Search Results (243)

Traditional ready-to-wear garments can mostly not conform to different body shapes because of the adoption of the generic sizing system, which leads to the local strain of concentration and morphological misfit. Auxetic structures, which have a negative Poisson’s ratio, permit enhanced redistribution of stress and geometry and allow deformation. Two auxetic knitted structures were developed by using 100% polyester and 100% nylon yarns with a fabric density of 41 Wales and 40 courses per inch. Characterization of the initial fabrics involved checking the behavior of negative Poisson’s ratio (NPR) where the polyester line (P1) structure shows the highest auxeticity, with a NPR of approximately −0.4 and peak strain reductions of 80–90%, as well as air permeability, moisture management, bend test, compression, roughness, friction properties and stiffness tests to check the mechanical and comfort-related performances. The standardized tunic garment was modeled in CLO 3D on three female body shapes—hourglass, pear and rectangle—with a constant size of 34. The fit map showed a strain of 91.49% in auxetic and 509.75% in single-jersey fabric at the hip area of the pear body shape when measuring fabric and body interaction. The findings indicate lower peak strain levels, which ascertain that increased adaptability is possible and support its use in the development of adaptive ready-to-wear garments. Full article

A novel data-driven modeling framework is developed for servo control using Long Short-Term Memory (LSTM) networks. The framework employs an LSTM model to directly map interpolation commands and feedback signals, such as velocity, acceleration, and jerk, to tracking errors. By adopting end-to-end architecture, the method bypasses complex sequential procedures, including system identification and friction modeling, significantly reducing development time and modeling complexity. Experimental results demonstrate that the LSTM model accurately predicts servo tracking behavior and enables rapid performance evaluation and parameter optimization without performing time-consuming trajectory testing. The proposed framework offers a practical and efficient alternative to traditional model-based techniques in precision motion control. Full article

To address the challenge of surrounding rock instability in deep-buried tunnels crossing fractured fault zones, this study focuses on the Xigu Tunnel of the Lanzhou–Hezuo Railway. A combination of laboratory triaxial tests, an optimized multi-source advanced geological prediction workflow, and a site-specific parameter-weakened Mohr–Coulomb numerical simulation is employed to systematically reveal the physical–mechanical properties, spatial distribution, and deformation response of fractured rock masses under excavation-induced disturbance. The triaxial test results show that the average peak strength of the surrounding rock reaches 149.04 MPa; however, significant variability is observed among samples, and the failure mode exhibits a typical brittle–shear composite feature. The measured cohesion and internal friction angle are 20.57 MPa and 49.91°, respectively, indicating high intrinsic strength of individual rock blocks. Nevertheless, due to the presence of densely developed joints and crushed structures, the overall mass is loose and highly sensitive to dynamic disturbances such as blasting and excavation, revealing a unique mechanical paradox of high-strength rock blocks with low overall rock mass stability in deep-buried fractured zones. Joint TSP (Tunnel Seismic Prediction Ahead) and ground-penetrating radar (GPR) prediction reveals decreased P-wave velocity, increased Poisson’s ratio, and intensive seismic reflection interfaces; a quantitative index system for identifying the boundaries of narrow deep-buried fractured zones is proposed based on these geophysical characteristics. Combined with geological face mapping, these results confirm the existence of a highly fractured zone approximately 130 m in width, characterized by well-developed joints, heterogeneous mechanical properties, and localized risks of blockfall and groundwater ingress. The developed numerical model, with parameters weakened based on triaxial test and geological prediction data, effectively reproduces the deformation law of the fractured zone, and the simulation results agree well with field monitoring data, with peak displacement concentrated at section DK4 + 595, thus accurately identifying the center of the fractured belt as a key engineering validation result of the integrated technical framework. During construction, based on the identified spatial characteristics of the fractured zone and the proposed targeted support insight, enhanced dynamic monitoring and targeted support measures at the fractured zone center are required to ensure structural safety and long-term stability of the tunnel. This study develops an integrated engineering-oriented technical framework for deep-buried tunnels crossing narrow fractured zones, and provides novel mechanical insights and quantitative identification indices for such complex geological engineering scenarios. Full article

