WorldWideScience

Sample records for soot model predictions

  1. Developing a predictive model for the chemical composition of soot nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Violi, Angela [Univ. of Michigan, Ann Arbor, MI (United States); Michelsen, Hope [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Hansen, Nils [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Wilson, Kevin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2017-04-07

    In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed a series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.

  2. Evaluation of a Lagrangian Soot Tracking Method for the prediction of primary soot particle size under engine-like conditions

    DEFF Research Database (Denmark)

    Cai Ong, Jiun; Pang, Kar Mun; Walther, Jens Honore

    2018-01-01

    This paper reports the implementation and evaluation of a Lagrangian soot tracking (LST) method for the modeling of soot in diesel engines. The LST model employed here has the tracking capability of a Lagrangian method and the ability to predict primary soot particle sizing. The Moss-Brookes soot...... in predicting temporal soot cloud development, mean soot diameter and primary soot size distribution is evaluated using measurements of n-heptane and n-dodecane spray combustion obtained under diesel engine-like conditions. In addition, sensitivity studies are carried out to investigate the influence of soot....... A higher rate of soot oxidation due to OH causes the soot particles to be fully oxidized downstream of the flame. In general, the LST model performs better than the Eulerian method in terms of predicting soot sizing and accessing information of individual soot particles, both of which are shortcomings...

  3. Soot formation in a blast furnace - Prediction via a parametric study, using detailed kinetic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Nordstroem, T; Kilpinen, P; Hupa, M [Aabo Akademi, Turku (Finland). Combustion Chemistry Group

    1997-12-31

    The objective of this work has been to investigate the soot formation in a blast furnace fired with heavy fuel oil, using detailed kinetic modelling. This work has been concentrated on parameter studies that could explain under which conditions soot is formed and how that formation could be avoided. The parameters investigated were temperature, pressure, stoichiometric ratio, pyrolysis gas composition and reactor model. The calculations were based on a reaction mechanism that consists of 100 species and 446 reactions including polyaromatic hydrocarbons (PAM) up to 7 aromatic rings SULA 2 Research Programme; 4 refs.

  4. Soot formation in a blast furnace - Prediction via a parametric study, using detailed kinetic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Nordstroem, T.; Kilpinen, P.; Hupa, M. [Aabo Akademi, Turku (Finland). Combustion Chemistry Group

    1996-12-31

    The objective of this work has been to investigate the soot formation in a blast furnace fired with heavy fuel oil, using detailed kinetic modelling. This work has been concentrated on parameter studies that could explain under which conditions soot is formed and how that formation could be avoided. The parameters investigated were temperature, pressure, stoichiometric ratio, pyrolysis gas composition and reactor model. The calculations were based on a reaction mechanism that consists of 100 species and 446 reactions including polyaromatic hydrocarbons (PAM) up to 7 aromatic rings SULA 2 Research Programme; 4 refs.

  5. Prediction of soot and thermal radiation in a model gas turbine combustor burning kerosene fuel spray at different swirl levels

    Science.gov (United States)

    Ghose, Prakash; Patra, Jitendra; Datta, Amitava; Mukhopadhyay, Achintya

    2016-05-01

    Combustion of kerosene fuel spray has been numerically simulated in a laboratory scale combustor geometry to predict soot and the effects of thermal radiation at different swirl levels of primary air flow. The two-phase motion in the combustor is simulated using an Eulerian-Lagragian formulation considering the stochastic separated flow model. The Favre-averaged governing equations are solved for the gas phase with the turbulent quantities simulated by realisable k-ɛ model. The injection of the fuel is considered through a pressure swirl atomiser and the combustion is simulated by a laminar flamelet model with detailed kinetics of kerosene combustion. Soot formation in the flame is predicted using an empirical model with the model parameters adjusted for kerosene fuel. Contributions of gas phase and soot towards thermal radiation have been considered to predict the incident heat flux on the combustor wall and fuel injector. Swirl in the primary flow significantly influences the flow and flame structures in the combustor. The stronger recirculation at high swirl draws more air into the flame region, reduces the flame length and peak flame temperature and also brings the soot laden zone closer to the inlet plane. As a result, the radiative heat flux on the peripheral wall decreases at high swirl and also shifts closer to the inlet plane. However, increased swirl increases the combustor wall temperature due to radial spreading of the flame. The high incident radiative heat flux and the high surface temperature make the fuel injector a critical item in the combustor. The injector peak temperature increases with the increase in swirl flow mainly because the flame is located closer to the inlet plane. On the other hand, a more uniform temperature distribution in the exhaust gas can be attained at the combustor exit at high swirl condition.

  6. Towards predictive simulations of soot formation: from surrogate to turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Blanquart, Guillaume [California Inst. of Technology (CalTech), Pasadena, CA (United States)

    2017-03-28

    The combustion of transportation fuels leads to the formation of several kinds of pollutants, among which are soot particles. These particles, also formed during coal combustion and in fires, are the source of several health problems and environmental issues. Unfortunately, our current understanding of the chemical and physical phenomena leading to the formation of soot particles remains incomplete, and as a result, the predictive capability of our numerical tools is lacking. The objective of the work was to reduce the gap in the present understanding and modeling of soot formation both in laminar and turbulent flames. The effort spanned several length scales from the molecular level to large scale turbulent transport.

  7. Simulation of temporal and spatial soot evolution in an automotive diesel engine using the Moss–Brookes soot model

    International Nuclear Information System (INIS)

    Pang, Kar Mun; Ng, Hoon Kiat; Gan, Suyin

    2012-01-01

    Highlights: ► Numerical models were validated against experimental data of two diesel engines. ► Soot model constant values were calibrated to predict in-cylinder soot processes. ► Effects of split-main injection parameters on soot distributions were determined. ► Soot cloud was distributed towards cylinder wall when using large dwell period. ► Greater soot deposition expected with large dwell period and retarded injection. - Abstract: In this reported work, computational study on the formation processes of soot particles from diesel combustion is conducted using an approach where Computational Fluid Dynamics (CFD) is coupled with a chemical kinetic model. A multi-step soot model which accounts for inception, surface growth, coagulation and oxidation was applied. Model constant values in the Moss–Brookes soot formation and Fenimore–Jones soot oxidation models were calibrated, and were validated against in-cylinder soot evolution and exhaust soot density of both heavy- and light-duty diesel engines, respectively. Effects of various injection parameters such as start of injection (SOI) timing, split-main ratio and dwell period of the split-main injection strategy on in-cylinder temporal/spatial soot evolution in a light-duty diesel engine were subsequently investigated. The spatial soot distributions at each crank angle degree after start of injection were found to be insensitive to the change of values in SOI and split-main ratio when close-coupled injection was implemented. Soot cloud was also observed to be distributed towards the cylinder wall when a large separation of 20° was used, even with an advanced SOI timing of −6° after top dead centre (ATDC). The use of large separation is hence not desired for this combustion system as it potentially leads to soot deposition on surface oil film and greater tailpipe soot emissions.

  8. Empirical soot formation and oxidation model

    Directory of Open Access Journals (Sweden)

    Boussouara Karima

    2009-01-01

    Full Text Available Modelling internal combustion engines can be made following different approaches, depending on the type of problem to be simulated. A diesel combustion model has been developed and implemented in a full cycle simulation of a combustion, model accounts for transient fuel spray evolution, fuel-air mixing, ignition, combustion, and soot pollutant formation. The models of turbulent combustion of diffusion flame, apply to diffusion flames, which one meets in industry, typically in the diesel engines particulate emission represents one of the most deleterious pollutants generated during diesel combustion. Stringent standards on particulate emission along with specific emphasis on size of emitted particulates have resulted in increased interest in fundamental understanding of the mechanisms of soot particulate formation and oxidation in internal combustion engines. A phenomenological numerical model which can predict the particle size distribution of the soot emitted will be very useful in explaining the above observed results and will also be of use to develop better particulate control techniques. A diesel engine chosen for simulation is a version of the Caterpillar 3406. We are interested in employing a standard finite-volume computational fluid dynamics code, KIVA3V-RELEASE2.

  9. Measuring and predicting sooting tendencies of oxygenates, alkanes, alkenes, cycloalkanes, and aromatics on a unified scale

    Energy Technology Data Exchange (ETDEWEB)

    Das, Dhrubajyoti D.; St. John, Peter C.; McEnally, Charles S.; Kim, Seonah; Pfefferle, Lisa D.

    2018-04-01

    Databases of sooting indices, based on measuring some aspect of sooting behavior in a standardized combustion environment, are useful in providing information on the comparative sooting tendencies of different fuels or pure compounds. However, newer biofuels have varied chemical structures including both aromatic and oxygenated functional groups, which expands the chemical space of relevant compounds. In this work, we propose a unified sooting tendency database for pure compounds, including both regular and oxygenated hydrocarbons, which is based on combining two disparate databases of yield-based sooting tendency measurements in the literature. Unification of the different databases was made possible by leveraging the greater dynamic range of the color ratio pyrometry soot diagnostic. This unified database contains a substantial number of pure compounds (greater than or equal to 400 total) from multiple categories of hydrocarbons important in modern fuels and establishes the sooting tendencies of aromatic and oxygenated hydrocarbons on the same numeric scale for the first time. Using this unified sooting tendency database, we have developed a predictive model for sooting behavior applicable to a broad range of hydrocarbons and oxygenated hydrocarbons. The model decomposes each compound into single-carbon fragments and assigns a sooting tendency contribution to each fragment based on regression against the unified database. The model's predictive accuracy (as demonstrated by leave-one-out cross-validation) is comparable to a previously developed, more detailed predictive model. The fitted model provides insight into the effects of chemical structure on soot formation, and cases where its predictions fail reveal the presence of more complicated kinetic sooting mechanisms. This work will therefore enable the rational design of low-sooting fuel blends from a wide range of feedstocks and chemical functionalities.

  10. Understanding and predicting soot generation in turbulent non-premixed jet flames.

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hai (University of Southern California, Los Angeles, CA); Kook, Sanghoon; Doom, Jeffrey; Oefelein, Joseph Charles; Zhang, Jiayao; Shaddix, Christopher R.; Schefer, Robert W.; Pickett, Lyle M.

    2010-10-01

    This report documents the results of a project funded by DoD's Strategic Environmental Research and Development Program (SERDP) on the science behind development of predictive models for soot emission from gas turbine engines. Measurements of soot formation were performed in laminar flat premixed flames and turbulent non-premixed jet flames at 1 atm pressure and in turbulent liquid spray flames under representative conditions for takeoff in a gas turbine engine. The laminar flames and open jet flames used both ethylene and a prevaporized JP-8 surrogate fuel composed of n-dodecane and m-xylene. The pressurized turbulent jet flame measurements used the JP-8 surrogate fuel and compared its combustion and sooting characteristics to a world-average JP-8 fuel sample. The pressurized jet flame measurements demonstrated that the surrogate was representative of JP-8, with a somewhat higher tendency to soot formation. The premixed flame measurements revealed that flame temperature has a strong impact on the rate of soot nucleation and particle coagulation, but little sensitivity in the overall trends was found with different fuels. An extensive array of non-intrusive optical and laser-based measurements was performed in turbulent non-premixed jet flames established on specially designed piloted burners. Soot concentration data was collected throughout the flames, together with instantaneous images showing the relationship between soot and the OH radical and soot and PAH. A detailed chemical kinetic mechanism for ethylene combustion, including fuel-rich chemistry and benzene formation steps, was compiled, validated, and reduced. The reduced ethylene mechanism was incorporated into a high-fidelity LES code, together with a moment-based soot model and models for thermal radiation, to evaluate the ability of the chemistry and soot models to predict soot formation in the jet diffusion flame. The LES results highlight the importance of including an optically-thick radiation

  11. Investigation of mass and energy coupling between soot particles and gas species in modelling ethylene counterflow diffusion flames

    NARCIS (Netherlands)

    Zimmer, L.; Pereira, F.M.; van Oijen, J.A.; de Goey, L.P.H.

    2017-01-01

    A numerical model is developed aiming at investigating soot formation in ethylene counterflow diffusion flames. The mass and energy coupling between soot solid particles and gas-phase species is investigated in detail. A semi-empirical two-equation model is chosen for predicting soot mass fraction

  12. A Phenomenological Model for Prediction Auto-Ignition and Soot Formation of Turbulent Diffusion Combustion in a High Pressure Common Rail Diesel Engine

    Directory of Open Access Journals (Sweden)

    Qinghui Zhou

    2011-06-01

    Full Text Available A new phenomenological model, the TP (Temperature Phase model, is presented to carry out optimization calculations for turbulent diffusion combustion in a high-pressure common rail diesel engine. Temperature is the most important parameter in the TP model, which includes two parts: an auto-ignition and a soot model. In the auto-ignition phase, different reaction mechanisms are built for different zones. For the soot model, different methods are used for different temperatures. The TP model is then implemented in KIVA code instead of original model to carry out optimization. The results of cylinder pressures, the corresponding heat release rates, and soot with variation of injection time, variation of rail pressure and variation of speed among TP model, KIVA standard model and experimental data are analyzed. The results indicate that the TP model can carry out optimization and CFD (computational fluid dynamics and can be a useful tool to study turbulent diffusion combustion.

  13. Molecular mechanics and quantum mechanical modeling of hexane soot structure and interactions with pyrene

    Directory of Open Access Journals (Sweden)

    Kubicki JD

    2000-09-01

    Full Text Available Molecular simulations (energy minimizations and molecular dynamics of an n-hexane soot model developed by Smith and co-workers (M. S. Akhter, A. R. Chughtai and D. M. Smith, Appl. Spectrosc., 1985, 39, 143; ref. 1 were performed. The MM+ (N. L. Allinger, J. Am. Chem. Soc., 1977, 395, 157; ref. 2 and COMPASS (H. Sun, J. Phys. Chem., 1998, 102, 7338; ref. 3 force fields were tested for their ability to produce realistic soot nanoparticle structure. The interaction of pyrene with the model soot was simulated. Quantum mechanical calculations on smaller soot fragments were carried out. Starting from an initial 2D structure, energy minimizations are not able to produce the observed layering within soot with either force field. Results of molecular dynamics simulations indicate that the COMPASS force field does a reasonably accurate job of reproducing observations of soot structure. Increasing the system size from a 683 to a 2732 atom soot model does not have a significant effect on predicted structures. Neither does the addition of water molecules surrounding the soot model. Pyrene fits within the soot structure without disrupting the interlayer spacing. Polycyclic aromatic hydrocarbons (PAH, such as pyrene, may strongly partition into soot and have slow desorption kinetics because the PAH-soot bonding is similar to soot–soot interactions. Diffusion of PAH into soot micropores may allow the PAH to be irreversibly adsorbed and sequestered so that they partition slowly back into an aqueous phase causing dis-equilibrium between soil organic matter and porewater.

  14. T-matrix modeling of linear depolarization by morphologically complex soot and soot-containing aerosols

    International Nuclear Information System (INIS)

    Mishchenko, Michael I.; Liu, Li; Mackowski, Daniel W.

    2013-01-01

    We use state-of-the-art public-domain Fortran codes based on the T-matrix method to calculate orientation and ensemble averaged scattering matrix elements for a variety of morphologically complex black carbon (BC) and BC-containing aerosol particles, with a special emphasis on the linear depolarization ratio (LDR). We explain theoretically the quasi-Rayleigh LDR peak at side-scattering angles typical of low-density soot fractals and conclude that the measurement of this feature enables one to evaluate the compactness state of BC clusters and trace the evolution of low-density fluffy fractals into densely packed aggregates. We show that small backscattering LDRs measured with ground-based, airborne, and spaceborne lidars for fresh smoke generally agree with the values predicted theoretically for fluffy BC fractals and densely packed near-spheroidal BC aggregates. To reproduce higher lidar LDRs observed for aged smoke, one needs alternative particle models such as shape mixtures of BC spheroids or cylinders. -- Highlights: ► New superposition T-matrix code is applied to soot aerosols. ► Quasi-Rayleigh side-scattering peak in linear depolarization (LD) is explained. ► LD measurements can be used for morphological characterization of soot aerosols

  15. Numerical modeling of soot formation in a turbulent C2H4/air diffusion flame

    Directory of Open Access Journals (Sweden)

    Manedhar Reddy Busupally

    2016-06-01

    Full Text Available Soot formation in a lifted C2H4-Air turbulent diffusion flame is studied using two different paths for soot nucleation and oxidation; by a 2D axisymmetric RANS simulation using ANSYS FLUENT 15.0. The turbulence-chemistry interactions are modeled using two different approaches: steady laminar flamelet approach and flamelet-generated manifold. Chemical mechanism is represented by POLIMI to study the effect of species concentration on soot formation. P1 approximation is employed to approximate the radiative transfer equation into truncated series expansion in spherical harmonics while the weighted sum of gray gases is invoked to model the absorption coefficient while the soot model accounts for nucleation, coagulation, surface growth, and oxidation. The first route for nucleation considers acetylene concentration as a linear function of soot nucleation rate, whereas the second route considers two and three ring aromatic species as function of nucleation rate. Equilibrium-based and instantaneous approach has been used to estimate the OH concentration for soot oxidation. Lee and Fenimore-Jones soot oxidation models are studied to shed light on the effect of OH on soot oxidation. Moreover, the soot-radiation interactions are also included in terms of absorption coefficient of soot. Furthermore, the soot-turbulence interactions have been invoked using a temperature/mixture fraction-based single variable PDF. Both the turbulence-chemistry interaction models are able to accurately predict the flame liftoff height, and for accurate prediction of flame length, radiative heat loss should be accounted in an accurate way. The soot-turbulence interactions are found sensitive to the PDF used in present study.

  16. Modelling thermal radiation and soot formation in buoyant diffusion flames

    International Nuclear Information System (INIS)

    Demarco Bull, R.A.

    2012-01-01

    The radiative heat transfer plays an important role in fire problems since it is the dominant mode of heat transfer between flames and surroundings. It controls the pyrolysis, and therefore the heat release rate, and the growth rate of the fire. In the present work a numerical study of buoyant diffusion flames is carried out, with the main objective of modelling the thermal radiative transfer and the soot formation/destruction processes. In a first step, different radiative property models were tested in benchmark configurations. It was found that the FSCK coupled with the Modest and Riazzi mixing scheme was the best compromise in terms of accuracy and computational requirements, and was a good candidate to be implemented in CFD codes dealing with fire problems. In a second step, a semi-empirical soot model, considering acetylene and benzene as precursor species for soot nucleation, was validated in laminar co flow diffusion flames over a wide range of hydrocarbons (C1-C3) and conditions. In addition, the optically-thin approximation was found to produce large discrepancies in the upper part of these small laminar flames. Reliable predictions of soot volume fractions require the use of an advanced radiation model. Then the FSCK and the semi-empirical soot model were applied to simulate laboratory-scale and intermediate-scale pool fires of methane and propane. Predicted flame structures as well as the radiant heat flux transferred to the surroundings were found to be in good agreement with the available experimental data. Finally, the interaction between radiation and turbulence was quantified. (author)

  17. Numerical investigation on soot particles emission in compression ignition diesel engine by using particulate mimic soot model

    Directory of Open Access Journals (Sweden)

    Ibrahim Fadzli

    2017-01-01

    Full Text Available Research via computational method, specifically by detailed-kinetic soot model offers much more advantages than the simple model as more detailed formation/oxidation process is taken into consideration, thus providing better soot mass concentration, soot size, soot number density as well as information regarding other related species. In the present computational study, investigation of in-cylinder soot concentration as well as other emissions in a single cylinder diesel engine has been conducted, using a commercial multidimensional CFD software, CONVERGE CFD. The simulation was carried out for a close-cycle combustion environment from inlet valve closing (IVC to exhaust valve opening (EVO. In this case, detailed-kinetic Particulate Mimic (PM soot model was implemented as to take benefit of the method of moment, instead of commonly implemented simple soot model. Analyses of the results are successfully plotted to demonstrate that the soot size and soot mass concentration are strongly dependent on the detailed soot formation and oxidation process rates. The calculated of soot mass concentration and average soot size at EVO provide the end value of 29.2 mg/m3 and 2.04 × 10−8 m, respectively. Besides, post-processing using EnSight shows the qualitative results of soot concentration along simulation period in the combustion chamber.

