Search Results (340)

Tire-Derived Aggregate (TDA) is a recycled fill material made by cutting scrap tires into small pieces that satisfy the gradation requirements in ASTM D 6270. Since its introduction to civil engineering applications, TDA fill and TDA backfill have been successfully implemented in many projects. However, the dynamic behavior of the TDA backfill under significant earthquakes has not been substantially addressed. The present study used nonlinear time-history Finite Element Analysis (FEA) to analyze the dynamic behavior of a retaining wall with TDA backfill captured from the full-scale shake table test. Unlike typical soil failure observed in a similar retaining wall with conventional soil backfill, significant wall sliding occurred because lightweight TDA contributed to reducing the friction resistance of the wall footing. Therefore, the analysis required modeling capability of rigid body motion and impact loading from the separation between the wall stem and the backfill. With adequate friction models and softened contact models, the FEA generated the dynamic motion of the retaining wall that matched well with the measured responses, including the wall sliding. The friction model between the wall footing and soil was most critical in accurately reproducing wall sliding motion. It was determined to use different friction coefficients for the two different earthquakes used in the study in order to simplify the rate dependence of the coefficient. Also, the softened contact model generated more reasonable impact force by allowing overclosure and finite stiffness during impact. The FEA model and modeling technique in the present study can be used for the seismic design of various field-scale retaining walls with TDA backfill. Full article

This study proposed an innovative assembled blast-resistant composite structure integrating ultra-high performance concrete plates and ceramic foam layers, designed to enhance blast protection for a power valve hall hole blocking system. Based on the full-scale blast test and numerical simulation, the dynamic response of the structure under blast load was revealed. The parametric studies showed that when the thickness of the UHPC ribbed plate was increased from 30 mm to 40 mm, the maximum displacement at the edge of the hole was reduced by 60.9%. However, a further increase in thickness to 50 mm led to an increase in the inertia effect due to the high stiffness, resulting in a reduction in the maximum displacement value by only 8.61%. In addition, a machine learning framework combining generative adversarial networks (GANs) and Extremely Randomized Trees (ERT) model was constructed to predict the maximum displacement of the structure under blast loading. Furthermore, interpretability analysis by the (SHapley Additive exPlanations) SHAP algorithm verified the consistency of the decision logic of the ERT model with the physical mechanism of the explosion. This study established a full-chain design framework of structural design, mechanism research and intelligent prediction, which provided theoretical support and an intelligent tool system for protection engineering. Full article

Online identification of HV cable circuits is vital for routine inspection and maintenance, yet existing passive electromagnetic wave injection methods are limited to offline operations. To fill the gap and achieve the online identification of HV cable circuits, an online circuit identification methodology based on sheath current temporal characteristics and deep embedded clustering is proposed. First, an equivalent circuit model of the multi-circuit cross-bonded cable sheath was built to deduce the temporal similarity of sheath currents within the same circuit, establishing the identification criterion. Second, the robustness of the temporal similarity under various operating conditions was verified via simulation based on the Dynamic Time Warping (DTW) distance. Then, a combined model of Temporal Convolutional Network Autoencoder (TCN-AE) and K-medoids was established to transform circuit identification into a temporal clustering problem of sheath currents, realizing circuit determination by synchronously monitoring the time-series sheath current data of multi-circuit HV cross-bonded cables. The method was verified on a full-scale 110 kV cable test platform. The results show that the identification accuracy reached 95.37%, and the proposed method can effectively identify the circuits of cross-bonded cables with high robustness against the domain gap, having significant engineering application value. Full article

