Statistical method for the determination of the ignition energy of dust cloud-experimental validation

Powdery materials such as metallic or polymer powders play a considerable role in many industrial processes. Their use requires the introduction of preventive safeguard to control the plants safety. The mitigation of an explosion hazard, according to the ATEX 137 Directive (1999/92/EU), requires, among other things, the assessment of the dust ignition sensitivity. PRISME laboratory (University of Orléans) has developed an experimental set-up and methodology, using the Langlie test, for the quick determination of the explosion sensitivity of dusts. This method requires only 20 shots and ignition sensitivity is evaluated through the E₅₀ (energy with an ignition probability of 0.5). A Hartmann tube, with a volume of 1.3 l, was designed and built. Many results on the energy ignition thresholds of partially oxidised aluminium were obtained using this experimental device (Baudry, 2007) and compared to literature. E₅₀ evolution is the same as MIE but their respective values are different and MIE is lower than E₅₀ however the link between E₅₀ and MIE has not been elucidated.In this paper, the Langlie method is explained in detail for the determination of the parameters (mean value E₅₀ and standard deviation σ) of the associated statistic law. The ignition probability versus applied energy is firstly measured for Lycopodium in order to validate the method. A comparison between the normal and the lognormal law was achieved and the best fit was obtained with the lognormal law.In a second part, the Langlie test was performed on different dusts such as aluminium, cornstarch, lycopodium, coal, and PA12 in order to determine E₅₀ and σ for each dust. The energies E₀₅ and E₁₀ corresponding respectively to an ignition probability of 0.05 and 0.1 are determined with the lognormal law and compared to MIE find in literature. E₀₅ and E₁₀ values of ignition energy were found to be very close and were in good agreement with MIE in the literature.     

Modelling radiative balance in a row-crop canopy: Cross-row distribution of net radiation at the soil surface and energy available to clusters in a vineyard

Distribution of energy at the soil surface in a row-crop influences mainly soil temperature and water content, and therefore root activity, nitrogen mineralization and within canopy air temperature, which all affect plant physiology. In the case of a vineyard, it is also closely related to the energy available to the berries and therefore most influential for fruit quality. The aim of this study was to develop a simplified model of available energy distribution at the soil surface and at the bottom of the rows, where most of the clusters are located. Such a model would be helpful for optimising some aspects of row-crop management like training system choice, row geometry, leaf area density, and soil surface maintenance practices.The model simulated radiation balance at the soil surface, split up into downward and upward short- and long-wave fluxes. Row shadows were calculated at any point of the inter-row space, in interaction with actual row geometry and simplified porosity distribution within row volume. All hemispheric radiations (long-wave and diffuse solar radiation) were calculated according to view factors between the row and soil surfaces. Input variables were therefore incoming solar radiation over the canopy, air temperatures near the row walls and soil surface temperatures. Parameters were row geometry, dimensions and porosities.The model was validated in a 7 years old Merlot vineyard in the Médoc area, by comparing model predictions to measured net radiation (Rns) at five positions above the inter-row soil surface. Along the row sampling was achieved by a moving device carrying the net-radiometers. Structure of the vegetation was kept constant during the experiment and gap fraction parameters were derived from pictures of shadows at the soil surface. Since Rns measurements are impracticable directly at the soil surface and horizontal distribution of Rns is heterogeneous, comparison was performed by calculating net radiation at the actual measurement height which was close to average cluster height.Model prediction agreed with field measurement in most conditions, which suggests that all short- and long-wave radiation fluxes, as well as interactions with the canopy structure, were well described. Rns, energy available to clusters, and soil surface temperature variations were all mainly driven by shading due to the rows. Coupling the model to soil heat transfer and convective fluxes to the atmosphere models will help forecasting soil temperature distribution at the surface and in depth as well as canopy microclimate. The model will also be an essential part of a more elaborate model of cluster microclimate, a key determinant of berry quality.     

Radio (<Superscript>14</Superscript>C)- and fluorescent-doubly labeled silica nanoparticles for biological and environmental toxicity assessment

A new and efficient synthetic route to fluorescent and ¹⁴C-double-labeled silica-based nanoparticles (NPs) is described. The synthesis has been carried out using the “oil-in-water” micro-emulsion technique. Fluorescent and radioactive labeling have been achieved entrapping labeled poly(ethylene glycol) (PEG) molecules in the NPs. The produced particles have been analyzed by means of scanning electron microscopy, photon correlation spectroscopy, confocal microscopy, scintillation counting and oxidation/combustion experiments. Fluorescence quenching experiments confirm that the label is entrapped in the particles. The results presented suggest that the silica matrix does not block the β-radiations emitted from the labeled PEG molecules entrapped in the NPs.