A Review on Methods for Measurement of Free Water Surface.

Turbulent free-surface flows are encountered in several engineering applications and are typically characterized by the entrainment of air bubbles due to intense mixing and surface deformation. The resulting complex multiphase structure of the air-water interface presents a challenge in precise and reliable measurements of the free-water-surface topography. Conventional methods by manometers, wave probes, point gauges or electromagnetic/ultrasonic devices are proven and reliable, but also time-consuming, with limited accuracy and are mostly intrusive. Accurate spatial and temporal measurements of complex three-dimensional free-surface flows in natural and man-made hydraulic structures are only viable by high-resolution non-contact methods, namely, LIDAR-based laser scanning, photogrammetric reconstruction from cameras with overlapping field of view, or laser triangulation that combines laser ranging with high-speed imaging data. In the absence of seeding particles and optical calibration targets, sufficient flow aeration is essential for the operation of both laser- and photogrammetry-based methods, with local aeration properties significantly affecting the measurement uncertainty of laser-based methods.

1H NMR metabolomics of microbial metabolites in the four MW agricultural biogas plant reactors: A case study of inhibition mirroring the acute rumen acidosis symptoms.

In this study, nuclear magnetic resonance (1H NMR) spectroscopic profiling was used to provide a more comprehensive view of microbial metabolites associated with poor reactor performance in a full-scale 4 MW mesophilic agricultural biogas plant under fully operational and also under inhibited conditions. Multivariate analyses were used to assess the significance of differences between reactors whereas artificial neural networks (ANN) were used to identify the key metabolites responsible for inhibition and their network of interaction. Based on the results of nm-MDS ordination the subsamples of each reactor were similar, but not identical, despite homogenization of the full-scale reactors before sampling. Hence, a certain extent of variability due to the size of the system under analysis was transferred into metabolome analysis. Multivariate analysis showed that fully active reactors were clustered separately from those containing inhibited reactor metabolites and were significantly different. Furthermore, the three distinct inhibited states were significantly different from each other. The inhibited metabolomes were enriched in acetate, caprylate, trimethylamine, thymine, pyruvate, alanine, xanthine and succinate. The differences in the metabolic fingerprint between inactive and fully active reactors observed in this study resembled closely the metabolites differentiating the (sub) acute rumen acidosis inflicted and healthy rumen metabolomes, creating thus favorable conditions for the growth and activity of pathogenic bacteria. The consistency of our data with those reported before for rumen ecosystems shows that 1H NMR based metabolomics is a reliable approach for the evaluation of metabolic events at full-scale biogas reactors.