Simulating organization of convective cloud fields and interactions with the surface

The mesoscale organization and structure of convective clouds is thought to be rooted in the thermodynamic properties of the atmosphere and in the turbulent to mesoscale dynamics of the flow. Such structure may contribute to the transition between shallow and deep convection. The thermodynamic state of the boundary layer is forced by the amount of surface fluxes from below. Conversely, landscape patterns and land-cover heterogeneity may equally give rise to focused regions for deep convection triggering, in particular when patch sizes exceed 10 km. Since the convective boundary layer has a mediating function between the surface and deep storm clouds, the connection between surface and upper atmosphere is not straightforward. It is generally believed to involve local erosion of the capping inversion layer, the build-up of a moist energy supply, gradual humidification of the lower-free troposphere that reduces dry air entrainment into burgeoning deeper clouds, and thermal mesoscale circulations that can generate moisture convergence and locally forced ascent. To what extent microscale realistic surface heterogeneity and an interactive surface response matter to shallow and deep convection and its organization remains an open question. In this dissertation, we describe the coupling of a physiology-based vegetation model (HYBRID) and of a sea surface flux algorithm (COARE) to the cloud-resolving Active Tracer High-resolution Atmospheric Model (ATHAM). We investigate the full diurnal cycle of convection based on the example of the Hector storm over Tiwi Islands, notably the well-characterized event on 30th November 2005. The model performs well in terms of timing and cloud dynamics in comparison to a range of available observations. Also, ATHAM-HYBRID seems to do well in terms of flux partitioning. Whilst awaiting more thorough flux validation, we remain confident that the interactive surface response of both HYBRID and COARE is suited for the purpose of simulating convective-scale processes. We find the storm system evolution in 3D simulations to be robust with respect to differences in surface configuration and initialization. Within our 3D sensitivity runs, we could not identify a strong dependence on either realistic surface heterogeneity in the island landscape or on the interactive surface response. We conclude that in our case study at least, atmospheric (turbulent) dynamics likely dominate over surface heterogeneity effects, provided that the bulk magnitude of the surface energy fluxes, and their partitioning into sensible and latent heat (Bowen ratio), remain unaltered. This is consistent with 2D sensitivity studies, where we find model grid-spacing and momentum diffusion, governing the dynamics, to have an important influence on the overall evolution of deep convection. Fine grid-spacing is necessary, as the median width of updraught cores mostly does not exceed 1000 m. We associate this influence with the dry air entrainment rate in the wake of rising parcels, and with how resolution and diffusion act on coherent structures in the flow. In 2D sensitivity studies with differences in realistic heterogeneities of surface properties, we find little evidence for a clear deterministic influence of these properties on the transition between shallow and deep convection, in spite of largely different storm evolutions across the various runs. In these runs, we tentatively ascribe triggering to stochastic features in the flow, without discarding the relevance of convergence lines produced by mesoscale density currents, such as the sea breeze and cold pool storm outflows.This research has been funded through the Fonds National de la Recherche (FNR), Luxembourg, under the grant BFR07-089, and supported by the Luxembourgish Ministry for Higher Education and Research through CEDIES, by the Cambridge European Trust (CET) and the National Environment Research Council (NERC), UK, as well as by Prof. Hans-F. Graf

Preventing the Tyranny of the Majority - Experimental Evidence on the Choice of Voting Thresholds in Bayesian Games

In democracies, an absolute majority of the population may choose policies that are harmful to the rest of the population. A purpose of super-majority rules is to prevent this from happening. We study whether individuals optimally choose sub- or super-majority rules when the rights of minorities should be protected. Subjects propose more extreme voting rules for more skewed distributions, but we also find that rule choices are biased towards balanced rules, leading substantial welfare losses

Editorial: Body representations, peripersonal space, and the self: humans, animals, robots

Contains fulltext : 220410.pdf (publisher's version ) (Open Access)4 p

Single-Cell Tests to Explore the Reliability of Sofc Installations Operating Offshore

