A FIRST-AND SECOND-ORDER TURBULENCE MODELS IN HYDROGEN NON-PREMIXED FLAME

ABSTRACT The mathematical modelling of turbulent flames is a difficult task due to the intense coupling between turbulent transport processes and chemical kinetics. The model presented within this paper is focused on the turbulence-chemistry interaction. The topic of this study is the numerical simulation of turbulent non-premixed hydrogen flame with different turbulent models in order to invest gate their predictive capability. The two turbulent models are compared: the (k-ε) model with a limited Pope's correction and the Reynolds stress model (RSM). The predictions are validated against experimental data provided by Raman and laser Doppler anemometry (LDA) measurements for a turbulent jet hydrogen-air diffusion flame. The turbulence-chemistry interaction is handled with flame let approach. Simulations of test cases with simple geometries verify the developed model and compare favourably with results of earlier investigations that employed both (k-ε) and RSM closures with the CMC and PDF approache

Modelling the impacts of agricultural management practices on river water quality in Eastern England

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km2. A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable