9 research outputs found
Effect of different nitrogen sources and nitrification inhibitors on soil nitrogen distribution in Kinnow orchard
This record was migrated from the OpenDepot repository service in June, 2017 before shutting down
Studies on remelting of tungsten carbide and rare earth modified nickel base alloy composite coating
Effect of irradiation and storage temperature on quality parameters of Kesar mango (Mangifera indica L.)
Large Scale Triboelectric Nanogenerator and Self-Powered Pressure Sensor Array Using Low Cost Roll-to-Roll UV Embossing
The assessment of localized remobilization and geochemical process of 14 metals at sediment/water interface (SWI) of Yingkou coast (China) by diffusive gradients in thin films (DGT)
A flexible triboelectric-piezoelectric hybrid nanogenerator based on P(VDF-TrFE) nanofibers and PDMS/MWCNT for wearable devices
A piezoelectric micro generator worked at low frequency and high acceleration based on PZT and phosphor bronze bonding
Modelling macronutrients in shelf sea sediments: fitting model output to experimental data using a genetic algorithm
Purpose:Diagenetic modelling, the mathematical simulation of the breakdown of sedimentary organic matter and subsequent fate of associated nutrients, has progressed to a point where complex, non-steady state environments can be accurately modelled. A genetic algorithm has never been used in conjunction with an early diagenetic model, and so we aim to discover whether this method is viable to determining a set of realistic model parameters, which itself is often a difficult task.Materials and methods:A range of sensitivity analyses were conducted to establish the parameters for which the model was most sensitive before a micro-genetic algorithm (?GA) was used to fit an output from a previously published diagenetic model (OMEXDIA) to observational data, taken at the North Dogger site from a series of cruises in the North Sea. Profiles of carbon, oxygen, nitrate and ammonia were considered. The method allows a set of parameters to be determined in a manner analogous to natural selection. Each iteration of the genetic algorithm within each experiment decreases the variance between the observed profiles and those calculated by OMEXDIA.Results and discussion:Despite some of the observed profiles, particularly for carbon, showing unusual patterns, the genetic algorithm was able to generate a set of parameters which was able to fit the observations. The genetic algorithm can therefore help to determine the values of other parameters used in the model, for which observational values are difficult to measure (e.g. the flux of organic matter to the sediment from the overlying water column and the rates of degradation of organic matter). We also show that the values of the parameters determined by the ?GA technique are able to be used in a potentially temporally predictive manner.Conclusions:The ?GA used is a viable method to fit carbon and nutrient sedimentary profiles observed in complex, dynamic shelf sea systems, despite OMEXDIA originally being designed for a different sedimentary environment. The results therefore show that this novel use of a genetic algorithm is a suitable method for both model calibration and validation and that the technique may help in explaining processes which are poorly understood