PdCoNi nanoparticles supported on nitrogen-doped porous carbon nanosheets for room temperature dehydrogenation of formic acid

The development of cost-effective heterogeneous catalysts for the dehydrogenation of formic acid (FA) is the key challenge for the commercialization of FA as a hydrogen-storage medium. Herein, PdCoNi nanoparticles (NPs) with different element ratios supported on N-doped carbon nanosheets (N-CN) were designed, which exhibit excellent catalytic dehydrogenation performance for FA. Compared with PdCoNi NPs loaded on the carbon nanosheets (CN), the introduction of pyrrolic N to CN induces the formation of ultrafine, monodispersed and amorphous Pd_0.6Co_0.2Ni_0.2 NPs with a size of 1.60 nm, which significantly increases the number of active sites and the instant contact between FA and catalysts. The as-prepared Pd_0.6Co_0.2Ni_0.2/N-CN catalyst shows more than 99% conversion and 100% H₂ selectivity at room temperature, with a record-high initial turnover frequency (TOF_initial) of 1249.0 h⁻¹ among non-noble containing Pd-based catalysts, which demonstrates the high potential of Pd_0.6Co_0.2Ni_0.2/N-CN as a practical catalyst for the hydrogen generation from FA.     

Investigation of response of metro tunnels due to adjacent large excavation and protective measures in soft soils

The inevitable influence of large excavation in soft soils on nearby tunnels is of great concern in practice. In this paper, the influence of a nearby large excavation on existing metro tunnels of the Ningbo Metro Line 1 in sensitive soft soils is investigated and presented. Considerable displacement in the left tunnel closer to the excavation induced by the nearby excavation was revealed by field monitoring. Visible cracks and leakages were observed in left tunnel linings. Three dimensional numerical simulations are conducted to investigate the responses of the ground and left tunnel due to the adjacent excavation. The development of bending moment and displacement of the left tunnel during different construction stages of the nearby excavation is obtained. Then the interaction mechanism between the nearby excavation, surrounding soils and existing twin tunnels is investigated, which is of significance to the interpretation of the influence of the nearby excavation on the existing twin tunnels. Several protective measures for alleviating the influence of adjacent excavation on left tunnel are studied, including divided excavation, soil improvement and a cut-off wall. It is found that the left tunnel is influenced to varying degrees during different construction stages and the time effect is distinct for this large excavation in soft soils, which would be suggestive to engineers to pay more attention to the protection of adjacent tunnel during the crucial construction stages. The bending moment and displacement of the left tunnel is strongly related to the unloading effects and displacement of surrounding soils, which can be alleviated by means of proper improvement of excavation sequence. Comparatively, longitudinally divided excavation is more effective in protecting the left tunnel than soil improvement or a cut-off wall. This study is of certain reference value for protecting metro tunnels adjacent excavation in soft soils.     

Effects of europium content on structures and luminescence properties of tunable light-emitting silicon oxynitride phosphors

A series of europium (Eu)-activated silicon oxynitride samples with various atomic ratios x of Eu/Si from 0.001 to 0.057 was prepared by employing the polymer-derived method with polycarbosilane and Eu acetylacetonate as starting materials. Chemical compositions, phase structures, morphologies, and luminescence properties of the samples were investigated. It was found that all samples contained a dominated β-Si₃N₄-like phase, and had emission spectra with two peaks. The emission colors of the samples under near-UV excitation were tunable from blue to white, and then to yellow as x in the samples increased from 0.009 to 0.030, and then to 0.057. The white emitting sample with x = 0.030 was in the β-Si₃N₄-like single phase with its particles being single-crystallized in two space groups P6₃ and P6₃/m. Eu²⁺ ions located at interstitial sites of lattices and were coordinated by nine N/O atoms with different average bond lengths for the two space groups. A discussion was given to attribute the difference in the lattice environments for Eu²⁺ ions in two space groups P6₃ and P6₃/m to the appearance of two emission peaks at the lower (597 nm) and higher (454 nm) energy levels for the sample with x = 0.030.     

