• Energy Research

Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.

For practical applications, both environmental and economic aspects are highly required to consider in the development of recycling of fibre reinforced polymers (FRPs) encountering their end-of-life. Here, a sustainable, low cost, and efficient approach for the recycling of the glass fibre (GF) from GF reinforced epoxy polymer (GFRP) waste is introduced, based on a microwave-assisted chemical oxidation method. It was found that in a one-step process using microwave irradiation, a mixture of hydrogen peroxide (H2O2) as a green oxidiser and tartaric acid (TA) as a natural organic acid could be used to decompose the epoxy matrix of a waste GFRP up to 90% yield. The recycled GFs with ~92.7% tensile strength, ~99.0% Young’s modulus, and ~96.2% strain-to-failure retentions were obtained when compared to virgin GFs (VGFs). This short microwave irradiation time using these green and sustainable recycling solvents makes this a significantly low energy consumption approach for the recycling of end-of-life GFRPs.