Non-proportional multiaxial stress states deserve more explicit consideration in vibration fatigue, as they naturally arise in this context. Under broadband vibration loading, modal superposition gives rise to phase-lagged stress interaction, rotating stress directions, and complex in-plane shear trajectories, which in vibration fatigue are neither adequately described in their statistical characteristics nor consistently reflected in corresponding fatigue criteria. This paper develops a phase-aware statistical framework for the description of such stress states under vibration loading. A central contribution is the introduction of a complex-valued covariance matrix, which extends the classical second-order description by the full phase-bearing characteristics between stress components. Using candidate-plane stresses as application context, the framework enables the characterization of the correlation structure and trajectory class of non-proportional stress states. To demonstrate its practical relevance, the Findley criterion is adopted as a representative critical-plane criterion for random-vibration and high-cycle-fatigue applications. Based on the proposed descriptors, an efficient screening concept is formulated to identify Findley-relevant plane orientations in large-scale FE models, extending the popular maximum-variance criterion toward non-proportional stress states. Calibration is performed by Monte-Carlo simulation and followed by validation on a broadband-excited multiaxial FE model. The paper contributes to raising awareness of the importance of non-proportional stress states in vibration fatigue, to improving their statistical description, and to implementing these advances in practical fatigue assessment.
GMAW hardfacing with consumables containing tungsten carbides is limited by the dissolution of the carbide particles in the droplet and subsequently in the weld pool. This study investigates the dissolution behavior of unmodified, commercially used eutectoid WC/W2C carbides (WSC) and carburized variants (cWSC) featuring a stabilizing WC surface layer under an energy-reduced, controlled short-circuit GMAW hardfacing process. Thermal exposure is considered as two consecutive stages involving dissolution in the molten droplet and diffusion-dominated dissolution during weld-pool residence. Transient electrical process data and weld-pool surface temperature measurements are used to determine the specific droplet enthalpy and the relevant temperature–time regimes. An analytical model based on the shrinking-core concept is developed to quantify carbide dissolution as a function of particle size and cooling time and is validated experimentally by statistical particle-size analysis and particle-counting methods. The results reveal a pronounced size dependence of dissolution, with particles smaller than approximately 80 µm undergoing extensive degradation largely independent of heat input. Carburized carbides exhibit significantly reduced dissolution compared to conventional eutectoid carbides, retaining an intact WC surface layer throughout processing. Furthermore, dissolution is markedly enhanced in iron-based melts compared to iron-nickel systems, indicating that Fe-Ni matrices in combination with carburized carbides are preferable for minimizing carbide degradation in GMAW hardfacing applications.
Aviation’s climate impact continues to grow, with little progress toward emission reductions aligned with global targets. While technological advances attract attention, operational efficiency across aircraft, airlines, airports, city pairs, and regions remains underexplored. Here we assess carbon dioxide efficiency for 27.5 million flights between 26,156 city pairs in 2023, using data from Airline Data, International Civil Aviation Organization, International Air Transport Association. Results show wide variation: 32–890 gram carbon dioxide per revenue passenger kilometres across routes and 60–360 gram carbon dioxide per revenue passenger kilometre across aircraft models. Efficiency differs by region and is lowest in Africa, Australia, and Norway, and highest in Brazil, India, and Southeast Asia. Operating all routes at their demonstrated optimum could cut emissions by 10.7
This article proposes a mission-profile-based sizing methodology for DC-link capacitors in eVTOL propulsion inverters. While DC-link capacitors contribute significantly to converter volume, traditional design relies on conservative worst-case operating points, leading to significant oversizing. To address this, an electro-thermal modelling approach is developed to evaluate capacitor lifetime based on core temperature fluctuations throughout a dynamic flight profile. The methodology accounts for thermal properties, modulation strategies, and the effects of fault-tolerant operation. Although the method is applicable to various inverter topologies and capacitor technologies, the three-level T-type (3L-TT) fault-tolerant converter benefits most, as demonstrated by an exemplary design achieving a 37.5
Effective urban traffic signal control in large-scale networks remains challenging due to complex interdependencies among intersections and unpredictable fluctuations in traffic conditions. To address these challenges, this paper proposes a novel Adaptive Hybrid Multi-Objective Optimization Algorithm with Reinforcement Learning (AHMOA-RL) for robust and scalable traffic signal management. The core innovation of AHMOA-RL lies in a hierarchical optimization framework that efficiently decomposes the problem into global region-level coordination and local intersection-level refinements, significantly reducing computational complexity while ensuring synchronized control across extensive urban networks. A Q-learning agent dynamically selects among multiple evolutionary operators-Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, and Local Search-to strategically balance exploration and exploitation during optimization. Additionally, a memory-based evaluation mechanism leveraging historical data is integrated to smooth transient traffic anomalies and provide stable performance estimates. Extensive simulations on large-scale city networks inspired by Manhattan, Paris, S & atilde;o Paulo, and Istanbul demonstrate that AHMOA-RL consistently outperforms state-of-the-art methods, achieving substantial reductions in average vehicle delays, improved network stability, and enhanced robustness under diverse traffic conditions. The algorithm's compact Pareto fronts and superior convergence characteristics validate its effectiveness for practical deployment in complex urban environments.