A novel evolutionary-negative correlated mixture of experts model in tourism demand estimation

Mixtures of experts (ME) model are widely used in many different areas as a recognized ensemble learning approach to account for nonlinearities and other complexities in the data, such as time series estimation. With the aim of developing an accurate tourism demand time series estimation model, a mixture of experts model called LSPME (Lag Space Projected ME) is presented by combining ideas from subspace projection methods and negative correlation learning (NCL). The LSPME uses a new cluster-based lag space projection (CLSP) method to automatically obtain input space to train each expert focused on the difficult instances at each step of the boosting approach. For training experts of the LSPME, a new NCL algorithm called Sequential Evolutionary NCL algorithm (SENCL) is proposed that uses a moving average for the correlation penalty term in the error function of each expert to measure the error correlation between it and its previous experts. The LSPME model was compared with other ensemble models using monthly tourist arrivals to Japan from four markets: The United States, United Kingdom, Hong Kong and Taiwan. The experimental results show that the estimation accuracy of the proposed LSPME model is significantly better than the other ensemble models and can be considered to be a promising alternative for time series estimation problems.     

Wave climate analysis for the design of wave energy harvesters in the Mediterranean Sea

The objective of this paper is to provide a synthetic tool for determining expeditiously the wave climate conditions in several areas of the Mediterranean Sea. In the open literature, several authors have already conducted this specific analysis also for the area under examination in this paper. However, the need of discussing aspects strictly related to the design of wave energy harvesters is still relevant. Therefore, considering the variety of devices and the amount of information needed for conducting both an energy-wise optimization and a structural reliability assessment, a holistic view on the topic is provided. Specifically, the paper elucidates the theoretical aspects involved in the estimation of wave energy statistics and in the calculation of relevant return values. Next, it provides synthetic data representing the mean wave power and the return value of extreme events in several coastal areas of the Mediterranean Sea. In this regard, the paper complements information available in the open literature by discussing the influence of the directional pattern of the sea states in the determination of sea state statistics as well as in the design of a wave energy harvester.     

Oscillating-water-column wave energy converters and air turbines: A review

The ocean waves are an important renewable energy resource that, if extensively exploited, may contribute significantly to the electrical energy supply of countries with coasts facing the sea. A wide variety of technologies has been proposed, studied, and in some cases tested at full size in real ocean conditions. Oscillating-water-column (OWC) devices, of fixed structure or floating, are an important class of wave energy devices. A large part of wave energy converter prototypes deployed so far into the sea are of OWC type. In an OWC, there is a fixed or floating hollow structure, open to the sea below the water surface, that traps air above the inner free-surface. Wave action alternately compresses and decompresses the trapped air which is forced to flow through a turbine coupled to a generator. The paper presents a comprehensive review of OWC technologies and air turbines. This is followed by a survey of theoretical, numerical and experimental modelling techniques of OWC converters. Reactive phase control and phase control by latching are important issues that are addressed, together with turbine rotational speed control.     

Investigations and model validation of a ground-coupled heat pump for the combination with solar collectors

The operation of ground-coupled heat pumps in combination with solar collectors requires comprising knowledge of the heat pump behavior under non-standard conditions. Especially higher temperatures and varying flow rates in comparison to non-solar systems have to be taken into account. Furthermore the dynamic behavior becomes more important.At ISFH, steady-state and dynamic tests of a typical brine/water heat pump have been carried out in order to analyze its behavior under varying operation conditions. It has been shown, that rising source temperatures do only significantly increase the coefficient of performance (COP), if the source temperature is below 10–20 °C, depending on the temperature lift between source and sink. The flow rate, which has been varied both on the source and the sink side, only showed a minor influence on the exergetic efficiency. Additionally a heat pump model for TRNSYS has been validated under non-standard conditions. The results are assessed by means of TRNSYS simulations.     

An intelligence-based route choice model for pedestrian flow in a transportation station

This study proposes a method that uses an artificial neural network (ANN) to mimic human decision-making about route choice in a crowded transportation station. Although ANN models have been developed rapidly and widely adopted in various fields in the last three decades, their application to predict human decision-making in pedestrian flows is limited, because the video clip technology used to collect pedestrian movement data in crowded conditions is still primitive. Data collection must be carried out manually or semi-manually, which requires extensive resources and is time consuming. This study adopts a semi-manual approach to extract data from video clips to capture the route choice behaviour of travellers, and then applies an ANN to mimic such decision-making. A prediction accuracy of 86% (ANN model with ensemble approach) is achieved, which demonstrates the feasibility of applying the ANN approach to decision-making in pedestrian flows.