Passive sampling systems are an emerging technology for detecting pollutants in the aquatic environment. A passive sampling system has been developed based on diffusion through a porous surface to a receiving phase, where the analyte is removed by chelation at a solid phase. The diffusion process can be described by Fickian diffusion through the sampler. The sampler has a well-defined surface area, which permits calibration in terms of concentration. Passive sampling systems can be used to determine pollutant concentrations if the diffusion process can be described and understood within environmental limits. In natural water systems, diffusion coefficients for metal transport across the porous membrane will be affected by external conditions, including biofouling and variation in turbulence and temperature. Uptake rates for the analytes Cu, Cd and Pb have been determined for the complete passive sampling system. Two different cases have been investigated, a batch case, where the bulk concentration decreases with time, and a flow-through case, where the bulk concentration remains constant. Diffusion coefficients were determined for the two conditions and compared with the calculated value obtained for the Stokes-Einstein equation in pure water. Diffusion coefficients for metals were found to be lower than for diffusion in pure water, a difference attributed to the effect of the porous membrane. The effect of the hydraulic conditions on the metal diffusion was studied for both a conventional magnetic stirrer creating turbulence in the system and for a rotated sampler, the latter providing a well-defined boundary layer system. The boundary layer was found to be negligible compared with the diffusion limiting membrane in the presence of sufficient turbulence or if the rotation of the sampler was high.

The macroscopic response of short fiber reinforced composites (SFRCs) is dependent on an extensive range of microstructural parameters. Thus, micromechanical modeling of these materials is challenging and in some cases, computationally expensive. This is particularly important when path-dependent plastic behavior is needed to be predicted. A solution to this challenge is to enhance micromechanical solutions with machine learning techniques such as artificial neural networks. In this work, a recurrent deep neural network model is trained to predict the path-dependent elasto-plastic stress response of SFRCs, given the microstructural parameters and the strain path. Micromechanical mean-field simulations are conducted to create a database for training the validating the model. The model gives very accurate predictions in a computationally efficient manner when compared with independent micromechanical simulations.

Deposition of particles in selective catalytic reduction DeNO x monolithic catalysts was studied by low-dust pilot-scale experiments. The experiments showed a total deposition efficiency of about 30%, and the deposition pattern was similar to that observed in full-scale low-dust applications. On extended exposure to the dust-laden flue gas, complete blocking of channels was observed, showing that also in low-dust applications soot blowing is necessary to keep the catalyst clean. A particle deposition model was developed in computational fluid dynamics, and simulations were carried out assuming either laminar or turbulent flow. Assuming laminar flow, the accumulated mass was underpredicted with a factor of about 17, whereas assuming turbulent flow overpredicted the experimental result with a factor of about 2. The simulations showed that turbulent diffusion in the monolith channels and inertial impaction and gravitational settling on the top of the monolith were the dominating mechanisms for particle deposition on the catalyst.

We have compared 14 different sediment incubation chambers, most of them were used on bottom landers. Measurements of mixing time, pressure gradients at the bottom and Diffusive Boundary Layer thickness (DBL) were used to describe the hydrodynamic properties of the chambers and sediment-water solute fluxes of silicate (34 replicates) and oxygen (23 replicates) during three subsequently repeated incubation experiments on a homogenized, macrofauna-free sediment. The silicate fluxes ranged from 0.24 to 1.01 mmol m−2 day−1 and the oxygen fluxes from 9.3 to 22.6 mmol m−2 day−1. There was no statistically significant correlation between measured fluxes and the chamber design or between measured fluxes and hydrodynamic settings suggesting that type of chamber was not important in these flux measurements. For verification of sediment homogeneity, 61 samples of meiofauna were taken and identified to major taxa. In addition, 13 sediment cores were collected, sectioned into 5-10-mm slices and separated into pore water and solid phase. The pore water profiles of dissolved silicate were used to calculate diffusive fluxes of silicate. These fluxes ranged from 0.63 to 0.87 mmol m−2 day−1. All of the collected sediment parameters indicated that the sediment homogenization process had been satisfactorily accomplished. Hydrodynamic variations inside and between chambers are a reflection of the chamber design and the stirring device. In general, pump stirrers with diffusers give a more even distribution of bottom currents and DBL thicknesses than paddle wheel-type stirrers. Most chambers display no or low static differential pressures when the water is mixed at rates of normal use. Consequently, there is a low risk of creating stirrer induced pressure effects on the measured fluxes. Centrally placed stirrers are preferable to off-center placed stirrers which are more difficult to map and do not seem to give any hydrodynamic advantages. A vertically rotating stirrer gives about five times lower static differential pressures at the same stirring speed as the same stirrer mounted horizontally. If the aim is to simulate or mimic resuspension at high flow velocities, it cannot be satisfactorily done in a chamber using a horizontal (standing) rotating impeller (as is the case for most chambers in use) due to the creation of unnatural conditions, i.e. large static differential pressures and premature resuspension at certain locations in the chamber.