Modelling of redox flow battery electrode processes at a range of length scales : a review

In this article, the different approaches reported in the literature for modelling electrode processes in redox flow batteries (RFBs) are reviewed. RFB models vary widely in terms of computational complexity, research scalability and accuracy of predictions. Development of RFB models have been quite slow in the past, but in recent years researchers have reported on a range of modelling approaches for RFB system optimisation. Flow and transport processes, and their influence on electron transfer kinetics, play an important role in the performance of RFBs. Macro-scale modelling, typically based on a continuum approach for porous electrode modelling, have been used to investigate current distribution, to optimise cell design and to support techno-economic analyses. Microscale models have also been developed to investigate the transport properties within porous electrode materials. These microscale models exploit experimental tomographic techniques to characterise three-dimensional structures of different electrode materials. New insights into the effect of the electrode structure on transport processes are being provided from these new approaches. Modelling flow, transport, electrical and electrochemical processes within the electrode structure is a developing area of research, and there are significant variations in the model requirements for different redox systems, in particular for multiphase chemistries (gas–liquid, solid–liquid, etc.) and for aqueous and non-aqueous solvents. Further development is essential to better understand the kinetic and mass transport phenomena in the porous electrodes, and multiscale approaches are also needed to enable optimisation across the relevent length scales

Evaluation of geostatistics methods for interpolation of agrometeorological indices used to define climatic risks

The definition of the best sowing dates for corn, adopted in the Zoning of Climatic Risks,of the State of Sao Paulo, Brazil, was based on space-temporary variations of the water stress index (ISNA), using the pondered average as the interpolation method to spatialize this parameter. This method does not consider the spatial propagation of errors, leading to imprecise interpretations of the best sowing dates, mainly at the beginning and at the end of the cycle. The objective of this work was to compare methods of spatializing numeric values of agrometeorological indices and to evaluate their spatial space variation. The methods of the pondered means ordinary kriging and indication kriging were used. The indication kriging was the most suitable method for spatializing ISNA and to define the best sowing date for corn, in the State of Sao Paulo.38216117

Estimation Of Single Station Interfrequency Receiver Bias Using Gps-Tec

Dual-frequency Global Positioning System (GPS) receivers present a plausible and cost-effective way of computing Total Electron Content (TEC). For accurate estimates of TEC, frequency-dependent satellite and receiver instrumental biases should be removed from GPS measurements properly. Although instrumental satellite bias values are widely available through the internet from various International GPS Service (IGS) analysis centers, receiver biases (also known as differential code biases or interfrequency biases) are provided only for a very few GPS stations and a select number of days. This makes it very difficult to compute TEC for a single station. In this study, an online, single station receiver bias estimation algorithm, IONOLAB-BIAS, is developed and implemented to obtain daily and monthly averages of receiver bias. The algorithm is successfully applied to both quiet and disturbed days of the ionosphere for stations positioned in high-latitude, midlatitude, and equatorial regions. The receiver bias estimates are compared with two of the basic methods in the literature that can be applied off-line, and also with the receiver bias values provided from the IGS centers for a select number of stations. It is observed that IONOLAB-BIAS is in excellent accordance with the sparse estimates from the IGS centers for all ionospheric states and regions. IONOLAB-BIAS has a high potential to be an alternative receiver bias computation algorithm with its ease of implementation and accurate estimates for any single station GPS-TEC.Wo