Improving the performances of earth air heat exchangers through Constructal design

Earth to air heat exchanger (EAHE) is a well‐known technique used to preheat or precool outdoor air before blowing it into a building. However, its geometry is often very simple as it consists in one or multiple straight pipes, while more complex arrangements can be found in heat exchangers design. In this paper, we explore the advantage of designing an EAHE as a network through the Constructal law point of view. A methodology is first proposed to design a single pipe EAHE when the need is defined in terms of cooling power, overall efficiency and enthalpy difference between the inlet air and the ground. Next, the single pipe EAHE is used as a reference for designing a tree‐shaped network under the constraint of identical fluid volume and cooling power. The geometrical features are allowed to change for the different branches of the network. The network coefficient of performance is found to increase significantly with the bifurcation level, illustrating the superior performances of the network. This approach was found to be robust as the improvements were not depending on the cooling demand or the environmental conditions. However, further work is needed to move from this theoretical result to practical considerations.     

Effects of Aluminium Contamination on the Nervous System of Freshwater Aquatic Vertebrates: A Review

Aluminium (Al) is the most common natural metallic element in the Earth’s crust. It is released into the environment through natural processes and human activities and accumulates in aquatic environments. This review compiles scientific data on the neurotoxicity of aluminium contamination on the nervous system of aquatic organisms. More precisely, it helps identify biomarkers of aluminium exposure for aquatic environment biomonitoring in freshwater aquatic vertebrates. Al is neurotoxic and accumulates in the nervous system of aquatic vertebrates, which is why it could be responsible for oxidative stress. In addition, it activates and inhibits antioxidant enzymes and leads to changes in acetylcholinesterase activity, neurotransmitter levels, and in the expression of several neural genes and nerve cell components. It also causes histological changes in nerve tissue, modifications of organism behaviour, and cognitive deficit. However, impacts of aluminium exposure on the early stages of aquatic vertebrate development are poorly described. Lastly, this review also poses the question of how accurate aquatic vertebrates (fishes and amphibians) could be used as model organisms to complement biological data relating to the developmental aspect. This “challenge” is very relevant since freshwater pollution with heavy metals has increased in the last few decades.     

Isolation of Non-methylene Interrupted or Acetylenic Fatty Acids from Seed Oils Using Semi-preparative Supercritical Chromatography

Preparative scale supercritical fluid chromatography was used for isolating and purifying uncommon non-methylene interrupted or acetylenic polyunsaturated fatty acids ethyl esters from seed oils. Fractionation of Biota orientalis seed oil ethyl esters was performed by supercritical fluid chromatography to obtain juniperonic acid [(5Z,11Z,14Z,17Z)-eicosa-5,11,14,17-tetraenoic acid], a non-methylene interrupted polyunsaturated fatty acid. Fractionation of sandalwood seed oil ethyl esters yielded ximenynic acid [(E)-octadec-11-en-9-ynoic acid], an acetylenic polyunsaturated fatty acid. The effects of CO₂ flow rate, column stationary phase and particle size were explored to optimize ximenynic and juniperonic ethyl ester recovery and purity from ethyl ester mixtures using online UV/Vis detection. Particle size, followed by the stationary phase, were found to be the most important parameters to achieving good separation. Under optimized conditions, ximenynic and juniperonic ethyl ester purities greater than 99 and 95%, respectively, were achieved in a one step process without co-solvent. The isolation and recovery of juniperonic acid from biota seed oil free fatty acids was also attempted. Using free fatty acids as the feed material, the non-methylene interrupted polyunsaturated sciadonic acid was also able to be separated from other compounds including juniperonic acid under some conditions, and gave an increase in concentration of more than 17 times.     

Colloidal Processing of Zirconium Diboride Ultra‐High Temperature Ceramics

Colloidal processing of the Ultra‐High Temperature Ceramic (UHTC) zirconium diboride (ZrB₂) to develop near?net‐shaping techniques has been investigated. The use of the colloidal processing technique produces higher particle packing that ultimately enables achieving greater densification at lower temperatures and pressures, even pressureless sintering. ZrB₂ suspension formulations have been optimized in terms of rheological behavior. Suspensions were shaped into green bodies (63% relative density) using slip casting. The densification was carried out at 1900°C, 2000°C, and 2100°C, using both hot pressing at 40 MPa and pressureless sintering. The colloidally processed materials were compared with materials prepared by a conventional dry processing route (cold pressed at 50 MPa) and subjected to the same densification procedures. Sintered densities for samples produced by the colloidal route are higher than produced by the dry route (up to 99.5% relative density by hot pressing), even when pressureless sintering is performed (more than 90% relative density). The promising results are considered as a starting point for the fabrication of complex‐shaped components that can be densified at lower sintering temperatures without pressure.     

Influence of the growth conditions on the defect density of single-walled carbon nanotubes

The influence of the temperature and precursor pressure on the defect density of single-walled carbon nanotubes (SWCNTs) grown by catalytic chemical vapor deposition was studied for several catalyst–precursor couples. The SWCNT defect density was assessed by studying the Raman D band. In situ Raman monitoring was used to determine experimental conditions allowing the preparation of samples free of pyrolytic carbon and not altered by air exposure. The most striking feature is that the Arrhenius plots of the I_G/I_D ratio systematically display a convex shape, i.e. the apparent activation energy decreases with increasing temperature. From HRTEM observations and oxidation experiments, this evolution of the D band features is ascribed to the catalytic growth of long SWCNTs with few defects at high temperature and of short and defective SWCNTs and carbon structures at low temperature. The convex Arrhenius behavior is well accounted by two kinetic models: (i) a model considering a change of intermediate states as a function of the temperature (for instance due to a phase transition of the catalyst particle or a change of intermediate carbon species) and (ii) a model considering a high-temperature process of defect creation (for instance by reaction with reactive gas species).     

Shuffle or update parallel differential evolution for large-scale optimization

This paper proposes a novel algorithm for large-scale optimization problems. The proposed algorithm, namely shuffle or update parallel differential evolution (SOUPDE) is a structured population algorithm characterized by sub-populations employing a Differential evolution logic. The sub-populations quickly exploit some areas of the decision space, thus drastically and quickly reducing the fitness value in the highly multi-variate fitness landscape. New search logics are introduced into the sub-population functioning in order to avoid a diversity loss and thus premature convergence. Two simple mechanisms have been integrated in order to pursue this aim. The first, namely shuffling, consists of randomly rearranging the individuals over the sub-populations. The second consists of updating all the scale factors of the sub-populations. The proposed algorithm has been run on a set of various test problems for five levels of dimensionality and then compared with three popular meta-heuristics. Rigorous statistical and scalability analyses are reported in this article. Numerical results show that the proposed approach significantly outperforms the meta-heuristics considered in the benchmark and has a good performance despite the high dimensionality of the problems. The proposed algorithm balances well between exploitation and exploration and succeeds to have a good performance over the various dimensionality values and test problems present in the benchmark. It succeeds at outperforming the reference algorithms considered in this study. In addition, the scalability analysis proves that with respect to a standard Differential Evolution, the proposed SOUPDE algorithm enhances its performance while the dimensionality grows.