Water transport pipelines in the mining industry face significant corrosion challenges due to extreme environmental conditions, such as arid climates, temperature fluctuations, and abrasive soils. This study evaluates the effectiveness of three advanced inspection technologies—Guided Wave Ultrasonic Testing (GWUT), Metal Magnetic Memory (MMM), and In-Line Inspection (ILI)—in maintaining pipeline integrity under such conditions. A structured methodology combining diagnostic assessment, technology research, and comparative evaluation was applied, using key performance indicators like detection capability, operational impact, and feasibility. The results show that GWUT effectively identifies surface anomalies and wall thinning over long pipeline sections but faces depth and diameter limitations. MMM excels at detecting early-stage stress and corrosion in inaccessible locations, benefiting from minimal preparation and strong market availability. ILI provides comprehensive internal and external assessments but requires piggable pipelines and operational adjustments, limiting its use in certain systems. A case study of critical aqueducts of mining site water supply illustrates real-world technology selection challenges. The findings underscore the importance of an integrated inspection approach, leveraging the complementary strengths of these technologies to ensure reliable pipeline integrity management. Future research should focus on quantitative performance metrics and cost-effectiveness analyses to optimize inspection strategies for mining infrastructure.

U-shaped seismic dampers, passive metallic devices that dissipate energy by cyclic plastic deformation, are designed to mitigate the effects of seismic loads on structures. This study focuses on the development of an advanced computational model of a U-shaped damper, chosen for its unique design of variable thickness and width, which contributes to its superior performance. The simulation uses nonlinear finite element analysis and a bilinear hardening model calibrated to the actual stress–strain curve of the low-carbon steel. To ensure accuracy, a rigorous mesh convergence analysis is performed to quantify numerical prediction errors and establish a model suitable for predicting local deformation phenomena, including strain and stress fields, throughout the displacement-based loading protocol. Mesh sensitivity analysis, performed by examining the equivalent stress and cumulative plastic strain, derives the damper hysteresis curve and confirms the convergence criteria of the mesh within the experimentally observed plastic response range of the material. The resulting computational model is a novel contribution that provides reliable predictions of local inhomogeneous deformation and energy dissipation, essential for optimizing damper design and performance through more sophisticated damage-fatigue models that guarantee the lifetime of a damper.

Passive metallic dampers are critical for the seismic resilience of structures, yet their design has historically relied on incremental modifications rather than systematic optimization. This study introduces and validates a data-driven workflow that combines the Taguchi method with nonlinear finite element analysis to design novel U-shaped seismic dampers (USSDs) with superior performance. Building on an experimentally validated computational model from prior work, an L25 orthogonal array was employed to systematically investigate key geometric parameters, with an Analysis of Variance (ANOVA) identifying height, thickness, and length as the most influential factors on damper behavior. This statistical insight guided the creation of two optimized models, with the UD-M4 model demonstrating a nearly seven-fold increase in total energy dissipation (340.6 kJ vs. 51.2 kJ), a nine-fold increase in stiffness, and a 50% improvement in deformability compared to the commercial UD-40 baseline. The primary contribution of this work is the validation of an efficient statistical–computational methodology for the performance-based design of next-generation seismic protection devices, moving beyond traditional trial-and-error approaches.

Metallic seismic dampers are an effective tool for reducing structural damage during seismic events. While previous reviews have often focused on cataloging device types, this review presents a deep analysis of the underlying science governing their performance. Particular emphasis is placed on advanced computational methods, such as non-linear kinematic hardening (e.g., Chaboche) and micromechanical damage models (e.g., GTN), which are essential for accurately predicting low-cycle fatigue and fracture. Furthermore, advances in materials science are analyzed, ranging from low-yield-strength (LYS) steels to self-centering shape memory alloys (SMAs). Finally, the influence of manufacturing processes (including additive manufacturing) is explored, and critical future challenges in design, modeling, and long-term durability are identified. This analysis provides a foundational resource for researchers seeking to advance beyond simple phenomenological design toward physics-based prediction of damper performance.