  18. Implementation of two-equation soot flamelet models for laminar diffusion flames

    Energy Technology Data Exchange (ETDEWEB)

    Carbonell, D.; Oliva, A.; Perez-Segarra, C.D. [Centre Tecnologic de Transferencia de Calor (CTTC), Universitat Politecnica de Catalunya (UPC), ETSEIAT, Colom 11, E-08222, Terrassa (Barcelona) (Spain)

    2009-03-15

    The two-equation soot model proposed by Leung et al. [K.M. Leung, R.P. Lindstedt, W.P. Jones, Combust. Flame 87 (1991) 289-305] has been derived in the mixture fraction space. The model has been implemented using both Interactive and Non-Interactive flamelet strategies. An Extended Enthalpy Defect Flamelet Model (E-EDFM) which uses a flamelet library obtained neglecting the soot formation is proposed as a Non-Interactive method. The Lagrangian Flamelet Model (LFM) is used to represent the Interactive models. This model uses direct values of soot mass fraction from flamelet calculations. An Extended version (E-LFM) of this model is also suggested in which soot mass fraction reaction rates are used from flamelet calculations. Results presented in this work show that the E-EDFM predict acceptable results. However, it overpredicts the soot volume fraction due to the inability of this model to couple the soot and gas-phase mechanisms. It has been demonstrated that the LFM is not able to predict accurately the soot volume fraction. On the other hand, the extended version proposed here has been shown to be very accurate. The different flamelet mathematical formulations have been tested and compared using well verified reference calculations obtained solving the set of the Full Transport Equations (FTE) in the physical space. (author)

  19. Sooting Characteristics and Modeling in Counterflow Diffusion Flames

    KAUST Repository

    Wang, Yu

    2013-11-01

    Soot formation is one of the most complex phenomena in combustion science and an understanding of the underlying physico-chemical mechanisms is important. This work adopted both experimental and numerical approaches to study soot formation in laminar counterfl ow diffusion flames. As polycyclic aromatic hydrocarbons (PAHs) are the precursors of soot particles, a detailed gas-phase chemical mechanism describing PAH growth upto coronene for fuels with 1 to 4 carbon atoms was validated against laminar premixed and counter- flow diffusion fl ames. Built upon this gas-phase mechanism, a soot model was then developed to describe soot inception and surface growth. This soot model was sub- sequently used to study fuel mixing effect on soot formation in counterfl ow diffusion flames. Simulation results showed that compared to the baseline case of the ethylene flame, the doping of 5% (by volume) propane or ethane in ethylene tends to increase the soot volume fraction and number density while keeping the average soot size almost unchanged. These results are in agreement with experimental observations. Laser light extinction/scattering as well as laser induced fluorescence techniques were used to study the effect of strain rate on soot and PAH formation in counterfl ow diffusion ames. The results showed that as strain rate increased both soot volume fraction and PAH concentrations decreased. The concentrations of larger PAH were more sensitive to strain rate compared to smaller ones. The effect of CO2 addition on soot formation was also studied using similar experimental techniques. Soot loading was reduced with CO2 dilution. Subsequent numerical modeling studies were able to reproduce the experimental trend. In addition, the chemical effect of CO2 addition was analyzed using numerical data. Critical conditions for the onset of soot were systematically studied in counterfl ow diffusion ames for various gaseous hydrocarbon fuels and at different strain rates. A sooting

  20. Evaluation and optimisation of phenomenological multi-step soot model for spray combustion under diesel engine-like operating conditions

    Science.gov (United States)

    Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song; Schramm, Jesper

    2015-05-01

    In this work, a two-dimensional computational fluid dynamics study is reported of an n-heptane combustion event and the associated soot formation process in a constant volume combustion chamber. The key interest here is to evaluate the sensitivity of the chemical kinetics and submodels of a semi-empirical soot model in predicting the associated events. Numerical computation is performed using an open-source code and a chemistry coordinate mapping approach is used to expedite the calculation. A library consisting of various phenomenological multi-step soot models is constructed and integrated with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases with ambient temperature lower than 850 K. The variation of the soot precursor production with respect to the change of ambient oxygen levels qualitatively agrees with that of the conceptual models when the skeletal n-heptane mechanism is integrated with a reduced pyrene chemistry. Subsequently, a comprehensive sensitivity analysis is carried out to appraise the existing soot formation and oxidation submodels. It is revealed that the soot formation is captured when the surface growth rate is calculated using a square root function of the soot specific surface area and when a pressure-dependent model constant is considered. An optimised soot model is then proposed based on the knowledge gained through this exercise. With the implementation of optimised model, the simulated soot onset and transport phenomena before reaching quasi-steady state agree reasonably well with the experimental observation. Also, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced.

  1. T-matrix modeling of linear depolarization by morphologically complex soot and soot-containing aerosols

    Science.gov (United States)

    Mishchenko, Michael I.; Liu, Li; Mackowski, Daniel W.

    2013-07-01

    We use state-of-the-art public-domain Fortran codes based on the T-matrix method to calculate orientation and ensemble averaged scattering matrix elements for a variety of morphologically complex black carbon (BC) and BC-containing aerosol particles, with a special emphasis on the linear depolarization ratio (LDR). We explain theoretically the quasi-Rayleigh LDR peak at side-scattering angles typical of low-density soot fractals and conclude that the measurement of this feature enables one to evaluate the compactness state of BC clusters and trace the evolution of low-density fluffy fractals into densely packed aggregates. We show that small backscattering LDRs measured with ground-based, airborne, and spaceborne lidars for fresh smoke generally agree with the values predicted theoretically for fluffy BC fractals and densely packed near-spheroidal BC aggregates. To reproduce higher lidar LDRs observed for aged smoke, one needs alternative particle models such as shape mixtures of BC spheroids or cylinders.

  2. Steady State Investigations of DPF Soot Burn Rates and DPF Modeling

    DEFF Research Database (Denmark)

    Cordtz, Rasmus Lage; Ivarsson, Anders; Schramm, Jesper

    2011-01-01

    and soot mass concentrations are used as model boundary conditions. An in-house developed raw exhaust gas sampling technique is used to measure the soot concentration upstream the DPF which is also needed to find the DPF soot burn rate. The soot concentration is measured basically by filtering the soot...... characteristics are used to fit model constants of soot and filter properties. Measured DPF gas conversions and soot burn rates are used to fit model activation energies of four DPF regeneration reactions using O2 and NO2 as reactants. Modeled DPF pressure drops and soot burn rates are compared to the steady...... state DPF experiments in the temperature range between 260 and 480 °C. The model widely reproduces the experimental results. Especially the exponential soot burn rate versus temperature is accurately reproduced by the model....

  3. Numerical Modelling of Soot Formation in Laminar Axisymmetric Ethylene-Air Coflow Flames at Atmospheric and Elevated Pressures

    KAUST Repository

    Rakha, Ihsan Allah

    2015-05-01

    The steady coflow diffusion flame is a widely used configuration for studying combustion kinetics, flame dynamics, and pollutant formation. In the current work, a set of diluted ethylene-air coflow flames are simulated to study the formation, growth, and oxidation of soot, with a focus on the effects of pressure on soot yield. Firstly, we assess the ability of a high performance CFD solver, coupled with detailed transport and kinetic models, to reproduce experimental measurements, like the temperature field, the species’ concentrations and the soot volume fraction. Fully coupled conservation equations for mass, momentum, energy, and species mass fractions are solved using a low Mach number formulation. Detailed finite rate chemistry describing the formation of Polycyclic Aromatic Hydrocarbons up to cyclopenta[cd]pyrene is used. Soot is modeled using a moment method and the resulting moment transport equations are solved with a Lagrangian numerical scheme. Numerical and experimental results are compared for various pressures. Reasonable agreement is observed for the flame height, temperature, and the concentrations of various species. In each case, the peak soot volume fraction is predicted along the centerline as observed in the experiments. The predicted integrated soot mass at pressures ranging from 4-8 atm, scales as P2.1, in satisfactory agreement with the measured integrated soot pressure scaling (P2.27). Significant differences in the mole fractions of benzene and PAHs, and the predicted soot volume fractions are found, using two well-validated chemical kinetic mechanisms. At 4 atm, one mechanism over-predicts the peak soot volume fraction by a factor of 5, while the other under-predicts it by a factor of 5. A detailed analysis shows that the fuel tube wall temperature has an effect on flame stabilization.

  4. Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels

    KAUST Repository

    Wang, Yu; Raj, Abhijeet Dhayal; Chung, Suk-Ho

    2015-01-01

    of ethylene and its binary mixtures with methane, ethane and propane based on the method of moments. The soot model has 36 soot nucleation reactions from 8 PAH molecules including pyrene and larger PAHs. Soot surface growth reactions were based on a modified

  5. NOx, Soot, and Fuel Consumption Predictions under Transient Operating Cycle for Common Rail High Power Density Diesel Engines

    Directory of Open Access Journals (Sweden)

    N. H. Walke

    2016-01-01

    Full Text Available Diesel engine is presently facing the challenge of controlling NOx and soot emissions on transient cycles, to meet stricter emission norms and to control emissions during field operations. Development of a simulation tool for NOx and soot emissions prediction on transient operating cycles has become the most important objective, which can significantly reduce the experimentation time and cost required for tuning these emissions. Hence, in this work, a 0D comprehensive predictive model has been formulated with selection and coupling of appropriate combustion and emissions models to engine cycle models. Selected combustion and emissions models are further modified to improve their prediction accuracy in the full operating zone. Responses of the combustion and emissions models have been validated for load and “start of injection” changes. Model predicted transient fuel consumption, air handling system parameters, and NOx and soot emissions are in good agreement with measured data on a turbocharged high power density common rail engine for the “nonroad transient cycle” (NRTC. It can be concluded that 0D models can be used for prediction of transient emissions on modern engines. How the formulated approach can also be extended to transient emissions prediction for other applications and fuels is also discussed.

  6. Stochastic Simulation of Soot Formation Evolution in Counterflow Diffusion Flames

    Directory of Open Access Journals (Sweden)

    Xiao Jiang

    2018-01-01

    Full Text Available Soot generally refers to carbonaceous particles formed during incomplete combustion of hydrocarbon fuels. A typical simulation of soot formation and evolution contains two parts: gas chemical kinetics, which models the chemical reaction from hydrocarbon fuels to soot precursors, that is, polycyclic aromatic hydrocarbons or PAHs, and soot dynamics, which models the soot formation from PAHs and evolution due to gas-soot and soot-soot interactions. In this study, two detailed gas kinetic mechanisms (ABF and KM2 have been compared during the simulation (using the solver Chemkin II of ethylene combustion in counterflow diffusion flames. Subsequently, the operator splitting Monte Carlo method is used to simulate the soot dynamics. Both the simulated data from the two mechanisms for gas and soot particles are compared with experimental data available in the literature. It is found that both mechanisms predict similar profiles for the gas temperature and velocity, agreeing well with measurements. However, KM2 mechanism provides much closer prediction compared to measurements for soot gas precursors. Furthermore, KM2 also shows much better predictions for soot number density and volume fraction than ABF. The effect of nozzle exit velocity on soot dynamics has also been investigated. Higher nozzle exit velocity renders shorter residence time for soot particles, which reduces the soot number density and volume fraction accordingly.

  7. Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels

    KAUST Repository

    Wang, Yu

    2015-03-01

    A soot model was developed based on the recently proposed PAH growth mechanism for C1-C4 gaseous fuels (KAUST PAH Mechanism 2, KM2) that included molecular growth up to coronene (A7) to simulate soot formation in counterflow diffusion flames of ethylene and its binary mixtures with methane, ethane and propane based on the method of moments. The soot model has 36 soot nucleation reactions from 8 PAH molecules including pyrene and larger PAHs. Soot surface growth reactions were based on a modified hydrogen-abstraction-acetylene-addition (HACA) mechanism in which CH3, C3H3 and C2H radicals were included in the hydrogen abstraction reactions in addition to H atoms. PAH condensation on soot particles was also considered. The experimentally measured profiles of soot volume fraction, number density, and particle size were well captured by the model for the baseline case of ethylene along with the cases involving mixtures of fuels. The simulation results, which were in qualitative agreement with the experimental data in the effects of binary fuel mixing on the sooting structures of the measured flames, showed in particular that 5% addition of propane (ethane) led to an increase in the soot volume fraction of the ethylene flame by 32% (6%), despite the fact that propane and ethane are less sooting fuels than is ethylene, which is in reasonable agreement with experiments of 37% (14%). The model revealed that with 5% addition of methane, there was an increase of 6% in the soot volume fraction. The average soot particle sizes were only minimally influenced while the soot number densities were increased by the fuel mixing. Further analysis of the numerical data indicated that the chemical cross-linking effect between ethylene and the dopant fuels resulted in an increase in PAH formation, which led to higher soot nucleation rates and therefore higher soot number densities. On the other hand, the rates of soot surface growth per unit surface area through the HACA mechanism were

  8. Soot Formation Modeling of n-dodecane and Diesel Sprays under Engine-Like Conditions

    DEFF Research Database (Denmark)

    Pang, Kar Mun; Poon, Hiew Mun; Ng, Hoon Kiat

    2015-01-01

    This work concerns the modelling of soot formation process in diesel spray combustion under engine-like conditions. The key aim is to investigate the soot formation characteristics at different ambient temperatures. Prior to simulating the diesel combustion, numerical models including a revised...

  9. Comprehensive Laser-induced Incandescence (LII) modeling for soot particle sizing

    KAUST Repository

    Lisanti, Joel

    2015-03-30

    To evaluate the current state of the art in LII particle sizing, a comprehensive model for predicting the temporal incandescent response of combustion-generated soot to absorption of a pulsed laser is presented. The model incorporates particle heating through laser absorption, thermal annealing, and oxidation at the surface as well as cooling through sublimation and photodesorption, radiation, conduction and thermionic emission. Thermodynamic properties and the thermal accommodation coefficient utilized in the model are temperature dependent. In addition, where appropriate properties are also phase dependent, thereby accounting for annealing effects during laser heating and particle cooling.

  10. A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)

    KAUST Repository

    Skeen, Scott A.

    2016-04-05

    The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

  11. A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)

    KAUST Repository

    Skeen, Scott A.; Manin, Julien; Pickett, Lyle M.; Cenker, Emre; Bruneaux, Gilles; Kondo, Katsufumi; Aizawa, Tets; Westlye, Fredrik; Dalen, Kristine; Ivarsson, Anders; Xuan, Tiemin; Garcia-Oliver, Jose M; Pei, Yuanjiang; Som, Sibendu; Hu, Wang; Reitz, Rolf D.; Lucchini, Tommaso; D'Errico, Gianluca; Farrace, Daniele; Pandurangi, Sushant S.; Wright, Yuri M.; Chishty, Muhammad Aqib; Bolla, Michele; Hawkes, Evatt

    2016-01-01

    The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

  12. Molecular modelling investigations on the possibility of phenanthrene dimers to be the primary nuclei of soot

    Science.gov (United States)

    Wei, Mingrui; Wu, Sheng; Li, Fan; Zhang, Dongju; Zhang, Tingting; Guo, Guanlun

    2017-11-01

    Pyrene dimerisation was successfully used to model the beginning of soot nucleation in some simulation models. However, the quantum mechanics (QM) calculations proved that the binding energy of a PAH dimer with three six-member rings was similar to that of a pyrene dimer. Meanwhile, the high concentration of phenanthrene at flame conditions indicated high probability of collisions among them. The small difference of the binding energy and high concentration indicated that PAHs structurally smaller than pyrene also could be involved in soot inception. Hence, binary collisions of phenanthrene were simulated to find out whether phenanthrene dimers can serve as soot primary nuclei or not by using non-equilibrium molecular dynamics (MD). Three temperatures, six collision orientations and 155 initial translational velocities (ITVs) were considered. The results indicated that the number of dimers with lifetime over 10 ps which can serve as soot nuclei decreased from 52 at 1000 K to 17 at 1600 K, and further to 6 at 2400 K, which means that low temperature was more favourable for phenanthrene to form soot nuclei. Meanwhile, no soot nuclei were formed at the high velocity region (HVR), compared to 43 and 9 at low and middle velocity regions (LVR and MVR), respectively, when temperature was 1000 K. Also, no soot nuclei were formed at HVR when the temperature was raised to 1600 K and 2400 K. This indicated that HVR was unfavourable for phenanthrene to form soot nuclei. The results computationally further illustrated that small PAHs such as phenanthrene could serve as soot primary nuclei, since they have similar mole fractions in some flames. This may be useful for future soot simulation models.

  13. Asymptotic analysis soot model and experiment for a directed injection engine

    Science.gov (United States)

    Liu, Yongfeng; Pei, Pucheng; Xiong, Qinghui; Lu, Yong

    2012-09-01

    The existing soot models are either too complex and can not be applied to the internal combustion engine, or too simple to make calculation errors. Exploring the soot model becomes the pursuit of the goal of many researchers within the error range in the current computer speed. On the basis of the latest experimental results, TP (temperature phases) model is presented as a new soot model to carry out optimization calculation for a high-pressure common rail diesel engine. Temperature and excess air factor are the most important two parameters in this model. When zone temperature T0.6, only the soot precursors—polycyclic aromatic hydrocarbons(PAH) is created and there is no soot emission. When zone temperature T ⩾ 1 500 K and excess air factor Φinjection time, variation of rail pressure and variation of speed among TP models. The experimental results indicate that the TP model can carry out optimization and computational fluid dynamics can be a tool to calculate for a high-pressure common rail directed injection diesel engine. The TP model result is closer than the use of the original KIVA-3V results of soot model accuracy by about 50% and TP model gives a new method for engine researchers.

  14. Experimental and computational investigation of temperature effects on soot mechanisms

    Directory of Open Access Journals (Sweden)

    Bi Xiaojie

    2014-01-01

    Full Text Available Effects of initial ambient temperatures on combustion and soot emission characteristics of diesel fuel were investigated through experiment conducted in optical constant volume chamber and simulation using phenomenological soot model. There are four difference initial ambient temperatures adopted in our research: 1000 K, 900 K, 800 K and 700 K. In order to obtain a better prediction of soot behavior, phenomenological soot model was revised to take into account the soot oxidation feedback on soot number density and good agreement was observed in the comparison of soot measurement and prediction. Results indicated that ignition delay prolonged with the decrease of initial ambient temperature. The heat release rate demonstrated the transition from mixing controlled combustion at high ambient temperature to premixed combustion mode at low ambient temperature. At lower ambient temperature, soot formation and oxidation mechanism were both suppressed. But finally soot mass concentration reduced with decreasing initial ambient temperature. Although the drop in ambient temperature did not cool the mean in-cylinder temperature during the combustion, it did shrink the total area of local high equivalence ratio, in which soot usually generated fast. At 700 K initial ambient temperature, soot emissions were almost negligible, which indicates that sootless combustion might be achieved at super low initial temperature operation conditions.

  15. Validation of an LES Model for Soot Evolution against DNS Data in Turbulent Jet Flames

    Science.gov (United States)

    Mueller, Michael

    2012-11-01

    An integrated modeling approach for soot evolution in turbulent reacting flows is validated against three-dimensional Direct Numerical Simulation (DNS) data in a set of n-heptane nonpremixed temporal jet flames. As in the DNS study, the evolution of the soot population is described statistically with the Hybrid Method of Moments (HMOM). The oxidation of the fuel and formation of soot precursors are described with the Radiation Flamelet/Progress Variable (RFPV) model that includes an additional transport equation for Polycyclic Aromatic Hydrocarbons (PAH) to account for the slow chemistry governing these species. In addition, the small-scale interactions between soot, chemistry, and turbulence are described with a presumed subfilter PDF approach that accounts for the very large spatial intermittency characterizing soot in turbulent reacting flows. The DNS dataset includes flames at three different Damköhler numbers to study the influence of global mixing rates on the evolution of PAH and soot. In this work, the ability of the model to capture these trends quantitatively as Damköhler number varies is investigated. In order to reliably assess the LES approach, the LES is initialized from the filtered DNS data after an initial transitional period in an effort to minimize the hydrodynamic differences between the DNS and the LES.

  16. Particulate matter emission modelling based on soot and SOF from direct injection diesel engines

    International Nuclear Information System (INIS)

    Tan, P.Q.; Hu, Z.Y.; Deng, K.Y.; Lu, J.X.; Lou, D.M.; Wan, G.

    2007-01-01

    Particulate matter (PM) emission is one of the major pollutants from diesel engines, and it is harmful for human health and influences the atmospheric visibility. In investigations for reducing PM emission, a simulation model for PM emission is a useful tool. In this paper, a phenomenological, composition based PM model of direct injection (DI) diesel engines has been proposed and formulated to simulate PM emission. The PM emission model is based on a quasi-dimensional multi-zone combustion model using the formation mechanisms of the two main compositions of PM: soot and soluble organic fraction (SOF). First, the quasi-dimensional multi-zone combustion model is given. Then, two models for soot and SOF emissions are established, respectively, and after that, the two models are integrated into a single PM emission model. The soot emission model is given by the difference between a primary formation model and an oxidation model of soot. The soot primary formation model is the Hiroyasu soot formation model, and the Nagle and Strickland-Constable model is adopted for soot oxidation. The SOF emission model is based on an unburned hydrocarbons (HC) emission model, and the HC emission model is given by the difference between a HC primary formation model and a HC oxidation model. The HC primary formation model considers fuel injected and mixed beyond the lean combustion limit during ignition delay and fuel effusing from the nozzle sac volume at low pressure and low velocity. In order to validate the PM emission model, experiments were performed on a six cylinder, turbocharged and intercooled DI diesel engine. The simulation results show good agreement with the experimental data, which indicates the validity of the PM emission model. The calculation results show that the distinctions between PM and soot formation rates are mainly in the early combustion stage. The SOF formation has an important influence on the PM formation at lower loads, and soot formation dominates the

  17. Development of high fidelity soot aerosol dynamics models using method of moments with interpolative closure

    KAUST Repository

    Roy, Subrata P.

    2014-01-28

    The method of moments with interpolative closure (MOMIC) for soot formation and growth provides a detailed modeling framework maintaining a good balance in generality, accuracy, robustness, and computational efficiency. This study presents several computational issues in the development and implementation of the MOMIC-based soot modeling for direct numerical simulations (DNS). The issues of concern include a wide dynamic range of numbers, choice of normalization, high effective Schmidt number of soot particles, and realizability of the soot particle size distribution function (PSDF). These problems are not unique to DNS, but they are often exacerbated by the high-order numerical schemes used in DNS. Four specific issues are discussed in this article: the treatment of soot diffusion, choice of interpolation scheme for MOMIC, an approach to deal with strongly oxidizing environments, and realizability of the PSDF. General, robust, and stable approaches are sought to address these issues, minimizing the use of ad hoc treatments such as clipping. The solutions proposed and demonstrated here are being applied to generate new physical insight into complex turbulence-chemistry-soot-radiation interactions in turbulent reacting flows using DNS. © 2014 Copyright Taylor and Francis Group, LLC.

