Crack Growth in Solid Oxide Fuel Cell Materials: From Discrete to Continuum Damage Modeling

This paper addresses the damage and fracture issues of glass and ceramic materials used in solid oxide fuel cells. Analyses of an internal crack and of an interface crack between dissimilar materials were conducted using a modified boundary layer modeling approach. In this approach, fracture is allowed to occur in a small process window situated at an initial crack tip. Elastic displacement crack-tip fields are prescribed as remote boundary conditions. Crack propagation was first modeled discretely. Next, a continuum damage mechanics (CDM) model for brittle materials was developed to capture damage and crack growth in the process window. In particular, the damage model was applied to a glass-ceramic material that had been developed in-house for sealing purposes. Discrete and continuum damage solutions were then compared. Finally, the CDM model was used to determine the crack propagation direction as a function of a mode mixity measure.     

Alternating active-phase algorithm for multimaterial topology optimization problems: a 115-line MATLAB implementation

Structural and Multidisciplinary Optimization - A new algorithm for the solution of multimaterial topology optimization problems is introduced in the present study. The presented method is based on...     

Buoyancy effects on gaseous slip flow in a vertical rectangular microchannel

Consideration is given to the buoyancy effects on the fully developed gaseous slip flow in a vertical rectangular microduct. Two different cases of the thermal boundary conditions are considered, namely uniform temperature at two facing duct walls with different temperatures and adiabatic other walls (case A) and uniform heat flux at two walls and uniform temperature at other walls (case B). The rarefaction effects are treated using the first-order slip boundary conditions. By means of finite Fourier transform method, analytical solutions are obtained for the velocity and temperature distributions as well as the Poiseuille number. Furthermore, the threshold value of the mixed convection parameter to start the flow reversal is evaluated. The results show that the Poiseuille number of case A is an increasing function of the mixed convection parameter and a decreasing function of the channel aspect ratio, whereas its functionality on the Knudsen number is not monotonic. For case B, the Poiseuille number is decreased by increasing each of the mixed convection parameter, the Knudsen number, and the channel aspect ratio.     

NN-based Prediction Interval for Nonlinear Processes Controller

Neural networks (NNs) are extensively used in modelling, optimization, and control of nonlinear plants. NN-based inverse type point prediction models are commonly used for nonlinear process control. However, prediction errors (root mean square error (RMSE), mean absolute percentage error (MAPE) etc.) significantly increase in the presence of disturbances and uncertainties. In contrast to point forecast, prediction interval (PI)-based forecast bears extra information such as the prediction accuracy. The PI provides tighter upper and lower bounds with considering uncertainties due to the model mismatch and time dependent or time independent noises for a given confidence level. The use of PIs in the NN controller (NNC) as additional inputs can improve the controller performance. In the present work, the PIs are utilized in control applications, in particular PIs are integrated in the NN internal model-based control framework. A PI-based model that developed using lower upper bound estimation method (LUBE) is used as an online estimator of PIs for the proposed PI-based controller (PIC). PIs along with other inputs for a traditional NN are used to train the PIC to predict the control signal. The proposed controller is tested for two case studies. These include, a chemical reactor, which is a continuous stirred tank reactor (case 1) and a numerical nonlinear plant model (case 2). Simulation results reveal that the tracking performance of the proposed controller is superior to the traditional NNC in terms of setpoint tracking and disturbance rejections. More precisely, 36% and 15% improvements can be achieved using the proposed PIC over the NNC in terms of IAE for case 1 and case 2, respectively for setpoint tracking with step changes.

     

Process Mining Approach of a New Water Quality Index for Long-Term Assessment under Uncertainty Using Consensus-Based Fuzzy Decision Support System

One of the biggest challenges in water quality monitoring is how to optimize big Data gathered from a wide range of resources. This paper presented a new software-based pathway of process mining approach for extending a flexible WQI (Water Quality Index) that would deal with uncertainties derived from missing data occurrence in short- and long-term assessments. The methodology is based on integration of four multi-criteria group decision-making models coupled with fuzzy simulation including AHP (Analytical Hierarchy Process), fuzzy OWA (Ordered Weighting Average), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and fuzzy TOPSIS that were used for data mining and group consensus evaluation.. Examining the methodology on groundwater resources being supplied for drinking in Shiraz, Iran showed high integrity, accuracy, and proximity-to-real interpretation of water quality. This was the first study where decision-making risks such as Decision Makers’ risk-prone or risk-aversion attitudes (optimistic degree), DMs’ power, and consensus degree of each water quality parameter have been considered in WQI research. The proposed index offered a flexible choice in defining the intended project duration, stakeholders’ judgments, types of water use and water resource, standards, as well as type and number of water quality parameters. Thus, beside sustaining the unity in structure, this methodology could be suggested as a potentially WQI for other regions. The presented methodology would help more efficient monitoring of water resources for drinking purpose with respect to water quality.

     

A study on melt recycling of bio-based polypropylene/thermoplastic starch compound

The compulsion to use bioplastics has increased significantly today. One of the important aspects of plastics is their recyclability. Therefore, the important question of this research is that although bio-based compounds containing starch are sensitive to thermal-mechanical recycling processes, are such products thermally recyclable? To answer the question, polypropylene (PP)/thermoplastic starch (TPS) compound granules were extruded up to five times, and in the other part, single-extruded granules were blended at different ratios with virgin granules by extrusion. In order to characterize these samples, Fourier transform infrared spectroscopy, thermogravimetric analysis, differential scanning calorimetry, rotational disc rheometry, tensile properties, and appearance evaluation were used. The results showed that it is possible to recycle PP/TPS granules up to four times repetition of the extrusion operation and the fifth repetition also showed slight changes. There was also a blend of single-extruded granules with virgin material up to a 50:50% composition without significant variation.     

Receptance coupling for end mills

Identification of chatter free cutting conditions, the chatter stability lobes, requires a measurement of the frequency response function (FRF) of each tool mounted on the spindle. This paper presents a method of assembling known dynamics of the spindle–tool holder with an analytically modeled end mill using the receptance coupling technique. The classical receptance technique is enhanced by proposing a method of identifying the end mill–spindle/tool holder joint dynamics, which include both translational and rotational degrees of freedom. The method requires measurement of FRFs with impact tests applied on the spindle–tool holder assembly and blank calibration cylinders attached to the spindle. The spindle and tool holder characteristics are completely identified from the two experiments, and used for the mathematical prediction of FRF for end mills with arbitrary dimensions. The proposed method is experimentally proven and verified in cutting tests.