Under the dual carbon background, a multi-domain communication architecture was constructed to address issues such as a single communication mode and poor adaptability between business and communication technology in the new power load management system. The key supporting technologies of this architecture were comprehensively analyzed. Additionally, an adaptability evaluation system for business and communication technology was developed based on varying business types and their specific communication requirements. A communication technology adaptation method was proposed, employing the fuzzy analytic hierarchy process (FAHP), the CRITIC method, and grey relational analysis-technique for order preference by similarity to an ideal solution (GRA-TOPSIS). The proposed method facilitates the analysis of adaptability between differentiated business requirements and multi-domain communication technologies. The analysis of case studies indicates that the proposed architecture and the adaptation method offer an effective theoretical basis and solution for selecting multi-domain communication technology for the new power load management system business.

In order to reveal the characteristics and geological significance of the main micronutrient geochemistry in the Carboniferous-Permian Taiyuan Formation in Ningdong coalfield which deposited in marine-land transition coal-accumulating environment, the X-ray fluorescence(XRF) spectrometry, inductively coupled plasma-mass spectrometry(ICP-MS), macerals identification and industrial analysis were used to study the source, occurrence and environmental significance of trace elements in coals. The results show that the content of major and trace elements in Carboniferous coals of Ningdong coalfield are varies greatly, except the Fe₂O₃ content is lower than the mean content of China coals. The Rb(5.1) is enriched in Weierkuang while other elements are slightly enriched in different micronutrient. The major and trace elements in coal are mainly occurs in clay minerals, and come from the supply of terrigenous clasts and the combination with organic matter and authigenic minerals in water-soluble state and ion state. The ratio of TiO₂/Al₂O₃indicate that the minerals in the coal are mainly derived from felsic clastic rocks, and the positive correlation between CaO and MgO indicates that they coexist in the form of dolomite. The ratio of Sr/Cu and CaO/(MgO·Al₂O₃) and the other parameters indicate the coal-accumulating period is in a warm and humid environment, it is inferred that the temperature is between 15 ℃ and 30 ℃, the ratio of Sr/Ba indicates that the coal-forming marsh is a brackish water environment, which indicates that it is affected by seawater. The parameters of Cu/Zn, V/(V + Ni), Ni/Co and V/Cr revealed that the peat-formed bog was in an anaerobic redox environment.

In recent years, multiple exploration breakthroughs have been made in the Maokou Formation of the Sichuan Basin. Currently, the overall exploration level is low.The type and distribution of sedimentary facies are still unclear. The characteristics and formation mechanism of the reservoir are unclear. Techniques such as core observation, pore permeability testing, conventional and cast thin section identification were used to clarify the sedimentary and reservoir characteristics of the 2nd Member of the Maokou Formation in the front of the Longmen Mountains in western Sichuan and to explore the main controlling factors of high-quality reservoirs.Research shows that the 2nd Member of the Maokou Formation in the front of Longmen Mountain in western Sichuan develops in a northwest southeast direction. The southern and middle sections of Longmen Mountain are the development areas of high-energy shoals of the lower sub section of the second section of Maokou Formation. The middle and northern sections of the Longmen Mountain in the upper sub section of the second section of the Maokou Formation are the development areas of high-energy dolomitized platform edge sand debris shoals. The reservoir lithology of the upper sub section of the Maokou Formation is mainly composed of residual bioclastic sandstone dolomite, bioclastic grain dolomite, and residual grain dolomite.The reservoir lithology of the lower sub section of the second section of the Maokou Formation is mainly composed of residual sandstone dolomite and residual grain dolomite. The storage space consists of intergranular dissolution pores, intergranular dissolution pores, intragranular dissolution pores, and expansion fracture pores. The second section of the Maokou Formation is Ⅱ to Ⅲ porous reservoir. The reservoir foundation is composed of high-energy beach deposits. The leaching and dissolution of atmospheric fresh water during the contemporaneous period is the key to reservoir formation. The reservoir has been improved and maintained through shallow burial dolomitization.