  18. AKTIS Nr. 12: To better understand radioactive aerosol deposit in order to better measure it; Radio-induced lesions: a new step towards healing; Modelling the collapse of an immersed grain column; To better model soot deposit; Towards the prediction of the leakage rate of containment enclosures

    International Nuclear Information System (INIS)

    Benderitter, Marc; Perales, Frederic; Monerie, Yann; Maro, Denis; Boyer, Patrick; Lemaitre, Pascal; Porcheron, Emmanuel; Depuydt, Guillaume; Masson, Olivier; Gensdarmes, Francois

    2013-04-01

    This publication presents the main results of researches undertaken by the IRSN in the field of radiation protection, nuclear safety and security. The topics herein addressed are: radio-induced lesions as a new step towards healing (case of injection mesenchymal stem cells for the treatment of induced severe colorectal lesions), the modelling of the collapse of an immersed grain column (to study the nuclear fuel behaviour in an accidental situation through a modelling of fluid-grain interactions), a better understanding of radioactive aerosol deposit (to study particle or aerosol deposits after radioactive releases in the atmosphere in case of accident), a better modelling of soot deposits (in case of fire), the prediction of leakage rates of containment enclosures (ageing phenomena of installations, systems and equipment, with the case of cracks due to material ageing and resulting in confinement losses which could thus be quantified)

  19. Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

    Directory of Open Access Journals (Sweden)

    Yanting Du

    2018-02-01

    Full Text Available In order to estimate the diesel particulate filter (DPF soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF. The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

  20. Modeling annual benzene, toluene, NO2, and soot concentrations on the basis of road traffic characteristics

    International Nuclear Information System (INIS)

    Carr, David; Ehrenstein, Ondine von; Weiland, Stephan; Wagner, Claudia; Wellie, Oliver; Nicolai, Thomas; Mutius, Erika von

    2002-01-01

    The investigation of potential adverse health effects of urban traffic-related air pollution is hampered by difficulties encountered with exposure assessment. Usually public measuring sites are few and thereby do not adequately describe spatial variation of pollutant levels over an urban area. In turn, individual monitoring of pollution exposure among study subjects is laborious and expensive. We therefore investigated whether traffic characteristics can be used to adequately predict benzene, NO 2 , and soot concentrations at individual addresses of study subjects in the city area of Munich, Germany. For all road segments with expected traffic volumes of at least 4000 vehicles a day (n=1840), all vehicles were counted manually or a single weekday in 1995. The proportion of vehicles in 'stop-go' mode, n estimate of traffic jam, was determined. Furthermore, annual concentrations of benzene, NO 2 , and soot from 18 high-concentration sites means: 8.7, 65.8, and 12.9 μg/m 3 , respectively) and from 16 school sites with moderate concentrations (means: 2.6, 32.2, and 5.7 μg/m 3 , respectively) were measured from 1996 to 1998. Statistical analysis of the data was performed using components of two different statistical models recently used to predict air pollution levels in comparable settings. Two traffic characteristics, traffic volume and traffic jam percentage, adequately described air pollutant concentrations (R 2 : 0.76-0.80, P=0.0001). This study shows that air pollutant concentrations can be accurately predicted by two traffic characteristics and that these models compare favorably with other more complex models in the literature

  1. Soot and Spectral Radiation Modeling for a High-Pressure Turbulent Spray Flame

    Energy Technology Data Exchange (ETDEWEB)

    Ferreryo-Fernandez, Sebastian [Pennsylvania State Univ., University Park, PA (United States); Paul, Chandan [Pennsylvania State Univ., University Park, PA (United States); Sircar, Arpan [Pennsylvania State Univ., University Park, PA (United States); Imren, Abdurrahman [Pennsylvania State Univ., University Park, PA (United States); Haworth, Daniel C [Pennsylvania State Univ., University Park, PA (United States); Roy, Somesh P [Marquette University (United States); Modest, Michael F [University of California Merced (United States)

    2017-04-26

    Simulations are performed of a transient high-pressure turbulent n-dodecane spray flame under engine-relevant conditions. An unsteady RANS formulation is used, with detailed chemistry, a semi-empirical two-equation soot model, and a particle-based transported composition probability density function (PDF) method to account for unresolved turbulent fluctuations in composition and temperature. Results from the PDF model are compared with those from a locally well-stirred reactor (WSR) model to quantify the effects of turbulence-chemistry-soot interactions. Computed liquid and vapor penetration versus time, ignition delay, and flame lift-off height are in good agreement with experiment, and relatively small differences are seen between the WSR and PDF models for these global quantities. Computed soot levels and spatial soot distributions from the WSR and PDF models show large differences, with PDF results being in better agreement with experimental measurements. An uncoupled photon Monte Carlo method with line-by-line spectral resolution is used to compute the spectral intensity distribution of the radiation leaving the flame. This provides new insight into the relative importance of molecular gas radiation versus soot radiation, and the importance of turbulent fluctuations on radiative heat transfer.

  2. Evaluation and optimisation of phenomenological multi-step soot model for spray combustion under diesel engine-like operating conditions

    DEFF Research Database (Denmark)

    Pang, Kar Mun; Jangi, Mehdi; Bai, Xue-Song

    2015-01-01

    with the spray combustion solver. Prior to the soot modelling, combustion simulations are carried out. Numerical results show that the ignition delay times and lift-off lengths exhibit good agreement with the experimental measurements across a wide range of operating conditions, apart from those in the cases......, variation of spatial soot distribution and soot mass produced at oxygen molar fractions ranging from 10.0 to 21.0% for both low and high density conditions are reproduced....

  3. Soot and Spectral Radiation Modeling in ECN Spray A and in Engines

    Energy Technology Data Exchange (ETDEWEB)

    Haworth, Daniel C [Pennsylvania State Univ., University Park, PA (United States); Ferreyro-Fernandez, Sebastian [Pennsylvania State Univ., University Park, PA (United States); Paul, Chandan [Pennsylvania State Univ., University Park, PA (United States); Sircar, Arpan [Pennsylvania State Univ., University Park, PA (United States); Imren, Abdurrahman [Pennsylvania State Univ., University Park, PA (United States); Roy, Somesh P [Marquette University (United States); Modest, Michael F [University of California Merced (United States); Ge, Wenjun [University of California Merced (United States)

    2017-04-03

    The amount of soot formed in a turbulent combustion system is determined by a complex system of coupled nonlinear chemical and physical processes. Different physical subprocesses can dominate, depending on the hydrodynamic and thermochemical environments. Similarly, the relative importance of reabsorption, spectral radiation properties, and molecular gas radiation versus soot radiation varies with thermochemical conditions, and in ways that are difficult to predict for the highly nonhomogeneous in-cylinder mixtures in engines. Here it is shown that transport and mixing play relatively more important roles as rate-determining processes in soot formation at engine-relevant conditions. It is also shown that molecular gas radiation and spectral radiation properties are important for engine-relevant conditions.

  4. A model study of aggregates composed of spherical soot monomers with an acentric carbon shell

    Science.gov (United States)

    Luo, Jie; Zhang, Yongming; Zhang, Qixing

    2018-01-01

    Influences of morphology on the optical properties of soot particles have gained increasing attentions. However, studies on the effect of the way primary particles are coated on the optical properties is few. Aimed to understand how the primary particles are coated affect the optical properties of soot particles, the coated soot particle was simulated using the acentric core-shell monomers model (ACM), which was generated by randomly moving the cores of concentric core-shell monomers (CCM) model. Single scattering properties of the CCM model with identical fractal parameters were calculated 50 times at first to evaluate the optical diversities of different realizations of fractal aggregates with identical parameters. The results show that optical diversities of different realizations for fractal aggregates with identical parameters cannot be eliminated by averaging over ten random realizations. To preserve the fractal characteristics, 10 realizations of each model were generated based on the identical 10 parent fractal aggregates, and then the results were averaged over each 10 realizations, respectively. The single scattering properties of all models were calculated using the numerically exact multiple-sphere T-matrix (MSTM) method. It is found that the single scattering properties of randomly coated soot particles calculated using the ACM model are extremely close to those using CCM model and homogeneous aggregate (HA) model using Maxwell-Garnett effective medium theory. Our results are different from previous studies. The reason may be that the differences in previous studies were caused by fractal characteristics but not models. Our findings indicate that how the individual primary particles are coated has little effect on the single scattering properties of soot particles with acentric core-shell monomers. This work provides a suggestion for scattering model simplification and model selection.

  5. Experiments and Model Development for the Investigation of Sooting and Radiation Effects in Microgravity Droplet Combustion

    Science.gov (United States)

    Choi, Mun Young; Yozgatligil, Ahmet; Dryer, Frederick L.; Kazakov, Andrei; Dobashi, Ritsu

    2001-01-01

    Today, despite efforts to develop and utilize natural gas and renewable energy sources, nearly 97% of the energy used for transportation is derived from combustion of liquid fuels, principally derived from petroleum. While society continues to rely on liquid petroleum-based fuels as a major energy source in spite of their finite supply, it is of paramount importance to maximize the efficiency and minimize the environmental impact of the devices that burn these fuels. The development of improved energy conversion systems, having higher efficiencies and lower emissions, is central to meeting both local and regional air quality standards. This development requires improvements in computational design tools for applied energy conversion systems, which in turn requires more robust sub-model components for combustion chemistry, transport, energy transport (including radiation), and pollutant emissions (soot formation and burnout). The study of isolated droplet burning as a unidimensional, time dependent model diffusion flame system facilitates extensions of these mechanisms to include fuel molecular sizes and pollutants typical of conventional and alternative liquid fuels used in the transportation sector. Because of the simplified geometry, sub-model components from the most detailed to those reduced to sizes compatible for use in multi-dimensional, time dependent applied models can be developed, compared and validated against experimental diffusion flame processes, and tested against one another. Based on observations in microgravity experiments on droplet combustion, it appears that the formation and lingering presence of soot within the fuel-rich region of isolated droplets can modify the burning rate, flame structure and extinction, soot aerosol properties, and the effective thermophysical properties. These observations led to the belief that perhaps one of the most important outstanding contributions of microgravity droplet combustion is the observation that in the

  6. Numerical Modelling of Soot Formation in Laminar Axisymmetric Ethylene-Air Coflow Flames at Atmospheric and Elevated Pressures

    KAUST Repository

    Abdelgadir, Ahmed; Rakha, Ihsan Allah; Steinmetz, Scott A.; Attili, Antonio; Bisetti, Fabrizio; Roberts, William L.

    2015-01-01

    , coupled with detailed transport and kinetic models, to reproduce experimental measurements of a series of ethylene-air coflow flames. Detailed finite rate chemistry describing the formation of Polycyclic Aromatic Hydro-carbons is used. Soot is modeled

  7. Estimating soot emissions from an elevated flare

    Science.gov (United States)

    Almanza, Victor; Sosa, Gustavo

    2009-11-01

    Combustion aerosols are one of the major concerns in flaring operations, due to both health and environmental hazards. Preliminary results are presented for a 2D transient simulation of soot formation in a reacting jet with exit velocity of 130 m/s under a 5 m/s crossflow released from a 50 m high elevated flare and a 50 cm nozzle. Combustion dynamics was simulated with OpenFOAM. Gas-phase non-premixed combustion was modeled with the Chalmers PaSR approach and a κ-ɛ turbulence model. For soot formation, Moss model was used and the ISAT algorithm for solving the chemistry. Sulfur chemistry was considered to account for the sourness of the fuel. Gas composition is 10 % H2S and 90 % C2H4. A simplified Glassman reaction mechanism was used for this purpose. Results show that soot levels are sensitive to the sulfur present in the fuel, since it was observed a slight decrease in the soot volume fraction. NSC is the current oxidation model for soot formation. Predicted temperature is high (about 2390 K), perhaps due to soot-radiation interaction is not considered yet, but a radiation model implementation is on progress, as well as an oxidation mechanism that accounts for OH radical. Flame length is about 50 m.

  8. Large eddy simulation of soot evolution in an aircraft combustor

    Science.gov (United States)

    Mueller, Michael E.; Pitsch, Heinz

    2013-11-01

    An integrated kinetics-based Large Eddy Simulation (LES) approach for soot evolution in turbulent reacting flows is applied to the simulation of a Pratt & Whitney aircraft gas turbine combustor, and the results are analyzed to provide insights into the complex interactions of the hydrodynamics, mixing, chemistry, and soot. The integrated approach includes detailed models for soot, combustion, and the unresolved interactions between soot, chemistry, and turbulence. The soot model is based on the Hybrid Method of Moments and detailed descriptions of soot aggregates and the various physical and chemical processes governing their evolution. The detailed kinetics of jet fuel oxidation and soot precursor formation is described with the Radiation Flamelet/Progress Variable model, which has been modified to account for the removal of soot precursors from the gas-phase. The unclosed filtered quantities in the soot and combustion models, such as source terms, are closed with a novel presumed subfilter PDF approach that accounts for the high subfilter spatial intermittency of soot. For the combustor simulation, the integrated approach is combined with a Lagrangian parcel method for the liquid spray and state-of-the-art unstructured LES technology for complex geometries. Two overall fuel-to-air ratios are simulated to evaluate the ability of the model to make not only absolute predictions but also quantitative predictions of trends. The Pratt & Whitney combustor is a Rich-Quench-Lean combustor in which combustion first occurs in a fuel-rich primary zone characterized by a large recirculation zone. Dilution air is then added downstream of the recirculation zone, and combustion continues in a fuel-lean secondary zone. The simulations show that large quantities of soot are formed in the fuel-rich recirculation zone, and, furthermore, the overall fuel-to-air ratio dictates both the dominant soot growth process and the location of maximum soot volume fraction. At the higher fuel

  9. Soot emissions from turbulent diffusion flames burning simple alkane fuels

    Energy Technology Data Exchange (ETDEWEB)

    Canteenwalla, P.M.; Johnson, M.R. [Carleton Univ., Ottawa, ON (Canada). Dept. of Mechanical and Aerospace Engineering; Thomson, K.A.; Smallwood, G.J. [National Research Council of Canada, Ottawa, ON (Canada). Inst. for Chemical Process and Environmental Technology

    2007-07-01

    A classic problem in combustion involves measurement and prediction of soot emissions from turbulent diffusion flames. Very high-sensitivity measurements of particulate matter (PM) from very low-sooting diffusion flames burning methane and other simple alkane fuels have been enabled from recent advances in laser-induced incandescence (LII). In order to quantify soot emissions from a lab-scale turbulent diffusion flame burner, this paper presented a study that used LII to develop a sampling protocol. The purpose of the study was to develop an experimentally based model to predict PM emissions from flares used in industry using soot emissions from lab-scale flares. Quantitative results of mass of soot emitted per mass of fuel burned were presented across a range of flow conditions and fuels. The experiment used digital imaging to measure flame lengths and estimate flame residence times. Comparisons were also made between current measurements and results of previous researchers for soot in the overfire region. The study also considered the validity applicability of buoyancy based models for predicting and scaling soot emissions. The paper described the experimental setup including sampling system and flame length imaging. Background information on soot yield and a comparison of flame residence time definitions were provided. The results and discussion of results were also presented. It was concluded that the results highlighted the subjective nature of flame length measurements. 10 refs., 4 figs.

  10. Modelling and Simulation of Packed Bed Catalytic Converter for Oxidation of Soot in Diesel Powered Vehicles Flue Gas

    Directory of Open Access Journals (Sweden)

    Mohammad Nasikin

    2010-10-01

    Full Text Available Diesel vehicle is used in Indonesia in very big number. This vehicle exhausts pollutants especially diesel soot that can be reduces by using a catalytic converter to convert the soot to CO2. To obtain the optimal dimension of catalytic converter it is needed a model that can represent the profile of soot weight, temperature and pressure along the catalytic converter. In this study, a model is developed for packed bed catalytic converter in an adiabatic condition based on a kinetic study that has been  reported previously. Calculation of developed equations in this model uses Polymath 5.X solver with Range Kutta Method. The simulation result shows that temperature profile along catalytic converter increases with the decrease of soot weight,  while pressure profile decreases. The increase of soot weight in entering gas increases the needed converter length. On the other hand, the increase of catalyst diameter does not affect to soot weight along converter and temperature profile, but results a less pressure drop. For 2.500 c diesel engine, packed bed catalytic converter with ellipse's cross sectional of 14,5X7,5 cm diagonal and 0,8 cm catalyst particle diameter, needs 4,1 cm length.

  11. Sooting turbulent jet flame: characterization and quantitative soot measurements

    Science.gov (United States)

    Köhler, M.; Geigle, K. P.; Meier, W.; Crosland, B. M.; Thomson, K. A.; Smallwood, G. J.

    2011-08-01

    Computational fluid dynamics (CFD) modelers require high-quality experimental data sets for validation of their numerical tools. Preferred features for numerical simulations of a sooting, turbulent test case flame are simplicity (no pilot flame), well-defined boundary conditions, and sufficient soot production. This paper proposes a non-premixed C2H4/air turbulent jet flame to fill this role and presents an extensive database for soot model validation. The sooting turbulent jet flame has a total visible flame length of approximately 400 mm and a fuel-jet Reynolds number of 10,000. The flame has a measured lift-off height of 26 mm which acts as a sensitive marker for CFD model validation, while this novel compiled experimental database of soot properties, temperature and velocity maps are useful for the validation of kinetic soot models and numerical flame simulations. Due to the relatively simple burner design which produces a flame with sufficient soot concentration while meeting modelers' needs with respect to boundary conditions and flame specifications as well as the present lack of a sooting "standard flame", this flame is suggested as a new reference turbulent sooting flame. The flame characterization presented here involved a variety of optical diagnostics including quantitative 2D laser-induced incandescence (2D-LII), shifted-vibrational coherent anti-Stokes Raman spectroscopy (SV-CARS), and particle image velocimetry (PIV). Producing an accurate and comprehensive characterization of a transient sooting flame was challenging and required optimization of these diagnostics. In this respect, we present the first simultaneous, instantaneous PIV, and LII measurements in a heavily sooting flame environment. Simultaneous soot and flow field measurements can provide new insights into the interaction between a turbulent vortex and flame chemistry, especially since soot structures in turbulent flames are known to be small and often treated in a statistical manner.

  12. Computational Investigation of Soot and Radiation in Turbulent Reacting Flows

    Science.gov (United States)

    Lalit, Harshad

    This study delves into computational modeling of soot and infrared radiation for turbulent reacting flows, detailed understanding of both of which is paramount in the design of cleaner engines and pollution control. In the first part of the study, the concept of Stochastic Time and Space Series Analysis (STASS) as a numerical tool to compute time dependent statistics of radiation intensity is introduced for a turbulent premixed flame. In the absence of high fidelity codes for large eddy simulation or direct numerical simulation of turbulent flames, the utility of STASS for radiation imaging of reacting flows to understand the flame structure is assessed by generating images of infrared radiation in spectral bands dominated by radiation from gas phase carbon dioxide and water vapor using an assumed PDF method. The study elucidates the need for time dependent computation of radiation intensity for validation with experiments and the need for accounting for turbulence radiation interactions for correctly predicting radiation intensity and consequently the flame temperature and NOx in a reacting fluid flow. Comparison of single point statistics of infrared radiation intensity with measurements show that STASS can not only predict the flame structure but also estimate the dynamics of thermochemical scalars in the flame with reasonable accuracy. While a time series is used to generate realizations of thermochemical scalars in the first part of the study, in the second part, instantaneous realizations of resolved scale temperature, CO2 and H2O mole fractions and soot volume fractions are extracted from a large eddy simulation (LES) to carry out quantitative imaging of radiation intensity (QIRI) for a turbulent soot generating ethylene diffusion flame. A primary motivation of the study is to establish QIRI as a computational tool for validation of soot models, especially in the absence of conventional flow field and measured scalar data for sooting flames. Realizations of

  13. Modelling soot formation from wall films in a gasoline direct injection engine using a detailed population balance model

    International Nuclear Information System (INIS)

    Wang, Buyu; Mosbach, Sebastian; Schmutzhard, Sebastian; Shuai, Shijin; Huang, Yaqing; Kraft, Markus

    2016-01-01

    Highlights: • Soot formation from a wall film in a GDI engine is simulated. • Spray impingement and wall film evaporation models are added to SRM Engine Suite. • Soot is modelled using a highly detailed population balance model. • Particle size distributions are measured experimentally. • Evolution of wall region is shown in equivalence ratio-temperature diagrams. - Abstract: In this study, soot formation in a Gasoline Direct Injection (GDI) engine is simulated using a Stochastic Reactor Model (SRM Engine Suite) which contains a detailed population balance soot model capable of describing particle morphology and chemical composition. In order to describe the soot formation originating from the wall film, the SRM Engine Suite is extended to include spray impingement and wall film evaporation models. The cylinder is divided into a wall and a bulk zone to resolve the equivalence ratio and temperature distributions of the mixture near the wall. The combustion chamber wall is assumed to exchange heat directly only with the wall zone. The turbulent mixing within each zone and between the two zones are simulated with different mixing models. The effects of key parameters on the temperature and equivalence ratio in the two zones are investigated. The mixing rate between the wall and bulk zone has a significant effect on the wall zone, whilst the mixing rate in the wall zone only has a negligible impact on the temperature and equivalence ratio below a certain threshold. Experimental data are obtained from a four-cylinder, gasoline-fuelled direct injection spark ignition engine operated stoichiometrically. An injection timing sweep, ranging from 120 CAD BTDC to 330 CAD BTDC, is conducted in order to investigate the effect of spray impingement on soot formation. The earliest injection case (330 CAD BTDC), which produces significantly higher levels of particle emissions than any other case, is simulated by the current model. It is found that the in-cylinder pressure

  14. Determination of the spectral behaviour of atmospheric soot using different particle models

    Science.gov (United States)

    Skorupski, Krzysztof

    2017-08-01

    In the atmosphere, black carbon aggregates interact with both organic and inorganic matter. In many studies they are modeled using different, less complex, geometries. However, some common simplification might lead to many inaccuracies in the following light scattering simulations. The goal of this study was to compare the spectral behavior of different, commonly used soot particle models. For light scattering simulations, in the visible spectrum, the ADDA algorithm was used. The results prove that the relative extinction error δCext, in some cases, can be unexpectedly large. Therefore, before starting excessive simulations, it is important to know what error might occur.

