Thermomechanical stability and inelastic energy dissipation as durability criteria for fuel cell gas diffusion media with pre-assembly effects

In this article, pre-assembly hot-press pressure and thermal expansion effects in gas-diffusion layers (GDLs) are addressed to explore the practicalities of the constitutive model reported in the companion article. A facile technique is proposed to include deformation history dependent residual strain effects. The model is implemented in the numerical environment and compared with widely followed conventional models such as isotropic and orthotropic material models. With the normal and accelerated thermal expansion effects no significant variation in stresses or strains is reported with the compressible GDL model in contrast to the conventional incompressible form of the GDL model. The present work identifies the critical differences with advanced and extended variants of the model along with conventional GDL material models in terms of planar stress/strain distribution and the membrane response. Finally, the model is simulated for micro-cyclic stress loads of varying amplitudes that imitate the real working conditions of fuel cell. The inelastic energy dissipation in GDLs is predicted using the proposed model, which is utilized further to distinguish the safe (elastic) and unsafe (inelastic shakedown) operating limits. The inelastic collapse of GDLs is shown to be a active function of high amplitude micro-cyclic load with high initial clamping load.     

Analysis of suitability of TPP ash-slag waste as materials for hydrogen fuel storage

The current trends in energy were described, the main of which is the use of alternative energy sources, especially hydrogen. The most common methods of hydrogen accumulation were proposed: accumulation of compressed gaseous hydrogen in high-pressure tanks; accumulation of liquid hydrogen in cryogenic tanks; storing hydrogen in a chemically bound state; accumulation of gaseous hydrogen in carriers with a high specific surface area. Based on the combination of advantages and disadvantages, the most promising methods of accumulation were selected: storage of liquid hydrogen and storage of hydrogen in carriers with a high specific surface area. The main requirement for materials for hydrogen storage by these methods was revealed – a high specific surface area. Prospects for the development of waste-free low-emission technologies due to the recycling of secondary raw materials and the development of low-temperature technologies for the synthesis of functional and structural materials were substantiated. The applicability of large-scale ash and slag waste from coal-fired thermal power plants as a raw material for obtaining materials by low-temperature technologies was shown. The traditional ways of using ash and slag waste as a raw material, active additive and filler in the production of cements were described. Modern technologies for the production of innovative materials with a unique set of properties were presented, namely carbon nanotubes, silica aerogel and geopolymer materials. The prospect of using geopolymer matrices as a precursor for the synthesis of a number of materials was described; the most promising type of materials was selected – geopolymer foams, which are mainly used as sorbents for purifying liquids and gases or accumulating target products, as well as heat-insulating materials. The possibility of obtaining products of any shape and size on the basis of geopolymer matrices without high-temperature processing was shown. The special efficiency of the development of the technology of porous granules and powders obtained from a geopolymer precursor using various methods was substantiated. The obtained granules can be used in the following hydrogen storage technologies: direct accumulation of hydrogen in porous granules; creation of insulating layers for liquid hydrogen storage units.     

Techno-economic feasibility assessment of sorption enhanced gasification of municipal solid waste for hydrogen production

Waste-to-fuel coupled with carbon capture and storage is forecasted to be an effective way to mitigate the greenhouse gas emissions, reduce the waste sent to landfill and, simultaneously, reduce the dependence of fossil fuels. This study evaluated the techno-economic feasibility of sorption enhanced gasification, which involves in-situ CO₂ capture, and benchmarked it with the conventional steam gasification of municipal solid waste for H₂ production. The impact of a gate fee and tax levied on the fossil CO₂ emissions in economic feasibility was assessed. The results showed that the hydrogen production was enhanced in sorption enhanced gasification, that achieved an optimum H₂ production efficiency of 48.7% (T = 650 °C and SBR = 1.8). This was 1.0% points higher than that of the conventional steam gasification (T = 900 °C and SBR = 1.2). However, the total efficiency, which accounts for H₂ production and net power output, for sorption enhanced gasification was estimated to be 49.3% (T = 650 °C and SBR = 1.8). This was 4.4% points lower than the figure estimated for the conventional gasification (T = 900 °C and SBR = 1.2). The economic performance assessment showed that the sorption enhanced gasification will result in a significantly higher levelised cost of hydrogen (5.0 €/kg) compared to that estimated for conventional steam gasification (2.7 €/kg). The levelised cost of hydrogen can be reduced to 4.5 €/kg on an introduction of the gate fee of 40.0 €/t_MSW. The cost of CO₂ avoided was estimated to be 114.9 €/tCO₂ (no gate fee and tax levied). However, this value can be reduced to 90.1 €/tCO₂ with the introduction of an emission allowance price of 39.6 €/tCO₂. Despite better environmental performance, the capital cost of sorption enhanced gasification needs to be reduced for this technology to become competitive with mature gasification technologies.     

