Pipelines, as critical infrastructure in energy transmission, municipal facilities, industrial production, and specialized equipment, are essential to national economic security and social stability. This paper systematically reviews the domestic and international research status of pipeline in-line inspection (ILI) technologies, with a focus on four major technological systems: electromagnetic, acoustic, optical, and robotic technologies. The operational principles, application scenarios, advantages, and limitations of each technology are analyzed in detail. Although existing technologies have achieved significant progress in defect detection accuracy and environmental adaptability, they still face challenges including insufficient adaptability to complex environments, the inherent trade-off between detection accuracy and efficiency, and high equipment costs. Future research directions are identified as follows: intelligent algorithm optimization for multi-physics collaborative detection, miniaturized and integrated design of inspection devices, and scenario-specific development for specialized environments. Through technological innovation and multidisciplinary integration, pipeline ILI technologies are expected to progressively realize efficient, precise, and low-cost lifecycle safety monitoring of pipelines.

Subsea pipelines are extensively utilized in transportation systems. Conducting regular and effective internal inspections of these pipelines to promptly identify internal defects and potential risks is of paramount importance to ensure safe operational practices. In response to the practical engineering requirements for the internal inspection of subsea pipelines, this paper presents the design of an inspection device capable of capturing point cloud data from pipelines with internal diameters of 100 mm and above and performing three-dimensional reconstruction through coding. This device clearly reveals internal pipeline defects and enables both qualitative and quantitative analyses. Upon designing the motion module, control system, and LiDAR-based detection module of the internal pipeline inspection device, the capacity to collect internal point cloud data and perform 3D reconstruction was achieved. An experimental prototype of the inspection device was manufactured and tested using a simulated pipeline constructed to replicate real-world conditions. An analysis of the inspection results demonstrates that the device can travel steadily inside the pipeline, and the collected point cloud data can be used for 3D reconstruction via coding, accurately and clearly displaying the internal 3D structure of the pipeline and its defects. This device provides a basis for the prediction of pipelines’ service lives.

To address the insufficient prediction accuracy of traditional Arrhenius-type empirical correlations for hydrogen–oxygen combustion ignition delay time (IDT) over wide operating conditions, this paper proposes a data-driven prediction method based on Gaussian Process Regression (GPR). Based on 413 sets of shock tube and rapid compression machine experimental data, with temperature, pressure, and equivalence ratio as input features, an IDT prediction model was constructed. The GPR model adopts the Matérn 3/2 kernel function combined with the Automatic Relevance Determination (ARD) strategy for hyperparameter optimization. As a benchmark comparison, LASSO regression was employed for feature selection and parameter estimation of the Arrhenius empirical correlation. On a stratified sampling test set, the GPR model achieved a coefficient of determination R² of 0.8587 ($R_{ln}^2$ = 0.9271 on logarithmic scale), significantly outperforming the Arrhenius model’s R² of 0.5422 ($R_{ln}^2$ = 0.7027). In 50 random-split stability tests, GPR yielded a mean R² of 0.9180 with a standard deviation of only 0.0333, demonstrating excellent robustness. This study provides a valuable reference for ignition performance prediction of hydrogen–oxygen combustion systems.

The cloud model provides a unified mathematical framework for representing both randomness and fuzziness simultaneously, offering an effective mathematical tool for modeling complex systems. This paper focuses on the emergent phenomenon of spontaneous synchronous flashing in fireflies and employs Gaussian cloud model theory to develop an initialization framework. Uncertainty is quantified using three core numerical characteristics of the cloud model—expectation, entropy, and hyperentropy—while a Gaussian potential function is adopted to characterize how interaction strength varies with spatial distance. A MATLAB-based simulation platform is developed to reproduce the emergent transition of fireflies from disordered flashing to synchronous behavior across different spatial domains. Our results demonstrate that group synchronization efficiency is strongly governed by the initial spatial configuration of individuals. Introducing driving nodes (special agents) can accelerate synchronization, but increasing their quantity yields diminishing marginal returns; the optimal strategy is a single special agent placed at the domain center. Collective emergence depends more strongly on the topological structure of inter-individual interactions than on the number of driving nodes. These findings confirm that interaction topology dominates synchronization performance over driving-node quantity, providing a theoretical basis for guiding unmanned swarm coordination with minimal control nodes.

In response to the current limitation where conventional constant volume combustion apparatuses are generally confined to pressure ratings of 5–20 MPa, insufficient for the demands of ultra-high-pressure combustion fundamental research, this study designs and verifies a high-pressure-resistant constant volume combustion apparatus with a rated working pressure of 250 MPa. The strength design and safety factor calculation for the combustion chamber main body were conducted based on the Lame thick-walled cylinder elastic theory. A finite element numerical simulation method was systematically employed to perform static analysis, transient impact response analysis, and high-cycle fatigue-life assessment of the key components of the apparatus. The results indicate that under a 250 MPa design internal pressure load, the maximum circumferential stress at the inner wall of the combustion chamber main body is 328.0 MPa, with a safety factor greater than 1.5, complying with relevant safety codes for high-pressure vessels. Under transient loading simulating combustion impact, the maximum equivalent stress of all structural components is below the material yield strength, with a maximum elastic deformation of less than 0.06 mm, demonstrating excellent structural stiffness and impact resistance. Fatigue assessment with a design-life target of 1.0 × 10⁶ pressure cycles shows that the cumulative damage values for all components are significantly less than 1.0, meeting the reliability requirements for long-term cyclic service. This apparatus integrates functional modules such as high-pressure precision gas mixing, high-energy reliable ignition, high-speed transient parameter acquisition, and safe product collection, providing a stable, controllable, and safe experimental platform for in-depth research on the combustion mechanisms of gaseous fuels under ultra-high-pressure conditions.