Numerical simulation of water and heat transport in the cathode channel of a PEM fuel cell

Cathode channel of a PEM fuel cell is the critical domain for the transport of water and heat. In this study, a mathematical model of water and heat transport in the cathode channel is established by considering two-phase flow of water and air as well as the phase change between water and vapor. The transport process of the species of air is governed by the convection-diffusion equation. The VOSET (coupled volume-of-fluid and level set method) method is used to track the interface between air and water, and the phase equilibrium method of water and vapor is employed to calculate the mass transfer rate on the two-phase interface. The present model is validated against the results in the literature, then applied to investigate the characteristics of two-phase flow and heat transfer in the cathode channel. The results indicate that in the inlet section, water droplets experience three evolution stages: the growing stage, the coalescence stage and the generation stage of dispersed water drops. However, in the middle and outlet sections of the channel, there are only two stages: the growth of water droplets, and the formation of a water film. The mass transfer rate of phase change in the inlet section of the channel varies over time, exhibiting an initial increase, a decrease followed, and a stabilization finally, with the maximum and stable values of 1.78 × 10^?4 kg/s and 1.52 × 10^?4 kg/s for Part 1, respectively. In the middle and outlet sections, the mass transfer rate increase firstly and then keeps stable gradually. Furthermore, regarding the distribution of the temperature and vapor mass fraction in the channel, near the upper surface of the channel, the temperature and vapor mass fraction first change slightly (x < 0.03 m) and then rapidly decrease with fluctuations (x > 0.03 m). In the middle of the channel, the temperature and vapor mass fraction slowly decrease with fluctuation.     

Preparation and electrical conductivity of KTaO3-based proton conductor

KTaO₃ and KTa_0.9M_0.1O_3-α (M = Ti, Hf, Zr) were prepared by solid state reaction at 1330 °C for 2 h and characterized by x-ray diffraction. The AC impedance technique was used to analyze the sintered solid electrolytes in 1%H₂/Ar and dry air atmosphere. Among KTa_0.9M_0.1O_3-α (M = Ti, Hf, Zr), KTa_0.9Zr_0.1O_3-α displays the highest conductivity in 1%H₂/Ar atmosphere. The carriers transport numbers of solid electrolytes were measured by concentration cell method. The results show KTa_0.9Zr_0.1O_3-α is a pure proton conductor below 525 °C. Stability tests show that KTa_0.9Zr_0.1O_3-α has good chemical stability against CO₂ and H₂O.     

Lean production system design for fishing net manufacturing using lean principles and simulation optimization

Value stream mapping (VSM) is a useful tool for describing the manufacturing state, especially for distinguishing between those activities that add value and those that do not. It can help in eliminating non-value activities and reducing the work in process (WIP) and thereby increase the service level. This research follows the guidelines for designing future state VSM. These guidelines consist of five factors which can be changed simply, without any investment. These five factors are (1) production unit; (2) pacemaker process; (3) number of batches; (4) production sequence; and (5) supermarket size. The five factors are applied to a fishing net manufacturing system. Using experimental design and a simulation optimizing tool, the five factors are optimized. The results show that the future state maps can increase service level and reduce WIP by at least 29.41% and 33.92% respectively. For the present study, the lean principles are innovatively adopted in solving a fishing net manufacturing system which is not a well-addressed problem in literature. In light of the promising empirical results, the proposed methodologies are also readily applicable to similar industries.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

Biodegradability Study of the Biosurfactant Contained in a Crude Extract from Corn Steep Water

Over the last few years, the global biosurfactant market has raised due to the increasing awareness among consumers, for the use of biological or bio-based products. Because of their composition, it can be speculated that these are more biocompatible and more biodegradable than their chemical homologous. However, at the moment, no studies exist in the literature about the biodegradability of biosurfactants. In this work, a biosurfactant contained in a crude extract, obtained from a corn wet-milling industry stream that ferments spontaneously in the presence of lactic acid bacteria, was subjected to a biodegradation study, without addition of external microbial biomass, under different conditions of temperature (5–45 °C), biodegradation time (15–55 days), and pH (5–7). For that, a Box–Behnken factorial design was applied, which allowed to predict the percentage of biodegradation for the biosurfactant contained in the crude extract, between the range of the independent variables selected in the study, obtaining biodegradation values between 3 and 80%. The percentage of biodegradation for the biosurfactant was calculated based on the increase in the surface tension of samples of the crude extract. Furthermore, it was also possible to predict the variation in t_1/2 for the biosurfactant (time to achieve the 50% of biodegradation) under different conditions.     

Chloride migration in concrete with superabsorbent polymers

Superabsorbent polymers (SAP) can be used as a means for internal curing of concrete. In the present study, the development of transport properties of concrete with SAP is investigated. The chloride migration coefficient according to NT BUILD 492 is used as a measure of this. Twenty concrete mixtures are tested 7, 14, and 28 days after casting. The development of degree of hydration is followed for 20 corresponding paste mixtures.Both when SAP is added with extra water to compensate the SAP water absorption in fresh concrete and without extra water, the internal curing water held by SAP may contribute to increase the degree of hydration. No matter if SAP is added with or without extra water, it appears that the so-called gel space ratio can be used as a key parameter to link age and mixture proportions (water-to-cement ratio and SAP dosage) to the resulting chloride migration coefficient; the higher the volume of gel solid relative to the space available for it, the lower the chloride migration coefficient, because the pore system becomes more tortuous and the porosity becomes less.     

Formation and properties of high entropy oxides in Co-Cr-Fe-Mg-Mn-Ni-O system: Novel (Cr,Fe,Mg,Mn,Ni)3O4 and (Co,Cr,Fe,Mg,Mn)3O4 high entropy spinels

Possibility of formation of quinary and senary equimolar high entropy oxides from the Co-Cr-Fe-Mg-Mn-Ni-O system is presented. Different proposed compositions are synthesized using the solid-state reaction route at high temperatures (900−1100 °C) and quenched to room temperature. Phase composition of the samples is studied, showing tendency toward formation of two main phases: rock salt-structured Fm-3 m and spinel-structured Fd-3 m. It is documented that the annealing temperature has a profound effect on stability of both structures, and at 1100 °C usually the highest content of Fm-3 m phase is usually observed. Three different oxides, namely, (Co,Cr,Fe,Mn,Ni)₃O₄, (Co,Cr,Fe,Mg,Mn)₃O₄ and (Cr,Fe,Mg,Mn,Ni)₃O₄ are obtained as single-phase materials, which structure can be described as the high entropy Fd-3 m spinel one. The latter two compounds have not been previously reported in the literature. Activated character of the electrical conductivity dependence on temperature is observed, with relatively high total conductivity at high temperatures and corresponding high absolute values of Seebeck coefficient.