互联网时代下的学校图书管理信息化建设

如何在互联网时代打造一个信息化的管理模式,已经成为广大学校图书管理发展过程中亟待处理的问题。文章就互联网时代下的高职图书管理信息化建设进行了详细探讨,以期能够给广大同仁提供一些借鉴参考,共同为图书管理工作的现代化改革和发展贡献力量。     

Catalytic combustion synthesis of CNTs/MgO composite powders and the influences on the thermal shock resistance of low-carbon Al2O3–C refractories

Using MgC₂O₄, Mg powders as raw materials and Ni(NO₃)₂?6H₂O as a catalyst, CNTs/MgO composite powders were prepared by a catalytic combustion synthesis method. The CNTs/MgO composite powders were characterized by XRD, Raman spectroscopy, FESEM/EDS and HRTEM. The effects of catalyst content on the degree of graphitization and aspect ratio of the CNTs in composite powders were investigated. Moreover, the thermal shock resistance of low-carbon Al₂O₃–C refractories after adding the composite powder was investigated. The results indicated that the CNTs prepared with 1 wt% Ni(NO₃)₂?6H₂O addition had a higher degree of graphitization and aspect ratio. In particular, the aspect ratio could reach approximately 200. The growth mechanism of hollow bamboo-like CNTs in the composite powders was proven to be a V-L-S mechanism. The thermal shock resistance of Al₂O₃–C samples could be improved significantly after adding CNTs/MgO composite powders. In particular, compared with CM0, the residual strength ratio of Al₂O₃–C samples with added 2.5 wt% composite powders could be increased 63.9%.     

Investigation of liquid water heterogeneities in large area proton exchange membrane fuel cells using a Darcy two-phase flow model in a multiphysics code

Proper management of the liquid water and heat produced in proton exchange membrane (PEM) fuel cells remains crucial to increase both its performance and durability. In this study, a two-phase flow and multicomponent model, called two-fluid model, is developed in the commercial COMSOL Multiphysics® software to investigate the liquid water heterogeneities in large area PEM fuel cells, considering the real flow fields in the bipolar plate. A macroscopic pseudo-3D multi-layers approach has been chosen and generalized Darcy's relation is used both in the membrane-electrode assembly (MEA) and in the channel. The model considers two-phase flow and gas convection and diffusion coupled with electrochemistry and water transport through the membrane. The numerical results are compared to one-fluid model results and liquid water measurements obtained by neutron imaging for several operating conditions. Finally, according to the good agreement between the two-fluid and experimentation results, the numerical water distribution is examined in each component of the cell, exhibiting very heterogeneous water thickness over the cell surface.     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

The effect of alkali metal oxide on the properties of borosilicate fireproof glass: Structure,thermal properties,viscosity, chemical stability

The purpose of the current work was to research the effect of alkali metal oxide on the structure, thermal properties, viscosity and chemical stability in the glass system (R₂O–CaO–B₂O₃–SiO₂) systematically. Because the glass would emulsify when Li₂O was added to the glass batch, this article did not discuss Li₂O. The results showed that when the amount of Na₂O was less than 4 mol.%, there was a higher interconnectivity of borate and silicate sub-networks in glass, as more mixed Si–O–B bonds were present in glass. The glass samples exhibited excellent thermal properties and chemical stabilities. As the amount of Na₂O exceeded 4 mol.%, the interconnectivity of borate and silicate sub-networks was weakened. The thermal properties and chemical stabilities of the glass samples were reduced. The connectivity of the silicate sub-network was weakened slightly as the Na/K ratio varied, and the coefficient of thermal expansion (CTE) of the glass samples gradually increased, and the resistance to thermal shock (RTS) value gradually decreased. Moreover, the viscosity of the glass samples decreased with the ratio of Na/Si and Na/K increased.     

Use of La2O3 with 8YSZ as thermal barrier coating and its effect on thermal cycle behavior,microstructure, mechanical properties and performance of diesel engine operated by hydrogen-algae biodiesel blend

In this present work, the effect of lanthanum oxides (La₂O₃) on the thermal cycle behavior of TBC coatings and mechanical properties such as adhesion strength and microhardness of 8% Yttria Stabilized Zirconia (8YSZ) TBCs were investigated. CoNiCrAlY and aluminium alloy (Al–13%Si) were used as bond coat and substrate materials. 8YSZ and different wt % of La₂O₃ (10, 20, and 30%) top coatings were applied using the atmospheric plasma spray (APS) method. The thermal cycling test for TBC coated samples were conducted at 800 °C in the electric furnace. The XRD pattern shows that the La₂O₃ doped 8YSZ material transformed to cubic pyrochloric structured La₂Zr₂O₇ during thermal cycling. Further, the Taguchi-based grey relation analysis (GRA) method was applied to optimize the TBC coating parameters to achieve better mechanical properties such as adhesion strength and microhardness. And the optimized La₂O₃/8YSZ TBC coating was coated on CRDI engine combustion chamber components. The engine was tested with microalgae biodiesel and hydrogen, and the results were promising for the TBC-coated engine. The engine performance increased while using La₂O₃/8YSZ coated components, and the emissions from engine exhaust gas such as CO, HC, and smoke reduced considerably. It was found that there was no separation crack and spallation of the coating layer in the microstructure. Ultimately, the microstructural analysis of the optimized TBC coated piston sample after 50 h of running in the diesel engine confirmed that the developed coating had a superior thermal insulation effect and longer life.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.