With the increasingly serious problem of climate change, green and low-carbon operations have become an important principle for the sustainable development of the air transportation industry. Taking a single runway transport airport as the research object and green and low-carbon and passenger walking distance as the optimization objective, a green and low-carbon gate assignment model under multiple scenarios was constructed, and a genetic-tabu search combined optimization algorithm was designed to solve it. Finally, a transport airport in northeast China was taken as an example for simulation experiment. The experimental results are shown as follows. In the optimal assignment scheme, if considering green and low-carbon, the fuel consumption can be reduced by 3.1%, the taxiing distance of the aircraft by 3.1%, HC emission by 4.2%, CO emission by 3.6%, NO_X emission by 3.1%, and CO₂ emission by 3.1% comparatively. But passenger walking distance can be increased by 5.3% at the same time. If considering green and low-carbon as well as the interests of the passengers, the fuel consumption can be decreased by 2.1%, the taxiing distance of the aircraft by 2.2%, HC emission by 3.8%, CO emission by 2.7%, NO_X emission by 2.0%, CO₂ emission by 2.1%, and passenger walking distance by 2.1% comparatively. Thus, it is possible to strike a balance between green and low-carbon development and the interests of travelers.

In recent years, digital class D power amplifiers have attracted widespread attention in the audio electronics field due to their high efficiency and seamless integration with digital audio sources. As one of the crucial digital signal processing modules in digital class D amplifiers, the Sigma-Delta modulator plays a pivotal role for digital audio signal processing. The noise-shaping characteristic of the Sigma-Delta modulator can reduce the implementation cost of the power amplifier system while maintaining or even improving the output signal-to-noise ratio of the system, and can suppress the noise introduced by some signal transmission paths. Firstly, the working principle and mainstream architecture of digital D-class power amplifiers were summarized. Then, based on the basic principle of Sigma-Delta modulators, the design schemes of Sigma-Delta modulators used in digital D-class power amplifiers in recent years were discussed, with a focus on the architecture design and noise transfer function design of Sigma-Delta modulators. Finally, the research and development of Sigma-Delta modulators for digital D-class power amplifiers were summarized.

Based on the sand-mud interlayer core of a block in Ordos Basin, denoising neural network based on wavelet transformation (DWTNet) was used to denoise the core image. The evaluation of this method was carried out by comparing the peak signal-to-noise ratio (PSNR) and the post-denoising image outcomes. The investigation reveals that by applying the DWTNet denoising algorithm to the test sets YX1 and YX2, and contrasting it with other denoising algorithms such as EGDNet, the PSNR values at noise levels of 25, 50, and 75 dB are respectively 0.527, 0.418, and 1.1 dB higher than those achieved by the EGDNet algorithm. The proposed algorithm surpasses others in terms of metrics including peak signal to noise ratio(PSNR), and visually, the resulting images processed by it exhibit enhanced clarity. The introduction of this method holds substantial significance for the calculation of parameters like porosity, mean specific surface area, mean curvature, among other rock properties, thereby advancing the capabilities in digital core technology, CT scanning analysis, and understanding of rock characteristics.

Shared bikes represent a crucial component of urban transportation. The randomness of user demand for shared bikes with fixed piles leads to unbalanced demand in time and space, and even the difficulty in renting a bike, which cannot meet the user demand during peak hours. Therefore, high-frequency users frequently travel to nearby stations to rent a bike for serving, which means that there are implicit demands. As for the hidden demand, firstly, the state changes of the site were described by the rental number and the return number, and the critical state of the reference site was determined by mining the user travel conditions of nearby sites. The hidden demand of the site was determined based on the site state change diagram and the demand judgment model. Then, according to the real needs of the site, the long short-term memory(LSTM) network prediction model was established, and the regional scheduling model of shared bicycles based on the real needs was established. The model takes the cost minimization as the goal, and obtains the path with minimum scheduling cost through genetic algorithm, which provides a reference for balanced scheduling based on real demand. The results demonstrate that, when transportation costs are similar, the scheduling method under real demand can alleviate the problem of users’ difficulty in renting a bike, thereby reducing the loss of high-frequency users.

The tension string system with concentrated viscous damping belongs to a hybrid dynamic system in mechanical models. Approximate methods are typically used to solve its inherent problems for engineering applications. In order to further clarify the vibration characteristics of the system, two centrally damped symmetrical damping string systems were taken as the basic research object, and their complex eigenvalues were solved analytically. The complex frequency equation and the eigenvalue expression of the system were derived, and the transformation of the complex frequency equation beyond the function form was treated as algebraic form, and the explicit solution of the complex eigenvalue of the system was given by the algebraic equation. The structure and properties of the complex eigenvalues of the system were analyzed, and the variation of vibration characteristics with damping coefficient was discussed. The results show that the eigenvalue solution of the system can be divided into three branches, in which the real part of the eigenvalue(the inverse is the decay rate) does not change with the order of the system motion, but the imaginary part of the eigenvalue(the frequency) increases with the order of the motion. The decay rate curves corresponding to each solution branch increase first and then decrease with the damping coefficient, and in the damping range of the decay rate curve, the frequencies of each order of the system are equal.

Addressing the challenge of insufficient accuracy in building regional cultural heritage 3D models using single-image modeling techniques, a method for optimizing regional ancient architectural three-dimensional models through the fusion of laser and imagery was proposed. Initially, imagery data of the target area was acquired through drone-based cross-flight aerial photography combined with close-range photography. Subsequently, laser scanning data was obtained using a 3D laser scanner to cover blind spots from drone aerial photography. Then, the laser scanning data was fused and registered with the imagery data to generate a complete point cloud model of the target area, which is then used to reconstruct a refined 3D model of the regional cultural heritage. Finally, the superiority of the proposed method was validated through error analysis of the fused heterogeneous data and comparative analysis of accuracy and texture completeness with single-image modeling results. The results indicate that the fused heterogeneous data achieves high fitting accuracy, and the resulting regional ancient architectural 3D model exhibits high accuracy and texture completeness, thereby providing valuable technical reference for the detailed modeling of ancient architectural complexes within the target scope and holding broad application prospects in enhancing the digital archive storage of ancient architectural three-dimensional models.