  15. Laboratory and modeling studies on the effects of water and soot emissions and ambient conditions on the properties of contrail ice particles in the jet regime

    Directory of Open Access Journals (Sweden)

    H.-W. Wong

    2013-10-01

    Full Text Available Contrails and contrail-induced cirrus clouds are identified as the most uncertain components in determining aviation impacts on global climate change. Parameters affecting contrail ice particle formation immediately after the engine exit plane (< 5 s in plume age may be critical to ice particle properties used in large-scale models predicting contrail radiative forcing. Despite this, detailed understanding of these parametric effects is still limited. In this paper, we present results from recent laboratory and modeling studies conducted to investigate the effects of water and soot emissions and ambient conditions on near-field formation of contrail ice particles and ice particle properties. The Particle Aerosol Laboratory (PAL at the NASA Glenn Research Center and the Aerodyne microphysical parcel model for contrail ice particle formation were employed. Our studies show that exhaust water concentration has a significant impact on contrail ice particle formation and properties. When soot particles were introduced, ice particle formation was observed only when exhaust water concentration was above a critical level. When no soot or sulfuric acid was introduced, no ice particle formation was observed, suggesting that ice particle formation from homogeneous nucleation followed by homogeneous freezing of liquid water was unfavorable. Soot particles were found to compete for water vapor condensation, and higher soot concentrations emitted into the chamber resulted in smaller ice particles being formed. Chamber conditions corresponding to higher cruising altitudes were found to favor ice particle formation. The microphysical model captures trends of particle extinction measurements well, but discrepancies between the model and the optical particle counter measurements exist as the model predicts narrower ice particle size distributions and ice particle sizes nearly a factor of two larger than measured. These discrepancies are likely due to particle

  16. Lidar cross-sections of soot fractal aggregates: Assessment of equivalent-sphere models

    Science.gov (United States)

    Ceolato, Romain; Gaudfrin, Florian; Pujol, Olivier; Riviere, Nicolas; Berg, Matthew J.; Sorensen, Christopher M.

    2018-06-01

    This work assesses the ability of equivalent-sphere models to reproduce the optical properties of soot aggregates relevant for lidar remote sensing, i.e. the backscattering and extinction cross sections. Lidar cross-sections are computed with a spectral discrete dipole approximation model over the visible-to-infrared (400-5000 nm) spectrum and compared with equivalent-sphere approximations. It is shown that the equivalent-sphere approximation, applied to fractal aggregates, has a limited ability to calculate such cross-sections well. The approximation should thus be used with caution for the computation of broadband lidar cross-sections, especially backscattering, at small and intermediate wavelengths (e.g. UV to visible).

  17. A computational study of ethylene–air sooting flames: Effects of large polycyclic aromatic hydrocarbons

    KAUST Repository

    Selvaraj, Prabhu

    2015-11-05

    An updated reduced gas-phase kinetic mechanism was developed and integrated with aerosol models to predict soot formation characteristics in ethylene nonpremixed and premixed flames. A primary objective is to investigate the sensitivity of the soot formation to various chemical pathways for large polycyclic aromatic hydrocarbons (PAH). The gas-phase chemical mechanism adopted the KAUST-Aramco PAH Mech 1.0, which utilized the AramcoMech 1.3 for gas-phase reactions validated for up to C2 fuels. In addition, PAH species up to coronene (C24H12 or A7) were included to describe the detailed formation pathways of soot precursors. In this study, the detailed chemical mechanism was reduced from 397 to 99 species using directed relation graph with expert knowledge (DRG-X) and sensitivity analysis. The method of moments with interpolative closure (MOMIC) was employed for the soot aerosol model. Counterflow nonpremixed flames at low strain rate sooting conditions were considered, for which the sensitivity of soot formation characteristics to different nucleation pathways were investigated. Premixed flame experiment data at different equivalence ratios were also used for validation. The findings show that higher PAH concentrations result in a higher soot nucleation rate, and that the total soot volume and average size of the particles are predicted in good agreement with experimental results. Subsequently, the effects of different pathways, with respect to pyrene- or coronene-based nucleation models, on the net soot formation rate were analyzed. It was found that the nucleation processes (i.e., soot inception) are sensitive to the choice of PAH precursors, and consideration of higher PAH species beyond pyrene is critical for accurate prediction of the overall soot formation.

  18. Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung

    Directory of Open Access Journals (Sweden)

    Sundaram Taneshwaren

    2017-01-01

    Full Text Available With an ever increasing demand for energy, Malaysia has become a nation that thrives on solid power generation sector to meet the energy demand and supply market. In a coal fired power plant, soot blowing operation is commonly used as a cleaning mechanism inside the boiler. There are many types of sequence available for this soot blowing operation. Hence, there is no efficient ways in utilizing the soot blowing operation to enhance the efficiency of boiler. Soot blowing optimization requires specific set of data preparation and simulation in order to achieve the best modal. Computational Fluid Dynamics (CFD is used to model a 700MW super-critical boiler, whereby parameters with effect to soot blowing operation is studied. Two different boiler condition is studied to analyze parameters in a clean and faulty boiler. Artificial Neural Network (ANN is used to train neural network modal with back propagation method to determine the best modal that will be used to predict soot blowing operation. Combination of neural network different number of neurons, hidden layers, training algorithm, and training functions is trained to find the modal with lowest error. By improving soot blowing sequence, efficiency of boiler can be improved by providing best parameter and model. This model is then used as a reference for advisory tool whereby a Neural Network Predictive Tool is suggested to the station to predict the soot blowing operation that occurs.

  19. Investigation of soot formation and temperature field in laminar diffusion flames of LPG-air mixture

    Energy Technology Data Exchange (ETDEWEB)

    Shahad, Haroun A.K.; Mohammed, Yassar K.A. [Babylon Univ., Dept. of Mechanical Engineering, Babylon (Israel)

    2000-11-01

    Soot formation and burnout were studied at atmospheric pressure in co-flowing, axisymmetric buoyant laminar diffusion flames and double flames of liquefied petroleum gases (LPG)-air mixtures. In diffusion flames, two different fuel flow rates were examined. In double flames, three different primary air flow rates were examined. A soot sampling probe and a thermocouple were used to measure the local soot mass concentration and flame temperature, respectively. Flame residence time was predicted using a uniformly accelerated motion model as function of axial distance of the flame. The increase of primary air flow rate was found to suppress the energy transfer from the annular region, at which the soot is produced, to the flame axis. The time required to initiate soot formation at the flame axis becomes longer as the primary air is increased. The trend rate of soot formation was found to be similar along the flame axis in all tested diffusion flames. The increase of primary air by 10% of the stoichiometric air requirement of the fuel results in a 70% reduction in maximum soot concentration. The final exhaust of soot, which is determined by the net effect of soot formation and burnout, is much lower in double flames than that in diffusion flames. (Author)

  20. Effects of Large Polycyclic Aromatic Hydrocarbons on the Soot Formation in Ethylene-Air Nonpremixed Flames

    KAUST Repository

    Prabhu, S.; Arias, P.G.; Wang, Y.; Gao, Y.; Park, S.; Im, Hong G.; Sarathy, Mani; Chung, Suk-Ho; Lu, T.

    2015-01-01

    This study presents updated comprehensive gas-phase kinetic mechanism and aerosol models to predict soot formation characteristics in ethylene-air nonpremixed flames. A main objective is to investigate the sensitivity of the soot formation rate to various chemical pathways for large polycyclic aromatic hydrocarbons (PAH). In this study, the detailed chemical mechanism was reduced from 397 to 99 species using directed relation graph (DRG) and sensitivity analysis. The method of moments with interpolative closure (MOMIC) was employed for the soot aerosol model. Counterflow nonpremixed flames of pure ethylene at low strain rate sooting conditions are considered, for which the sensitivity of soot formation characteristics with respect to hetrogeneous nucleation is investigated. Results show that higher PAH concentrations result in higher soot nucleation rate, and that the average size of the particles are in good agreement with experimental results. It is found that the nucleation processes (i.e., soot inception) from higher PAH precursors, coronene in particular, is critical for accurate prediction of the overall soot formation.

  1. Effects of Large Polycyclic Aromatic Hydrocarbons on the Soot Formation in Ethylene-Air Nonpremixed Flames

    KAUST Repository

    Prabhu, S.

    2015-03-30

    This study presents updated comprehensive gas-phase kinetic mechanism and aerosol models to predict soot formation characteristics in ethylene-air nonpremixed flames. A main objective is to investigate the sensitivity of the soot formation rate to various chemical pathways for large polycyclic aromatic hydrocarbons (PAH). In this study, the detailed chemical mechanism was reduced from 397 to 99 species using directed relation graph (DRG) and sensitivity analysis. The method of moments with interpolative closure (MOMIC) was employed for the soot aerosol model. Counterflow nonpremixed flames of pure ethylene at low strain rate sooting conditions are considered, for which the sensitivity of soot formation characteristics with respect to hetrogeneous nucleation is investigated. Results show that higher PAH concentrations result in higher soot nucleation rate, and that the average size of the particles are in good agreement with experimental results. It is found that the nucleation processes (i.e., soot inception) from higher PAH precursors, coronene in particular, is critical for accurate prediction of the overall soot formation.

  2. Development of high fidelity soot aerosol dynamics models using method of moments with interpolative closure

    KAUST Repository

    Roy, Subrata P.; Arias, Paul G.; Lecoustre, Vivien R.; Haworth, Daniel C.; Im, Hong G.; Trouvé , Arnaud C.

    2014-01-01

    of ad hoc treatments such as clipping. The solutions proposed and demonstrated here are being applied to generate new physical insight into complex turbulence-chemistry-soot-radiation interactions in turbulent reacting flows using DNS. © 2014 Copyright

  3. Numerical Modelling of Soot Formation in Laminar Axisymmetric Ethylene-Air Coflow Flames at Atmospheric and Elevated Pressures

    KAUST Repository

    Abdelgadir, Ahmed

    2015-03-30

    A set of coflow diffusion flames are simulated to study the formation, growth, and oxidation of soot in flames of diluted hydrocarbon fuels, with focus on the effects of pressure. Firstly, we assess the ability of a high performance CFD solver, coupled with detailed transport and kinetic models, to reproduce experimental measurements of a series of ethylene-air coflow flames. Detailed finite rate chemistry describing the formation of Polycyclic Aromatic Hydro-carbons is used. Soot is modeled with a moment method and the resulting moment transport equations are solved with a Lagrangian numerical scheme. Numerical and experimental results are compared for various pressures. Finally, a sensitivity study is performed assessing the effect of the boundary conditions and kinetic mechanisms on the flame structure and stabilization properties.

  4. Investigating Soot Morphology in Counterflow Flames at Elevated Pressures

    KAUST Repository

    Amin, Hafiz Muhammad Fahid

    2018-01-01

    volume fraction from 2 to 10 atm. Local soot volume fraction increased with pressure and soot concentration profiles showed good agreements when measured by both techniques. Experimental data obtained in this work is very helpful for the modelers for validating their codes and predicting the soot formation in pressurized flames.

  5. Influence of thermal radiation on soot production in Laminar axisymmetric diffusion flames

    International Nuclear Information System (INIS)

    Demarco, R.; Nmira, F.; Consalvi, J.L.

    2013-01-01

    The aim of this paper is to study the effect of radiative heat transfer on soot production in laminar axisymmetric diffusion flames. Twenty-four C 1 –C 3 hydrocarbon–air flames, consisting of normal (NDF) and inverse (IDF) diffusion flames at both normal gravity (1 g) and microgravity (0 g), and covering a wide range of conditions affecting radiative heat transfer, were simulated. The numerical model is based on the Steady Laminar Flamelet (SLF) model, a semi-empirical two-equation acetylene/benzene based soot model and the Statistical Narrow Band Correlated K (SNBCK) model coupled to the Finite Volume Method (FVM) to compute thermal radiation. Predictions relative to velocity, temperature, soot volume fraction and radiative losses are on the whole in good agreement with the available experimental data. Model results show that, for all the flames considered, thermal radiation is a crucial process with a view to providing accurate predictions for temperatures and soot concentrations. It becomes increasingly significant from IDFs to NDFs and its influence is much greater as gravity is reduced. The radiative contribution of gas prevails in the weakly-sooting IDFs and in the methane and ethane NDFs, whereas soot radiation dominates in the other flames. However, both contributions are significant in all cases, with the exception of the 1 g IDFs investigated where soot radiation can be ignored. The optically-thin approximation (OTA) was also tested and found to be applicable as long as the optical thickness, based on flame radius and Planck mean absorption coefficient, is less than 0.05. The OTA is reasonable for the IDFs and for most of the 1 g NDFs, but it fails to predict the radiative heat transfer for the 0 g NDFs. The accuracy of radiative-property models was then assessed in the latter cases. Simulations show that the gray approximation can be applied to soot but not to combustion gases. Both the non-gray and gray soot versions of the Full Spectrum Correlated

  6. Physical and chemical comparison of soot in hydrocarbon and biodiesel fuel diffusion flames: A study of model and commercial fuels

    Energy Technology Data Exchange (ETDEWEB)

    Matti Maricq, M. [Research and Advanced Engineering, Ford Motor Company, Dearborn, MI (United States)

    2011-01-15

    Data are presented to compare soot formation in both surrogate and practical fatty acid methyl ester biodiesel and petroleum fuel diffusion flames. The approach here uses differential mobility analysis to follow the size distributions and electrical charge of soot particles as they evolve in the flame, and laser ablation particle mass spectrometry to elucidate their composition. Qualitatively, these soot properties exhibit a remarkably similar development along the flames. The size distributions begin as a single mode of precursor nanoparticles, evolve through a bimodal phase marking the onset of aggregate formation, and end in a self preserving mode of fractal-like particles. Both biodiesel and hydrocarbon fuels yield a common soot composition dominated by C{sub x}H{sub y}{sup +} ions, stabilomer PAHs, and fullerenes in the positive ion mass spectrum, and C{sub x}{sup -} and C{sub 2x}H{sup -} in the negative ion spectrum. These ion intensities initially grow with height in the diffusion flames, but then decline during later stages, consistent with soot carbonization. There are important quantitative differences between fuels. The surrogate biodiesel fuel methyl butanoate substantially reduces soot levels, but soot formation and evolution in this flame are delayed relative to both soy and petroleum fuels. In contrast, soots from soy and hexadecane flames exhibit nearly quantitative agreement in their size distribution and composition profiles with height, suggesting similar soot precursor chemistry. (author)

  7. Modelling heterogeneous ice nucleation on mineral dust and soot with parameterizations based on laboratory experiments

    Science.gov (United States)

    Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.

    2016-12-01

    Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.

  8. Small particles big effect? - Investigating ice nucleation abilities of soot particles

    Science.gov (United States)

    Mahrt, Fabian; David, Robert O.; Lohmann, Ulrike; Stopford, Chris; Wu, Zhijun; Kanji, Zamin A.

    2017-04-01

    Atmospheric soot particles are primary particles produced by incomplete combustion of biomass and/or fossil fuels. Thus soot mainly originates from anthropogenic emissions, stemming from combustion related processes in transport vehicles, industrial and residential uses. Such soot particles are generally complex mixtures of black carbon (BC) and organic matter (OM) (Bond et al., 2013; Petzold et al., 2013), depending on the sources and the interaction of the primary particles with other atmospheric matter and/or gases BC absorbs solar radiation having a warming effect on global climate. It can also act as a heterogeneous ice nucleating particle (INP) and thus impact cloud-radiation interactions, potentially cooling the climate (Lohmann, 2002). Previous studies, however, have shown conflicting results concerning the ice nucleation ability of soot, limiting the ability to predict its effects on Earth's radiation budget. Here we present a laboratory study where we systematically investigate the ice nucleation behavior of different soot particles. Commercial soot samples are used, including an amorphous, industrial carbon frequently used in coatings and coloring (FW 200, Orion Engineered Carbons) and a fullerene soot (572497 ALDRICH), e.g. used as catalyst. In addition, we use soot generated from a propane flame Combustion Aerosol Standard Generator (miniCAST, JING AG), as a proxy for atmospheric soot particles. The ice nucleation ability of these soot types is tested on size-selected particles for a wide temperature range from 253 K to 218 K, using the Horizontal Ice Nucleation Chamber (HINC), a Continuous Flow Diffusion Chamber (CFDC) (Kanji and Abbatt, 2009). Ice nucleation results from these soot surrogates will be compared to chemically more complex real world samples, collected on filters. Filters will be collected during the 2016/2017 winter haze periods in Beijing, China and represent atmospheric soot particles with sources from both industrial and residential

  9. Influence of thermal radiation on soot production in Laminar axisymmetric diffusion flames

    Science.gov (United States)

    Demarco, R.; Nmira, F.; Consalvi, J. L.

    2013-05-01

    The aim of this paper is to study the effect of radiative heat transfer on soot production in laminar axisymmetric diffusion flames. Twenty-four C1-C3 hydrocarbon-air flames, consisting of normal (NDF) and inverse (IDF) diffusion flames at both normal gravity (1 g) and microgravity (0 g), and covering a wide range of conditions affecting radiative heat transfer, were simulated. The numerical model is based on the Steady Laminar Flamelet (SLF) model, a semi-empirical two-equation acetylene/benzene based soot model and the Statistical Narrow Band Correlated K (SNBCK) model coupled to the Finite Volume Method (FVM) to compute thermal radiation. Predictions relative to velocity, temperature, soot volume fraction and radiative losses are on the whole in good agreement with the available experimental data. Model results show that, for all the flames considered, thermal radiation is a crucial process with a view to providing accurate predictions for temperatures and soot concentrations. It becomes increasingly significant from IDFs to NDFs and its influence is much greater as gravity is reduced. The radiative contribution of gas prevails in the weakly-sooting IDFs and in the methane and ethane NDFs, whereas soot radiation dominates in the other flames. However, both contributions are significant in all cases, with the exception of the 1 g IDFs investigated where soot radiation can be ignored. The optically-thin approximation (OTA) was also tested and found to be applicable as long as the optical thickness, based on flame radius and Planck mean absorption coefficient, is less than 0.05. The OTA is reasonable for the IDFs and for most of the 1 g NDFs, but it fails to predict the radiative heat transfer for the 0 g NDFs. The accuracy of radiative-property models was then assessed in the latter cases. Simulations show that the gray approximation can be applied to soot but not to combustion gases. Both the non-gray and gray soot versions of the Full Spectrum Correlated k (FSCK

  10. Compositional effects on PAH and soot formation in counterflow diffusion flames of gasoline surrogate fuels

    KAUST Repository

    Park, Sungwoo

    2017-02-05

    Gasoline surrogate fuels are widely used to understand the fundamental combustion properties of complex refinery gasoline fuels. In this study, the compositional effects on polycyclic aromatic hydrocarbons (PAHs) and soot formation were investigated experimentally for gasoline surrogate mixtures comprising n-heptane, iso-octane, and toluene in counterflow diffusion flames. A comprehensive kinetic model for the gasoline surrogate mixtures was developed to accurately predict the fuel oxidation along with the formation of PAHs and soot in flames. This combined model was first tested against ignition delay times and laminar burning velocities data. The proposed model for the formation and growth of PAHs up to coronene (C24H12) was based on previous studies and was tested against existing and present new experimental data. Additionally, in the accompanied soot model, PAHs with sizes larger than (including) pyrene were used for the inception of soot particles, followed by particle coagulations and PAH condensation/chemical reactions on soot surfaces. The major pathways for the formation of PAHs were also identified for the surrogate mixtures. The model accurately captures the synergistic PAH formation characteristics observed experimentally for n-heptane/toluene and iso-octane/toluene binary mixtures. Furthermore, the present experimental and modeling results also elucidated different trends in the formation of larger PAHs and soot between binary n-heptane/iso-octane and ternary n-heptane/iso-octane/toluene mixtures. Propargyl radicals (C3H3) were shown to be important in the formation and growth of PAHs for n-heptane/iso-octane mixtures when the iso-octane concentration increased; however, reactions involving benzyl radicals (C6H5CH2) played a significant role in the formation of PAHs for n-heptane/iso-octane/toluene mixtures. These results indicated that the formation of PAHs and subsequently soot was strongly affected by the composition of gasoline surrogate mixtures.