Structural displacement monitoring is an essential component of structural health monitoring of bridges, providing valuable information for performance evaluation, numerical model validation, and damage detection. While conventional contact-based sensors provide high accuracy, their installation is often complex, costly, and disruptive to traffic. Recent developments in unmanned aerial vehicle (UAV) platforms and vision-based measurement techniques offer a flexible, non-contact alternative; however, platform motion remains a major source of uncertainty. This study evaluates the accuracy and operational feasibility of UAV-based homography for static and dynamic displacement monitoring. The proposed approach is validated through three complementary experimental campaigns: a controlled calibration field test, a beam static load test, and bridge monitoring under traffic loading, with direct comparison to LVDT and RTS measurements. Under controlled conditions, sub-millimetre vertical precision was achieved, with RMSE values below 0.3 mm. In full-scale bridge applications, the method captured traffic-induced displacement trends with errors generally within 1–2 mm compared to LVDT data and with RMSE values below 1.4 mm. The results demonstrate that, when appropriate reference point configuration and imaging geometry are ensured, UAV-based homography provides a practical and sufficiently accurate solution for bridge displacement monitoring which is especially important in applications where sensor installation is difficult or unsafe. Full article

This paper presents a patented design of a gravity flow rack with an energy recovery system, intended for pallet storage in first-in–first-out (FIFO) and last-in–first-out (LIFO) modes. Compared with conventional flow racks, the proposed solution integrates control of load-unit motion dynamics with energy recovery, thereby reducing losses and stabilising pallet flow. A Rack Energy Performance Index (REPI) is proposed to enable quantitative assessment of the energy consumption of storage racks in intralogistics applications. The research methodology comprised: (i) development of the mechanical architecture and pallet guidance principles; (ii) numerical modelling in the MSC Adams environment at Technology Readiness Level 3 (TRL-3); and (iii) validation using a full-scale prototype installed in a logistics centre. Operational tests confirmed stable operation, the required throughput, and the capability for energy compensation and recovery during storage cycles. The results indicate that energy-recovering racks can support the design of energetically passive warehouses. Full article

This study develops a conceptual framework for characterizing reservoir architecture in multi-component, discrete systems using pressure transient analysis (PTA), aimed at calibrating inflow geometry prior to full-field dynamic simulation for subsurface gas storage applications such as CO₂ and hydrogen. A secondary objective is to identify variations in permeability over time by analyzing flow capacity trends and evaluating the dynamic influence of faults and fractures. The analysis is based on a gas-condensate field comprising seven wells and four zones (A, B, C, D), using integrated dynamic datasets including extended well tests (EWTs), mud loss, production logs, and production data. Detailed interpretation of PX-1’s EWT indicated delayed re-pressurization and persistent under-pressure, suggesting a compartmentalized or transient system with limited gas-in-place connectivity. Four reservoir architecture concepts were developed: (1) lithology-dominated inflow, (2) structurally controlled inflow, (3) discrete, weakly connected compartments, and (4) transient-dominated systems with tight matrix GIIP. These concepts informed four reservoir models: matrix-only (M), areal heterogeneity (A), sparse bodies (B), and sparse networks (S). Application of these models across other wells revealed consistent localized KH (permeability–thickness product) behavior, with all models fitting short-duration data comparably. However, only sparse drainage models (B/S) adequately matched PX-1’s EWT response. PTA results confirm that well tests constrain KH locally but provide limited insight into large-scale reservoir architecture. EWTs may reach ~1 km, while shorter tests are confined to ~200–400 m, typically within one to two simulation grid blocks. This study demonstrates how integrating PTA with multi-scale data improves characterization of naturally fractured, tight carbonate reservoirs and supports reservoir simulation and history matching for hydrogen storage evaluation. Based on reservoir simulations, this study concluded that naturally fractured carbonate gas reservoirs can provide significant storage and injection capacities for underground hydrogen storage. This study exemplifies how to characterize the naturally fractured tight carbonate reservoirs by integrating multi-scale and multi-dimensional data such as PTA. Furthermore, this study assists in gridding for full-field reservoir models, for history matching and quantifying the potential of hydrogen storage in these complex reservoirs. The proposed workflow provides an uncertainty-bounded reservoir characterization framework and should not be interpreted as a complete field-design methodology for hydrogen storage. The modeling does not explicitly couple geomechanical fracture growth, hydrogen diffusion, long-term geochemical reactions, or caprock integrity degradation. Therefore, the presented storage scenarios represent technically feasible cases under defined assumptions. Comprehensive site-specific geomechanical and containment assessments are required prior to field-scale implementation. Full article

