1,052 research outputs found
Integrating remote sensing datasets into ecological modelling: a Bayesian approach
Process-based models have been used to simulate 3-dimensional complexities of
forest ecosystems and their temporal changes, but their extensive data
requirement and complex parameterisation have often limited their use for
practical management applications. Increasingly, information retrieved using
remote sensing techniques can help in model parameterisation and data
collection by providing spatially and temporally resolved forest information. In
this paper, we illustrate the potential of Bayesian calibration for integrating such
data sources to simulate forest production. As an example, we use the 3-PG
model combined with hyperspectral, LiDAR, SAR and field-based data to
simulate the growth of UK Corsican pine stands. Hyperspectral, LiDAR and
SAR data are used to estimate LAI dynamics, tree height and above ground
biomass, respectively, while the Bayesian calibration provides estimates of
uncertainties to model parameters and outputs. The Bayesian calibration
contrasts with goodness-of-fit approaches, which do not provide uncertainties
to parameters and model outputs. Parameters and the data used in the
calibration process are presented in the form of probability distributions,
reflecting our degree of certainty about them. After the calibration, the
distributions are updated. To approximate posterior distributions (of outputs
and parameters), a Markov Chain Monte Carlo sampling approach is used (25
000 steps). A sensitivity analysis is also conducted between parameters and
outputs. Overall, the results illustrate the potential of a Bayesian framework for
truly integrative work, both in the consideration of field-based and remotely
sensed datasets available and in estimating parameter and model output uncertainties
Pressure-based large-eddy simulation of under-expanded hydrogen jets for engine applications
An assessment of Large-Eddy Simulations (LES) of non-reactive under-expanded hydrogen jets by using a pressure-based algorithm is presented. Such jets feature strong compressible discontinuities often considered to be best dealt with by a density-based solver. The crucial contribution of this work is to evaluate the suitability of the pressure- based solver to correctly describe the flow field of gaseous hydrogen jets for engine ap- plications, despite the presence of shock waves in the under-expanded near-orifice region. Inherently, the paper aims at providing guidance on the corresponding numerical aspects to simulate these flows. Hydrogen jets in an argon atmosphere at three different injection pressures are simulated and the results are compared to experiments in literature. Jet tip penetration and cone angle are the main investigated parameters. A good match is found, confirming the solidity of the proposed model. Different LES sub-grid scale models and discretisation schemes are then investigated in order to find the best approach in terms of accuracy and required computational cost. In particular, it is found that the WALE model coupled with a 4th-order cubic scheme for the convective terms yields the most suitable configuration
Effects of preferential diffusion on soot modeling with the sectional method and FGM tabulated chemistry
Chemical flux analysis of low-temperature plasma-enhanced oxidation of methane and hydrogen in argon
Plasma can be used to enhance the reactivity of combustible mixtures at low temperatures. In this article, the chemical pathways predicted by three different reaction mechanisms are investigated for the low-temperature oxidation of hydrogen and methane. To validate our model and the reaction mechanisms, the numerical results are compared against experimental results in a diluted flow reactor. Our model with all three reaction mechanisms predicts trends similar to those observed in the experiments. Moreover, all predicted quantities show reasonable quantitative agreement with the experiments. Flux analysis is used to identify the main pathways of oxidation at different temperatures. Three different modes, each active in a different temperature range, are identified in the oxidation of hydrogen. When the temperature is increased, these modes become increasingly self-sustained. Similarly, three different pathways are identified in the oxidation of methane. Below 1000K, methane quickly removes hydroxyl radicals from the radical pool, inhibiting self-sustained oxidation. From our analysis, we conclude that plasma provides activation of the low-temperature chemistry by the generation of radicals
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