  11. Compositional effects on PAH and soot formation in counterflow diffusion flames of gasoline surrogate fuels

    KAUST Repository

    Park, Sungwoo; Wang, Yu; Chung, Suk-Ho; Sarathy, Mani

    2017-01-01

    Gasoline surrogate fuels are widely used to understand the fundamental combustion properties of complex refinery gasoline fuels. In this study, the compositional effects on polycyclic aromatic hydrocarbons (PAHs) and soot formation were investigated experimentally for gasoline surrogate mixtures comprising n-heptane, iso-octane, and toluene in counterflow diffusion flames. A comprehensive kinetic model for the gasoline surrogate mixtures was developed to accurately predict the fuel oxidation along with the formation of PAHs and soot in flames. This combined model was first tested against ignition delay times and laminar burning velocities data. The proposed model for the formation and growth of PAHs up to coronene (C24H12) was based on previous studies and was tested against existing and present new experimental data. Additionally, in the accompanied soot model, PAHs with sizes larger than (including) pyrene were used for the inception of soot particles, followed by particle coagulations and PAH condensation/chemical reactions on soot surfaces. The major pathways for the formation of PAHs were also identified for the surrogate mixtures. The model accurately captures the synergistic PAH formation characteristics observed experimentally for n-heptane/toluene and iso-octane/toluene binary mixtures. Furthermore, the present experimental and modeling results also elucidated different trends in the formation of larger PAHs and soot between binary n-heptane/iso-octane and ternary n-heptane/iso-octane/toluene mixtures. Propargyl radicals (C3H3) were shown to be important in the formation and growth of PAHs for n-heptane/iso-octane mixtures when the iso-octane concentration increased; however, reactions involving benzyl radicals (C6H5CH2) played a significant role in the formation of PAHs for n-heptane/iso-octane/toluene mixtures. These results indicated that the formation of PAHs and subsequently soot was strongly affected by the composition of gasoline surrogate mixtures.

  12. Radiation turbulence interactions in pulverized coal flames: Chaotic map models of soot fluctuations in turbulent diffusion flames. Quarterly report, October 1995--December 1995

    Energy Technology Data Exchange (ETDEWEB)

    McDonough, J.M.; Menguc, M.P.; Mukerji, S.; Swabb, S.; Manickavasagam, S.; Ghosal, S.

    1995-12-31

    In this paper, we introduce a methodology to characterize soot volume fraction fluctuations in turbulent diffusion flames via chaotic maps. The approach is based on the hypothesis that the fluctuations of properties in turbulent flames is deterministic in nature, rather than statistical. Out objective is to develop models to mimic these fluctuations. The models will be used eventually in comprehensive algorithms to study the true physics of turbulent flames and the interaction of turbulence with radiation. To this extent, we measured the time series of soot scattering coefficient in an ethylene diffusion flame from light scattering experiments. Following this, corresponding power spectra and delay maps were calculated. It was shown that if the data were averaged, the characteristics of the fluctuations were almost completely washed out. The psds from experiments were successfully modeled using a series of logistic maps.

  13. Effects of soot formation on shape of a nonpremixed laminar flame established in a shear boundary layer in microgravity

    International Nuclear Information System (INIS)

    Wang, H Y; Merino, J L Florenciano; Dagaut, P

    2011-01-01

    A numerical study was performed to give a quantitative description of a heavily sooting, nonpremixed laminar flame established in a shear boundary layer in microgravity. Controlling mechanisms of three dimensional flow, combustion, soot and radiation are coupled. Soot volume fraction were predicted by using three approaches, referred respectively to as the fuel, acetylene and PAH inception models. It is found that the PAH inception model, which is based on the formation of two and three-ringed aromatic species, reproduces correctly the experimental data from a laminar ethylene diffusion flame. The PAH inception model serves later to better understand flame quenching, flame stand-off distance and soot formation as a function of the dimensionless volume coefficient, defined as C q = V F /V ox where V F is the fuel injection velocity, and V ox air stream velocity. The present experiments showed that a blue unstable flame, negligible radiative feedback, may change to a yellow stable flame, significant radiative loss with an increase of C q ; this experimental trend was numerically reproduced. The flame quenching occurs at the trailing edge due to radiative heat loss which is significantly amplified by increasing V F or decreasing V ox , favouring soot formation. Along a semi-infinite fuel zone, the ratio, d f /d b , where d f is the flame standoff distance, and d b the boundary layer thickness, converges towards a constant value of 1.2, while soot resides always within the boundary layer far away from the flame sheet.

  14. Aromatics Oxidation and Soot Formation in Flames

    Energy Technology Data Exchange (ETDEWEB)

    Howard, J. B.; Richter, H.

    2005-03-29

    This project is concerned with the kinetics and mechanisms of aromatics oxidation and the growth process to polycyclic aromatic hydrocarbons (PAH) of increasing size, soot and fullerenes formation in flames. The overall objective of the experimental aromatics oxidation work is to extend the set of available data by measuring concentration profiles for decomposition intermediates such as phenyl, cyclopentadienyl, phenoxy or indenyl radicals which could not be measured with molecular-beam mass spectrometry to permit further refinement and testing of benzene oxidation mechanisms. The focus includes PAH radicals which are thought to play a major role in the soot formation process while their concentrations are in many cases too low to permit measurement with conventional mass spectrometry. The radical species measurements are used in critical testing and improvement of a kinetic model describing benzene oxidation and PAH growth. Thermodynamic property data of selected species are determined computationally, for instance using density functional theory (DFT). Potential energy surfaces are explored in order to identify additional reaction pathways. The ultimate goal is to understand the conversion of high molecular weight compounds to nascent soot particles, to assess the roles of planar and curved PAH and relationships between soot and fullerenes formation. The specific aims are to characterize both the high molecular weight compounds involved in the nucleation of soot particles and the structure of soot including internal nanoscale features indicative of contributions of planar and/or curved PAH to particle inception.

  15. Quantitative effects of rapid heating on soot-particle sizing through analysis of two-pulse LII

    KAUST Repository

    Cenker, Emre

    2017-02-27

    During the rapid laser pulse heating and consecutive cooling in laser-induced incandescence (LII), soot particles may undergo thermal annealing and sublimation processes which lead to a permanent change in its optical properties and its primary particle size, respectively. Overall, effects of these two processes on soot and LII model-based particle sizing are investigated by measuring the two-color time-resolved (2C-TiRe) LII signal decay from in-flame soot after two consecutive laser pulses at 1064-nm wavelength. Experiments are carried out on a non-premixed laminar ethylene/air flame from a Santoro burner with both low and moderate laser fluences suitable for particle sizing. The probe volume is set to a radial position close to the flame axis where the soot particles are known to be immature or less graphitic. With the first pulse, soot is pre-heated, and the LII signal after the consecutive second pulse is used for analysis. The two-color incandescence emission technique is used for the pyrometric determination of the LII-heated peak soot temperature at the second pulse. A new LII simulation tool is developed which accounts for particle heating via absorption and annealing, and cooling via sublimation, conduction, and radiation with various existing sub-models from the literature. The same approach of using two laser pulses is implemented in the simulations. Measurements indicate that thermal annealing and associated absorption enhancement becomes important at laser fluences above 0.17 J/cm2 for the immature in-flame soot. After a heating pulse at 0.33 J/cm2, the increase of the soot absorption function is calculated as 35% using the temperature measured at the second pulse and an absorption model based on the Rayleigh approximation. Present annealing model, on the other hand, predicts graphitization of soot even in the absence of laser heating at typical flame temperatures. Recorded experimental LII signal decays and LII-heated peak soot temperature

  16. Comprehensive Laser-induced Incandescence (LII) modeling for soot particle sizing

    KAUST Repository

    Lisanti, Joel; Cenker, Emre; Roberts, William L.

    2015-01-01

    utilized in the model are temperature dependent. In addition, where appropriate properties are also phase dependent, thereby accounting for annealing effects during laser heating and particle cooling.

  17. Ignition delay and soot oxidative reactivity of MTBE blended diesel fuel

    KAUST Repository

    Yang, Seung Yeon; Naser, Nimal; Chung, Suk-Ho; Al-Qurashi, Khalid

    2014-01-01

    Methyl tert-butyl ether (MTBE) was added to diesel fuel to investigate the effect on ignition delay and soot oxidative reactivity. An ignition quality tester (IQT) was used to study the ignition propensity of MTBE blended diesel fuels in a reactive spray environment. The IQT data showed that ignition delay increases linearly as the MTBE fraction increases in the fuel. A four-stroke single cylinder diesel engine was used to generate soot samples for a soot oxidation study. Soot samples were pre-treated using a tube furnace in a nitrogen environment to remove any soluble organic fractions and moisture content. Non-isothermal oxidation of soot samples was conducted using a thermogravimetric analyzer (TGA). It was observed that oxidation of 'MTBE soot' started began at a lower temperature and had higher reaction rate than 'diesel soot' across a range of temperatures. Several kinetic analyses including an isoconversional method and a combined model fitting method were carried out to evaluate kinetic parameters. The results showed that Diesel and MTBE soot samples had similar activation energy but the pre-exponential factor of MTBE soot was much higher than that of the Diesel soot. This may explain why MTBE soot was more reactive than Diesel soot. It is suggested that adding MTBE to diesel fuel is better for DPF regeneration since an MTBE blend can significantly influence the ignition characteristics and, consequently, the oxidative reactivity of soot. Copyright © 2014 SAE International.

  18. Ignition delay and soot oxidative reactivity of MTBE blended diesel fuel

    KAUST Repository

    Yang, Seung Yeon

    2014-04-01

    Methyl tert-butyl ether (MTBE) was added to diesel fuel to investigate the effect on ignition delay and soot oxidative reactivity. An ignition quality tester (IQT) was used to study the ignition propensity of MTBE blended diesel fuels in a reactive spray environment. The IQT data showed that ignition delay increases linearly as the MTBE fraction increases in the fuel. A four-stroke single cylinder diesel engine was used to generate soot samples for a soot oxidation study. Soot samples were pre-treated using a tube furnace in a nitrogen environment to remove any soluble organic fractions and moisture content. Non-isothermal oxidation of soot samples was conducted using a thermogravimetric analyzer (TGA). It was observed that oxidation of \\'MTBE soot\\' started began at a lower temperature and had higher reaction rate than \\'diesel soot\\' across a range of temperatures. Several kinetic analyses including an isoconversional method and a combined model fitting method were carried out to evaluate kinetic parameters. The results showed that Diesel and MTBE soot samples had similar activation energy but the pre-exponential factor of MTBE soot was much higher than that of the Diesel soot. This may explain why MTBE soot was more reactive than Diesel soot. It is suggested that adding MTBE to diesel fuel is better for DPF regeneration since an MTBE blend can significantly influence the ignition characteristics and, consequently, the oxidative reactivity of soot. Copyright © 2014 SAE International.

  19. Mutagenicity of diesel exhaust soot dispersed in phospholipid surfactants

    Energy Technology Data Exchange (ETDEWEB)

    Wallace, W.; Keane, M.; Xing, S.; Harrison, J.; Gautam, M.; Ong, T.

    1994-06-01

    Organics extractable from respirable diesel exhaust soot particles by organic solvents have been known for some time to be direct acting frameshift mutagens in the Ames Salmonella typhimurium histidine reversion assay. Upon deposition in a pulmonary alveolus or respiratory bronchiole, respirable diesel soot particles will contact first the hypophase which is coated by and laden with surfactants. To model interactions of soot and pulmonary surfactant, the authors dispersed soots in vitro in the primary phospholipid pulmonary surfactant dipalmitoyl glycerophosphorylcholine (lecithin) (DPL) in physiological saline. They have shown that diesel soots dispersed in lecithin surfactant can express mutagenic activity, in the Ames assay system using S. typhimurium TA98, comparable to that expressed by equal amounts of soot extracted by dichloromethane/dimethylsulfoxide (DCM/DMSO). Here the authors report additional data on the same system using additional exhaust soots and also using two other phospholipids, dipalmitoyl glycerophosphoryl ethanolamine (DPPE), and dipalmitoyl phosphatidic acid (DPPA), with different ionic character hydrophilic moieties. A preliminary study of the surfactant dispersed soot in an eucaryotic cell test system also is reported.

  20. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  1. Impact on vehicle fuel economy of the soot loading on diesel particulate filters made of different substrate materials

    International Nuclear Information System (INIS)

    Millo, Federico; Andreata, Maurizio; Rafigh, Mahsa; Mercuri, Davide; Pozzi, Chiara

    2015-01-01

    Wall flow DPFs (Diesel Particulate Filters) are nowadays universally adopted for all European passenger cars. Since the properties of the filter substrate material play a fundamental role in determining the optimal soot loading level to be reached before DPF regeneration, three different filter material substrates (Silicon Carbide, Aluminum Titanate and Cordierite) were investigated in this work, considering different driving conditions, after treatment layouts and regeneration strategies. In the first step of the research, an experimental investigation on the three different substrates over the NEDC (New European Driving Cycle) was performed. The data obtained from experiments were then used for the calibration and the validation of a one dimensional fluid-dynamic engine and after treatment simulation model. Afterward, the model was used to predict the vehicle fuel consumption increments as a function of the exhaust back pressure due to the soot loading for different driving cycles. The results showed that appreciable fuel consumption increments could be noticed only in particular driving conditions, and, as a consequence, in most of the cases the optimal filter regeneration strategy corresponds to reach the highest soot loading that still ensures the component safety even in case of uncontrolled regeneration events. - Highlights: • Three different substrate materials for a Diesel Particulate Filter were investigated. • Fuel consumption increases due to DPF soot loading were generally not appreciable. • Optimal soot loading before regeneration was the highest safeguarding DPF integrity. • SiC substrate showed highest soot load limit and lowest fuel consumption penalties. • AT and Cd substrate properties lead to lower soot load limits than SiC

  2. Dynamics of flow–soot interaction in wrinkled non-premixed ethylene–air flames

    KAUST Repository

    Arias, Paul G.

    2015-08-17

    A two-dimensional simulation of a non-premixed ethylene–air flame was conducted by employing a detailed gas-phase reaction mechanism considering polycyclic aromatic hydrocarbons, an aerosol-dynamics-based soot model using a method of moments with interpolative closure, and a grey gas and soot radiation model using the discrete transfer method. Interaction of the sooting flame with a prescribed decaying random velocity field was investigated, with a primary interest in the effects of velocity fluctuations on the flame structure and the associated soot formation process for a fuel-strip configuration and a composition with mature soot growth. The temporally evolving simulation revealed a multi-layered soot formation process within the flame, at a level of detail not properly described by previous studies based on simplified soot models utilizing acetylene or naphthalene precursors for initial soot inception. The overall effect of the flame topology on the soot formation was found to be consistent with previous experimental studies, while a unique behaviour of localised strong oxidation was also noted. The imposed velocity fluctuations led to an increase of the scalar dissipation rate in the sooting zone, causing a net suppression in the soot production rate. Considering the complex structure of the soot formation layer, the effects of the imposed fluctuations vary depending on the individual soot reactions. For the conditions under study, the soot oxidation reaction was identified as the most sensitive to the fluctuations and was mainly responsible for the local suppression of the net soot production. © 2015 Taylor & Francis

  3. Significant Climate Changes Caused by Soot Emitted From Rockets in the Stratosphere

    Science.gov (United States)

    Mills, M. J.; Ross, M.; Toohey, D. W.

    2010-12-01

    A new type of hydrocarbon rocket engine with a larger soot emission index than current kerosene rockets is expected to power a fleet of suborbital rockets for commercial and scientific purposes in coming decades. At projected launch rates, emissions from these rockets will create a persistent soot layer in the northern middle stratosphere that would disproportionally affect the Earth’s atmosphere and cryosphere. A global climate model predicts that thermal forcing in the rocket soot layer will cause significant changes in the global atmospheric circulation and distributions of ozone and temperature. Tropical ozone columns decline as much as 1%, while polar ozone columns increase by up to 6%. Polar surface temperatures rise one Kelvin regionally and polar summer sea ice fractions shrink between 5 - 15%. After 20 years of suborbital rocket fleet operation, globally averaged radiative forcing (RF) from rocket soot exceeds the RF from rocket CO_{2} by six orders of magnitude, but remains small, comparable to the global RF from aviation. The response of the climate system is surprising given the small forcing, and should be investigated further with different climate models.

  4. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  5. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  6. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  7. Investigations of Sooting Laminar Coflow Diffusion Flames at Elevated Pressures

    KAUST Repository

    Steinmetz, Scott A.

    2016-12-01

    Soot is a common byproduct of hydrocarbon based combustion systems. It poses a risk to human and environmental health, and can negatively or positively affect combustor performance. As a result, there is significant interest in understanding soot formation in order to better control it. More recently, the need to study soot formation in engine relevant conditions has become apparent. One engine relevant parameter that has had little focus is the ambient pressure. This body of work focuses on the formation of soot in elevated pressure environments, and a number of investigations are carried out with this purpose. Laminar coflow diffusion flames are used as steady, simple soot producers. First, a commonly studied flame configuration is further characterized. Coflow flames are frequently used for fundamental flame studies, particularly at elevated pressures. However, they are more susceptible to buoyancy induced instabilities at elevated pressures. The velocity of the coflow is known to have an effect on flame stability and soot formation, though these have not been characterized at elevated pressures. A series of flames are investigated covering a range of flowrates, pressures, and nozzle diameters. The stability limits of coflow flames in this range is investigated. Additionally, an alternative strategy for scaling these flames to elevated pressures is proposed. Finally, the effect of coflow rate on soot formation is evaluated. Identification of fundamental flames for coordinated research can facilitate our understanding of soot formation. The next study of this work focuses on adding soot concentration and particle size information to an existing fundamental flame dataset for the purpose of numerical model validation. Soot volume fraction and average particle diameters are successfully measured in nitrogen-diluted ethylene-air laminar coflow flames at pressures of 4, 8, 12, and 16 atm. An increase in particle size with pressure is found up to 12 atm, where particle

  8. Soot Formation in Laminar Premixed Methane/Oxygen Flames at Atmospheric Pressure

    Science.gov (United States)

    Xu, F.; Lin, K.-C.; Faeth, G. M.

    1998-01-01

    Flame structure and soot formation were studied within soot-containing laminar premixed mc1hane/oxygen flames at atmospheric pressure. The following measurements were made: soot volume fractions by laser extinction, soot temperatures by multiline emission, gas temperatures (where soot was absent) by corrected fine-wire thermocouples, soot structure by thermophoretic sampling and transmission electron microscope (TEM), major gas species concentrations by sampling and gas chromatography, and gas velocities by laser velocimetry. Present measurements of gas species concentrations were in reasonably good agreement with earlier measurements due to Ramer et al. as well as predictions based on the detailed mechanisms of Frenklach and co-workers and Leung and Lindstedt: the predictions also suggest that H atom concentrations are in local thermodynamic equilibrium throughout the soot formation region. Using this information, it was found that measured soot surface growth rates could be correlated successfully by predictions based on the hydrogen-abstraction/carbon-addition (HACA) mechanisms of both Frenklach and co-workers and Colket and Hall, extending an earlier assessment of these mechanisms for premixed ethylene/air flames to conditions having larger H/C ratios and acetylene concentrations. Measured primary soot particle nucleation rates were somewhat lower than the earlier observations for laminar premixed ethylene/air flames and were significantly lower than corresponding rates in laminar diffusion flames. for reasons that still must be explained.