Based on Monte Carlo method, Python and Abaqus interface were used for secondary development, and an interfacial transition zone was generated to distinguish between natural coarse aggregates and new and old interfacial transition zone(ITZ) and recycled aggregate concrete (RAC) 2D meso-five phase model of new and old mortar. An improved moisture-chloride ion coupling model under dry-wet cycles was proposed, and the computational results of this model were compared and validated against physical experiments, with good agreement. This model was then applied to analyze the effects of dry-wet cycle periods, ITZ permeability, water-cement ratio, and natural aggregate volume fraction on chloride ion transport properties. The numerical results show that as the number of dry-wet cycles increases, the diffusion depth and concentration of chloride ions in RAC also increases. When the ratio of ITZ diffusion coefficient to the new mortar diffusion coefficient increases, the chloride ion concentration in the diffusion region increases significantly, especially at the front end of the diffusion zone. In addition, there is a positive correlation between RAC materials with different water-cement ratios and chloride ion transport capacity, with little variation in chloride ion transport performance within the high water-cement ratio range. Finally, the volume fraction of recycled aggregates has a significant impact on the chloride ion permeability of RAC, indicating that the ITZ and new and old mortar have an important influence on the transport of chloride ions.

The scientific extraction of urban built-up area information and the exploration of the spatial-temporal characteristics of urban expansion have significant relevance for urban planning and management. The local-optimal thresholding method was refined for the quantitative extraction of urban built-up area information within the Baiyangdian Basin, and the extraction process utilized PANNDA nighttime light data and Landsat series data from four periods: 1990, 2000, 2010, and 2020. Subsequently, an analysis of the spatial-temporal characteristics of urban built-up area expansion in the basin over the past 30 years was conducted using the urban expansion index and landscape index. The results show the optimized local-optimal thresholding method is successfully used to extract the data of the built-up areas in the basin for all phases, and it is confirmed that the method exhibits enhanced applicability compared to its pre-optimization state. The urban built-up area in the Baiyangdian Basin experienced significant expansion throughout the study period, with a growth rate of 154.48%. The sizes of the built-up areas across the 35 cities in the basin exhibited high heterogeneity. Temporally, the expansion of urban built-up areas predominantly exhibited an accelerating trend, with a widening disparity in the pace of expansion among the cities within the basin. Spatially, the built-up area to the left of the Zhengding-Zhuozhou line was less developed than that to the right. Notable expansion trends were observed in municipal districts or county-level cities such as Lianchi District, Jingxiu District, and Gaobeidian City. Based on the results of the landscape index, the expansion of urban built-up areas in Baiyangdian Basin shows the spatial characteristics of “dispersion-fusion” during the study period, and the boundary of built-up areas showed the evolution characteristics of “regular-complex-regular”.

Multivariate time series classification is a key problem in many fields, but the current research on multivariate time series classification is faced with some problems, such as high dimensionality of original data, low accuracy, and lack of interpretability, which limits the performance improvement of models and makes it difficult to meet the actual requirements. Aiming at above problem, a multivariate time series classification method based on Shapelets was proposed. Firstly, unsupervised Shapelet learning of adaptive neighbors was used to automatically learn significant multivariate Shapelets by combining Shapelets transform and adaptive weights. Then, the method was combined with Shapelet similarity and class label constraint to enhance the interpretability and classification accuracy of the model. Finally, the optimization strategy of the model was proposed to obtain the best Shapelets to further improve the classification accuracy of the model. Three different types of 11 algorithms were compared on 11 public data sets, and the experimental results show that the proposed algorithm has high classification accuracy.

A geomagnetic storm is a periodic natural disaster in which the changing geomagnetic field can induce an induced geoelectric field. A geomagnetic induced current (GIC) loop is formed between the transmission line and the earth conductor through the neutral points of grounding transformers. GIC seriously threatens the safe and stable operation of extra-high and ultra-high voltage AC transmission systems. There are many types of terrain and complex structures in our country, which makes the influence of geological landforms on induced geoelectric fields very significant. A finite element calculation method for GIC was proposed based on a three-dimensional earth conductivity model to address the difficulties in modeling and calculating GIC. Firstly, a three-dimensional earth conductivity model was established considering the anisotropy of geological structures. Meanwhile, a calculation model for electromagnetic field penetration depth under multi-layer geological conditions was given. Secondly, a mathematical model based on time-varying electromagnetic fields was established. Combined with the topology of the power grid, an equivalent calculation model for the power grid GIC was derived. Finally, taking the Shache-Turpan 750 kV transmission line in Xinjiang area as an example, a corresponding physical model was built in COMSOL Multiphysics finite element simulation software. The three-dimensional distribution of the induced ground electric field in the power grid was obtained through geometric modeling, boundary condition setting, grid division, and iterative solution. Furthermore, the GIC flowing through the neutral point of the 750 kV transformer was obtained. The research results indicatethat the overall level of GIC obtained by the 3D model is higher than that of the 2D model. Besides, the 3D model considers the geometric angle between the transmission line and different terrains, which can provide a more detailed distribution of induced geoelectric fields. The research results verify the effectiveness of the method proposed, which provides a reference basis for scientific planning of ultra-high and ultra-high voltage transmission corridors.