Airborne electromagnetic (AEM) surveys map subsurface electrical structures by deploying transmitter and receiver coils on an airborne platform. However, platform-induced vibrations are transmitted to the sensors, generating strong motion-induced noise that severely degrades signal quality. To mitigate such noise, this study proposed the use of granular materials as a cushioning medium. An impact model based on the Discrete Element Method (DEM) was developed and validated against drop-weight experiments. Both granular material properties and impactor characteristics were investigated. The study examined the cushioning effects on both the base plate and the impactor under impact loading, and the sensitivity of key parameters was evaluated. The results showed that granular properties had minimal influence on the impactor peak force. Increasing particle Young’s modulus, density, or friction coefficient led to higher peak forces on the base plate, with Young’s modulus and density having significantly stronger effects than friction coefficient. Additionally, both the impactor size and velocity correlate positively with the peak forces transmitted to the base plate and experienced by the impactor. Under thin layer conditions, the impactor force was more sensitive to impact parameters, while in thick layers it was mainly determined by particle rearrangement and energy dissipation mechanisms. These findings reveal the mechanisms governing granular cushioning and provide a theoretical basis for vibration isolation design in AEM systems to preserve high-fidelity signals. Full article

Friction stir welding (FSW) of dissimilar aluminium alloys often results in non-uniform microstructure and hardness distributions due to asymmetric temperature fields and material flow. The objective of this study is to establish a quantitative relationship between thermal history, microstructural evolution, and hardness distribution in dissimilar AA5052-H32/AA6061-T6 FSW joints by combining experimental characterisation with validated thermal modelling. AA5052-H32 and AA6061-T6 plates were welded under five different parameter sets. A thermal finite element model was developed in COMSOL Multiphysics to simulate temperature evolution during welding and was validated using embedded thermocouple measurements, with predicted peak temperatures ranging from 455 °C to 641 °C. Optical microscopy, scanning electron microscopy (SEM), and electron backscatter diffraction (EBSD) were employed to characterise grain structure and dynamic recrystallisation (DRX) behaviour, while Vickers microhardness mapping was used to evaluate the local mechanical response. The results show that DRX occurred in the nugget zone (NZ), leading to significant grain refinement, with a minimum grain diameter of 6.07 µm, representing an approximately eightfold reduction compared with the base material AA5052-H32. In contrast, the thermo-mechanically affected zone (TMAZ) experienced limited recrystallisation due to insufficient plastic deformation and temperature. The lowest hardness was observed in the TMAZ on the AA5052-H32 side, with the hardness reduction of 22% primarily caused by work hardening loss. Hardness was also reduced by 34% on the AA6061-T6 side due to decreased precipitation strengthening caused by high temperatures. This combined experimental–numerical study provides a systematic thermal–microstructure–hardness framework for understanding and predicting local property variations in dissimilar FSW joints. Full article

We present two models for incorporating the total effect of market friction noise into the dynamic pricing of assets and European options. The first model is developed under a continuous-time Black–Scholes–Merton framework. The second model is a discrete, binomial tree model developed as an extension of the static Grossman–Stiglitz model. Both models are market-complete and provide a unique equivalent martingale measure that establishes a unique map between parameters governing the risk-neutral and real-world price dynamics. We provide empirical examples to extract the coefficients of the model, in particular those coefficients characterizing the influence of the frictions on prices. In addition to isolating the impact of noise on the volatility, the discrete model enables us to extract the noise impact on the drift coefficient. We provide evidence for the primary market friction that we believe our empirical examples capture. Full article