  9. Numerical Investigation of Soot Formation in Non-premixed Flames

    KAUST Repository

    Abdelgadir, Ahmed Gamaleldin

    2017-05-01

    Soot is a carbon particulate formed as a result of the combustion of fossil fuels. Due to the health hazard posed by the carbon particulate, government agencies have applied strict regulations to control soot emissions from road vehicles, airplanes, and industrial plants. Thus, understanding soot formation and evolution is critical. Practical combustion devices operate at high pressure and in the turbulent regime. Elevated pressures and turbulence on soot formation significantly and fundamental understanding of these complex interactions is still poor. In this study, the effects of pressure and turbulence on soot formation and growth are investigated numerically. As the first step, the evolution of the particle size distribution function (PSDF) and soot particles morphology are investigated in turbulent non-premixed flames. A Direct Simulation Monte Carlo (DSMC) code is developed and used. The stochastic reactor describes the evolution of soot in fluid parcels following Lagrangian trajectories in a turbulent flow field. The trajectories are sampled from a Direct Numerical Simulation (DNS) of an n-heptane turbulent non-premixed flame. Although individual trajectories display strong bimodality as in laminar flames, the ensemble-average PSDF possesses only one mode and a broad tail, which implies significant polydispersity induced by turbulence. Secondly, the effect of the flow and mixing fields on soot formation at atmospheric and elevated pressures is investigated in coflow laminar diffusion flames. The experimental observation and the numerical prediction of the spatial distribution are in good agreement. Based on the common scaling methodology of the flames (keeping the Reynolds number constant), the scalar dissipation rate decreases as pressure increases, promoting the formation of PAH species and soot. The decrease of the scalar dissipation rate significantly contributes to soot formation occurring closer to the nozzle and outward on the flames wings as pressure

  10. On the formation and early evolution of soot in turbulent nonpremixed flames

    KAUST Repository

    Bisetti, Fabrizio

    2012-01-01

    A Direct Numerical Simulation (DNS) of soot formation in an n-heptane/air turbulent nonpremixed flame has been performed to investigate unsteady strain effects on soot growth and transport. For the first time in a DNS of turbulent combustion, Polycyclic Aromatic Hydrocarbons (PAH) are included via a validated, reduced chemical mechanism. A novel statistical representation of soot aggregates based on the Hybrid Method of Moments is used [M.E. Mueller, G. Blanquart, H. Pitsch, Combust. Flame 156 (2009) 1143-1155], which allows for an accurate state-of-the-art description of soot number density, volume fraction, and morphology of the aggregates. In agreement with previous experimental studies in laminar flames, Damköhler number effects are found to be significant for PAH. Soot nucleation and growth from PAH are locally inhibited by high scalar dissipation rate, thus providing a possible explanation for the experimentally observed reduction of soot yields at increasing levels of mixing in turbulent sooting flames. Furthermore, our data indicate that soot growth models that rely on smaller hydrocarbon species such as acetylene as a proxy for large PAH molecules ignore or misrepresent the effects of turbulent mixing and hydrodynamic strain on soot formation due to differences in the species Damköhler number. Upon formation on the rich side of the flame, soot is displaced relative to curved mixture fraction iso-surfaces due to differential diffusion effects between soot and the gas-phase. Soot traveling towards the flame is oxidized, and aggregates displaced away from the flame grow primarily by condensation of PAH on the particle surface. In contrast to previous DNS studies based on simplified soot and chemistry models, surface reactions are found to contribute barely to the growth of soot, for nucleation and condensation processes occurring in the fuel stream are responsible for the most of soot mass generation. Furthermore, the morphology of the soot aggregates is

  11. Strain rate effect on sooting characteristics in laminar counterflow diffusion flames

    KAUST Repository

    Wang, Yu

    2016-01-20

    The effects of strain rate, oxygen enrichment and fuel type on the sooting characteristics of counterflow diffusion flames were studied. The sooting structures and relative PAH concentrations were measured with laser diagnostics. Detailed soot modeling using recently developed PAH chemistry and surface reaction mechanism was performed and the results were compared with experimental data for ethylene flames, focusing on the effects of strain rates. The results showed that increase in strain rate reduced soot volume fraction, average size and peak number density. Increase in oxygen mole fraction increased soot loading and decreased its sensitivity on strain rate. The soot volume fractions of ethane, propene and propane flames were also measured as a function of global strain rate. The sensitivity of soot volume fraction to strain rate was observed to be fuel dependent at a fixed oxygen mole fraction, with the sensitivity being higher for more sooting fuels. However, when the soot loadings were matched at a reference strain rate for different fuels by adjusting oxygen mole fraction, the dependence of soot loading on strain rate became comparable among the tested fuels. PAH concentrations were shown to decrease with increase in strain rate and the dependence on strain rate is more pronounced for larger PAHs. Soot modeling was performed using detailed PAH growth chemistry with molecular growth up to coronene. A qualitative agreement was obtained between experimental and simulation results, which was then used to explain the experimentally observed strain rate effect on soot growth. However, quantitatively, the simulation result exhibits higher sensitivity to strain rate, especially for large PAHs and soot volume fractions.

  12. Soot formation characteristics of gasoline surrogate fuels in counterflow diffusion flames

    KAUST Repository

    Choi, Byungchul

    2011-01-01

    The characteristics of polycyclic aromatic hydrocarbon (PAH) and soot for gasoline surrogate fuels have been investigated in counterflow diffusion flames by adopting laser-induced fluorescence (LIF) and laser-induced incandescence (LII) techniques for both soot formation and soot formation/oxidation flames. Tested fuels were three binary mixtures from the primary reference fuels of n-heptane, iso-octane, and toluene. The result showed that PAH and soot maintained near zero level for all mixtures of n-heptane/iso-octane case under present experimental conditions. For n-heptane/toluene and iso-octane/toluene mixtures, PAH initially increased and then decreased with the toluene ratio, exhibiting a synergistic effect. The soot formation increased monotonically with the toluene ratio, however the effect of toluene on soot formation was minimal for relatively small toluene ratios. These results implied that even though toluene had a dominant role in soot and PAH formations, small amount of toluene had a minimal effect on soot formation. Numerical simulations have also been conducted by adopting recently proposed two kinetic mechanisms. The synergistic behavior of aromatic rings was predicted similar to the experimental PAH measurement, however, the degree of the synergistic effect was over-predicted for the soot formation flame, indicating the need for refinements in the kinetic mechanisms. © 2010 Published by Elsevier Inc. on behalf of The Combustion Institute. All rights reserved.

  13. Formation of Soot in Counterflow Diffusion Flames with Carbon Dioxide Dilution

    KAUST Repository

    Wang, Yu

    2016-05-04

    Experimental and numerical modeling studies have been performed to investigate the effect of CO2 dilution on soot formation in ethylene counterflow diffusion flames. Thermal and chemical effects of CO2 addition on soot growth was numerically identified by using a fictitious CO2 species, which was treated as inert in terms of chemical reactions. The results showed that CO2 addition reduces soot formation both thermodynamically and chemically. In terms of chemical effect, the addition of CO2 decreases soot formation through various pathways, including: (1) reduced soot precursor (PAH) formation leading to lower inception rates and soot number density, which in turn results in lower surface area for soot mass addition; (2) reduced H, CH3, and C3H3 concentrations causing lower H abstraction rate and therefore less active site per surface area for soot growth; and (3) reduced C2H2 mole fraction and thus a slower C2H2 mass addition rate. In addition, the sooting limits were also measured for ethylene counterflow flames in both N2 and CO2 atmosphere and the results showed that sooting region was significantly reduced in the CO2 case compared to the N2 case. © 2016 Taylor & Francis.

  14. Size-resolved measurement of the mixing state of soot in the megacity Beijing, China: diurnal cycle, aging and parameterization

    Directory of Open Access Journals (Sweden)

    Y. F. Cheng

    2012-05-01

    intensities, actual turnover rates of soot (kex → in up to 20% h−1 were derived, which showed a pronounced diurnal cycle peaking around noon time. This result confirms that (soot particles are undergoing fast aging/coating with the existing high levels of condensable vapors in the megacity Beijing. (5 Diurnal cycles of Fin were different between Aitken and accumulation mode particles, which could be explained by the faster growth of smaller Aitken mode particles into larger size bins.

    To improve the Fin prediction in regional/global models, we suggest parameterizing Fin by an air mass aging indicator, i.e., Fin = a + bx, where a and b are empirical coefficients determined from observations, and x is the value of an air mass age indicator. At the Yufa site in the North China Plain, fitted coefficients (a, b were determined as (0.57, 0.21, (0.47, 0.21, and (0.52, 0.0088 for x (indicators as [NOz]/[NOy], [E]/[X] ([ethylbenzene]/[m,p-xylene] and ([IM] + [OM]/[EC] ([inorganic + organic matter]/[elemental carbon], respectively. Such a parameterization consumes little additional computing time, but yields a more realistic description of Fin compared with the simple treatment of soot mixing state in regional/global models.

  15. Soot and radiation in combusting boundary layers

    Energy Technology Data Exchange (ETDEWEB)

    Beier, R.A.

    1981-12-01

    In most fires thermal radiation is the dominant mode of heat transfer. Carbon particles within the fire are responsible for most of this emitted radiation and hence warrant quantification. As a first step toward understanding thermal radiation in full scale fires, an experimental and theoretical study is presented for a laminar combusting boundary layer. Carbon particulate volume fraction profiles and approximate particle size distributions are experimentally determined in both free and forced flow for several hydrocarbon fuels and PMMA (polymethylmethacrylate). A multiwavelength laser transmission technique determines a most probable radius and a total particle concentration which are two unknown parameters in an assumed Gauss size distribution. A sooting region is observed on the fuel rich side of the main reaction zone. For free flow, all the flames are in air, but the free stream ambient oxygen mass fraction is a variable in forced flow. To study the effects of radiation heat transfer, a model is developed for a laminar combusting boundary layer over a pyrolyzing fuel surface. An optically thin approximation simplifies the calculation of the radiant energy flux at the fuel surface. For the free flames in air, the liquid fuel soot volume fractions, f/sub v/, range from f/sub v/ approx. 10/sup -7/ for n-heptane, a paraffin, to f/sub v/ approx. 10/sup -7/ for toluene, an aromatic. The PMMA soot volume fractions, f/sub v/ approx. 5 x 10/sup -7/, are approximately the same as the values previously reported for pool fires. Soot volume fraction increases monotonically with ambient oxygen mass fraction in the forced flow flames. For all fuels tested, a most probable radius between 20 nm and 80 nm is obtained which varies only slightly with oxygen mass fraction, streamwise position, or distance normal to the fuel surface. The theoretical analysis yields nine dimensionless parameters, which control the mass flux rate at the pyrolyzing fuel surface.

  16. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  17. Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

    Science.gov (United States)

    Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

    2016-01-01

    Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

  18. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  19. Experimental determination of soot refractive index in the infrared

    International Nuclear Information System (INIS)

    Ouf, F.X.; Vendel, J.; Ouf, F.X.; Coppalle, A.; Weil, M.E.; Yon, J.

    2007-01-01

    The study of physical properties of soot particles produced during combustion is a complex subject but of a great interest within the framework of the study of the safety of an installation, with respect to the fire hazard. These characteristics are, in this case, particularly useful in order to predict the behaviour of containment barriers in situation of fire, but also in order to estimate the contribution of these particles to radiative transfers. The aim of this study is to determine the radiative properties of soot particles produced during combustion. A specific device, which establishes extinction and vertical-vertical scattering coefficients, has been developed and has allowed to determine the refractive index of soot particles in the infrared. This determination also needed the establishment of size distribution and morphological properties of soot aggregates. We present in this document the experimental device developed, and the validation of this device on latex spheres which optical properties are well known. First results of extinction coefficients will be presented and will underline the similar optical behaviour of different soot aggregates. Values of refractive index will be detailed and discussed, and a direct application of these values will be carried out in order to determine the soot volume fraction. A comparison with reference method will underline the efficiency of our method. We will conclude on the validity of the information brought by this device and on the prospects of this study. A discussion is included, on the utility of mean values of refractive index and on the determination of total emissivity of soot particles. (authors)

  20. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  1. CFD studies of soot production in a coflow laminar diffusion flame under conditions of micro-gravity in fire safety

    Directory of Open Access Journals (Sweden)

    Arnaud Mbainguebem

    2017-07-01

    Full Text Available This work which is in the fire safety framework is focused on a numerical study of the production of soot in a laminar diffusion flame, under different conditions of micro-gravity in unsteady regime. It is intended to evaluate the temperature and rate at which the production of soot is predominant, to quantify their concentrations and volume fraction in dispersion. It has been accomplished by modification of the ReactingFOAM application source code of the OpenFOAM-2.3.0 by introducing for the first time, the equations of concentration transport and of volume fractions of soot. The results of the different values of gravity obtained are compared with the normal value of gravity and we ascertain that the results obtained were satisfactory and show the ability of the code to predict the speed and temperature of the formation of soot, their concentrations and their volume fractions. The maximum peak of the volume fraction varies from 7 × 10−8 to 4.5 × 10−6. The maximum temperature, which was 2423 K before changing the code, is about 2410 K after implementation of our modifications due to the taking into account of the numerical model.

  2. Development of Kinetics for Soot Oxidation at High Pressures Under Fuel-Lean Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Lighty, JoAnn [Univ. of Utah, Salt Lake City, UT (United States); Vander Wal, Randy [Pennsylvania State Univ., University Park, PA (United States)

    2014-04-21

    The focus of the proposed research was to develop kinetic models for soot oxidation with the hope of developing a validated, predictive, multi-­scale, combustion model to optimize the design and operation of evolving fuels in advanced engines for transportation applications. The work focused on the relatively unstudied area of the fundamental mechanism for soot oxidation. The objectives include understanding of the kinetics of soot oxidation by O2 under high pressure which require: 1) development of intrinsic kinetics for the surface oxidation, which takes into account the dependence of reactivity upon nanostructure and 2) evolution of nanostructure and its impact upon oxidation rate and 3) inclusion of internal surface area development and possible fragmentation resulting from pore development and /or surface oxidation. These objectives were explored for a variety of pure fuel components and surrogate fuels. This project was a joint effort between the University of Utah (UU) and Pennsylvania State University (Penn State). The work at the UU focuses on experimental studies using a two-­stage burner and a high- pressure thermogravimetric analyzer (TGA). Penn State provided HRTEM images and guidance in the fringe analysis algorithms and parameter quantification for the images. This report focuses on completion done under supplemental funding.

  3. Mixing state of regionally transported soot particles and the coating effect on their size and shape at a mountain site in Japan

    Science.gov (United States)

    Adachi, Kouji; Zaizen, Yuji; Kajino, Mizuo; Igarashi, Yasuhito

    2014-05-01

    Soot particles influence the global climate through interactions with sunlight. A coating on soot particles increases their light absorption by increasing their absorption cross section and cloud condensation nuclei activity when mixed with other hygroscopic aerosol components. Therefore, it is important to understand how soot internally mixes with other materials to accurately simulate its effects in climate models. In this study, we used a transmission electron microscope (TEM) with an auto particle analysis system, which enables more particles to be analyzed than a conventional TEM. Using the TEM, soot particle size and shape (shape factor) were determined with and without coating from samples collected at a remote mountain site in Japan. The results indicate that ~10% of aerosol particles between 60 and 350 nm in aerodynamic diameters contain or consist of soot particles and ~75% of soot particles were internally mixed with nonvolatile ammonium sulfate or other materials. In contrast to an assumption that coatings change soot shape, both internally and externally mixed soot particles had similar shape and size distributions. Larger aerosol particles had higher soot mixing ratios, i.e., more than 40% of aerosol particles with diameters >1 µm had soot inclusions, whereas <20% of aerosol particles with diameters <1 µm included soot. Our results suggest that climate models may use the same size distributions and shapes for both internally and externally mixed soot; however, changing the soot mixing ratios in the different aerosol size bins is necessary.

  4. Cosmic: Carbon Monoxide And Soot In Microgravity Inverse Combustion

    Science.gov (United States)

    Mikofski, M. A.; Blevins, L. G.; Davis, R. W.; Moore, E. F.; Mulholland, G. W.; Sacksteder, Kurt (Technical Monitor)

    2003-01-01

    Almost seventy percent of fire related deaths are caused by the inhalation of toxins such as CO and soot that are produced when fires become underventilated.(1) Although studies have established the importance of CO formation during underventilated burning,(2) the formation processes of CO (and soot) in underventilated fires are not well understood. The goal of the COSMIC project is to study the formation processes of CO and soot in underventilated flames. A potential way to study CO and soot production in underventilated flames is the use of inverse diffusion flames (IDFs). An IDF forms between a central air jet and a surrounding fuel jet. IDFs are related to underventilated flames because they may allow CO and soot to escape unoxidized. Experiments and numerical simulations of laminar IDFs of CH4 and C2H4 were conducted in 1-g and micro-g to study CO and soot formation. Laminar flames were studied because turbulent models of underventilated fires are uncertain. Microgravity was used to alter CO and soot pathways. A IDF literature survey, providing background and establishing motivation for this research, was presented at the 5th IWMC.(3) Experimental results from 1-g C2H4 IDFs and comparisons with simulations, demonstrating similarities between IDFs and underventilated fires, were presented at the 6th IWMC.(4) This paper will present experimental results from micro-g and 1-g IDFs of CH4 and C2H4 as well as comparisons with simulations, further supporting the relation between IDFs and underventilated flames.

  5. Effect of soot on oil properties and wear of engine components

    International Nuclear Information System (INIS)

    Green, D A; Lewis, R

    2007-01-01

    The objective of the work outlined in this paper was to increase the understanding of the wear mechanisms that occur within a soot contaminated contact zone, to help in future development of a predictive wear model to assist in the automotive engine valve train design process. The paper builds on previous work by the author, through testing of different lubricants and increased levels of soot contamination. Wear testing has been carried out using specimens operating under realistic engine conditions, using a reciprocating test-rig specifically designed for this application, where a steel disc is held in a heated bath of oil and a steel ball is attached to a reciprocating arm (replicating a sliding elephant's foot valve train contact). Detailed analysis of the test specimens has been performed using scanning electron microscopy to identify wear features relating to the proposed wear mechanisms. Analysis of worn engine components from durability engine tests has also been carried out for a comparison between specimen tests and engine testing. To assist the understanding of the wear test results obtained, the physical properties of contaminated lubricants were investigated, through viscosity, traction and friction measurements. The results have revealed how varying lubrication conditions change the wear rate of engine components and determine the wear mechanism that dominates in specific situations. Testing has also shown the positive effects of advanced engine lubricants to reduce the amount of wear produced with soot present

  6. Influence of turbulence-chemistry interaction for n-heptane spray combustion under diesel engine conditions with emphasis on soot formation and oxidation

    Science.gov (United States)

    Bolla, Michele; Farrace, Daniele; Wright, Yuri M.; Boulouchos, Konstantinos; Mastorakos, Epaminondas

    2014-03-01

    The influence of the turbulence-chemistry interaction (TCI) for n-heptane sprays under diesel engine conditions has been investigated by means of computational fluid dynamics (CFD) simulations. The conditional moment closure approach, which has been previously validated thoroughly for such flows, and the homogeneous reactor (i.e. no turbulent combustion model) approach have been compared, in view of the recent resurgence of the latter approaches for diesel engine CFD. Experimental data available from a constant-volume combustion chamber have been used for model validation purposes for a broad range of conditions including variations in ambient oxygen (8-21% by vol.), ambient temperature (900 and 1000 K) and ambient density (14.8 and 30 kg/m3). The results from both numerical approaches have been compared to the experimental values of ignition delay (ID), flame lift-off length (LOL), and soot volume fraction distributions. TCI was found to have a weak influence on ignition delay for the conditions simulated, attributed to the low values of the scalar dissipation relative to the critical value above which auto-ignition does not occur. In contrast, the flame LOL was considerably affected, in particular at low oxygen concentrations. Quasi-steady soot formation was similar; however, pronounced differences in soot oxidation behaviour are reported. The differences were further emphasised for a case with short injection duration: in such conditions, TCI was found to play a major role concerning the soot oxidation behaviour because of the importance of soot-oxidiser structure in mixture fraction space. Neglecting TCI leads to a strong over-estimation of soot oxidation after the end of injection. The results suggest that for some engines, and for some phenomena, the neglect of turbulent fluctuations may lead to predictions of acceptable engineering accuracy, but that a proper turbulent combustion model is needed for more reliable results.

  7. Impact of morphology on the radiative properties of fractal soot aggregates

    International Nuclear Information System (INIS)

    Doner, Nimeti; Liu, Fengshan

    2017-01-01

    The impact of morphology on the radiative properties of fractal soot aggregates was investigated using the discrete dipole approximation (DDA). The optical properties of four different types of aggregates of freshly emitted soot with a fractal dimension D f =1.65 and a fractal pre-factor k f =1.76 were calculated. The four types of aggregates investigated are formed by uniform primary particles in point-touch, by uniform but overlapping primary particles, by uniform but enlarged primary particles in point-touch, and formed by point-touch and polydisperse primary particles. The radiative properties of aggregates consisting of N=20, 56 and 103 primary particles were numerically evaluated for a given refractive index at 0.532 and 1.064 μm. The radiative properties of soot aggregates vary strongly with the volume equivalent radius a eff and wavelength. The accuracy of DDA was evaluated in the first and fourth cases against the generalized multi-sphere Mie (GMM) solution in terms of the vertical–vertical differential scattering cross section (C vv ). The model predicted the average relative deviations from the base case to be within 15–25% for C vv , depending on the number of particles for the aggregate. The scattering cross sections are only slightly affected by the overlapping but more significantly influenced by primary particle polydispersity. It was also found that the enlargement of primary particles by 20% has a strong effect on soot aggregate radiative properties. - Highlights: • The radiative properties of aggregates of N=20, 56 and 103 primary particles were investigated. • Four different cases, formed by point-touch, overlapping, aggregate expansion and polydispersion, were studied. • The effects of overlapping and aggregate expansion on morphology are found to be the same.

  8. Laser-induced incandescence: Towards quantitative soot volume fraction measurements

    Energy Technology Data Exchange (ETDEWEB)

    Tzannis, A P; Wienbeucker, F; Beaud, P; Frey, H -M; Gerber, T; Mischler, B; Radi, P P [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1999-08-01

    Laser-Induced Incandescence has recently emerged as a versatile tool for measuring soot volume fraction in a wide range of combustion systems. In this work we investigate the essential features of the method. LII is based on the acquisition of the incandescence of soot when heated through a high power laser pulse. Initial experiments have been performed on a model laboratory flame. The behaviour of the LII signal is studied experimentally. By applying numerical calculations we investigate the possibility to obtain two-dimensional soot volume fraction distributions. For this purpose a combination of LII with other techniques is required. This part is discussed in some extent and the future work is outlined. (author) 4 figs., 3 refs.

