general level of regional fire service accessibility. It is recommended that additional fire resources be deployed during peak hours and that fire station layouts in peripheral areas be optimized to improve fire safety in underground parking garages. Full article

Unmanned aerial vehicles (UAVs) are increasingly used indoors for inspection, security, and emergency tasks. Achieving accurate and robust localization under Global Navigation Satellite System (GNSS) unavailability and obstacle occlusions is therefore a critical challenge. Due to their inherent physical limitations, Inertial Measurement Unit (IMU)–based localization errors accumulate over time, Ultra-Wideband (UWB) measurements suffer from systematic biases in Non-Line-of-Sight (NLOS) environments and Visual–Inertial Odometry (VIO) depends heavily on environmental features, making it susceptible to long-term drift. We propose a tightly coupled fusion framework based on the Error-State Kalman Filter (ESKF). Using an IMU motion model for prediction, the method incorporates raw UWB ranges, VIO relative poses, and TFmini altitude in the update step. To suppress abnormal UWB measurements, a multi-epoch outlier rejection method constrained by VIO is developed, which can robustly eliminate NLOS range measurements and effectively mitigate the influence of outliers on observation updates. This framework improves both observation quality and fusion stability. We validate the proposed method on a real-world platform in an underground parking garage. Experimental results demonstrate that, in complex indoor environments, the proposed approach exhibits significant advantages over existing algorithms, achieving higher localization accuracy and robustness while effectively suppressing UWB NLOS errors as well as IMU and VIO drift. Full article

Surface dust serves as a significant carrier and potential source of various pollutants in urban environments. However, limited attention has been paid to toxic metals in underground parking garages’ (UPGs) surface dust. In this study, thirty surface dust samples were collected from UPGs to determine the toxic metals contents, their risk and disease burden to local residents, and their potential source. The mean contents of V, Cr, Co, Ni, Cu, Zn, Cd, Sb, Pb, Hg, and As were 68.06, 126.48, 8.73, 27.68, 76.25, 287.07, 0.74, 4.28, 172.67, 0.24, and 8.66 mg/kg, respectively. Accumulation index revealed that the geoaccumulation index of Cr, Cu, Cd, Zn, Sb, Pb, and Hg ranged from 0.52 to 1.85. Pollution load index verified that the surface dust was slightly (56.67%), moderately (30.00%), or heavily polluted (13.33%). Risk assessment revealed that the total non-carcinogenic risks for children all exceeded the acceptable level (HI > 1.0). Notably, the carcinogenic burden reached 12.9 disability-adjusted life years per 100,000 population, with Cr contributing 84.1%. Furthermore, these toxic metals mainly derived from vehicle-related activities, use of coal, and the aging of decoration materials, and their accumulation in UPGs’ surface dust was almost unaffected by the essential conditions of residential areas. Full article

Underground spaces hold significant potential for enhancing urban resilience against disasters, a key dimension of sustainable urban development. However, due to persistent associations of underground environments with negative psychological perceptions, these spaces—despite their superior protective advantages—are often overlooked as viable refuge options during emergencies. Guided by the theoretical framework of environmental psychology, this research focuses on underground parking garages in Hangzhou, China as its primary research object. The target participants are residents of Hangzhou aged 18–58 years (encompassing diverse occupations such as students, office workers, and service industry employees), who represent potential users of such spaces as refuges. To explore human behavioral patterns, psychological responses, and needs related to underground refuge spaces, we employed a two-phase methodology: first, a questionnaire survey to capture broader behavioral tendencies and subjective perceptions; complementing this, Virtual Reality (VR) experiments—a more immersive method—utilizing semantic analysis and the Likert scale to assess psychological indicators influenced by underground environments. The experimental data were analyzed via mean analysis, correlation analysis, and multiple linear regression analysis to identify the key environmental factors that influence psychological responses, as well as their optimal design parameters. These analyses reveal significant correlations between various environmental factors and psychological indicators. This research synthesizes individuals’ psychological tendencies in underground environments and proposes quantitative physical design guidelines to meet fundamental psychological needs. The findings provide theoretical and practical support for the design of underground space for refuge and the development of sustainable urban emergency shelter systems, thereby contributing to resilient and sustainable urban development. Full article

Under the frequent occurrence of urban waterlogging disasters globally, underground spaces, due to their unique environmental conditions and structural vulnerabilities, are facing growing flood pressure, resulting in substantial economic losses that hinder sustainable urban development. This study focused on a high-density urban area in China, investigating surface waterlogging conditions under rainfall characteristics as the primary driver of flooding. Focusing on the main nodes—entrances and exits—within the waterlogging disaster chain of underground garages, a risk assessment framework was constructed that encompasses three key dimensions: the attributes of extreme rainfall, the structural characteristics of entrances/exits, and emergency response capacities. Subsequently, a waterlogging risk assessment was conducted for selected underground garages in the study area under a 100-year return period extreme rainfall scenario. The results revealed that the flood depth at entrances/exits and the structural height of entrances/exits are the primary factors influencing flood risk in urban underground garages. Under this simulation scenario, 37.5% of the entrances and exits exhibited varying degrees of flood risk. The assessment framework and indicator system developed in this study provide valuable insights for flood risk evaluation in underground garage systems and offer decision-makers a more scientific and robust foundation for formulating improvement measures. 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 ultra-wideband (UWB) base station (BS) deployment pattern seriously affects mobile tag positioning accuracy, but the traditional classical deployment methods, such as rectangular and diamond deployment, cannot take into account the influence of non-line-of-sight (NLOS) occlusion, which leads to a blind area in positioning. In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. The simulation experiment results show that the locatable space coverage rate of rectangular and diamond deployment models gradually decreases and the blind positioning area gradually increases with the increase in NLOS occlusion. The locatable space coverage rate of the LPSO-optimized deployment is better than that of the standard PSO-optimized deployment model, while it is 19.0% and 22.6% better than the rectangular deployment and 3.0% and 6.5% better than the diamond deployment when the NLOS values are 3 and 5 for complex occlusion environments, respectively. The experimental results of the underground garage demonstrate that the optimal 13 BS layout scheme, obtained through LPSO, outperforms the 7 BS layout scheme by 34.9% while reducing the horizontal dilution of precision (HDOP) values by 81.7%. Therefore, the proposed UWB BS layout optimization scheme exhibits superior adaptability to large and complex indoor environments, effectively enhances signal coverage and positioning accuracy, and holds significant practical value. Full article