This paper studies the robustness of off-shore solid oxide fuel cell (SOFC) installations and the nature and causes of possible cell degradation in marine environments. Two important, cathode-related, impediments to ensuring SOFC reliability in off-shore installations are: cathode degradation due to salt contamination and oxygen depletion in the air supply. Short-term and long-term tests show the effect of salt contamination in the cathode feed on cell performance, and reveal the underlying cause of the degradation seen. SEM/X-ray Diffraction/(XRD) analyses made it possible to identify salt taken up in the cathode microstructure after the short-term testing while the macroscopic cell structure remained intact after the short-term tests. The long-term degradation was found to be more severe, and SEM images showed delamination at the cathode/electrolyte interface with salt present, something that was not seen after long-term testing without salt. The effect of oxygen depletion on the performance was also determined at three different temperatures using I-V curves.publishedVersio

Flow loop study of a cold and cohesive slurry. Pressure drop and formation of plugs

Slurries of cohesive particles constitute a significant risk during subsea petroleum production due to their potential to plug the flow. This article describes a flow loop study of a slurry consistent with 0.23-mm ice particles in decane. The experiments were conducted for the concentration of particles up to 20.3% vol. and Re 25000. The cohesion of ice was suggested by controlling the temperature of the slurry. The relative viscosity of the slurry was computed as a function of particle concentration using pressure drop measurements. The relative viscosity was 3.1 for the concentration of 20.3%. The Bingham-fluid model agreed with the empirical calculations within the discrepancy of 15.5%. Increased viscosity of slurry led to a higher pressure drop in the flow loop compared to the single-phase case. Pressure drops for 20.3% slurry flow were 5.2% and 44.4% higher than for pure decane at Reynolds numbers of 24778 and 4956, respectively. The test section of the loop was equipped with an orifice to induce the formation of plugs. The plugs were observed at particle concentrations below 7.0%. The article presents detailed experimental logs depicting the process of plug formation. The observed blocking cases partially agreed with flow maps from the literature. In addition, we note the applicability of the blockage risk evaluation technique from the Colorado School of Mines.publishedVersio

Review of productivity decline in sown grass pastures

Productivity decline in sown grass pastures is widespread in northern Australia and reduces production by approximately 50%, a farm gate cost to industry of > $17B over the next 30 years. Buffel grass is the most widely established sown species (>75% of plantings) and has been estimated to be “dominant” on 5.8 M hectares and “common” on a further 25.9 M hectares of Queensland. Legumes are the most cost effective mitigation option and can reclaim 30-50% of lost production. Commercial use of legumes has achieved mixed results with notable successes but many failures. There is significant opportunity to improve commercial results from legumes using existing technologies, however there is a need for targeted research to improve the reliability of establishment and productivity of legumes. This review recommends the grazing industry invest in targeted R,D&E to assist industry in improving production and sustainability of rundown pastures

Cohesive collisions of particles in liquid media studied by CFD-DEM, video tracking, and Positron Emission Particle Tracking

This paper investigates the cohesive collision of ice in an oil phase at temperatures ranging from −15.7 °C to −0.3 °C. The new information on the coefficient of restitution (COR) was obtained using three different velocity measurement methods: high-speed experimental video recording, Positron Emission Particle Tracking (PEPT), and numerical simulations. A new type of PEPT tracer was developed for the experiments. The COR values were in the interval 0.57...0.82, with a maximum at around −10 °C. The CFD-DEM coupled approach was applied to reproduce experiments with an ice particle drop and its collision with an inclined ice surface in a decane. The particle–wall interaction is modeled using commercial software, considering particle cohesion, particle size, and shape. CFD-DEM predicted the COR with an average deviation 10% from the experimental data. The numerical model’s results agree with the experiments, demonstrating that the CFD-DEM method is suitable for describing multiphase cohesive interactions

Development of soft computing and applications in agricultural and biological engineering

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and applied in the last three decades for scientific research and engineering computing. In agricultural and biological engineering, researchers and engineers have developed methods of fuzzy logic, artificial neural networks, genetic algorithms, decision trees, and support vector machines to study soil and water regimes related to crop growth, analyze the operation of food processing, and support decision-making in precision farming. This paper reviews the development of soft computing techniques. With the concepts and methods, applications of soft computing in the field of agricultural and biological engineering are presented, especially in the soil and water context for crop management and decision support in precision agriculture. The future of development and application of soft computing in agricultural and biological engineering is discussed