In this study, the effect of boron carbide (B₄C), hexagonal boron nitride (hBN), holy super graphene (HSG), and hybrid (B₄C + hBN + HSG) nano-additives on the tribological performance of SAE 5W-30 gasoline engine oil was investigated on Al-Si-based samples (Al 4032) prepared by cutting from a single-cylinder gasoline engine block. The addition of nano-additives regularly increased the kinematic viscosity; the 63.80 mm²/s (BO) value rose to 68.90 mm²/s at the highest level of B₄C and to 70.50 mm²/s in the hybrid oil (≈10.5% increase). The lowest and most stable friction performance was found in the hybrid 0.025 g/25 mL nano-additive oil, which remained between 0.03 and 0.05 during the entire COF test. The EDS mapping and line scan results confirmed the formation of tribofilm by identifying the additive elements (B for B₄C, B and N for hBN, C for HSG) in the wear scar, and the presence of increased O elements showed the restricted formation of tribo-oxidation. The results show that hybrid nano-additive oils provide the most effective friction and wear improvement, especially at low concentrations, while at high additive levels, performance does not show a consistent increase due to particle accumulation and third-body effects. Full article

This study delves into how the literature conceptualizes banking efficiency as a capability shaping sustainability-oriented pathways under conditions of systemic uncertainty, including recurrent economic–financial disruptions and geopolitical shocks. Using records indexed in the Web of Science Core Collection, the study combines bibliometric mapping with conceptual structuring to examine publication dynamics, collaboration networks, and the thematic evolution of research linking bank efficiency, green finance intermediation, sustainable digital innovation, and risk governance. The study reveals a multidimensional knowledge base organized around two converging streams: (i) research on efficiency, stability, and crisis transmission emphasizing intermediation quality, performance under stress, and prudential responses; and (ii) sustainability and innovation scholarship focusing on how financial systems enable eco-innovation diffusion and low-carbon transition through capital allocation, governance mechanisms, and digitally enabled transformation. Across these streams, banking efficiency is increasingly discussed not merely as a performance ratio, but as a strategic capability that becomes particularly salient in crisis environments: it can reduce intermediation frictions when funding conditions tighten, strengthen screening and monitoring of green projects amid elevated uncertainty, and support the continuity and scaling of eco-innovations by improving decision speed and resource allocation through digital tools. Collaboration patterns indicate growing interdisciplinary engagement—especially among European and Asian institutions—where crisis, sustainability, and innovation perspectives are integrated into systems-based approaches to green finance. Building on these insights, the article outlines a research agenda oriented toward innovation outcomes in turbulent contexts, emphasizing (a) measurement strategies that connect efficiency to eco-innovation diffusion and adoption rates during stress periods; (b) comparative analyses of how policy incentives and green market signals interact with bank efficiency across crisis episodes; and (c) hybrid methodological designs combining econometric identification, network analytics, scenario-based stress framing, and AI-enabled analytical tools to capture nonlinear dynamics in efficiency–innovation linkages. Overall, the study clarifies how banking efficiency may condition the capacity of financial institutions to sustain green investment intermediation and advance eco-innovation pathways when uncertainty is systemic rather than episodic. Full article

Hydrogen combustion is known to be fast compared to traditional hydrocarbon fuels. The fast combustion leads to a higher thermal efficiency. In this research a 600 cc single cylinder hydrogen engine was tested at 1250 rpm, lambda = 2 and 3, and three load levels (load was represented by Manifold Absolute Pressure (MAP); MAPs tested were 75, 95 and 120 kPa) and compared to operation with gasoline and propane. The fast burn duration (Mass Fraction Burnt MFB10% to MFB90%) and the MFB 50% were determined and analyzed. The hydrogen MFB50% location for Minimum Timing for Best Torque (MBT) was found to occur at around the typical 8 Crank Angle Degrees (CADs) After Top Dead Center (ATDC). Measurements of ignition delay based on the fast data direct measurement of spark ignition coil current drop to the change in polarity of net heat release are presented. With shifts towards direct injection and higher injection pressures, consideration was given to the hydrogen pressurization penalty, where it was calculated that pressurizing hydrogen to 100 bar at the flow required for lambda = 2 operation is 2.3 bar, i.e., higher than the Friction Mean Effective Pressure (FMEP)! Furthermore, hydrogen is widely cited to have a higher heat loss than typical hydrocarbon fuels. In this paper, detailed analyses at lambda 2 and lambda 3 showed that hydrogen in fact has lower heat losses. Full article