  9. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

  10. Phototransformation rate constants of PAHs associated with soot particles

    International Nuclear Information System (INIS)

    Kim, Daekyun; Young, Thomas M.; Anastasio, Cort

    2013-01-01

    Photodegradation is a key process governing the residence time and fate of polycyclic aromatic hydrocarbons (PAHs) in particles, both in the atmosphere and after deposition. We have measured photodegradation rate constants of PAHs in bulk deposits of soot particles illuminated with simulated sunlight. The photodegradation rate constants at the surface (k p 0 ), the effective diffusion coefficients (D eff ), and the light penetration depths (z 0.5 ) for PAHs on soot layers of variable thickness were determined by fitting experimental data with a model of coupled photolysis and diffusion. The overall disappearance rates of irradiated low molecular weight PAHs (with 2–3 rings) on soot particles were influenced by fast photodegradation and fast diffusion kinetics, while those of high molecular weight PAHs (with 4 or more rings) were apparently controlled by either the combination of slow photodegradation and slow diffusion kinetics or by very slow diffusion kinetics alone. The value of z 0.5 is more sensitive to the soot layer thickness than the k p 0 value. As the thickness of the soot layer increases, the z 0.5 values increase, but the k p 0 values are almost constant. The effective diffusion coefficients calculated from dark experiments are generally higher than those from the model fitting method for illumination experiments. Due to the correlation between k p 0 and z 0.5 in thinner layers, D eff should be estimated by an independent method for better accuracy. Despite some limitations of the model used in this study, the fitted parameters were useful for describing empirical results of photodegradation of soot-associated PAHs. - Highlights: ► PAHs on soot were evaluated by a model of coupled photolysis and diffusion. ► Photodegradation rate at the surface, diffusion coefficient, and light penetration path were determined. ► Low MW PAHs were influenced by fast photodegradation and fast diffusion. ► High MW PAHs were controlled either by slow

  11. A mechanistic study on the simultaneous elimination of soot and nitric oxide from engine exhaust

    KAUST Repository

    Raj, Abhijeet; Zainuddin, Zakwan; Sander, Markus; Kraft, Markus

    2011-01-01

    The non-catalytic interaction between soot and nitric oxide (NO) resulting in their simultaneous elimination was studied on different types of reactive site present on soot. The reaction mechanism proposed previously was extended by including seven new reaction pathways for which the reaction energetics and kinetics were studied using density functional theory and transition state theory. This has led to the calculation of a new rate for the removal of carbon monoxide (CO) from soot. The new pathways have been added to our polycyclic aromatic hydrocarbon (PAH) growth model and used to simulate the NO-soot interaction to form CO, N2 and N2O. The simulation results show satisfactory agreement with experiment for the new CO removal rate. The NO-soot reaction was found to depend strongly on the soot site type and temperature. For a set of temperatures, computed PAH structures were analysed to determine the functional groups responsible for the decrease in the reactivity of soot with NO with increasing reaction time. In isothermal conditions, it was found that as temperature is increased, the number of oxygen atoms remaining on the soot surface decreases, while the number of nitrogen atoms increases for a given reaction time. © 2010 Elsevier Ltd. All rights reserved.

  12. Quantitative characterization of steady and time-varying, sooting, laminar diffusion flames using optical techniques

    Science.gov (United States)

    Connelly, Blair C.

    In order to reduce the emission of pollutants such as soot and NO x from combustion systems, a detailed understanding of pollutant formation is required. In addition to environmental concerns, this is important for a fundamental understanding of flame behavior as significant quantities of soot lower local flame temperatures, increase overall flame length and affect the formation of such temperature-dependent species as NOx. This problem is investigated by carrying out coupled computational and experimental studies of steady and time-varying sooting, coflow diffusion flames. Optical diagnostic techniques are a powerful tool for characterizing combustion systems, as they provide a noninvasive method of probing the environment. Laser diagnostic techniques have added advantages, as systems can be probed with high spectral, temporal and spatial resolution, and with species selectivity. Experimental soot volume fractions were determined by using two-dimensional laser-induced incandescence (LII), calibrated with an on-line extinction measurement, and soot pyrometry. Measurements of soot particle size distributions are made using time-resolved LII (TR-LII). Laser-induced fluorescence measurements are made of NO and formaldehyde. These experimental measurements, and others, are compared with computational results in an effort to understand and model soot formation and to examine the coupled relationship of soot and NO x formation.

  13. A mechanistic study on the simultaneous elimination of soot and nitric oxide from engine exhaust

    KAUST Repository

    Raj, Abhijeet

    2011-04-01

    The non-catalytic interaction between soot and nitric oxide (NO) resulting in their simultaneous elimination was studied on different types of reactive site present on soot. The reaction mechanism proposed previously was extended by including seven new reaction pathways for which the reaction energetics and kinetics were studied using density functional theory and transition state theory. This has led to the calculation of a new rate for the removal of carbon monoxide (CO) from soot. The new pathways have been added to our polycyclic aromatic hydrocarbon (PAH) growth model and used to simulate the NO-soot interaction to form CO, N2 and N2O. The simulation results show satisfactory agreement with experiment for the new CO removal rate. The NO-soot reaction was found to depend strongly on the soot site type and temperature. For a set of temperatures, computed PAH structures were analysed to determine the functional groups responsible for the decrease in the reactivity of soot with NO with increasing reaction time. In isothermal conditions, it was found that as temperature is increased, the number of oxygen atoms remaining on the soot surface decreases, while the number of nitrogen atoms increases for a given reaction time. © 2010 Elsevier Ltd. All rights reserved.

  14. PREDICTED PERCENTAGE DISSATISFIED (PPD) MODEL ...

    African Journals Online (AJOL)

    HOD

    their low power requirements, are relatively cheap and are environment friendly. ... PREDICTED PERCENTAGE DISSATISFIED MODEL EVALUATION OF EVAPORATIVE COOLING ... The performance of direct evaporative coolers is a.

  15. Formation of polycyclic aromatic hydrocarbons and soot in fuel-rich oxidation of methane in a laminar flow reactor

    DEFF Research Database (Denmark)

    Skjøth-Rasmussen, Martin Skov; Glarborg, Peter; Østberg, M.

    2004-01-01

    Conversion of methane to higher hydrocarbons, polycyclic aromatic hydrocarbons (PAHs), and soot was investigated under fuel-rich conditions in a laminar flow reactor. The effects of stoichiometry, dilution, and water vapor addition were studied at temperatures between 1073 and 1823 K. A chemical...... kinetic mechanism was established for methane oxidation, with emphasis on formation of higher hydrocarbons and PAH. A submodel for soot formation was adopted from the work of Frenklach and co-workers without changes. Modeling predictions showed good agreement with experimental results. Reactants, stable...... decrease with increasing addition of water vapor. The effect is described qualitatively by the reaction mechanism. The enhanced oxidation of acetylene is attributed to higher levels of hydroxyl radicals, formed from the reaction between the water vapor and hydrogen atoms....

  16. Dielectric properties of PMMA/Soot nanocomposites.

    Science.gov (United States)

    Clayton, Lanetra M; Cinke, Martin; Meyyappan, M; Harmon, Julie P

    2007-07-01

    Dielectric analysis (DEA) of relaxation behavior in poly(methyl methacrylate) (PMMA) soot nanocomposites is described herein. The soot, an inexpensive material, consists of carbon nanotubes, amorphous and graphitic carbon and metal particles. Results are compared to earlier studies on PMMA/multi-walled nanotube (MWNT) composites and PMMA/single-walled nanotube (SWNT) composites. The beta relaxation process appeared to be unaffected by the presence of the soot, as was noted earlier in nanotube composites. The gamma relaxation region in PMMA, normally dielectrically inactive, was "awakened" in the PMMA/soot composite. This occurrence is consistent with previously published data on nanotube composites. The dielectric permittivity, s', increased with soot content. The sample with 1% soot exhibited a permittivity (at 100 Hz and 25 degrees C) of 7.3 as compared to 5.1 for neat PMMA. Soot increased the dielectric strength, deltaE, of the composites. The 1% soot sample exhibited a dielectric strength of 6.38, while the neat PMMA had a value of 2.95 at 40 degrees C. The symmetric broadening term (alpha) was slightly higher for the 1% composite at temperatures near the secondary relaxation and near the primary relaxation, but all samples deviated from symmetrical semi-circular behavior (alpha = 1). The impact of the soot filler is seen more clearly in dielectric properties than in mechanical properties studies conducted earlier.

  17. Simulation of soot size distribution in an ethylene counterflow flame

    KAUST Repository

    Zhou, Kun; Abdelgadir, Ahmed Gamaleldin; Bisetti, Fabrizio

    2014-01-01

    Soot, an aggregate of carbonaceous particles produced during the rich combustion of fossil fuels, is an undesirable pollutant and health hazard. Soot evolution involves various dynamic processes: nucleation soot formation from polycyclic aromatic

  18. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  19. Simulation of soot size distribution in an ethylene counterflow flame

    KAUST Repository

    Zhou, Kun

    2014-01-06

    Soot, an aggregate of carbonaceous particles produced during the rich combustion of fossil fuels, is an undesirable pollutant and health hazard. Soot evolution involves various dynamic processes: nucleation soot formation from polycyclic aromatic hydrocarbons (PAHs) condensation PAHs condensing on soot particle surface surface processes hydrogen-abstraction-C2H2-addition, oxidation coagulation two soot particles coagulating to form a bigger particle This simulation work investigates soot size distribution and morphology in an ethylene counterflow flame, using i). Chemkin with a method of moments to deal with the coupling between vapor consumption and soot formation; ii). Monte Carlo simulation of soot dynamics.

  20. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... signal based on a process model, coping with constraints on inputs and ... paper, we will present an introduction to the theory and application of MPC with Matlab codes ... section 5 presents the simulation results and section 6.

  1. Subsonic aircraft soot. A tracer documenting barriers to inter-hemispheric mixing

    Energy Technology Data Exchange (ETDEWEB)

    Pueschel, R F [NASA Ames Research Center, Moffett Field, CA (United States)

    1998-12-31

    Meridional observations of soot aerosols and radioactive {sup 14}C, and models of the geographic distribution of nuclear bomb-released {sup 14}C and aircraft-emitted NO{sub x}, all show strong gradients between the hemispheres. Reason for it are decade-long inter-hemispheric mixing times which are much in excess of yearlong stratospheric residence times of tracers. Vertical mixing of soot aerosol is not corroborated by {sup 14}C observations. The reason could be radiometric forces that act on strongly absorbing soot. (author) 10 refs.

  2. Subsonic aircraft soot. A tracer documenting barriers to inter-hemispheric mixing

    Energy Technology Data Exchange (ETDEWEB)

    Pueschel, R.F. [NASA Ames Research Center, Moffett Field, CA (United States)

    1997-12-31

    Meridional observations of soot aerosols and radioactive {sup 14}C, and models of the geographic distribution of nuclear bomb-released {sup 14}C and aircraft-emitted NO{sub x}, all show strong gradients between the hemispheres. Reason for it are decade-long inter-hemispheric mixing times which are much in excess of yearlong stratospheric residence times of tracers. Vertical mixing of soot aerosol is not corroborated by {sup 14}C observations. The reason could be radiometric forces that act on strongly absorbing soot. (author) 10 refs.

  3. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Numerical simulation of combustion and soot under partially premixed combustion of low-octane gasoline

    KAUST Repository

    An, Yanzhao

    2017-09-23

    In-cylinder combustion visualization and engine-out soot particle emissions were investigated in an optical diesel engine fueled with low octane gasoline. Single injection strategy with an early injection timing (−30 CAD aTDC) was employed to achieve partially premixed combustion (PPC) condition. A high-speed color camera was used to record the combustion images for 150 cycles. The regulated emission of carbon dioxide, carbon monoxide, nitrogen oxides and soot mass concentration were measured experimentally. Full cycle engine simulations were performed using CONVERGE™ and the simulation results matched with the experimental results. The in-cylinder soot particle evolution was performed by coupling a reduced toluene reference fuel mechanism including the PAHs formation/oxidation reactions with particulate size mimic model. The results showed that PPC presents typical stratified combustion characteristics, which is significantly different from the conventional diesel spray-driven combustion. The in-cylinder temperature and equivalence ratio overlaid with soot-NO formation regime revealed that PPC operating condition under study mostly avoided the main sooting conditions throughout the entire combustion. The evaluation of temperature distribution showed formaldehyde could be regarded as an indicator for low temperature reactions, while hydroxyl group represents the high temperature reactions. Soot evolution happened during the combustion process, hydroxyl radicals promoted the soot oxidation.

  5. Numerical simulation of combustion and soot under partially premixed combustion of low-octane gasoline

    KAUST Repository

    An, Yanzhao; Jaasim, Mohammed; Vallinayagam, R.; Vedharaj, S.; Im, Hong G.; Johansson, Bengt.

    2017-01-01

    In-cylinder combustion visualization and engine-out soot particle emissions were investigated in an optical diesel engine fueled with low octane gasoline. Single injection strategy with an early injection timing (−30 CAD aTDC) was employed to achieve partially premixed combustion (PPC) condition. A high-speed color camera was used to record the combustion images for 150 cycles. The regulated emission of carbon dioxide, carbon monoxide, nitrogen oxides and soot mass concentration were measured experimentally. Full cycle engine simulations were performed using CONVERGE™ and the simulation results matched with the experimental results. The in-cylinder soot particle evolution was performed by coupling a reduced toluene reference fuel mechanism including the PAHs formation/oxidation reactions with particulate size mimic model. The results showed that PPC presents typical stratified combustion characteristics, which is significantly different from the conventional diesel spray-driven combustion. The in-cylinder temperature and equivalence ratio overlaid with soot-NO formation regime revealed that PPC operating condition under study mostly avoided the main sooting conditions throughout the entire combustion. The evaluation of temperature distribution showed formaldehyde could be regarded as an indicator for low temperature reactions, while hydroxyl group represents the high temperature reactions. Soot evolution happened during the combustion process, hydroxyl radicals promoted the soot oxidation.

  6. NASA: Black soot fuels global warming

    CERN Multimedia

    2003-01-01

    New research from NASA's Goddard Space Center scientists suggests emissions of black soot have been altering the way sunlight reflects off Earth's snow. The research indicates the soot could be responsible for as much as 25 percent of global warming over the past century (assorted news items, 1 paragraph each).

  7. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  8. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  9. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  10. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  11. Quantitative effects of rapid heating on soot-particle sizing through analysis of two-pulse LII

    KAUST Repository

    Cenker, Emre; Roberts, William L.

    2017-01-01

    particle size, respectively. Overall, effects of these two processes on soot and LII model-based particle sizing are investigated by measuring the two-color time-resolved (2C-TiRe) LII signal decay from in-flame soot after two consecutive laser pulses

  12. Emissions of soot particles from heat generators

    Science.gov (United States)

    Lyubov, V. K.; Popov, A. N.; Popova, E. I.

    2017-11-01

    «Soot carbon» or «Soot» - incomplete combustion or thermal decomposition particulate carbon product of hydrocarbons consisting of particles of various shapes and sizes. Soot particles are harmful substances Class 2 and like a dust dispersed by wind for thousands of kilometers. Soot have more powerful negative factor than carbon dioxide. Therefore, more strict requirements on ecological and economical performance for energy facilities at Arctic areas have to be developed to protect fragile Arctic ecosystems and global climate change from degradation and destruction. Quantity of soot particles in the flue gases of energy facilities is a criterion of effectiveness for organization of the burning process. Some of heat generators do not provide the required energy and environmental efficiency which results in irrational use of energy resources and acute pollution of environment. The paper summarizes the results of experimental study of solid particles emission from wide range of capacity boilers burning different organic fuels (natural gas, fuel oil, coal and biofuels). Special attention is paid to environmental and energy performance of the biofuels combustion. Emissions of soot particles PM2.5 are listed. Structure, composition and dimensions of entrained particles with the use of electronic scanning microscope Zeiss SIGMA VP were also studied. The results reveal an impact of several factors on soot particles emission.

  13. Investigation of black soot staining in houses

    Energy Technology Data Exchange (ETDEWEB)

    Fugler, D. [Canada Mortgage and Housing Corp., Ottawa, ON (Canada)

    2000-07-01

    Air quality investigators are frequently called upon to determine the origin of streaking, staining or soot marks in both new and old homes. Those marks display common characteristics: black marks along baseboards at interior or exterior walls, behind furniture and at doorways; black smudges on window frames and plastic cabinets; and even shadowing of studs on exterior wall drywall in a few cases. In most instances, carbon soot from a combustion source is the culprit. The combustion sources include furnaces, water heaters, fireplaces, gas dryers, gas ranges, smoking, vehicle exhaust and candle burning. Scepticism about candle soot is prevalent among callers. As a result, a study was initiated in homes where occupants burn candles regularly to investigate soot problems. Samples were collected from five homes, and included stained carpets, filters, and swab samples of black dust or soot. All the houses selected for the study had been built within a three-year period. Some samples of candles commonly burned in those homes were burnt in a laboratory. Air quality audits had been performed in the homes and had revealed other potential pollutant sources. Best practices for cost-effective clean up and control of soot were researched in industry information. The tests conducted in the laboratory found materials consistent with candle soot or residue during microscopic investigations, but no link was established with the stained material obtained from the homes. A few tips for homeowners were included concerning candle burning, and tips for builders were also offered. 1 tab.

  14. Effect of strain rate on sooting limits in counterflow diffusion flames of gaseous hydrocarbon fuels: Sooting temperature index and sooting sensitivity index

    KAUST Repository

    Wang, Yu

    2014-05-01

    The effect of the strain rate on the sooting limits in counterflow diffusion flames was investigated in various gaseous hydrocarbon fuels by varying the nitrogen dilution in the fuel and oxidizer streams. The sooting limit was defined as the critical fuel and oxygen mole fraction at which soot started to appear in the elastic light scattering signal. The sooting region for normal alkane fuels at a specified strain rate, in terms of the fuel and oxygen mole fraction, expanded as the number of carbon atoms increased. The alkene fuels (ethylene, propene) tested had a higher propensity for sooting as compared with alkane fuels with the same carbon numbers (ethane, propane). Branched iso-butane had a higher propensity for sooting than did n-butane. An increase in the strain rate reduced the tendency for sooting in all the fuels tested. The sensitivity of the sooting limit to the strain rate was more pronounced for less sooting fuels. When plotted in terms of calculated flame temperature, the critical oxygen mole fraction exhibited an Arrhenius form under sooting limit conditions, which can be utilized to significantly reduce the effort required to determine sooting limits at different strain rates. We found that the limiting temperatures of soot formation flames are viable sooting metrics for quantitatively rating the sooting tendency of various fuels, based on comparisons with threshold soot index and normalized smoke point data. We also introduce a sooting temperature index and a sooting sensitivity index, two quantitative measures to describe sooting propensity and its dependence on strain rate. © 2013 The Combustion Institute.

  15. Monte carlo simulation for soot dynamics

    KAUST Repository

    Zhou, Kun

    2012-01-01

    A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

  16. Soot volume fraction fields in unsteady axis-symmetric flames by continuous laser extinction technique.

    Science.gov (United States)

    Kashif, Muhammad; Bonnety, Jérôme; Guibert, Philippe; Morin, Céline; Legros, Guillaume

    2012-12-17

    A Laser Extinction Method has been set up to provide two-dimensional soot volume fraction field time history at a tunable frequency up to 70 Hz inside an axis-symmetric diffusion flame experiencing slow unsteady phenomena preserving the symmetry. The use of a continuous wave laser as the light source enables this repetition rate, which is an incremental advance in the laser extinction technique. The technique is shown to allow a fine description of the soot volume fraction field in a flickering flame exhibiting a 12.6 Hz flickering phenomenon. Within this range of repetition rate, the technique and its subsequent post-processing require neither any method for time-domain reconstruction nor any correction for energy intrusion. Possibly complemented by such a reconstruction method, the technique should support further soot volume fraction database in oscillating flames that exhibit characteristic times relevant to the current efforts in the validation of soot processes modeling.

  17. Oxidation kinetics and soot formation

    Science.gov (United States)

    Glassman, I.; Brezinsky, K.

    1983-01-01

    The research objective is to clarify the role of aromaticity in the soot nucleation process by determining the relative importance of phenyl radical/molecular oxygen and benzene/atomic oxygen reactions in the complex combustion of aromatic compounds. Three sets of chemical flow reactor experiments have been designed to determine the relative importance of the phenyl radical/molecular oxygen and benzene/atomic oxygen reactions. The essential elements of these experiments are 1) the use of cresols and anisole formed during the high temperature oxidation of toluene as chemical reaction indicators; 2) the in situ photolysis of molecular oxygen to provide an oxygen atom perturbation in the reacting aromatic system; and 3) the high temperature pyrolysis of phenol, the cresols and possibly anisole.

  18. Soot Formation In Turbulent Combusting Flows

    National Research Council Canada - National Science Library

    Santoro, Robert

    1998-01-01

    .... Laser-based techniques were used to measure the soot volume fraction, particle size and number density as well as the temperature and relative concentration of hydroxyl radicals and polycyclic aromatic hydrocarbons...

  19. Method for removing soot from exhaust gases

    Science.gov (United States)

    Suib, Steven L.; Dharmarathna, D. A. Saminda; Pahalagedara, Lakshitha R.

    2018-01-16

    A method for oxidizing soot from diesel exhaust gas from a diesel engine. The method involves providing a diesel particulate filter for receiving the diesel exhaust gas; coating a catalyst composition on the diesel particulate filter; and contacting the soot from the diesel exhaust gas with the catalyst coated diesel particulate filter at a temperature sufficient to oxidize the soot to carbon dioxide. The catalyst composition is a doped or undoped manganese oxide octahedral molecular sieve (OMS-2) material. A diesel exhaust gas treatment system that includes a diesel particulate filter for receiving diesel exhaust gas from a diesel engine and collecting soot; and a catalyst composition coated on the diesel particulate filter. The catalyst composition is a doped or undoped manganese oxide octahedral molecular sieve (OMS-2).

