Kinetic Intersections as a Source of Information on Rate Coefficients

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Aplikasi model baharu penambahbaikan pendekatan kalut ke atas peramalan siri masa kepekatan ozon

Kajian ini merupakan aplikasi pendekatan kalut ke atas peramalan siri masa bahan pencemar udara ozon di stesen asas Malaysia yang terletak di Jerantut, Pahang. Sebelum model peramalan dibina, siri masa diuji terlebih dahulu sama ada bersifat kalut atau tidak. Melalui plot ruang fasa dan kaedah Cao, siri masa bahan pencemar ozon didapati bersifat kalut bermatra rendah. Oleh itu, model peramalan melalui kaedah penghampiran linear setempat dibina. Sebagai inovasi, model ini ditambah baik. Sebagai perbandingan, model peramalan regresi linear turut dibina. Melalui pengiraan purata ralat mutlak, ralat punca purata kuasa dua dan pekali korelasi, keputusan menunjukkan bahawa model baharu penambahbaikan penghampiran linear setempat adalah lebih baik berbanding model-model yang lain. Maka, penambahbaikan yang dilakukan adalah berbaloi. Dengan itu, pendekatan kalut adalah pendekatan alternatif yang sesuai digunakan bagi membangunkan model peramalan siri masa bahan pencemar ozon. Penemuan model baharu dalam kajian ini diharap dapat membantu memudahkan usaha pihak-pihak berkepentingan dalam menguruskan isu pencemaran udara, khususnya ozon

On projection methods for functional time series forecasting

Two nonparametric methods are presented for forecasting functional time series (FTS). The FTS we observe is a curve at a discrete-time point. We address both one-step-ahead forecasting and dynamic updating. Dynamic updating is a forward prediction of the unobserved segment of the most recent curve. Among the two proposed methods, the first one is a straightforward adaptation to FTS of the k-nearest neighbors' methods for univariate time series forecasting. The second one is based on a selection of curves, termed the curve envelope, that aims to be representative in shape and magnitude of the most recent functional observation, either a whole curve or the observed part of a partially observed curve. In a similar fashion to k-nearest neighbors and other projection methods successfully used for time series forecasting, we ‘‘project’’ the nearest neighbors and the curves in the envelope for forecasting. In doing so, we keep track of the next period evolution of the curves. The methods are applied to simulated data, daily electricity demand, and NOx emissions and provide competitive results with and often superior to several benchmark predictions. The approach offers a model-free alternative to statistical methods based on FTS modeling to study the cyclic or seasonal behavior of many FTS

Study on premixed combustion characteristics of co-firing ammonia/methane fuels

Ammonia is believed eventually play an important role in substituting conventional fossil fuels for future energy systems. In this study, to gain a deep insight into the combustion properties of co-firing ammonia/methane fuel blends for the power and steel industry, a detailed chemical-kinetics mechanism model was developed for comprehensively modelling ammonia/methane fuels combustion. Characteristics of ignition delay time, unstretched laminar burning velocity and NO, CO2 and CO emissions in the exhaust gas were obtained over a wide range of equivalence ratios and ammonia fractions. High NO emissions will be a main problem as CO and CO2 emissions tend to drop when adding ammonia into methane. To gain a further understanding of the effect of ammonia substituting methane for combustion use, analyses of laminar premixed flame structures were performed. The impact of ammonia substitution was illustrated by analysing relevant specific radicals. Furthermore, to study the combustion characteristics of ammonia/methane under more practical conditions, effects of engine relevant conditions (elevated pressure and initial temperature) were also studied. Results indicate that pressure has a more prominent effect than initial temperature and there is a good potential that unwanted emissions can be reduced significantly under industrial conditions

Parametric uncertainty and sensitivity methods for reacting flows

textA Bayesian framework for quantification of uncertainties has been used to quantify the uncertainty introduced by chemistry models. This framework adopts a probabilistic view to describe the state of knowledge of the chemistry model parameters and simulation results. Given experimental data, this method updates the model parameters' values and uncertainties and propagates that parametric uncertainty into simulations. This study focuses on syngas, a combination in various ratios of H2 and CO, which is the product of coal gasification. Coal gasification promises to reduce emissions by replacing the burning of coal with the less polluting burning of syngas. Despite the simplicity of syngas chemistry models, they nonetheless fail to accurately predict burning rates at high pressure. Three syngas models have been calibrated using laminar flame speed measurements. After calibration the resulting uncertainty in the parameters is propagated forward into the simulation of laminar flame speeds. The model evidence is then used to compare candidate models. Sensitivity studies, in addition to Bayesian methods, can be used to assess chemistry models. Sensitivity studies provide a measure of how responsive target quantities of interest (QoIs) are to changes in the parameters. The adjoint equations have been derived for laminar, incompressible, variable density reacting flow and applied to hydrogen flame simulations. From the adjoint solution, the sensitivity of the QoI to the chemistry model parameters has been calculated. The results indicate the most sensitive parameters for flame tip temperature and NOx emission. Such information can be used in the development of new experiments by pointing out which are the critical chemistry model parameters. Finally, a broader goal for chemistry model development is set through the adjoint methodology. A new quantity, termed field sensitivity, is introduced to guide chemistry model development. Field sensitivity describes how information of perturbations in flowfields propagates to specified QoIs. The field sensitivity, mathematically shown as equivalent to finding the adjoint of the primal governing equations, is obtained for laminar hydrogen flame simulations using three different chemistry models. Results show that even when the primal solution is sufficiently close for the three mechanisms, the field sensitivity can vary.Aerospace Engineerin