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Causation analysis of crane-related accident reports by utilizing ChatGPT and complex networks
No full textThis study integrates ChatGPT and complex network (CN) techniques into an accident analysis framework designed to reduce manual effort in accident causation analysis. The proposed framework supports construction stakeholders in extracting causal factors (CFs) from accident reports and identifying both critical CFs and key causal paths. A multistep research design was adopted to develop and validate this novel framework for analyzing crane-related construction accident reports using ChatGPT and CN techniques. First, ChatGPT was prompted to extract CFs from a database of crane-related accident reports. Second, evaluation metrics and an expert questionnaire survey were developed to assess ChatGPT’s performance in CF extraction. Finally, CN analysis was conducted to explore the relationships among CFs and to identify critical causal paths. A total of 95 crane-related accidents from Hong Kong (2011-2020) were analyzed using the proposed framework. The critical CFs identified included: “carelessness”, “operation error”, “crane unbalanced”, “machine failure”, “parts of a crane fall”, “object strike”, “worker fall”, “trapping”, “collapse of crane”, and “load drop”. The critical path identified was: “broken/failed rope” → “load drop” → “object strike”. The primary contribution of this study lies in developing an AI-driven framework that combines the contextual understanding of ChatGPT with the structural analysis capabilities of CN methods—offering a novel and scalable approach to accident causation analysis in the construction industry. Safety managers and practitioners can leverage this framework to improve the automation, consistency, and interpretability of construction accident reporting
Multi-Objective Optimization of Tower Crane Layout Planning in Modular Integrated Construction Considering Efficiency, Cost, and Lifting Safety
No full textWith the increase of modular integrated construction (MiC) projects, the planning of tower crane layout (TCLP) becomes vitally essential to achieve a balance among multiple goals, such as efficiency, economy, and safety. However, existing TCLP studies are usually formed as single-objective optimization based on total lifting time for conventional construction sites. There should be trade-offs among multiple goals, especially safety. In addition, the heavier components of MiC, requiring cranes with larger lifting capacity, pose a challenge in terms of cost. Therefore, it is necessary to propose a more general and reasonable model to assist managers in making better decisions for TCLP. This study aims to develop a multi-objective optimization model with efficiency, cost, and lifting safety considerations for MiC projects. Firstly, based on literature research and accident statistics, the total transportation time, total cost of tower cranes, and total lifting moment are chosen as the three optimization objectives. Then, the improved three-objective optimization model, considering module positioning time and separate movement features of tower cranes, is proposed. To solve the proposed multi-objective problem, the evolutionary algorithm NSGA-III is used for solutions. The proposed model can provide a series of trade-off solutions for efficiency, cost, and safety, representing different combinations of crane location, supply point location, and orientation. A MiC project in Hong Kong is studied as a case to verify the feasibility and effectiveness of the proposed model. The results show that the proposed model can determine the optimized layout plan with minimum time, cost, and lifting moment by locating the tower crane point, supply point, and supply point orientation. Disregarding the orientation of the supply point would result in an additional 18.2% transportation time, leading to increased costs. Compared to the original layout scheme, the developed model can save up to 41.7% in transportation time and improve safety by 27.4%
Stabilizing Highly Erodible Sands against Wind Erosion Using Two MICP Pathways: Aerobic Denitrification and Nonsterile Ureolysis
No full textStabilizing soils against wind erosion is a critical challenge, particularly in regions with loose, sandy soils, such as dune sands. This study explores the potential of microbially induced calcite precipitation (MICP) to enhance the stability of poorly graded dune sands at the southern shores of Lake Superior against wind erosion. Two MICP pathways, i.e., ureolysis (U-MICP) and aerobic denitrification (D-MICP), were investigated using microorganism communities cultivated under nonsterile conditions from activated sludge. The nonsterile methods used to cultivate the required bacteria communities reduce the cost and facilitate the bacteria cultivation process required for future large-scale field applications. Furthermore, as denitrification is typically assumed to only occur under completely anoxic conditions, the application of this pathway is usually not considered for shallow ground improvement projects such as improving the wind erosion resistance of sand dunes. In this study, the ability of microorganism communities cultivated from activated sludge to perform denitrification in the presence of oxygen was confirmed using batch experiments. The cultivated microorganisms were then used to stabilize dune sands through D-MICP in the presence of oxygen. The spray method was used for both U-MICP and D-MICP treatments of dune sands. A series of laboratory wind tunnel tests were conducted on treated and untreated samples to evaluate the effectiveness of MICP in enhancing the wind erosion resistance of the soils. Additionally, sand column treatments and lab-scale cone penetration tests were performed to assess the effect of MICP treatments on soil strength as a key factor against wind erosion using the constant-head infiltration method. The results revealed the differences in the performance of the two MICP pathways, emphasizing the influence of the number of treatment cycles on soil stabilization. Particularly, it was shown that six cycles of aerobic D-MICP and one cycle of U-MICP significantly increased wind erosion resistance. The results also revealed that excess (unused) calcium chloride used in U-MICP treatment could precipitate within the treated samples and significantly impact soil stabilization against wind erosion
