Preparation of Pt/Ce–Zr–Y mixed oxide/anodized aluminium oxide catalysts for hydrogen passive autocatalytic recombination

The use of a Pt-based catalyst was evaluated for autocatalytic hydrogen recombination. The Pt was supported on a mixture of Ce-, Zr- and Y-oxides (CZY) to yield nanosized Pt particles. The Pt/CZY/AAO catalyst was then prepared by the spray-deposition of the Pt/CZY intermediate onto an anodized aluminium oxide (AAO) layer on a metallic aluminum core. The Pt/CZY/AAO catalyst (3 × 1 cm) was evaluated for hydrogen combustion (1–8 vol% hydrogen in the air) in a recombiner section testing station. The thermal distribution throughout the catalyst surface was investigated using an infrared camera. The maximum temperature gradient (ΔT) for the examined hydrogen concentrations did not exceed 36 °C. The Pt/CZY/AAO catalyst was also evaluated for prolonged hydrogen combustion duration to assess its durability. An average combustion temperature of 239.0 ± 10.0 °C was maintained for 53 days of catalytic hydrogen combustion, suggesting that there was limited, or no, catalyst deactivation. Finally, a Pt/CZY/AAO catalytic plate (14.0 × 4.5 cm) was prepared to investigate the thermal distribution. An average surface temperature of 212.5 °C and a maximum ΔT of 5.4 °C was obtained throughout the catalyst surface at a 3 vol% hydrogen concentration.     

Dielectric,ferroelectric, and piezoelectric properties of lead-free Ba0.95Ca0.05Ti1-xZrxO3 ceramics

Abstract

Ba_0.95Ca_0.05Ti_1-xZr_xO₃ (BCTZO) ceramics were prepared by a solid state reaction method. The samples were characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM) and X-ray absorption near edge structure (XANES). The ceramics exhibit a pure perovskite structure. The average grain size gradually decreases with increasing Zr concentration. XANES results indicate that the intensities of pre-edge peaks dropped with increasing Zr concentration. The BCTZO ceramic of x?=?0.05 has the optimum electrical properties with the maximum dielectric constant (ε'_m), remanent polarization (2P_r), coercive electric field (2E_c) and piezoelectric charge constant (d₃₃) of 7,244, 12.54 (μC/cm²), 5.29 (kV/cm) and 288 (pC/N), respectively.     

Neutral axis depth and moment redistribution in FRP and steel reinforced concrete continuous beams

The neutral axis depth is considered the best parameter for quantifying the moment redistribution in continuous concrete beams, as exemplified in various design codes worldwide. It is therefore important to well understand the variation of neutral axis depth against moment redistribution. This paper describes a theoretical investigation into the neutral axis depth and moment redistribution in concrete beams reinforced with fibre reinforced polymer (FRP) and steel bars. A finite element model has been developed. The model predictions are in favourable agreement with experimental results. Three types of reinforcement are considered, namely, glass fibre, carbon fibre and steel. Various levels of reinforcement ratio are used for a parametric evaluation. The results indicate that FRP reinforced concrete continuous beams exhibit significantly different response characteristics regarding the moment redistribution and variation of neutral axis depth from those of steel reinforced ones. In addition, it is found that the code recommendations are generally unsafe for calculating the permissible moment redistribution in FRP reinforced concrete beams, but the neglect of redistribution in such beams may be overconservative.     

A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems

Airline disruptions incurred huge cost for airlines and serious inconvenience for travelers. In this paper, we study the integrated aircraft and crew schedule recovery problem. A two stage heuristic algorithm for the integrated recovery problem is proposed. In the first stage, the integrated aircraft recovery and flight-rescheduling model with partial crew consideration is built. This model is based on the traditional multi-commodity network model for the aircraft schedule recovery problem. The objective of this model also includes minimization of the original crew connection disruption. In the second stage, the integrated crew schedule recovery and flight re-scheduling model with partial aircraft consideration is built. We proposed a new multi-commodity model for the crew schedule recovery. The main advantage of such model is that it is much more efficient to integrate the flight-scheduling and aircraft consideration. New constraints are incorporated to guarantee that the aircraft connections generated in the stage 1 are still feasible. Two stages are run iteratively until no improvement can be achieved. Experimental results show that our method can provide better recovery solutions compared with the benchmark algorithms.     

Trend Analysis and Spatial Prediction of Groundwater Levels Using Time Series Forecasting and a Novel Spatio-Temporal Method

Water Resources Management - Overexploitation of groundwater in the Malayer Plain has resulted in a continuous decline of groundwater levels over recent years with associated risks to water...     

Price ceilings as focal points to reach price uniformity: Evidence from a Chinese gasoline market

This paper studies the price uniformity in the Chinese gasoline market, using station-level data of Hohhot city, Inner Mongolia. We first document that the mode prices of the gasoline stations are consistent with the price ceilings set by the government, implying that the price ceiling regulation in the Chinese gasoline market may serve as a focal point for the gasoline stations to reach price uniformity. We corroborate the focal point hypothesis by providing evidence showing that some stations would “jump” to the ceilings as their prices approach the ceilings. Also, we find that local market structure, distance between stations, station capacity, market characteristics, and past pricing behavior could affect the probability of gas stations to price at the ceilings. Moreover, a higher price ceiling would reduce the probability that stations reach price uniformity. Our results provide another piece of evidence to the literature regarding the unintended effect of price ceiling regulation.     

Monthly Streamflow Forecasting Using Convolutional Neural Network

Monthly streamflow forecasting is vital for managing water resources. Recently, numerous studies have explored and evidenced the potential of artificial intelligence (AI) models in hydrological forecasting. In this study, the feasibility of the convolutional neural network (CNN), a deep learning method, is explored for monthly streamflow forecasting. CNN can automatically extract critical features from numerous inputs with its convolution–pooling mechanism, which is a distinct advantage compared with other AI models. Hydrological and large-scale atmospheric circulation variables, including rainfall, streamflow, and atmospheric circulation factors are used to establish models and forecast streamflow for Huanren Reservoir and Xiangjiaba Hydropower Station, China. The artificial neural network (ANN) and extreme learning machine (ELM) with inputs identified based on cross-correlation and mutual information analyses are established for comparative analyses. The performances of these models are assessed with several statistical metrics and graphical evaluation methods. The results show that CNN outperforms ANN and ELM in all statistical measures. Moreover, CNN shows better stability in forecasting accuracy.

     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.