Effect of microporous layer structural parameters on heat and mass transfer in proton exchange membrane fuel cells

Proton exchange membrane fuel cells offer promising clean energy solutions for various applications. However, their performance relies heavily on the properties of the microporous layer, which plays a crucial role in transporting and distributing the components in the fuel cell. To date, the potential for optimising the microporous layer...

Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits

Multi-objective Stochastic Linear bandit (MOSLB) plays a critical role in the sequential decision-making paradigm, however, most existing methods focus on the Pareto dominance among different objectives without considering any priority. In this paper, we study bandit algorithms under mixed Pareto-lexicographic orders, which can reflect...

Coordination and Optimization Control Framework for Vessels Platooning in Inland Waterborne Transportation System

Vessels sailing in a single platoon could reduce resistance from the perspective of the whole platoon and the individual vessel, and contribute to improving energy benefits. Moreover, transportation energy costs and traffic efficiency are essential indicators for measuring waterborne transportation systems. We attempt to minimize...

Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...

Experimental Simulation of Larger Quantum Circuits with Fewer Superconducting Qubits

Although near-term quantum computing devices are still limited by the quantity and quality of qubits in the so-called NISQ era, quantum computational advantage has been experimentally demonstrated. Moreover, hybrid architectures of quantum and classical computing have become the main paradigm for exhibiting NISQ applications, where low-depth...

Synchronization of power systems under stochastic disturbances

The synchronization of power generators is an important condition for the proper functioning of a power system, in which the fluctuations in frequency and the phase angle differences between the generators are sufficiently small when subjected to stochastic disturbances. Serious fluctuations can prompt desynchronization, which may lead to...

Synchronization of Coupled Phase Oscillators with Stochastic Disturbances and the Cycle Space of the Graph

The synchronization stability of a complex network system of coupled phase oscillators is discussed. In case the network is affected by disturbances, a stochastic linearized system of the coupled phase oscillators may be used to determine the fluctuations of phase differences in the lines between the nodes and to identify the vulnerable lines...

Autogenous deformation induced- stress evolution in high-volume GGBFS concrete: Macro-scale behavior and micro-scale origin

This study aims to experimentally investigate the autogenous deformation and the stress evolution in restrained high-volume ground granulated blast furnace slag (GGBFS) concrete. The Temperature Stress Testing Machine (TSTM) and Autogenous Deformation Testing Machine (ADTM) were used to study the macro-scale autogenous deformation and stress...

Evaluation of the fatigue properties for the long-term service asphalt pavement using the semi-circular bending tests and stereo digital image correlation technique

Reliable assessment of the fatigue resistance of asphalt pavement with a long-term service is critically crucial for the rational formulation of original pavement utilization strategies in reconstruction and expansion projects. Currently, the pavement performance evaluation indicators are mainly used to guide pavement preventive maintenance,...

Morphodynamic changes in the Yangtze Estuary under the impact of the Three Gorges Dam, estuarine engineering interventions and climate-induced sea level rise

The estuarine turbidity maximum (ETM) in the Yangtze Estuary Delta (YED) is muddy by definition and lacks bottom undulations. However, since 2013, a remarkable change has occurred in the YED. Recent images detected by a multibeam echosounder system, SeaBat 7125, for the first time have confirmed widespread regions of subaqueous dunes in the...

Random forest incorporating ab-initio calculations for corrosion rate prediction with small sample Al alloys data

Corrosion jeopardizes the materials longevity and engineering safety, hence the corrosion rate needs to be forecasted so as to better guide materials selection. Although field exposure experiments are dependable, the prohibitive cost and their time-consuming nature make it difficult to obtain large dataset for machine learning. Here, we...

Towards understanding and prediction of atmospheric corrosion of an Fe/Cu corrosion sensor via machine learning

The atmospheric corrosion of carbon steel was monitored by a Fe/Cu type galvanic corrosion sensor for 34 days. Using a random forest (RF)-based machine learning approach, the impacts of relative humidity, temperature and rainfall were identified to be higher than those of airborne particles, sulfur dioxide, nitrogen dioxide, carbon monoxide...

Revealing the Impact of Space-Charge Layers on the Li-Ion Transport in All-Solid-State Batteries

The influence of space-charge layers on the ionic charge transport over cathode-solid electrolyte interfaces in all-solid-state batteries remains unclear because of the difficulty to unravel it from other contributions to the ion transport over the interfaces. Here, we reveal the effect of the space-charge layers by systematically tuning the...

CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models

CGILS—the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)—investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow...

Marine low cloud sensitivity to an idealized climate change: The CGILS LES intercomparison

Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large-eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs) under well-mixed stratocumulus, cool SSTs under...