Toward an IoT based Software Defined Plumbing Network System with fault tolerance

in this paper we will see the application of computer science algorithms to the plumbing system. We propose a fault tolerant tap water system which is impossible without Internet of things and algorithms . We will show that the problem is a mutual exclusion group problem and we propose an adapted algorithm version from the literature as a solution . Coupling algorithms with the configurable plumbing network we believe that this will open new field of research on IoT we called it software defined plumbing Network where components that have been traditionally implemented in hardware (e.g. water mixers, spring faucets ,flow sensors, etc.) are instead implemented by means of software . This way we can solve other problem like instantaneous hot water,automatic cleaning of the water heater..etc since due to computer algorithms the systems can be easily smart, extensible and adaptive.

A Review of Computational Methods and Reduced Order Models for Flutter Prediction in Turbomachinery

Aeroelastic phenomena in turbomachinery are one of the most challenging problems to model using computational fluid dynamics (CFD) due to their inherent nonlinear nature, the difficulties in simulating fluid–structure interactions and the considerable computational requirements. Nonetheless, accurate modelling of self-sustained flow-induced vibrations, known as flutter, has proved to be crucial in assessing stability boundaries and extending the operative life of turbomachinery. Flutter avoidance and control is becoming more relevant in compressors and fans due to a well-established trend towards lightweight and thinner designs that enhance aerodynamic efficiency. In this paper, an overview of computational techniques adopted over the years is first presented. The principal methods for flutter modelling are then reviewed; a classification is made to distinguish between classical methods, where the fluid flow does not interact with the structure, and coupled methods, where this interaction is modelled. The most used coupling algorithms along with their benefits and drawbacks are then described. Finally, an insight is presented on model order reduction techniques applied to structure and aerodynamic calculations in turbomachinery flutter simulations, with the aim of reducing computational cost and permitting treatment of complex phenomena in a reasonable time.

The sensitivity of sea ice growth to the choice of ice shelf-ocean coupling algorithms.

<p>To quantify Antarctic ice mass loss and the subsequent sea level rise the geophysical modelling community is pushing towards frameworks that fully couple increasingly complex models of atmosphere, ocean, sea ice and ice sheets & shelves.  One particular hurdle remains the accurate representation of the vertical ocean-ice interaction at the base of ice shelves.  Parameterizations that are tuned to particular data sets naturally perform best in comparable ice shelf cavity environments. This poses the challenge in continental scale ocean-ice shelf models to chose one melt parameterizaton that performs sufficiently well in diverse cavity environment.  Thus adding uncertainty in ice shelf induced ocean freshening crucially affects modelled sea ice growth.  The impact magnitude of ice shelf supplied melt water on growth rates, thickness and extent of sea ice in the open ocean is currently debated in the literature.  <br>We reviewed and compared 16 commonly utilized melting/freezing parameterizations in coupled ocean-ice shelf models.  Melt rates differ hugely, in identical idealized conditions between 0.1m/yr to 3m/yr.  In this talk we present results of a realistic circum-Antarctic ice shelf and sea ice coupled ocean model (CICE, ROMS), where we look at the effects of the chosen ice shelf melt parameterization on modeled sea surface conditions and sea ice growth, regionally and circum Antarctic.</p>

Iterative Schwarz Method to Couple Ocean and Atmosphere in a Global Climate Model

<p>For historical and practical reasons, present-day coupling algorithms implemented in ocean-atmosphere models are primarily driven by the necessity to conserve energy and water at the air-sea interface. However the asynchronous coupling algorithms currently used in ocean-atmosphere do not allow for a correct phasing between the ocean and the atmosphere.</p><p>In an asynchronous coupling algorithm, the total simulation time is split into smaller time intervals (a.k.a. coupling periods) over which averaged-in-time<br>boundary data are exchanged. For a particular coupling period, the average atmospheric fluxes are computed in the atmospheric model using the oceanic surface properties computed and averaged by the oceanic model over the previous coupling period. Therefore, for a given coupling period, the fluxes used by the oceanic model are not coherent with the oceanic surface properties considered by the atmospheric model. The mathematical consistency of the solution at the interface is not guaranteed.</p><p>The use of an iterative coupling algorithm, such as Schwarz methods, is a way to correct this inconsistency and to properly reproduce the diurnal cycle when the coupling period is less than one day. In Lemarié et al. (2014), preliminary numerical experiments using the Schwarz coupling method for the simulation of a tropical cyclone with a regional coupled model were carried out. In ensemble simulations, the Schwarz iterative coupling method leads to a significantly reduced spread in the ensemble results (in terms of cyclone trajectory and intensity), thus suggesting that a source of error is removed with respect to the asynchronous coupling case.</p><p>In the present work, the Schwarz iterative method is implemented in IPSLCM6, a state-of-the-art global ocean-atmosphere coupled model used to study past, present and future climates. We analyse the convergence speed and the quality of the convergence. A partial iterative method is also tested: in a first phase, only the atmosphere physics and the vertical diffusion terms are computed, until the convergence. This provide a first guess for the full model which is then iterated until convergence of the whole system. The impact on the diurnal cycle will also be presented.</p>

A partitioned solution approach for fluid-structure interaction problems in the arterial system

The present work is concerned with the partitioned solution of the multifeld problem arising from a hierarchical modeling approach to cardiovascular fluid-structure interaction. Different strategies to couple the participating feld solvers are investigated in detail. This includes staggered and parallel coupling algorithms as well as different methods for convergence acceleration, spatial interpolation and temporal extrapolation of coupling quantities. In the developed modeling and simulation approach, a fully resolved model of a segment of the arterial network is coupled to reduced order models in order to account for the influence of the surrounding. There is experimental evidence that hemodynamic quantities such as the wall shear stress promote the progression cardiovascular disease. Cardiovascular FSI simulations, that can predict these quantities, are therefore of great interest and can aid in surgical planning and optimization of anastomoses shapes and graft materials. Contents...

Evolutionary couplings detect side-chain interactions

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.