In order to study the relationship between rainfall and regional geological disaster risk, construct the meteorological warning model of geological disasters in Huangshui Basin, and provide reference for the geological disaster warning work in the basin. Huangshui Basin in Qinghai Province was taken as an example, where the susceptibility to geological hazards was evaluated using the information value method. The independence of each factor was tested using the Pearson correlation coefficient, and the accuracy of the evaluation results was assessed through the receiver operating characteristic curve (ROC) and the area under the curve (AUC). Subsequently, a geological-rainfall coupling model was also established using the logistic regression method, incorporating rainfall data, to carry out geological disaster meteorological risk warning and verification. The results show that Huangshui Basin geological disasters of very high susceptibility area and high susceptibility area is mainly distributed in the river valley plain zone and its tributaries at all levels in the middle and lower reaches of the two sides, the region is a geological disaster area. The results of the susceptibility evaluation are assessed for precision, and an AUC value of 0.785 is found. Geological-rainfall coupled warning model in the susceptibility value, the day rainfall, the first 1 day rainfall, the first 2 days day rainfall, the first 2 days of rainfall and the first 3 days of rainfall on the disaster are all positive, the model's prediction accuracy for the occurrence of geological disasters is 84.2%, and the AUC value is 0.864. Based on the five typical geological disasters that occurred in Huangshui Basin on 29th August 2020, the established geological-rainfall coupling model was verified, and it is found that with the geological-rainfall coupling model warning, four geological disasters reach the first warning level, and the other one reaches the second warning level. Combined with the warning rainfall threshold, the model was used to achieve the early warning of the landslide in Hongyagou Village on 5 September 2024. It can be seen that the constructed meteorological early warning model for geological disasters in the Huangshui Basin has a good early warning effect and a relatively high prediction accuracy rate, which can provide references for disaster prevention and mitigation for relevant departments.

In order to help enterprises better adapt to the dynamic environment in the real business, a multiperiod intermodal routing and storage co-optimization model with transport price uncertainty was investigated. Firstly, an integer programming mathematical model was established in the environment of transport price certainty. Secondly, a robust optimization model was established in the environment of uncertain transport prices, and the robust optimization model was transformed into an equivalent linear robust peer-to-peer problem. Subsequently, on the basis of the traditional k-shortest algorithm, iterative greedy algorithm (IG) and adaptive large neighbourhood search algorithm (ALNS), a hybrid heuristic algorithm of MKIGALNS was proposed to solve the problems. Finally, the correctness of the proposed model as well as the effectiveness of the algorithm were verified by different sizes of arithmetic case experiments. The experimental results indicate that in 10 sets of arithmetic cases, the average total operating cost is CNY 439 191 when storage is not allowed and CNY 391 378 when storage is allowed, so the storage decision should be made, which is conducive to the reduction of operating cost. And through the related robust experiments, the total operating cost as well as the multiperiod intermodal operation strategy changes with the change of the uncertain budget value, which reveals the intrinsic connection.

In order to meet the needs of fast and efficient transportation for coal mine drilling construction operations with trackless transportation conditions, a trackless rubber tyre vehicle integrated drilling rig was used to travel directly from the ground to the drilling site without the need for secondary transportation. By comparing the advantages and disadvantages of integral and articulated chassis structures, the narrow body rubber tyre chassis structure was determined based on actual underground tunnel conditions, and key performance parameters for the vehicle design were provided. By comparing the advantages and disadvantages of integral and articulated chassis structures, the narrow body rubber tyre chassis structure was determined based on actual underground tunnel conditions, and key performance parameters for the vehicle design were provided. Based on the overall technical requirements, multiple key technologies of the trackless rubber tyre vehicle were designed and analyzed, and the static load capacity and dynamic characteristics of the frame under two working conditions, namely the driving process and the drilling process, were simulated and analyzed. The simulation results show that the stress and displacement meet the design requirements of the frame load capacity during the walking and drilling processes, and it has good stability. After the installation and adjustment of the rubber wheel chassis, a climbing test and comprehensive performance test were carried out. The test shows that the whole vehicle meets the 15 ° large angle climbing condition, all data meet the standard requirements, and the performance meets the transportation needs of the coal mine drilling rig. It can adapt to the complex working conditions underground in coal mines.

