Public data ownership confirmation policies, as an administrative regulatory tool, play a significant role in promoting the further openness and utilization of public data. 11 policy texts related to public data ownership confirmation issued by the three northeastern provinces of China was evaluated. A policy evaluation index system was constructed, and the PMC index model was applied for quantitative assessment. The results indicate that the overall policy level is close to satisfactory. However, issues such as low attention to policy content and feedback mechanisms, insufficient flexibility in policy design, and a relatively narrow policy perspective persist. Based on these findings, optimization pathways are proposed, including benchmarking to address internal shortcomings, enhancing short-term policy adjustments, broadening stakeholder participation, and expanding the horizons of policy formulation.

The Huailiangzi landslide has experienced significant deformation under continuous heavy rainfall, posing a serious threat to the safety of residents’ lives and property. Based on detailed geological surveys, a landslide numerical model was constructed using the finite difference method and a coupled seepage-stress analysis approach was employed to investigate the stability of the landslide, as well as the evolution characteristics of the seepage field and displacement field under different rainfall scenarios. The results show that the Huailiangzi landslide is generally stable under natural conditions. However, under the influence of external adverse factors such as heavy rainfall, the stability of the slope significantly decreases. In particular, under continuous rainfall, the increase in pore water pressure is substantial, significantly increasing the likelihood of overall landslide movement. The findings provide important theoretical support for early warning systems and mitigation engineering of similar landslides.

In order to investigate the characteristics of karst pipeline in Dongcun, Xinyu, Jiangxi Province, rationally develop and utilize Karst water resources and scientifically protect karst water environment, two kinds of fluorescence tracers, sodium fluorescein and Rhodamine, were selected for quantitative tracing test research on Karst pipeline. The distribution, morphology and hydraulic characteristics of the Karst pipeline through the penetration curve and clarifies the connectivity of groundwater recharge, runoff and discharge characteristics were analyzed. The test results show that Zhangmuqiao water-dissipation cave is connected to Niulang Zhinv cave underground river. The Karst development of the underground river is extremely developed, with large-scale Karst pipeline as the main Karst pipeline. The pipeline is single-like and the underground runoff path of the main Karst pipeline is short. Some parts of the groundwater has the characteristic of pressure-bearing. The direction of the underground runoff is from east to west. Its flow rate is fast, and so is the solute migration rate. There’s small possibility of other drainage outlets. However, there is no hydraulic connection between the Zhangmuqiao water-dissipation cave and Shenniu cave underground river outlet.

The research of landslide monitoring technology plays a key role in preventing landslide disasters, which is not only reflected in the pre-disaster early warning, but also provides a theoretical basis in the post-disaster reconstruction. A clear understanding of the history of landslide monitoring technology can not only understand the development situation of landslide monitoring, but also contribute to the improvement and update of the monitoring technology in the future. Through summarizing the work of a large number of domestic and foreign scholars, the research progress of landslide monitoring technology was expounded from three historical stages: manual monitoring stage, semi-automatic and manual monitoring stage, and semi-intelligent and automatic monitoring stage. The main instruments and methods of common monitoring technology in each period are reviewed. Combining the latest landslide monitoring technology research status, some problems necessary for further research and discussion were proposed from the four perspectives of data inversion, technology comprehensive, intelligent and low-cost technology of landslide monitoring technology.

Exploring the best method of regional landslide susceptibility assessment is of great importance for accomplishing regional hazard prevention and mitigation work.Taking Xishan mining area in Shanxi Province as the study area, nine assessment factors were selected including elevation, slope, aspect, relief, normalized vegetation index(NDVI), the engineering rock group, distance from faults, distance from roads, distance from drainages, the susceptibility of landslide hazard was evaluated and verified in certainty factor(CF) model, logistic regression model and CF-Logistic coupling model respectively, the location of landslide prone area in the study area is obtained, which provides reference for the prevention and control of geological disasters in this area.

Many types of defects are produced during the drilling of holes in carbon fiber reinforced composites, and of all the defects delamination has the most serious effect on the material. Therefore, it is crucial to develop an effective model that can accurately predict delamination in laminated materials. However, materials domain data is characterized by small samples, high latitude and complex relationships, which makes it necessary and feasible to use empirical knowledge to enhance the effectiveness of machine learning modeling. A knowledge-guided machine learning(KGML) model that integrates empirical knowledge and data-driven modeling is used to predict laminated material delamination, the fact that empirical knowledge is incorporated into the loss function as an adaptive weighting in order to enforce physical constraints during the training process. Finally, by comparing the prediction performance of the model without knowledge and the model with knowledge, the R² of the model with knowledge was improved from 0.79 to 0.91, which successfully demonstrated the advantages of empirical knowledge-based machine learning, and provide a generalized approach for delamination prediction to reduce the experimentation time and cost for researchers.