Ultra-High-Performance Concrete (UHPC) reinforced with steel fibers has emerged as a promising alternative to conventional concrete, which exhibits limited tensile capacity and a low modulus of rupture and is prone to brittle damage under cyclic loading—a critical drawback in seismic applications. The increasing demand for resilient, damage-tolerant construction materials in seismically active regions worldwide has intensified the need to evaluate the seismic performance of UHPC structural systems at the structural scale. However, the seismic behavior of full structural frames built entirely with cast-in-place UHPC remains largely unexplored. This study presents a full-scale experimental evaluation of single-story UHPC frames with two steel fiber volume fractions (1.0% and 1.5%) subjected to pseudostatic in-plane cyclic loading. A conventional reinforced concrete frame was tested for comparison. Key performance parameters—including hysteretic response, stiffness degradation, and energy dissipation—were assessed. The results suggest that the UHPC frames exhibited enhanced performance in comparison to the conventional frame across the measured parameters. The UHPC frame with 1.5% steel fiber content consistently outperformed both the 1.0% UHPC frame and the conventional reinforced concrete frame in terms of lateral strength, initial stiffness, and energy dissipation capacity, highlighting the critical role of fiber dosage in optimizing seismic performance. The 1.5% fiber UHPC frame reached approximately 59 kN in maximum lateral strength and 6.3 kN/mm in initial stiffness, representing increases of around 59% and 58%, respectively, relative to the conventional frame (~37 kN and 4.0 kN/mm). While stiffness degradation was observed in all specimens, the UHPC frames retained higher stiffness values throughout the test. At 5.5% drift, the 1.5% UHPC frame dissipated approximately 146,000 J, compared to 80,000 J for the conventional frame. These findings indicate that steel fiber-reinforced UHPC may improve the cyclic performance of frame structures and could serve as a viable alternative for earthquake-resistant construction. The results reported here should be interpreted as indicative trends rather than statistically generalizable conclusions. A key limitation of this study is that the experimental program focused solely on single-story frames under quasi-static loading; dynamic effects and multi-story behavior were not addressed. Full article

The evaluation of building energy performance under dynamic conditions requires reliable estimates of the thermophysical properties of envelope components. In existing buildings, however, the properties of multilayer walls are often unknown or uncertain, limiting the applicability of detailed physical models. To address this issue, this study proposes an inverse modeling framework for identifying the equivalent thermophysical parameters of a multilayer wall through a simplified homogeneous one-dimensional conduction model. The equivalent parameters are determined by matching the inner-side dynamic thermal response of the homogeneous model to that of the actual multilayer structure under the same external excitation. The approach explicitly accounts for the role of inner boundary conditions, which govern both the identifiability of the equivalent parameters and the formulation of the inverse problem. Adiabatic, isothermal, and more general inner boundary conditions are analyzed to determine how many independent parameters can be reliably identified and which response variables should be used in the objective function. Synthetic datasets, generated via numerical simulations driven by real weather data, are first employed to assess the method and to quantify the effect of transient initialization. The framework is then applied to experimental measurements collected from a full-scale test room. The results show that, under adiabatic conditions, the wall dynamics can be accurately reproduced by identifying a single equivalent thermal diffusivity, whereas isothermal and near-isothermal conditions require the simultaneous estimation of thermal conductivity and volumetric heat capacity. Moreover, the analysis demonstrates that inverse formulations based on inner heat flux are significantly more robust than temperature-based formulations, particularly when the inner-surface temperature is weakly varying or tightly controlled, as commonly occurs in real buildings. In a nearly isothermal experimental case, the inverse identification failed (${EF}_T=-5.76$) when based on the inner-surface temperature, while it resulted in a better match (${EF}_q=0.63$) when based on the inner heat flux. Overall, the proposed framework provides a physically consistent and practically robust methodology for the dynamic thermal characterization of multilayer building walls using equivalent homogeneous models. Full article