Air-cooled heat sinks remain a practical and cost-effective solution for thermal management in high power-density electronic systems. This study investigates the thermal–hydraulic performance of a plate pin-fin heat sink operating under forced convection, with emphasis on the coupled interaction between heat-transfer enhancement and pressure-drop penalty. The proposed hybrid configuration combines the low flow resistance of plate fins with the wake-induced mixing characteristics of pin-fin elements, thereby modifying boundary-layer development and flow structures within the fin channels. This review comprehensively analyzes existing experimental measurements across a range of Reynolds numbers to evaluate the average Nusselt number, thermal resistance, and friction factor. The results demonstrate that the inclusion of pin elements significantly enhances convective heat transfer through increased flow disruption and vortex formation, while incurring a moderate increase in pressure loss relative to conventional plate-fin designs. In addition, flow visualization and temperature mapping reveal improved heat transfer uniformity along the streamwise direction, particularly at intermediate Reynolds numbers where transition effects become pronounced. Empirical correlations were developed to relate the Nusselt number and friction factor to Reynolds number and key geometric ratios, providing predictive capability for thermo-hydraulic performance assessment. The findings indicate that fin-scale geometric optimization plays a dominant role in achieving improved overall performance and that the plate pin-fin configuration offers a favorable trade-off between heat-transfer augmentation and hydraulic efficiency for forced-convection electronic cooling applications. Full article

This paper addresses global path planning for a wheeled mobile robot with two different kinematic structures, considering both shortest path and minimum energy consumption criteria. The main research question concerns how the robot’s kinematic structure and the selected planning algorithm influence the resulting path with respect to these criteria. Our review of the state of the art discusses selected path planning methods, including model-based approaches. To determine the energy optimal path, a simplified model of the PIAP GRANITE robot was developed. The robot can be configured as either differentially driven or skid-steered. In the differentially driven configuration, the robot has two driven wheels and two caster wheels, whereas in the skid-steered configuration all wheels are independently driven. The robot’s models are based on previous theoretical and experimental studies and include kinematics, dynamics, drive units, and wheel slip phenomena. For path planning, it was assumed that the robot can move straight or turn. A flat terrain representative of typical urban environments was modeled as a grid of square cells, each characterized by friction and rolling resistance coefficients. Path planning was performed using A*, Theta*, and RRT* algorithms. In order to quantitatively evaluate the results, quality indexes were defined, including path length, energy consumption, computation time, and the number of analyzed nodes. Simulation results are presented for selected terrain maps, both robot configurations, all algorithms, and both optimization criteria. The results show that the differentially driven configuration is consistently more energy-efficient. For the skid-steered robot, minimizing the number of turns is crucial due to high turning energy costs. The A* algorithm consistently finds optimal paths, whereas RRT* is faster but produces non-optimal and non-repeatable results. Theta* does not always achieve optimality due to limitations imposed by the line-of-sight function. Full article

Assessing urban resilience under compound shocks requires observable and comparable process evidence that can inform resilient land governance and cross-jurisdiction planning. Using China’s Pilot Free Trade Zones (PFTZs) as a staged institutional setting, this research examines whether institutional exposure is associated with deviation–recovery trajectories of urban activity during the 2020 COVID-19 shock and whether these associations propagate through spatial spillovers with an identifiable scale profile. Institutional exposure is operationalized by the prefecture-level cities actually covered by PFTZ functional areas. With harmonized administrative boundaries, we construct an annual city-level VIIRS nighttime light (NTL) series for 2013–2024 and treat NTL as an activity-change signal rather than a direct proxy for output. We trace shock deviation in 2020 and subsequent recovery via staged differencing. Spatial interaction frictions are represented by least-cost path distance (LCPD) derived from a multi-source cost surface, which is used to build a gravity-based spatial weight matrix. Estimation relies on the Spatial Durbin Model (SDM), with LeSage–Pace impact decomposition to distinguish direct and spillover effects, complemented by distance-threshold diagnostics to map attenuation patterns. Results indicate persistent clustering within the PFTZ-related urban system. The shock year is characterized by compressed connectivity and fragmented brightening, whereas recovery proceeds in a layered manner with earlier core repair, partial corridor reconnection, and weaker adjustment at the periphery. Spatial dependence in activity change is statistically significant. Associations linked to institutional exposure are realized primarily locally, while structural and scale conditions more readily operate through spatial externalities. Spillovers are most detectable at meso-scales and attenuate gradually across distance thresholds. Overall, the integrated earth-observation and spatial-econometric framework provides replicable geospatial evidence to support resilient land governance and regional coordination under common shocks. Full article