In order to guide the optimal design and daily maintenance of explosive capacity bombs, the response characteristics of 20 L explosive capacity bombs under the explosion action of explosives were studied. Internal explosion tests of different masses of trinitrotoluene (TNT) explosive capacity bombs were designed. The strain distribution and variation law of the outer wall of the explosive capacity bomb were measured, and the internal explosion impact overpressure of the explosive capacity bomb was obtained. According to the test results, the equal-scale simulation calculation model was calibrated, and the propagation law of shock wave inside the explosive capacitor bomb after the explosive explosion was calculated, and the pressure distribution in the explosion field was obtained. The results show that the simulation results of internal pressure of explosive charge are basically consistent with the experimental results. Under the action of explosive explosion, the internal pressure of explosive capacitor presents a complex structure of multi-peaks, the maximum pressure appears at the corner of explosive capacitor, and the maximum strain of the outer wall of explosive capacitor appears at the lower position of the explosion center plane.

Storm rainfall patterns are critical to infrastructure flood control, but the main design methods are hindered by requiring high resolution data and ignoring the impacts of climate change. Taking the typical small and medium-sized river basin (Liudong River Basin) with relatively high flood control pressure in the Karst area of southwest China over the years as an example, based on the Gamma distribution with flexible distribution characteristics and wide application, and using the duration data of the maximum 24-hour rainstorm in the past 60 years, the model performance was evaluated, the parameters of the model were determined, and the evolution characteristics of the parameters were analyzed. Based on the above results, the changing trends of rain pattern uncertainty, complexity and predictability were calculated. The results show that the model has high accuracy, and the average correlation coefficient is greater than 0.92. The evolution trend of the model parameters indicates that under the background of climate change, the rain pattern of the maximum 24-hour rainstorm shows the characteristics of decreasing shape factor and increasing scale factor. The uncertainty of rain patterns has generally increased, and the complexity and predictability show high spatial heterogeneity. The research results will provide references for optimizing the rainstorm rain pattern model and analyzing its dynamic evolution, thereby better preventing and controlling flood disasters, especially in Karst areas with high precipitation uncertainty and complex underlying surface conditions.

The civil engineering industry faces with a vast array of unstructured textual information during its digital transformation. Large language models (LLMs) provide a new opportunity for the intelligent transformation of the industry because of its powerful natural language processing capability. A systematic literature review approach was employed, and based on the technical framework of LLMs and the current state of research in vertical domains, four major application scenarios for LLMs in civil engineering were suggested, along with corresponding technological approaches, challenges faced, and research trends. It is found that exploratory research and application of LLMs in civil engineering have been conducted, primarily focusing on content creation, intelligent Q & A, text summarization, and analytical reasoning, covering the entire lifecycle of civil engineering projects and featuring interdisciplinary and multimodal integration. However, the utilization of LLMs struggles with low specificity of knowledge, poor timeliness of information, and inferior data quality and interactivity. Based on this, a series of future research opportunities were proposed to enhance the breadth and depth of LLMs application in the field of civil engineering by using parametric efficient fine-tuning technology to inject expertise in model optimization. Combined with knowledge graph, LLMs can improve the accuracy, interpretability and timeliness of answers. Multi-modal data types were integrated to expand the application scenarios of LLMs in civil engineering. Appropriate model evaluation methods were developed to quantify the value and performance of LLMs applications in civil engineering. In terms of application scenarios, combined with the characteristics of LLMs and civil engineering fields, the application of LLMs in complex tasks such as document generation, question and answer system, information extraction and compliance review can be expanded, and the interaction efficiency between practitioners and data can be improved. The purpose of the study is to provide reference for the academic and business circles to further apply LLMs in the field of civil engineering.