The accurate reconstruction of the internal temperature field in rotary kilns is critical for optimizing the clinker calcination process and ensuring energy efficiency. In this study, a rapid and high-fidelity surrogate modeling framework is proposed, utilizing snapshot ensembles generated by full-order Computational Fluid Dynamics (CFD) simulations to reconstruct the temperature field of the axial center section. The framework incorporates a symmetric Autoencoder (AE) coupled with a TabPFN network as its core components. Capitalizing on the kiln’s strong axial symmetry, this reduction–regression system efficiently maps the high-dimensional nonlinear thermodynamic topology of the central section into a compact low-dimensional latent manifold via AE, while utilizing TabPFN to establish a robust mapping between operating boundary conditions and these latent features. By leveraging the In-Context Learning (ICL) mechanism for prior-data fitting, TabPFN effectively overcomes the data scarcity inherent in high-cost CFD sampling. Predictive results demonstrate that the model achieves a coefficient of determination (R²) of 0.897 for latent feature regression, outperforming traditional algorithms by 6.53%. In terms of field reconstruction on the test set, the model yields an average temperature error of 15.31 K. Notably, 93.83% of the nodal errors are confined within a narrow range of 0–50 K, and the reconstructed distributions exhibit high consistency with the CFD benchmarks. Furthermore, compared to the hours required for full-scale simulations, the inference time is reduced to 0.45 s, representing a speedup of four orders of magnitude. Consequently, the predictive system demonstrates excellent accuracy and efficiency, serving as an effective substitute for traditional models to realize online monitoring and intelligent optimization. Full article

Systems with large physical size such as wind turbines, aircraft, and ships are dominated by the inertia of the flow. In conventional experimental facilities, a reduction in scale is required, which can introduce viscous effects that are not present at full size. However, if the wind tunnel is operated with a heavy gas, the reduction in scale can be counteracted by an increase in density, and the flow that exists at full size can be recreated accurately. This work describes the design, construction, and basic flow characterization of a heavy gas wind tunnel facility, known as the Compressed Air Wind Tunnel (CAWT), that utilizes pressurized air as the working fluid at pressures up to 35 bar. The tunnel was designed to accommodate relatively large models inside the 1.04 meter-diameter test section while having improved optical access compared to existing facilities of this type. A series of flow characterization tasks were carried out on the completed facility, including quantifying the turbulence intensity and flow uniformity in the tunnel test section. Measurements showed a maximum turbulence intensity of 0.46% and an average of 0.22% across all conditions and locations tested. The maximum velocity non-uniformity between four locations in the test section was 0.36%, which occurred at the lowest tested wind speed of 2.4 m/s. The average non-uniformity across all tested conditions was less than 0.093%. Mapping the facility operating space has now enabled ongoing work examining rotorcraft, marine propeller, and wind turbine performance and wake development with the aim of answering long-standing questions regarding how the fluid dynamics depend on scale or Reynolds number effects. Full article

To address the need for high-efficiency vibration isolation in marine rotary pump units, this paper proposes a coupled isolation system that integrates vibration isolators and flexible connectors, and systematically investigates its vibration suppression performance. By combining experimental parameterized modeling with full-scale test platform validation, an efficient analytical framework capable of accurately predicting the system’s broadband vibration isolation performance has been established. This framework provides a reference for engineering design that balances model reliability and practical applicability. The study first obtained the transfer complex stiffness of the isolators through mechanical impedance experiments and, combined with the stiffness parameters of the flexible connectors measured by an MTS (Mechanical Testing & Simulation) testing machine, established a nonlinear spring-damper equivalent model for the isolators and flexible connectors. A three-dimensional finite element model of the rotary pump unit coupled isolation system was developed using the explicit dynamics method, and the vibration transmission characteristics of the coupled isolation system under complex excitation from the rotary pump were analyzed using the vibration acceleration level difference between the “machine foot” and “foundation” as the evaluation index. To verify the reliability of the model, a full-scale rotary pump unit isolation test platform was constructed, and multi-condition vibration tests were conducted. The results show that the finite element model of the coupled isolation system can effectively predict the vibration response, with the overall vibration level error between numerical calculations and experiments within ±3 dB. Under various operating conditions involving changes in rotational speed and water pressure, the system demonstrates good broadband isolation performance, with the maximum vibration acceleration level difference reaching 29.32 dB. The flexible connectors further suppress lateral vibration transmission from the pump unit to external pipelines, working in synergy with the isolators to achieve multi-directional vibration isolation. This study provides design references with both modeling reliability and engineering applicability for vibration and noise reduction in marine pump units. Full article

