Evaluation of cut cell cartesian method for simulation of a hook and claw type hydrogen pump

Hook and claw pumps are used for recirculation of excess hydrogen in fuel cells. Optimization of the pump design is essential. Computational Fluid Dynamic (CFD) is an effective method for performance optimization. However, it is difficult to conduct CFD simulation because of the sharp cusp of the rotor profile. Cut cell Cartesian mesh could be the solution to handle this complex and moving geometries. The aim of this paper is to evaluate ANSYS Forte for hook and claw pumps. Firstly, the conservation accuracy of the cut cell cartesian mesh is verified using an adiabatic piston cylinder case. Then, simulation results of hook and claw type pump are compared with experimental data. Finally, simulation results of air and hydrogen are compared. The results show that the CFD simulation of hook and claw pumps using cut cell cartesian mesh could provide an efficient and effective approach for the optimization of the system.     

Analysis and proposition of limiting current density measurement protocol

Limiting current density at different temperatures, backpressures, and balance gases can be used to separate molecular diffusion resistance, Knudsen diffusion resistance and local transport resistance of membrane electrode assembly (MEA). However, the measurement of limiting current density has no unified protocol. The diverse choices in the literature, either in the control of current or voltage or in the atmosphere like relative humidity and O₂ concentrations, make it difficult to compare the results and identify the true bottleneck hindering the mass transport. In this work, the current-voltage curves obtained by current scanning/stepping and voltage scanning/stepping methods under dilute O₂ of different concentrations and a wide range of relative humidity were measured and analyzed systematically. It is found that the voltage stepping method is superior to the other three ways of control for the reliable determination of the limiting current density. Aided with simultaneous electrochemical impedance spectroscopy measurement, the limiting current density can be determined with pinpoint accuracy. When the limiting current density is just used to qualitatively evaluate different MEA, the voltage scanning method can be used instead for its high time efficiency. The selection of the atmosphere also plays an important role in suppressing the distortion from excessive water and reducing the spurious contribution from proton conduction resistance. It is found that O₂ concentrations at 0.5 vol% and relative humidity at 90% can give the best estimation of O₂ transport resistance in membrane electrode assembly.     

Learn decision trees with deep visual primitives

In this paper, we strive to propose a self-interpretable framework, termed PrimitiveTree, that incorporates deep visual primitives condensed from deep features with a conventional decision tree, bridging the gap between deep features extracted from deep neural networks (DNNs) and trees’ transparent decision-making processes. Specifically, we utilize a codebook, which embeds the continuous deep features into a finite discrete space (deep visual primitives) to distill the most common semantic information. The decision tree adopts the spatial location information and the mapped primitives to present the decision-making process of the deep features in a tree hierarchy. Moreover, the trained interpretable PrimitiveTree can inversely explain the constituents of the deep features, highlighting the most critical and semantic-rich image patches attributing to the final predictions of the given DNN. Extensive experiments and visualization results validate the effectiveness and interpretability of our method.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

LBM investigation of a Cu-water nanofluid over various configurations of pipes in the mixed convection flow

Increasing the heat capacity of heat exchangers is a crucial need for modern devices. The thermal conductivity of the usual fluids and the Nusselt (Nu) number of flows containing such fluids are two bottlenecks in the way of increasing heat delivery in the heat exchangers. For this reason, nanofluids have been introduced. The effect of utilizing a Cu-water nanofluid as a coolant of two hot pipes in a square cavity is investigated numerically with a two-component lattice Boltzmann method. The volume fraction of nanoparticles is assumed to be constant (0.03) while the Richardson (Ri) number varies from 0.02 to 20. Results show that the effectiveness of nanoparticles is better observed in the natural convection mode. However, sedimentation is also very probable at high Ri numbers, which significantly reduces the effectiveness of the nanoparticles. Configurations which produce a natural convection stream similar to the forced convection one as well as the configurations with high spacing and hence, low heat stream interactions, are the best choices for a uniform heat rate from the pipes.     