The stepped frequency ground penetrating radar has the advantages of high sensitivity, large dynamic range, and high average power. Radio frequency system on chip(RFSOC) based stepped frequency ground penetrating radar transceiver system design was designed and implemented. The system mainly includes modules such as the transmission link, reception link, clock unit, field programmable gate array(FPGA) control system, and data transmission unit. By setting multiple numerically controlled oscillator (NCO) for synchronization between the transmission and reception ends, the carrier was synchronized on the same frequency and phase, ensuring the phase coherence of radar transmission and reception signals. A receiving time window was also designed in the data transmission unit. The experimental test results show that the system can achieve the transmission and reception of step frequency signals with a frequency range of 200 MHz~2 GHz and a step size of 2 MHz, and can effectively detect multiple scene targets such as free space, sand pits, and asphalt pavements.

Urban roads are recognized to facilitate daily human activities while simultaneously being observed to shape behavioral patterns. Currently, most studies simply analyze the relationship between roads and crime distribution as part of the built environment, and few studies have thoroughly explored the impact of different structural attributes of roads on crime. In order to further explore this impact mechanism and provide guidance for the optimization of police resource allocation by front-line police departments. The operational mechanisms were investigated by which geometric and topological road attributes influence theft distribution across varied transportation modalities. Using crime data from YC District, JB City, spatial crime hotspots and high-risk road segments were initially identified through geospatial analysis. Next, the road structure was systematically decomposed into two distinct dimensions: geometric attributes and topological properties. A space syntax segment model was created to quantitatively assess geometric characteristics and traffic modality-specific topological configurations. Finally, Statistical relationships were investigated using zero-inflated negative binomial regression complemented by multiple linear regression modeling. Research has found that theft incidence is demonstrated to be positively associated with segment length, angular curvature metrics, and branch road density within the network. Elevated crime probabilities are observed in extended roadway segments exhibiting complex geometric configurations and regions characterized by dense branch road networks. The closeness and betweenness of the road's topological structure exert varying significant effects on theft crime across different traffic modes. Specifically, in pedestrian traffic modes, a significant negative correlation is observed between road closeness and betweenness and the occurrence of theft crime. In bicycle traffic modes, road closeness and betweenness are found to have a positive effect on theft crime. In electric vehicle and motor vehicle traffic modes, road closeness have a positive effect on theft crime, while in electric vehicle traffic mode, betweenness was found to have a negative effect on theft crime. These findings contribute novel insights to environmental criminology theory while offering empirically grounded recommendations for strategic police deployment and urban security management.

To improve the utilization rate of waste clay, a composite curing agent composed of cement, alkali excitation agent, siliceous solid waste material and sulfate solid waste material was used to cure a waste clay. Unconfined compressive strength test (UCS), water stability test, X-ray diffraction test and scanning electron microscope(SEM) test were carried out to capture the mechanical behavior and reinforcing mechanism of the solidified clay. The results show that there is a significant solidification effect on the clay when the dosage of curing agent is from 10% to 12%, and the water stability coefficient of solidified clay is larger than 80%. The UCS of the solidified clay with 12% curing agent content is 2.45 MPa after curing for 28 days, which is 2.33 times the UCS of the solidified clay at a curing time of 7 days (1.05 MPa). A large number of hydration products such as calcium silicate (aluminate) hydrate and ettringite produced in the solidified clay can improve the performance of solidified soil by improving the micro-pore structure of soil and strengthening the cementation between aggregates. The present research can provide reference for the resource utilization of waste clay.

The plunger pump is one of the important power conversion components of the hydraulic system, and its performance directly affects the safety and stability of the hydraulic system. In order to accurately evaluate the operating status of the plunger pump, a plunger pump health status assessment method based on a combination of convolutional neural network(CNN) and long short-term memory network(LSTM) was proposed, and a genetic algorithm was introduced to optimize the parameters of the neural network. The vibration signals of the plunger pump at different operating moments were collected. The energy characteristics of the vibration signals were extracted by using wavelet packets. Combined with the time-frequency domain characteristics of the signals, a dataset of the health status characteristics of the plunger pump was constructed. The health status was identified and classified by the CNN-LSTM method, and the classification results were evaluated by sample entropy. To verify the effectiveness of this health assessment method, it was applied to the experimental test of the plunger pump. The results show that the recognition accuracy of this method reaches 99%, which can effectively improve the accuracy of the health status assessment of the plunger pump.