Under the guidance of the “14th Five-Year Plan” and the “Dual Carbon” goals, construction materials face significant challenges, particularly as the adaptability and accuracy of traditional concrete performance prediction models are questioned. Recently, machine learning (ML) has demonstrated high accuracy and efficiency in predicting concrete performance. The research progress of ML in this field was systematically reviewed, focusing on its applications in mechanical properties, mix design, and durability, while identifying its limitations and proposing improvement strategies. CiteSpace software was used to analyze the current state of ML research in construction engineering, examining publication volume, research hotspots, and trends. This analysis offers valuable reference for future researchers, aiding in the effective application of ML technology to drive innovation in construction materials and support environmental sustainability goals.

The role of gas storage in regulating natural gas peaks is crucial. Improper allocation of gas injection schemes during the injection process not only results in excessive energy consumption by compressors, but also leads to excessive pressure changes in certain individual wells and convergence of salt karst cavities, thereby affecting the long-term stable operation of gas storage. By combining the simulated annealing algorithm with actual field conditions, a multi-objective optimization function was established considering both compressor energy consumption and dispersion degree of wellhead pressures across all gas storage wells within the same block. The variable for this optimization was set as the gas injection volume during the task period for each gas storage well, while variables such as maximum design pressure of pipelines, minimum operating pressure, and maximum operating pressure of gas storage wells were taken into account. Additionally, constraints were imposed based on the maximum design flow rate measured by target flowmeters for multi-objective optimization purposes. Results indicate that compressor power consumption can be reduced by over 40% and formation pressure differences can be decreased by more than 90%. It is evident that this scheme provides assurance for ensuring long-term stable operation of gas storage through effective guidance on actual production operations.

In order to study the influence of slurry shield tunneling parameters on surface settlement, based on the slurry shield tunneling and monitoring data of the left line of the Hesong-Heshan stacked section of Harbin Metro Line 3 project, based on the BP neural network optimized by genetic algorithm, the different settlement output forms were studied. The tunnel distance label was introduced to optimize the neural network fitting effect, and the parameter sensitivity analysis was carried out according to this network model. Three most sensitive parameters were obtained, and exhaustive tests were carried out to further analyze the specific influence of parameters on surface settlement. The research shows that the surface settlement performance of slurry shield tunneling is not closely related to the tunneling parameters after passing through a certain ring for two days, and the surface settlement analysis can focus on the monitoring value of the day. Before, during and after the shield machine passes through a certain ring, it will have different effects on the surface settlement above the ring. Subsequent research on surface settlement based on neural network can be considered to include this index. Among the parameters of slurry shield tunneling, reducing slurry viscosity and increasing slurry specific gravity can control surface subsidence, and increasing propulsion speed can reduce the impact of construction on surface subsidence.

Aiming at the blindness of the current coal mine roadway surrounding rock support programme and its parameter design, in order to improve the effect of roadway surrounding rock support and meet the requirements of safe and efficient production of mines, taking the Jiaoping mining area as the engineering background, the roof strength, coal gang strength, bottom plate strength, the basic top comes to press the equivalent, mining disturbance, roadway buried depth, roadway protection coal pillar width, span height ratio, top height ratio and the maximum horizontal principal stress were selected as roadway stability master control indicators, and 16 typical roadways and chambers were selected as samples, and the weights of 10 classification indicators were determined based on the analytic hierarchy process. On this basis, the stability of the sample roadway was clustered and analyzed, and the optimal classification number was selected according to the F-statistic method to divide the sample roadway into five categories: very stable, stable, basically stable, unstable and extremely unstable, and then the cluster center of the stability of the mine roadway was constructed. Finally, based on the above theory, the stability of the surrounding rock in the 2407 return wind channel of Yuhua Mine was predicted, and the targeted support measures and parameters were proposed. The results show that the classification results of 2407 return wind channel roadway stability are in line with the actual field engineering, and the deformation control effect of surrounding rock is good, which provides a strong guarantee for the safe and efficient production of the working face.