With the rising adoption of electric vehicles (EVs), fire-related issues have garnered significant attention, prompting extensive research efforts. This study investigates the dispersion of toxic gases generated during EV fires in confined spaces, such as underground parking garages, to enhance fire safety protocols. Using the fire dynamics simulator (FDS), simulations were conducted for 24 kWh, 53 kWh, and 99.8 kWh battery scenarios to assess the impact of increasing battery capacities on toxic gas emissions. The results indicate that hydrogen fluoride (HF) concentrations in poorly ventilated areas peaked at 488.2 ppm, significantly exceeding the Acute Exposure Guideline Level (AEGL-2) threshold of 12 ppm. The exposure time exceeding AEGL-2 (30 min) was recorded as 53 min and 49 s for the 99.8 kWh scenario, highlighting a substantial risk to occupants and emergency responders. Additionally, the fractional effective dose (FED) for asphyxiant gases and the fractional effective concentration (FEC) for irritant gases were analyzed, revealing that larger battery capacities and proximity to the fire source reduced tenability time by up to 47% compared to smaller batteries. These findings provide critical insights into fire safety measures, emphasizing the necessity of early fire detection systems, enhanced ventilation strategies, and battery-specific fire suppression technologies in confined environments. Full article

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment. Full article

The use of the Vertical Shaft Sinking Machine (VSM) for shaft construction marks a significant advancement in modern technology and is recognized as one of the leading techniques in the field. However, much of the existing research focuses on mechanical and technical challenges, often overlooking the effects on surrounding soil and the structural integrity of shafts. This study demonstrates that increasing pile diameter by 20% improves load-bearing capacity by 15% and reduces soil settlement by 12%, though these improvements come with higher construction costs. Additionally, larger diameters improve lateral stability, but excessively long piles lead to diminishing returns. To address the limited research on reinforcement design in soft soils, a series of numerical models were employed to investigate the effects of pile spacing, length, and diameter on surrounding soil behavior. This in-depth analysis aims to provide a scientific foundation for optimizing VSM technology in caisson pile foundations, particularly in soft-soil conditions. Full article

Excavations for underground structures, such as working shafts, underground grain silos, and parking garages, are characterized by uniformity, consistent dimensions, large quantities, and strict timelines. Prefabricated recyclable supporting structures (PRSS) are gaining attention over traditional retaining structures due to their standardized design, efficient construction, and reusability, which suit such excavations better. To validate their performance, full-scale tests are conducted to analyze the deformation and stress characteristics of PRSS. The results show that the average maximum lateral displacement of supporting pile is 0.07% of the excavation depth (H_e), roughly half that of steel plate. Differences in ground surface settlement behind steel plates and the supporting piles are not as significant as those in their lateral displacements. While the displacement of the supporting piles is insufficient to induce soil movement into the active limit state on the non-excavation side, the circular excavation’s arching effect reduces the earth pressure on this side of the supporting piles below the active earth pressure limit. Furthermore, the earth pressure acting on the steel plates is lower than that acting on the supporting piles, suggesting the presence of a soil arching effect between two adjacent piles. These findings offer valuable insights for guiding the construction of PRSS. Full article

Using the Vertical Shaft Sinking Machine (VSM) for shaft construction is an emerging modern technology, which is also currently one of the most advanced techniques in the field of shaft sinking. Current research on VSM technology primarily focuses on mechanical and technical issues, neglecting the impact of the construction on the surrounding soil and the structure itself. This oversight leaves structural design lacking a reliable foundation. Additionally, there is insufficient information on the role of reinforcement design during construction in soft soils. These engineering challenges have hindered the widespread implementation of this new technology. Therefore, a series of numerical models were used to analyse the mechanical behaviour of shaft and soil during or after the sinking process, with the aim of addressing these gaps by investigating the influence of shafts constructed using VSM technology, and providing a scientific basis for reinforcement design in soft soil. The case study shows that increasing the soil-cement strength does not have a significant effect on the overall deformation of the soil surrounding the shaft, but leads to a notable reduction in the plastic zone volume, subsequently enhancing the overall stability of the neighbouring soil. The ring bottom beam design effectively reduces convergence deformation by about 50%, while also improving the horizontal internal force distribution near the cutting edge. However, this approach significantly escalates local vertical bending moments, necessitating thorough consideration in the design stage. Full article