The prevailing techniques for seismic phase analysis encompass waveform classification, seismic attribute feature mapping, and seismic geomorphological delineation. The waveform classification method is a well-established and extensively utilized technique for lithological, sand body, and oil and gas reservoir prediction. Nevertheless, the conventional approach relies on equal-length time window waveform similarity, which is only pertinent to the stable zone of formation thickness. As a consequence of changes in formation thickness, equal-length seismic waveforms cannot reflect the complete lithological information, or conversely, may lead to the phenomenon of ‘time-warp’, which in turn affects the accurate revelation of the relationship between reservoirs and waveforms. A seismic waveform classification method for unequally thick layers, intending proposes to reduce complexity and enhance classification efficacy. In comparison to the traditional classification method, this approach transfers unequal seismic signals from the time domain to the Hilbert domain with constant bandwidth, thereby ensuring the completeness of the waveform extraction and simplifying the traditional two-dimensional self-organized feature mapping network into a structure with fewer neurons and a one-dimensional output layer. This adaptation is better suited to the resolution of the seismic data and the need for classification efficiency. The enhanced network retains the capacity to modify the field and value of weight correction by with the responsiveness of the output neurons to the input neurons, thereby facilitating effective control of the network size, reducing the complexity of classification calculations, and enhancing classification efficacy. The practical results confirm the effectiveness of the method and significantly improve the accuracy of waveform classification.

In response to the technical difficulties of the deep exploration and evaluation well FG119 in the Xujiahe Formation of the Sichuan Basin, an “S” shaped wellbore trajectory was designed, with limited ground conditions, resulting in increased difficulty in trajectory controlling and high safety risks of drilling tools. The implementation plan of the ϕ165.1 mm slimming well was adopted, and the development of fractures in the Xujiahe Formation and the high and low pressure interlayers led to high well controlling risks. Therefore, optimization technology for slimming well wellbore structure, complex trajectory optimization design, establishment of four pressure profiles in fractured formations, and supporting technologies such as pre bending dynamic drilling tool combination, fine pressure control, and friction reduction were carried out. This ensured the smooth completion of the first deep “S” shaped slim well in the work area, providing technical reference for the subsequent construction of complex wellbore track wells in the block.

A layout optimization model was constructed to address the issues of multiple material handling intersections, high handling costs, and low area utilization caused by the unreasonable layout of KF Company’s general valve workshop. The model considers the direction of material flow in both directions and aims to minimize material handling costs, maximize non logistics relationships, and workshop area utilization. The system layout planning (SLP) method was used to optimize the workshop layout and obtain a preliminary layout plan. Based on the traditional nondominated sorting genetic algorithm II(NSGA-II), the initial layout plan obtained by the SLP method was encoded as part of the initial population to improve the diversity of the algorithm. The adaptive control strategy was introduced into the crossover and mutation operations, and the simulated annealing algorithm was added. Finally, the analytic hierarchy process(AHP) was used to optimize the workshop layout. Process, AHP make optimization decisions on a set of Pareto optimal solutions obtained by the algorithm. The results show that this method can reduce material handling costs by 38.83%, increase non logistics relationships by 44.83%, and optimize workshop area utilization by 19.50%, demonstrating the effectiveness of the model in workshop layout optimization.

In order to reduce the floor area of ground equipment for sand control operations, meet the fast and flexible installation and disassembly of subsequent sand control operations, as well as the post-phase inspection, maintenance, inspection and repair, the layout of sand control equipment and process in deepwater gas field was studied. The modular adaptability analysis, modular equipment design, selection and module key connection design were carried out, the modular combination of surface process equipment was realized to ensure the safety and smooth completion of development Wells. Finally, the finite element analysis software SACS was used to model and simulate the module, and the load condition of the module was analyzed and calculated. The modular related design satisfies the design index and safety analysis of the operation, and has certain reference significance for the popularization of the relevant modular technology and scheme in the self-operated deepwater development projects.