To address the challenge that traditional dam model materials are difficult to simultaneously meet the requirements of microstructural similarity, dynamic damage simulation, and environmental friendliness, a novel microparticle mortar simulated concrete was developed. This new material consists of cement, sand, gypsum, mineral oil, water, and baryte sand. Through systematic material mechanical tests, the effects of each component on the material’s strength, density, and elastic modulus were revealed, and the optimal mix ratio was determined. This enabled precise control of low elastic modulus and had a high density, while the material is environmentally friendly, non-toxic, and compatible with direct contact with natural water. Its mechanical properties are highly similar to those of the prototype concrete. Based on a 1:70 geometric scale, a shaking table model test of the concrete gravity dam-reservoir system was conducted. The dynamic response and damage evolution under empty and full reservoir conditions were compared and analyzed. The study shows that this material can accurately simulate the stress-strain relationship and failure mode of prototype concrete. Under the full reservoir condition, the dam’s fundamental frequency showed only a 2.72% deviation from the numerical simulation, and as the seismic excitation amplitude increased, the changes in the fundamental frequency effectively reflected the accumulation of damage. Under the design seismic motion, the measured accelerations and stress responses for both empty and full reservoir conditions were in good agreement with numerical calculations. Under overload conditions, the acceleration amplification factor at the dam crest decreased with damage accumulation, and the dam neck was identified as the seismic weak zone. As the peak ground acceleration (PGA) increased from 0.15 g to 0.70 g, the fundamental frequency changes effectively reflected the damage accumulation process in the dam, while the hydrodynamic pressure at the dam heel showed a linear increase (457% increase). The experimentally measured hydrodynamic pressure distribution was between the rigid dam and elastic dam hydrodynamic pressures, reflecting the real fluid-structure interaction effect. This study provides a reliable material solution and data support for dam seismic physical model testing. Full article

Despite extensive research on blast-resistant concrete structures, a clear scientific deficiency remains in the quantitative understanding of how fiber-reinforced concrete slabs behave under blast loading, particularly when experimental and numerical investigations are not conducted together under identical loading conditions. Existing studies often focus on either conventional reinforced concrete or isolated material systems, providing limited validation of comparative blast performance across different fiber-reinforced concretes. This study addresses this gap by investigating the blast resistance performance of four types of reinforced concrete slabs: normal concrete (NC), ultra-high-performance fiber-reinforced concrete (UHPFRC), organic fiber-reinforced high-performance concrete (O-HPC), and basalt FRP-sheet-strengthened slurry-infiltrated fiber concrete (F-SIFCON), using full-scale blast experiments and validated numerical simulations conducted with ANSYS Explicit Dynamics. Blast tests were performed to obtain time histories of reflected pressure, displacement, acceleration, reaction force, and internal energy. The influence of different fiber systems and FRP strengthening on dynamic response and failure mechanisms was systematically analyzed. The numerical models showed good agreement with experimental measurements, confirming their reliability. The results indicate that the normal concrete slab exhibited brittle failure and poor blast resistance, whereas the F-SIFCON slab demonstrated the best overall performance. Compared with the normal concrete slab, the F-SIFCON slab achieved approximately a 47% reduction in maximum displacement, a 56% increase in peak reaction force, and the highest internal energy absorption of 236 kJ. The UHPFRC and O-HPC slabs also showed improved blast resistance, although with different post-peak response characteristics. These findings demonstrate that hybrid fiber reinforcement combined with FRP strengthening can significantly enhance the blast resistance of concrete slabs and that coupled experimental–numerical approaches provide a robust framework for evaluating structural performance under extreme dynamic loading. Full article