Graphene, a 2D carbon allotrope with a hexagonal atomic structure, exhibits an exceptionally low friction coefficient of approximately 0.004, making it a superior alternative to traditional lubricants. This research investigates the performance of graphene as an additive in oil-based lubricants. Experimental trials will be conducted using a block-on-ring (B-o-R) setup involving a steel rod pressed against a rotating steel ring under a fixed load. By varying the sliding velocities, the study will map the Stribeck curve across the boundary (BL), mixed (ML), and hydrodynamic (HL) lubrication regimes. Furthermore, the lubricant’s durability under extreme pressure will be assessed via Timken testing. The study identified 0.08 wt.% as the optimal concentration for PAO8, achieving a 21.25% friction reduction in the boundary regime. Furthermore, graphene as an additive mitigated wear volume by up to 90% under extreme pressure conditions (1.3 GPa), whereas epoxidized soybean oil proved to be highly effective as a base lubricant without additional nano-additives. Full article

This paper proposes a methodological architecture to integrate Q-learning into economic modelling systematically. It addresses a common gap: the lack of a shared framework linking economic foundations to Reinforcement Learning components. Rather than introducing a new algorithm, it specifies and reports how preferences, frictions, information structures, and time horizons map to the reward function, discount factor, and learning environment design. Equilibrium outcomes serve as benchmarks for comparing learned policies, not as imposed axioms. This approach interprets learning dynamics through standard economic categories and enables comparability across studies. The architecture organizes models along explicit dimensions: behavioural preferences, institutional frictions, economic environment class, information structure, learning and exploration mechanisms, and evaluation metrics. A simulation illustrates how variations in frictions, risk attitudes, and intertemporal preferences affect learned policies, their stability, and their relationship to static benchmarks. The paper aims to promote the cumulative use of Reinforcement Learning in applied economics by providing a general specification that improves interpretability, comparability, and reproducibility, turning deviations from theoretical equilibria into measurable diagnostics that refine economic fundamentals. Full article

Wave-driven free-surface flows pose numerical challenges due to tensorial radiation stress forcing, anisotropic diffusion, and strong sensitivity to closure parameters. This paper investigates the numerical behavior of a quasi-3D wave-driven flow model using a coupled depth-integrated (2D) solver with a diagnostic three-dimensional (3D) reconstruction employed for consistency verification to evaluate the validity of dimensional reduction. The scheme is implemented on a staggered Arakawa C-grid with a terrain-following vertical coordinate and explicit pseudo-time-stepping, which enables the direct assessment of stability limits. A reference experiment and systematic sensitivity tests are performed for three idealized bathymetries of increasing complexity. Bottom friction primarily controls the free-surface response, with critical thresholds (e.g., $f\gtrsim 0.03$) identified via the free-surface displacement Z as markers for the onset of numerical stiffness. Horizontal eddy viscosity $N_h$ has a weak influence on depth-integrated transport over most of the tested range, whereas vertical eddy viscosity $N_v$ governs both transport magnitude and stability through the vertical diffusion constraint, acting as the primary bottleneck for computational efficiency. A stability map in the $(N_v,\Delta t,N_z)$ space is provided to delineate stable, marginal, and unstable regimes identifying an optimal vertical resolution of $N_z\approx 10$ for coastal applications. Grid resolution experiments quantify convergence trends and show that sensitivity increases with bathymetric complexity, revealing that bathymetric aliasing in multi-bar systems can lead to errors of up to 20% if gradients are under-resolved. Finally, a consistent set of diagnostic metrics is proposed for comparing 2D solutions with their vertically resolved counterparts, establishing a validity envelope where 2D models remain reliable versus regimes where explicit vertical shear resolution is mandatory. The results provide a practical roadmap for parameter selection, ensuring numerical robustness in complex, mechanically forced free-surface CFD applications. Full article