Stress wave propagation in adhesively bonded functionally graded cylinders: an improved model

This study presents an improved mathematical model to analyse the stress wave propagation in adhesively bonded functionally graded (FG) circular cylinders (butt joint) under an axial impulsive load. The volume fractions of the material constituents in the upper and lower cylinders were functionally tailored through the thickness of each cylinder using a power-law. The effective material properties of both cylinders, which are made of aluminum (Al) and silicon carbide (SiC), at any point were predicted by using the Mori–Tanaka homogenization scheme. In this improved model, the governing equations of the wave propagation include the spatial derivatives of local mechanical properties and were discretized by means of the finite difference method. The influence of these spatial derivatives and the compositional gradient exponent on the displacement and stress distributions of the joint was investigated. The material composition variations of both cylinders affected the displacement and stress fields whereas the compositional gradient exponent had a minor effect. The stress concentrations were alleviated in time, the displacement and stress distributions/variations around/along the upper and lower cylinder-adhesive interfaces were significantly affected by the adhesive layer. The spatial derivatives also affected the temporal histories of the displacement and stress components evaluated at the selected critical points of the upper cylinder, adhesive layer and lower cylinder. The consideration of the spatial local material derivatives provided a more accurate mathematical model of wave propagations through the graded layered structures.     

Review of electrospun hydrogel nanofiber system: Synthesis,Properties and Applications

Hydrogel-based nanofibers or vice versa are a relatively new class of nanomaterials, in which hydrogels are structured in nanofibrous form. Structure and size of the material directly governs its functionality, therefore, in hydrogel science, the nanofibrous form of hydrogels enables its usage in targeted applications. Hydrogel nanofiber system combines the desirable properties of both hydrogel and nanofiber like flexibility, soft consistency, elasticity, and biocompatibility due to high water content, large surface area to volume ratio, low density, small pore size and interconnected pores, high stiffness, tensile strength, and surface functionality. Swelling behavior is a critical property of hydrogels that is significantly increased in hydrogel nanofibers due to their small size. Electrospinning is the most popular method to fabricate “hydrogel nanofibers,” while other processes like self-assembly, solution blowing and template synthesis also exist. Merging the characteristics of both hydrogels and nanofibers in one system allows applications in drug delivery, tissue engineering, actuation, wound dressing, photoluminescence, light-addressable potentiometric sensor (LAPS), waterproof breathable membranes, and enzymatic immobilization. Treatment of wastewater, detection, and adsorption of metal ions are also emerging applications. In this review paper, we intend to summarize in detail about electrospun “hydrogel nanofiber” in relation to its synthesis, properties, and applications.     

Study on ice-melting performance of gradient gas diffusion layer in proton exchange membrane fuel cell

In this study, a three-dimensional model was established using the lattice Boltzmann method (LBM) to study the internal ice melting process of the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC). The single-point second-order curved boundary condition was adopted. The effects of GDL carbon fiber number, growth slope of the number of carbon fibers and carbon fiber diameter on ice melting were studied. The results were revealed that the temperature in the middle and lower part of the gradient distribution GDL is significantly higher than that of the no-gradient GDL. With the increase of the growth slope of the number of carbon fiber, the temperature and melting rate gradually increase, and the position of the solid-liquid interface gradually decreases. The decrease in the number of carbon fibers has a similar effect as the increase in the growth slope of the number of carbon fibers. In addition, as the diameter of the carbon fiber increases, the position of the solid-liquid interface gradually decreases first and then increases.     

A practical development of engineering simulation-assisted educational AR environments

Engineering simulations have opened several gates for today’s chemical engineers. They are powerful tools to provide technical content as physics-based numerical solvers. Augmented reality (AR) and virtual reality (VR), on the other hand, are already underway to digitize environments in many fields. The combination of AR/VR environments and simulations in engineering education has been attracting widespread interest. Literature has demonstrated a massive amount of digital educational environments in several contexts as being complementary to conventional educational methods. Nevertheless, hosting technical content produced by engineering simulations with educational AR/VR is still challenging and requires expertise from multiple disciplines throughout the technical development. Present work provides a facile and agile methodology for low-cost hardware but content-wise rich AR software development. Inspired by the Covid-19 pandemic, a case study is developed to teach chemical-engineering concepts using a liquid-soap synthesis process. Accordingly, we assess and conclude the digital development process to guide inexperienced developers for the digitalization of teaching content. The present contribution serves as an example of the power of integrating AR/VR with traditional engineering simulations for educational purposes. The digital tool developed in this work is shared in the online version.