Integrated Biorefinery Design with Techno-Economic and Life Cycle Assessment Tools in Polyhydroxyalkanoates Processing

To support and move toward a sustainable bioeconomy, the production of polyhydroxyalkanoates (PHAs) using renewable biomass has acquired more attention. However, expensive biomass pretreatment and low yield of PHAs pose significant disadvantages in its large-scale production. To overcome such limitations, the most recent advances in metabolic engineering strategies used to develop high-performance strains that are leading to a new manufacturing concept converting biomass to PHAs with co-products such as amino acids, proteins, biohydrogen, biosurfactants, and various fine chemicals are critically summarized. This review article presents a comprehensive roadmap that highlights the integrated biorefinery strategies, lifecycle analysis, and techno-economic assessment for sustainable and economic PHAs production. Finally, current and future challenges that must be addressed to transfer this technology to real-world applications are reviewed.     

Parameter identification of an elasto-plastic behaviour using artificial neural networks–genetic algorithm method

The simulation of the metal forming processes requires accurate constitutive models to describe the material behaviour at finite strain taking into account several conditions. The choice of a rheological model and the determination of its parameters should be made from a test that generates such conditions. The major difficulty encountered is that there is no experimental test satisfying all these criteria. The use of more than one test seems more and more essential, and it is utilized to characterize the rheological behaviour at operating conditions that correspond to metal forming applications. An Inverse analysis is then considered. Therefore, the difficulty lies within the long computing time taken when an optimization procedure is coupled with a finite element computation (FEC) to identify the material parameters. In order to solve the computing time problem, this paper proposes a hybrid identification method based on finite elements, neural network computations and genetic algorithm (GA) of an elasto-plastic behaviour model. The strategy suggested is then applied to identify the Karafillis and Boyce criterion and the Voce parameters model of the Stainless Steel AISI 304 using two tests (plane tensile test and bulge test with a circular die) at the same time.     

MHD conjugate heat transfer and entropy generation analysis of MWCNT/water nanofluid in a partially heated divided medium

The aim of this article is to conduct the lattice Boltzmann simulation of the magnetohydrodynamic (MHD) natural conjugate heat transfer in an apportioned cavity loaded with a multiwalled carbon nanotube/water nanofluid. The divided cavity is, to some extent, heated and cooled at the upright walls, whereas the horizontal walls are adiabatic. The nanofluid properties are evaluated on the basis of experimental correlations. The parameters ranges in the study are as follows: nanoparticles' volume fraction (%): 0 ≤ ? ≤ 0.5, temperature (°C): T = 27, Rayleigh number (Ra): 10³ ≤ Ra ≤ 10⁵, Hartmann number (Ha): 0 ≤ Ha ≤ 90, and the magnetic field inclination angle (γ): 0 ≤ γ ≤ π/2. The current outcomes are observed to be in great concurrence with the numerical results introduced in the literature. The impacts of the aforesaid parameters on local and average heat transfer, entropy generation, and Bejan number (Be) are explored and discussed. Indeed, the transfer of heat increases linearly with ? for a low Ra. As Ra increases, the average Nusselt number decreases for a high value of ?. The increase of nanoparticles' volume fraction leads to a reduction in the entropy generation and an increase in the Bejan number for a high Ra, but at low Ra, these functions remain constant. As the Ha increases, the transfer of heat and the entropy generation decreases, whereas there is an increase in Be. The transfer of heat, total entropy generation, and the Be depends strongly on the direction of the magnetic field. The increase of heater and cooler size has a great influence on the transfer of heat, entropy generation, and Be.     

Chemical treatment of sludge: in-depth study on toxic metal removal efficiency, dewatering ability and fertilizing property preservation

The presence of toxic metals in municipal sewage sludge restricts the application of this biomass in agricultural area. A chemical leaching process using a combination of inorganic acid and two oxidants has been developed for sludge decontamination. The present study investigated the effects of the concentrations of sulphuric acid (H2SO4), hydrogen peroxide and ferric chloride on metal solubilization from sewage sludge, as well as preservation of fertilizing properties (nutrient content) and dewatering ability of the treated sludge. The analysis of the results from batch leaching tests has allowed to define the optimal conditions for the reagent concentrations, which are 56 kg Fe3+ tonne(-1) of dry sludge solids (tds), 8 kg H2O2 tds(-1), and enough H2SO4 to reach a pH between 2.0 and 2.5 but less than 142 kg H2SO4 tds(-1). Finally, under these conditions, oxidoreduction potential values are found to be between 450 and 475 mV.     

Study and improvement in the radio communication quality for rotating electrical machine

Electrical Engineering - The wireless communication for rotating electrical machines is beneficial for diagnosis purposes as well as real-time monitoring. The electromagnetic waves propagation...     

Mechanical characterization and modeling of poly (β‐hydroxybutyrate)‐co‐poly(β‐hydroxyvalerate)–Alfa fiber‐reinforced composites

The mechanical properties of biobased composites of poly(β‐hydroxybutyrate)‐co‐poly(β‐hydroxyvalerate) biopolymer continuously reinforced with unidirectional Alfa fibers are investigated via tensile testing of oriented composite laminates. Simple mechanical models for the elastic stiffness, strength, and nonlinear hardening of the biobased composites are proposed with an emphasis on techniques that only require the independent properties of the fiber and matrix to facilitate composite design. Rule of mixtures (ROM) approaches are found to effectively predict the elastic properties of the composites but generally overestimate strength. Modified ROM approaches that discount the contribution of the matrix in the fiber loading direction and the contribution of the fiber in the transverse loading direction provide the most accurate strength predictions. Apparent elastic properties for composites with varying fiber orientations are predicted using a modified orthotropic laminate plate method which was found to overestimate composite stiffness in off‐axis loading directions. Postyield nonlinear hardening is modeled using a calibrated continuum yield and plasticity model and demonstrated to provide a close match of the experimental results. POLYM. COMPOS., 35:1758–1766, 2014. © 2014 Society of Plastics Engineers