This study investigates an inlet design for a gravitational vortex turbine (GVT), drawing inspiration from the ancient Nazca puquios. The puquios are ingenious subterranean aqueducts constructed by the Nazca culture (c. 100 BC–800 AD) in southern Peru, featuring spiral ojos de agua (water eyes) used to access groundwater and stabilize flow.The primary objective was to enhance vortex stability and overall GVT efficiency under low-head, low-flow operating conditions. A parametric Nazca-type inlet feeding a conical basin was defined by two controlling factors: the number of turns (N) and the inclination angle ($\theta$). The optimal geometry was determined through a $3^2$ full factorial design, computational fluid dynamics (CFD) simulations, and response surface methodology (RSM), with vortex circulation $(\Gamma )$ serving as the optimization metric. The best-performing inlet configuration ($N=4$, $\theta ={13}^{\circ }$) yielded $\Gamma =1.3459$ m²/s. This circulation level is comparable to that reported for optimized conventional wrap-around inlets at similar flow rates, but uniquely produced a broader and more symmetric vortex structure. Subsequently, two four-bladed runners (one with twisted blades and one with curved cross-flow blades) were evaluated numerically and experimentally using a laboratory-scale prototype operated at a consistent flow rate ($Q\approx 0.00143$ m³/s). CFD predicted maximum efficiencies of $15.37\%$ and $17.07\%$ for the twisted and curved runners, respectively, while experimental tests achieved $8.70\%$ and $11.61\%$, demonstrating similar efficiency ($\eta$) versus angular velocity ($\omega )$ characteristics. These results indicate reduced hydraulic effectiveness of the Nazca-inspired geometry for the GVT, with experimental efficiencies below those reported in the literature. Full article

Accurate braking-distance prediction for heavy-duty multi-axle trucks remains challenging due to the large gross vehicle weight, tandem-axle interactions, and strong transient load transfer during emergency braking. Recent studies on tire–road friction estimation, commercial-vehicle braking control (EBS/AEBS), and weigh-in-motion (WIM) sensing have highlighted that unmeasured vertical-load dynamics and time-varying friction are key sources of prediction uncertainty. To address these limitations, this study proposes an integrated sensing–simulation–AI framework that combines real-time axle-load estimation, full-scale robotic braking tests, fused road-friction sensing, and physics-consistent machine-learning modeling. A micro-electro-mechanical systems (MEMS)-based load-angle sensor was installed on the leaf-spring panel linking tandem axles, enabling the continuous estimation of dynamic vertical loads via a polynomial calibration model. Full-scale on-road braking tests were conducted at 40–60 km/h under systematically varied payloads (0–15.5 t) using an actuator-based braking robot to eliminate driver variability. A forward-looking optical friction module was synchronized with dynamic axle-load estimates and deceleration signals, and additional scenarios generated in a commercial ASM environment expanded the operational domain across a broader range of friction, grade, and loading conditions. A gradient-boosting regression model trained on the hybrid dataset reproduced measured stopping distances with a mean absolute error (MAE) of 1.58 m and a mean absolute percentage error (MAPE) of 2.46%, with most predictions falling within ±5 m across all test conditions. The results indicate that incorporating real-time dynamic axle-load sensing together with fused friction estimation improves braking-distance prediction compared with static-load assumptions and purely kinematic formulations. The proposed load-aware framework provides a scalable basis for advanced driver-assistance functions, autonomous emergency braking for heavy trucks, and infrastructure-integrated freight safety management. All full-scale braking tests were carried out at approximately 60% of the nominal service-brake pressure, representing non-panic but moderately severe braking conditions, and the proposed model is designed to accurately predict the resulting stopping distance under this prescribed braking regime rather than to minimize the absolute stopping distance itself. Full article