Rockburst is an extremely destructive geological disaster in deep underground engineering. In order to accurately predict the intensity level of rockburst, a method for rockburst intensity level prediction based on parallel fusion graph Transformer (PFGT) was proposed. Firstly, the similarity structure relationship of rockburst data in Euclidean space was utilized to construct graph-structured data. Besides, another kind of graph-structured data was constructed by utilizing multiple rockburst criteria to constrain the structural distortion of rockburst data in European space. Single-scale features of rockburst data was obtained through parallel training. Secondly, a feature fusion graph Transformer strategy was designed, which obtains multi-scale features of rockburst data by fusing two types of graph-structured data features based on Euclidean space and based on rockburst criteria. The method improves the data representation capability by simultaneously utilizing single-scale features and multi-scale features. During the training process, using Transformer for feature fusion enables the model to more comprehensively capture the optimized features of rockburst data, thus improving model performance. Compared with traditional neural networks and other machine learning algorithms, the prediction accuracy of the PFGT model is 94.87%, which is superior to other algorithms, proving the effectiveness of this algorithm and providing a new method for rockburst level prediction.

In order to explore the effects of different internal fixation systems on the biomechanical characteristics of the spine after orthopedic idiopathic scoliosis, a theoretical basis for the improvement of the internal fixation system was provided from the perspective of biomechanics. Based on reverse engineering, topology optimization and finite element modeling techniques, the finite element model of idiopathic scoliosis was established by taking actual cases as examples. The personalized fusion device was designed. Two kinds of internal fixation systems were established, namely full fixation and interval fixation. To simulate idiopathic scoliosis surgery and compare the biomechanical differences between spine and internal fixation system under different physiological conditions. The results show that the average stress of cortical bone and cancellous bone is increased by 17.19% and 12.37%, respectively, compared with that of interlocking nails. The maximum equivalent stress of fibrous annulus matrix and nucleus pulposus is increased by 1.78% and 1.1%, respectively, compared with that of full nailing. The maximum equivalent stress of pedicle screws is 11.64% higher than that of interlocking screws. The average stress of interbody fusion is increased by 6.15% compared with that of interbody fusion. In conclusion, compared with the interspaced nailing scheme, the total nailing scheme is better in vertebrae safety, but the risk of screw slip and screw loss is higher. Compared with the total nailing scheme, the interstice nailing scheme has better spinal fusion effect and effectively alleviates stress occlusion, but the incidence of bone hyperplasia is increased.

In image inpainting, it is crucial that the identification and inpainting of local detail features and the preservation of global features. The models based on fractional-order partial differential equations were characterized by rich evolutionary behaviors, which allow image details to be effectively understood and a certain sharpening effect to be exhibited in image inpainting. However, issues such as inaccurate identification of large-scale features and over-sharpening are prone to be encountered. An optimal control model was proposed and the objective function was defined by the total variation energy of image global features and the constraint was formulated by a spatial fractional-order vector-valued Cahn-Hilliard equation, aiming to achieve a balanced effect between local detail restoration and preservation of global features. L₂ gradient flow, H^-1 gradient flow, and convex splitting were applied to design a numerical scheme for non-convex constraint conditions. And then the split bregman method was used to optimize the objective function with a dynamic grayscale adjustment strategy was introduced to maintain grayscale discrimination capability while enhancing computational efficiency. The numerical experiments demonstrate that the new model achieves an improvement on peak signal to noise ratio(PSNR) ranging from 0.371 8 dB to 9.935 2 dB compared to other methods, exhibiting strong competitiveness in terms of structural similarity(SSIM) and greater effectiveness on images with fragmental damages. Moreover, compared to traditional fractional-order equation models, the computational time is reduced by a factor of 49.50% to 52.91%.