Bayesian Statistical Modeling Of System Energy
This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems.
This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents; second for gasification where soot particles are attacked by H 2O or CO 2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumption model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies.
Significant variation is found in the CO 2 gasification rates. Brigham Young Univ., Provo, UT (United States). Univ. Of Utah, Salt Lake City, UT (United States) Publication Date: 2017-08-22 Report Number(s): LA-UR-17-22618 Journal ID: ISSN 0887-0624 Grant/Contract Number: AC52-06NA25396 Type: Accepted Manuscript Journal Name: Energy and Fuels Additional Journal Information: Journal Volume: 31; Journal Issue: 10; Journal ID: ISSN 0887-0624 Publisher: American Chemical Society (ACS) Research Org: Los Alamos National Lab.
(LANL), Los Alamos, NM (United States) Sponsoring Org: USDOE National Nuclear Security Administration (NNSA) Country of Publication: United States Language: English Subject: 01 COAL, LIGNITE, AND PEAT; Soot, Oxidation, Gasification, Bayes' Law OSTI Identifier: 1406214. We present spatial profiles of temperature and soot-volume-fraction statistics from a sooting 2-m base diameter turbulent pool fire, burning a 10%-toluene / 90%-methanol fuel mixture. Dual-pump coherent anti-Stokes Raman scattering and laser-induced incandescence are utilized to obtain radial profiles of temperature and soot probability density functions (pdf) as well as estimates of temperature/soot joint statistics at three vertical heights above the surface of the methanol/toluene fuel pool. Results are presented both in the fuel vapor-dome region at ¼ base diameter and in the actively burning region at ½ and ¾ diameters above the fuel surface. The spatial evolution of the soot and temperature pdfs is discussed and profiles of the temperature and soot mean and rms statistics are provided.
Joint temperature/soot statistics are presented as spatially resolved conditional averages across the fire plume, and in terms of a joint pdf obtained by including measurements from multiple spatial locations. Gasoline particulate filters (GPF) are considered an enabling technology to meet stringent particulate matter (PM) regulations for gasoline direct-injection (GDI) engines, which are known to produce significant PM emissions. While ash loading in filters has been recognized to be detrimental in filter performance by increasing back pressure, increased ash fractions in soot were observed to enhance soot oxidation.
In this study, GDI soot samples derived from different gasoline/lube oil blends were evaluated to identify potential promoting factors when formulated lube oils were dosed into gasoline fuel. Ca-derived ash enhanced soot oxidation remarkably, while P- and ZDDP-derived ash deteriorated soot oxidation. It is apparent that the promoting effect of lube oil-derived ash is due mainly to the Ca component that is the most abundant among additive components in lube oil. Bulk and surface analyses of these ash compounds indicate that Ca-derived ash would be complex compounds, while the contribution of CaSO 4, which is one of the most abundant ash compounds from diesel engines, is almost negligible. For the validation of the ash promoting impact in filters, the regeneration experiments were compared for a TWC-coated GPF in a GDI engine before and after ash loading was performed. The pressure drop of the ash-loaded GPF decreased noticeably in the initial regeneration stage and it increased gradually, whereas that of no ash-loaded GPF increased gradually without any reduction.
So, it is concluded that the ash layer in the GPF assisted soot oxidation in the early regeneration stage when it was in close contact with soot. In this paper, experimental analyses are conducted into the GDI soot oxidation characteristics as dependent on engine operating conditions. Soot is sampled at various engine operating conditions of a commercial 2.4 L GDI engine with a naturally aspirated, homogeneous, and stoichiometric operation strategy. The oxidation reactivity, ash composition, and carbon nanostructure of the GDI soot samples are analyzed using thermogravimetric analysis (TGA), scanning electron microscope–energy-dispersive spectroscopy (SEM-EDS), high-resolution transmission electron microscopy (HR-TEM), and Raman spectroscopy. Based on the analyses, a global GDI soot oxidation mechanism is proposed which includes the effects of soluble organic fractions (SOF)/weakly bonded carbon (WBC), and three types of ash on GDI soot oxidation. The results show that GDI soot contains an order of magnitude higher ash fraction than does conventional diesel soot, and oxidation reactivity is significantly enhanced by the catalytic effects of ash, as a function of ash content in soot. A modified empirical kinetic correlation for GDI soot oxidation is suggested on the basis of the results, and the modified kinetic correlation predicts the GDI soot oxidation rate accurately for various engine operation points at wide ranges of soot conversion and temperature without modifying kinetic parameters.
Bayesian Statistical Modeling Of System Energy System
The kinetic parameters are determined from isothermal and non-isothermal thremogravimetric analysis (TGA) soot oxidation tests; the methods are elucidated in detail. A detailed model is proposed for predicting soot formation from complex solid fuels.
The proposed model resolves two particle size distributions, one for soot precursors and another for soot particles. The precursor size distribution is represented with a sectional approach while the soot particle-size distribution is represented with the method of moments and an interpolative closure method is used to resolve fractional methods. Based on established mechanisms, this model includes submodels for precursor coagulation, growth, and consumption, as well as soot nucleation, surface growth, agglomeration, and consumption. The model is validated with comparisons to experimental data for two systems: coal combustion over a laminar flat-flame burner and biomass gasification. Here, results are presented for soot yield for three coals at three temperatures each, and for soot yield from three types of biomass at two temperatures each.
Finally, these results represent a wide range of fuels and varying combustion environments, demonstrating the broad applicability of the model.