MICP via denitrification pathway under aerobic conditions
No full textMicrobially induced calcite precipitation (MICP) through the denitrification pathway is achieved when bacteria use nitrate as the electron acceptor to oxidize organic matter and generate ATP for growth. Most denitrifying bacteria are facultative anaerobes and in aerobic conditions, they use oxygen as the electron acceptor instead of nitrate. In other words, these bacteria can grow under aerobic conditions but they do not denitrify unless under anoxic conditions. This is because using oxygen yields more energy compared to denitrification. Recently, however, it has been shown that many bacteria (e.g., Paracoccus denitrificans) can denitrify under aerobic conditions even though it might result in lower levels of cell reproduction. These aerobic denitrifiers are commonly found in soil and aqueous environments including activated sludge used in wastewater treatment. In this study, batch experiments were conducted to confirm the occurrence of denitrification-MICP under aerobic conditions. Furthermore, samples from easily erodable sand dunes of the superior lake were treated via denitrification-MICP under aerobic conditions. Activated sludge from a local wastewater treatment facility was used as the source of denitrifiers. Carbonate content tests, Scanning Electron Microscopy, Energy Dispersive Spectroscopy, Transmission Electron Microscopy, and X-ray diffraction analysis were conducted on treated soils. The results confirmed that different calcium carbonate polymorphs including calcite were precipitated and also showed that some salts and extracellular polymeric substances (EPS) were precipitated at the soil surface
Improving interfacial bonding between ordinary Portland cement and geopolymer concrete using acid/alkaline-catalyzed nano-SiO₂ sols: Insights into performance and mechanisms
No full textConcrete infrastructure deterioration necessitates eco-friendly and durable repair materials. As an innovative material, geopolymer concrete (GPC) offers a strong alternative to conventional ordinary Portland cement (OPC) due to its low carbon footprint, yet its interfacial bonding with OPC remains a substantial obstacle. This work assesses the implications of acid- and alkaline-catalyzed nano-silica (NS) sols, synthesized via sol-gel methods, on the performance of GPC and its interfacial bonding with OPC. Results indicate that alkaline-catalyzed NS (AlC-NS) shows superior dispersion and significantly enhances compressive strength and interfacial bonding strength while reducing drying shrinkage. The optimal dosage of 5 wt% AlC-NS increases the interfacial bonding strength by 45.91 % (6.07 MPa). Microstructural analysis reveals that the improved interfacial transition zone (ITZ) is attributed to the formation of dense C-(A)-S-H/N-A-S-H gels and enhanced mechanical interlocking. These findings offer a promising pathway for developing green and durable repair materials in concrete infrastructure
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Fixed-Tilt Systems in the U.S. Eastern Interconnection for Weather Year 2014
No full textUsing 2014 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be 30-degree, fixed tilt systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Fixed-Tilt Systems in the U.S. Eastern Interconnection for Weather Year 2022
No full textUsing 2022 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be 30-degree, fixed tilt systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2018
No full textUsing 2018 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2017
No full textUsing 2017 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory\u27s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadat
Long-term nitrogen fertilization inhibits carbon and nitrogen loss during late-stage fungal necromass decomposition depending on necromass chemistry
No full textFungal necromass is increasingly recognized as a key component of soil carbon (C) and nitrogen (N) cycling. However, how C and N loss from fungal necromass during decomposition is impacted by global change factors such as anthropogenic N addition and changes to soil C supply (e.g. via changing root exudation and rhizosphere priming) remains unclear and understudied relative to plant tissues. To address these gaps, we conducted a year-long decomposition experiment with four species of fungal necromass incubated across four forested sites in plots that had received inorganic N and/or labile C fertilization for two decades in Minnesota, USA. We found that necromass chemistry was the primary driver of C and N loss from fungal necromass as well as the response to fertilization. Specifically, N addition suppressed late-stage decomposition, but this effect was weaker in melanin-rich necromass, contrary to the hypothesis based on plant litter dynamics that N addition should suppress the decomposition of more complex organic molecules. Labile C addition had no effect on either the early or late stages of necromass decomposition. Nitrogen release from necromass also varied among species, with N-poor necromass having lower N release after controlling for differences in mass loss via regression. The relatively minor effects of N fertilization on the proportion of initial necromass N released suggest that N demand by decomposers is the primary control on N loss during fungal necromass decomposition. Synthesis. Together, our results stress the importance of the afterlife effects of fungal chemical composition to forest soil C and N cycles. Further, they demonstrate that C and N release from this critical pool can be reduced by ongoing anthropogenic N addition