  20. Electrometric aviation soot monitor, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a highly sensitive and portable device to monitor soot particle mass distribution from aircraft engine exhaust. The proposed method is based on...

  1. Diesel soot oxidation under controlled conditions

    OpenAIRE

    Song, Haiwen

    2003-01-01

    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 11/12/2003. In order to improve understanding of diesel soot oxidation, an experimental rig was designed and set up, in which the soot oxidation conditions, such as temperature, oxygen partial pressure, and CO2 partial pressure, could be varied independently of each other. The oxidizing gas flow in the oxidizer was under laminar condition. This test rig comprised a naturally-aspirated single ...

  2. Sooting limit in counterflow diffusion flames of ethylene/propane fuels and implication to threshold soot index

    KAUST Repository

    Joo, Peter H.

    2013-01-01

    Sooting limits in counterflow diffusion flames of propane/ethylene fuels have been studied experimentally using a light scattering technique, including the effects of dilution, fuel mixing, and strain rate. The results are discussed in view of the threshold soot index (TSI). In soot-formation (SF) flames, where the flame is located on the oxidizer side of the stagnation plane, the sooting limit depends critically on fuel type and subsequently on flame temperature. The sooting limit has a non-linear dependence on the fuel-mixing ratio, which is similar to the non-linear mixing rule for TSI observed experimentally in rich premixed flames, where soot oxidation is absent for both SF and rich premixed flames. In soot-formation-oxidation (SFO) flames, where the flame is located on the fuel side, the sooting limit depends critically on flame temperature, while it is relatively independent on fuel type. This result suggests a linear mixing rule for sooting limits in SFO flames, which is similar to the TSI behavior for coflow diffusion flames. Soot oxidation takes place for both types of flames. The aerodynamic strain effect on the sooting limits has also been studied and an appreciable influence has been observed. Under sooting conditions, soot volume fraction was measured using a light extinction technique. The soot loadings in SF flames of the mixture fuels demonstrated a synergistic effect, i.e., soot production increased for certain mixture fuels as compared to the respective singlecomponent fuels. © 2012 The Combustion Institute.

  3. NATO Workshop on Soot in Combustion Systems

    CERN Document Server

    Prado, G

    1983-01-01

    Our interest in Mulhouse for carbon black and soot began some 30 years ago when J.B. Donnet developed the concept of surface chemistry of carbon and its involvement in interactions with gas, liquid and solid phases. In the late sixties, we began to study soot formation in pyrolytic systems and later on in flames. The idea of organ1z1ng a meeting on soot formation originated some four or five years ago, through discussions among Professor J.B. Howard, Dr. A. D'Alessio and ourselves. At that time the scientific community was becoming aware of the necessity to strictly control soot formation and emission. Being involved in the study of surface properties of carbon black as well as of formation of soot, we realized that the combustion community was not always fully aware of the progress made by the physical-chemists on carbon black. Reciprocally, the carbon specialists were often ignoring the research carried out on soot in flames. One objective of this workshop was to stimulate discussions between these two scie...

  4. The pH-dependent adsorption of tributyltin to charcoals and soot

    International Nuclear Information System (INIS)

    Fang Liping; Borggaard, Ole K.; Marcussen, Helle; Holm, Peter E.; Bruun Hansen, Hans Christian

    2010-01-01

    Widespread use of tributyltin (TBT) poses a serious environmental problem. Adsorption by black carbon (BC) may strongly affect its behavior. The adsorption of TBT to well characterized soot and two charcoals with specific surface area in the range of 62-111 m 2 g -1 have been investigated with main focus on pH effects. The charcoals but not soot possess acidic functional groups. TBT adsorption reaches maximum at pH 6-7 for charcoals, and at pH > 6 for soot. Soot has between 1.5 and 15 times higher adsorption density (0.09-1.77 μmol m -2 ) than charcoals, but charcoals show up to 17 times higher sorption affinities than soot. TBT adsorption is successfully described by a new pH-dependent dual Langmuir model considering electrostatic and hydrophobic adsorption, and pH effects on TBT speciation and BC surface charge. It is inferred that strong sorption of the TBTOH species to BC may affect TBT toxicity. - Tributyltin adsorption to black carbon increases at increasing pH but charcoal exhibits electrostatic and hydrophobic adsorption, whereas soot only adsorbs hydrophobically.

  5. The pH-dependent adsorption of tributyltin to charcoals and soot

    Energy Technology Data Exchange (ETDEWEB)

    Fang Liping, E-mail: fang@life.ku.d [Department of Basic Sciences and Environment, Faculty of Life Sciences, University of Copenhagen, Thorvaldsensvej 40, DK-1871 Frederiksberg C (Denmark); Borggaard, Ole K.; Marcussen, Helle; Holm, Peter E.; Bruun Hansen, Hans Christian [Department of Basic Sciences and Environment, Faculty of Life Sciences, University of Copenhagen, Thorvaldsensvej 40, DK-1871 Frederiksberg C (Denmark)

    2010-12-15

    Widespread use of tributyltin (TBT) poses a serious environmental problem. Adsorption by black carbon (BC) may strongly affect its behavior. The adsorption of TBT to well characterized soot and two charcoals with specific surface area in the range of 62-111 m{sup 2} g{sup -1} have been investigated with main focus on pH effects. The charcoals but not soot possess acidic functional groups. TBT adsorption reaches maximum at pH 6-7 for charcoals, and at pH > 6 for soot. Soot has between 1.5 and 15 times higher adsorption density (0.09-1.77 {mu}mol m{sup -2}) than charcoals, but charcoals show up to 17 times higher sorption affinities than soot. TBT adsorption is successfully described by a new pH-dependent dual Langmuir model considering electrostatic and hydrophobic adsorption, and pH effects on TBT speciation and BC surface charge. It is inferred that strong sorption of the TBTOH species to BC may affect TBT toxicity. - Tributyltin adsorption to black carbon increases at increasing pH but charcoal exhibits electrostatic and hydrophobic adsorption, whereas soot only adsorbs hydrophobically.

  6. Modelling studies of the oxidation and auto-ignition of alkanes, aromatics, and their mixtures at high pressure between 600 and 1500 K: reduction of detailed mechanisms: measurements of the building up of soot; Etudes par modelisation de l'oxydation et de l'autoinflammation d'alcanes et d'aromatiques purs et de melanges a haute pression entre 600 et 1500 K: reduction de mecanismes detailles: mesure de la formation des suies

    Energy Technology Data Exchange (ETDEWEB)

    Saylam, A.

    2005-11-15

    The understanding and control of many combustion phenomena requires an interactive work between experiments and modelling. The presentation of the two coupled approaches is a prerequisite to demonstrate the complexity of the phenomena (Chapters I and II). This complexity often precludes from fully elucidating the details of the chemistry of hydrocarbon oxidations. Such a failure has been shown by an attempt to improve the mechanism of oxidation of iso-octane (Chapter III). Hundreds of species and thousands of reactions come into play during the oxidation of an hydrocarbon and they all must be included into the detailed mechanisms. The need for smaller mechanisms logically has led to devise a technique of reduction (Chapter IV). Predictive thermo-kinetic mechanisms have been built, reduced, and validated with new experimental data and data collected from previous work or published elsewhere (Chapter V). Laser diagnostic techniques have been used to measure soot particles and PAH inside a methane flame (Chapter VI). (author)

  7. Dynamics of very small soot particles during soot burnout in diesel engines; Dynamik kleinster Russteilchen waehrend der Russausbrandphase im Dieselmotor

    Energy Technology Data Exchange (ETDEWEB)

    Bockhorn, H. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Chemische Technik; Peters, N. [RWTH Aachen (DE). Institut fuer Technische Mechanik (ITM); Pittermann, R. [WTZ fuer Motoren- und Maschinenforschung Rosslau gGmbH (Germany); Hentschel, J.; Weber, J.

    2003-07-01

    The investigations used advanced laser-optical methods for measuring soot particle size distributions, temporally and spectrally resolved measurements of engine combustion, measurements of composition and size distribution of particles in exhaust, and further development and validation of reaction-kinetic models. In all, it can be stated that mixing will affect not only soot particle formation but also soot particle emissions. Mixing can be influenced by using a fuel-water emulsion and by CR injection. Experiments and models both showed the advantageous effects of water added to the diesel fuels and of CR injection. The higher OH radical concentrations in the later combustion stages also serve to ensure faster oxidation of soot. (orig.) [German] Ziel des Projektes war es, Informationen ueber die Bildung und Oxidation von Russ sowie die Teilchendynamik der Russteilchen waehrend der Ausbrandphase zu erhalten. Dies wurde erreicht durch die Weiterentwicklung laseroptischer Methoden zur Bestimmung der Groessenverteilung von Russpartikeln, durch zeit- und spektral aufgeloeste Erfassung der motorischen Verbrennung, durch die Bestimmung von Zusammensetzung und Groessenverteilung von Partikeln im Abgas sowie durch die Weiterentwicklung und Validierung von reaktionskinetischen Modellen. Zusammenfassend laesst sich sagen, dass sich die Gemischbildung im Dieselmotor nicht nur auf die Bildung der Russpartikel sondern auch auf die Russpartikelemission auswirkt. Die Verwendung einer Kraftstoff-Wasser-Emulsion und die Common-Rail-Einspritzung stellen zwei Verfahren zur Beeinflussung der Gemischbildung dar. Sowohl die experimentellen Untersuchungen als auch die Modellierung zeigen den die Gemischbildung foerdernden Einfluss des Zusatzes von Wasser zum Dieselbrennstoff. Ein erhoehter Anteil an vorgemischter Verbrennung, wie er auch durch die Verwendung hoher Einspritzdruecke bei der Common-Rail-Einspritzung erreicht werden kann, verringert die waehrend der Verbrennung entstehende

  8. A chemical engineering model for predicting NO emissions and burnout from pulverised coal flames

    Energy Technology Data Exchange (ETDEWEB)

    Pedersen, L.S.; Glarborg, P.; Dam-Johansen, K.; Hepburn, P.W.; Hesselmann, G. [Technical University of Denmark, Lyngby (Denmark). Dept. of Chemical Engineering

    1998-07-01

    This work is concerned with the applicability of modelling swirling pulverised coal flames with ideal chemical reactors. The objectives were to predict the emissions of NO and CO, and the burnout of char. The fluid dynamics were simplified by use of a system of ideal chemical reactors. The near burner zone was modelled as a well-stirred reactor, the jet expansion as a plug flow reactor, the external recirculation zone as a well-stirred reactor, and the down stream zone as a number of well-stirred reactors in series. A reduced model of a detailed reaction mechanism was applied to model gas phase chemistry and a novel model was developed for soot oxidation. A population balance was used to keep track of size and density changes for the char combustion. Individual particle temperatures were calculated for each size fraction. The model includes only one burner specific calibration parameter which is related to the mixing of air and fuel. The model was validated against experimental results from a 160 kH{sub th} pulverised coal burner. For single staged combustion at varying stoichiometries, for two stage combustion, and for different coals good agreement between model and experiment was obtained for NO emissions and carbon in ash. This work also indicates that the interaction between the homogeneous gas phase chemistry and the heterogeneous chemistry (soot and char), due to recombination of radicals on the surfaces, is of importance for the nitrogen chemistry in coal flames, especially for ammonia formation. 84 refs., 31 figs., 7 tabs.

  9. Structure-reactivity correlation of diesel soot and characterization of polycyclic aromatic hydrocarbons and carbonyls in biofuel emissions; Struktur-Reaktivitaets-Korrelation von Dieselruss und Charakterisierung von PAHs und Carbonylen im Abgas von Biokraftstoffen

    Energy Technology Data Exchange (ETDEWEB)

    Knauer, Markus

    2010-12-29

    This work reports on the determination of the structure-reactivity correlation of soot using Raman microscopy (RM) and temperature programmed oxidation (TPO), as well as on changes in the emission level of polycyclic aromatic hydrocarbons (PAH) and carbonyls at the combustion of biofuels. To characterize the reactivity of soot the combustion behaviour of model- and diesel soot has been determined by means of TPO in the presence of oxygen. In this context, spark-discharge soot and graphite powder were applied as model substances, and EURO VI and IV diesel soot as real-diesel soots. The structure of soot samples was investigated by RM and structural changes during the TPO were observed. In order to make a statement about the changes in PAH and carbonyl compound emissions during combustion of biofuels, samples were taken at different engine testbenches. Fossil fuel, biodiesel and vegetable oil were used during this study, as well as fuel mixtures with different biofuel fractions.

  10. Structure-reactivity correlation of diesel soot and characterization of polycyclic aromatic hydrocarbons and carbonyls in biofuel emissions; Struktur-Reaktivitaets-Korrelation von Dieselruss und Charakterisierung von PAHs und Carbonylen im Abgas von Biokraftstoffen

    Energy Technology Data Exchange (ETDEWEB)

    Knauer, Markus

    2009-12-29

    This work reports on the determination of the structure-reactivity correlation of soot using Raman microscopy (RM) and temperature programmed oxidation (TPO), as well as on changes in the emission level of polycyclic aromatic hydrocarbons (PAH) and carbonyls at the combustion of biofuels. To characterize the reactivity of soot the combustion behaviour of model- and diesel soot has been determined by means of TPO in the presence of oxygen. In this context, spark-discharge soot and graphite powder were applied as model substances, and EURO VI and IV diesel soot as real-diesel soots. The structure of soot samples was investigated by RM and structural changes during the TPO were observed. In order to make a statement about the changes in PAH and carbonyl compound emissions during combustion of biofuels, samples were taken at different engine testbenches. Fossil fuel, biodiesel and vegetable oil were used during this study, as well as fuel mixtures with different biofuel fractions.

  11. The competition between mineral dust and soot ice nuclei in mixed-phase clouds (Invited)

    Science.gov (United States)

    Murray, B. J.; Atkinson, J.; Umo, N.; Browse, J.; Woodhouse, M. T.; Whale, T.; Baustian, K. J.; Carslaw, K. S.; Dobbie, S.; O'Sullivan, D.; Malkin, T. L.

    2013-12-01

    The amount of ice present in mixed-phase clouds, which contain both supercooled liquid water droplets and ice particles, affects cloud extent, lifetime, particle size and radiative properties. The freezing of cloud droplets can be catalysed by the presence of aerosol particles known as ice nuclei. In this talk our recent laboratory and global aerosol modelling work on mineral dust and soot ice nuclei will be presented. We have performed immersion mode experiments to quantify ice nucleation by the individual minerals which make up desert mineral dusts and have shown that the feldspar component, rather than the clay component, is most important for ice nucleation (Atkinson et al. 2013). Experiments with well-characterised soot generated with eugenol, an intermediate in biomass burning, and n-decane show soot has a significant ice nucleation activity in mixed-phase cloud conditions. Our results for soot are in good agreement with previous results for acetylene soot (DeMott, 1990), but extend the efficiency to much higher temperatures. We then use a global aerosol model (GLOMAP) to map the distribution of soot and feldspar particles on a global basis. We show that below about -15oC that dust and soot together can explain most observed ice nuclei in the Earth's atmosphere, while at warmer temperatures other ice nuclei types are needed. We show that in some regions soot is the most important ice nuclei (below -15oC), while in others feldspar dust dominates. Our results suggest that there is a strong anthropogenic contribution to the ice nuclei population, since a large proportion of soot aerosol in the atmosphere results from human activities. Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Carslaw, K. S., Whale, T. F., Baustian, K. J., Dobbie, S., O'Sullivan, D., and Malkin, T. L.: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds, Nature, 10.1038/nature12278, (2013). Demott, P. J. 1990. An Exploratory-Study of Ice Nucleation by Soot

  12. Simultaneous measurements of acetylene and soot during the pyrolysis of ethylene and benzene in a shock tube

    KAUST Repository

    KC, Utsav

    2016-10-12

    Acetylene is one of the most important precursors of soot and contributes to soot growth by the hydrogen-abstraction acetylene-addition (HACA) mechanism. In this work, we undertake time-resolved simultaneous measurements of acetylene and soot behind reflected shock waves at temperatures of 1600-2200. K and pressures of 3-5. bar. Acetylene mole fraction time-histories are measured from the absorption of a quantum-cascade laser operating around 13.6. μm. The soot volume fraction, particle size and number densities are calculated from the extinction and scattering of a cw Nd:Yag laser at 532. nm. Acetylene and soot are generated from the pyrolysis of 1% benzene in argon, 2.35% ethylene in argon, and binary mixtures of ethylene with propane/methane in argon. We note that acetylene time-histories exhibit a two-stage growth during the pyrolysis of benzene, which can be correlated to the initial rapid increase of soot volume fraction and a later plateauing. In comparison to ethylene pyrolysis, the pyrolysis of benzene results in larger values of the soot volume fraction, particle diameter and number density. We compare the measured data against the values simulated using the method-of-moments routine in Chemkin-Pro and a detailed PAH mechanism based on KM2 [1] and AramcoMech 1.3 [2]. Large discrepancies are observed between the measured and predicted values of the soot parameters. The data obtained from our experiments may assist future validation and development of soot mechanisms.

  13. Formation, growth, and transport of soot in a three-dimensional turbulent non-premixed jet flame

    KAUST Repository

    Attili, Antonio

    2014-07-01

    The formation, growth, and transport of soot is investigated via large scale numerical simulation in a three-dimensional turbulent non-premixed n-heptane/air jet flame at a jet Reynolds number of 15,000. For the first time, a detailed chemical mechanism, which includes the soot precursor naphthalene and a high-order method of moments are employed in a three-dimensional simulation of a turbulent sooting flame. The results are used to discuss the interaction of turbulence, chemistry, and the formation of soot. Compared to temperature and other species controlled by oxidation chemistry, naphthalene is found to be affected more significantly by the scalar dissipation rate. While the mixture fraction and temperature fields show fairly smooth spatial and temporal variations, the sensitivity of naphthalene to turbulent mixing causes large inhomogeneities in the precursor fields, which in turn generate even stronger intermittency in the soot fields. A strong correlation is apparent between soot number density and the concentration of naphthalene. On the contrary, while soot mass fraction is usually large where naphthalene is present, pockets of fluid with large soot mass are also frequent in regions with very low naphthalene mass fraction values. From the analysis of Lagrangian statistics, it is shown that soot nucleates and grows mainly in a layer close to the flame and spreads on the rich side of the flame due to the fluctuating mixing field, resulting in more than half of the total soot mass being located at mixture fractions larger than 0.6. Only a small fraction of soot is transported towards the flame and is completely oxidized in the vicinity of the stoichiometric surface. These results show the leading order effects of turbulent mixing in controlling the dynamics of soot in turbulent flames. Finally, given the difficulties in obtaining quantitative data in experiments of turbulent sooting flames, this simulation provides valuable data to guide the development of

  14. Formation, growth, and transport of soot in a three-dimensional turbulent non-premixed jet flame

    KAUST Repository

    Attili, Antonio; Bisetti, Fabrizio; Mü eller, Michael E.; Pitsch, Heinz G.

    2014-01-01

    The formation, growth, and transport of soot is investigated via large scale numerical simulation in a three-dimensional turbulent non-premixed n-heptane/air jet flame at a jet Reynolds number of 15,000. For the first time, a detailed chemical mechanism, which includes the soot precursor naphthalene and a high-order method of moments are employed in a three-dimensional simulation of a turbulent sooting flame. The results are used to discuss the interaction of turbulence, chemistry, and the formation of soot. Compared to temperature and other species controlled by oxidation chemistry, naphthalene is found to be affected more significantly by the scalar dissipation rate. While the mixture fraction and temperature fields show fairly smooth spatial and temporal variations, the sensitivity of naphthalene to turbulent mixing causes large inhomogeneities in the precursor fields, which in turn generate even stronger intermittency in the soot fields. A strong correlation is apparent between soot number density and the concentration of naphthalene. On the contrary, while soot mass fraction is usually large where naphthalene is present, pockets of fluid with large soot mass are also frequent in regions with very low naphthalene mass fraction values. From the analysis of Lagrangian statistics, it is shown that soot nucleates and grows mainly in a layer close to the flame and spreads on the rich side of the flame due to the fluctuating mixing field, resulting in more than half of the total soot mass being located at mixture fractions larger than 0.6. Only a small fraction of soot is transported towards the flame and is completely oxidized in the vicinity of the stoichiometric surface. These results show the leading order effects of turbulent mixing in controlling the dynamics of soot in turbulent flames. Finally, given the difficulties in obtaining quantitative data in experiments of turbulent sooting flames, this simulation provides valuable data to guide the development of

  15. Numerical Investigation of Soot Formation in Non-premixed Flames

    KAUST Repository

    Abdelgadir, Ahmed Gamaleldin

    2017-01-01

    Soot is a carbon particulate formed as a result of the combustion of fossil fuels. Due to the health hazard posed by the carbon particulate, government agencies have applied strict regulations to control soot emissions from road vehicles, airplanes

  16. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  17. A review of the literature on soot production during in-situ burning of oil

    International Nuclear Information System (INIS)

    Fraser, J.; Buist, I.

    1997-01-01

    Available literature on soot production during in-situ burning of oil was reviewed to determine the range of smoke yields generated by in-situ burning of petroleum oils in water, and to determine the effects of the size of fire and the type of oil burned. For crude oil, data sets statistical analysis showed that, with a fairly high degree of confidence, smoke yield increases with fire diameter. Based on a limited number of available data sets for identifiable oil types, it appears that most oils (Arabian crude the only exception) show roughly the same correlation of smoke yield with fire diameter. Pool fires from aromatic hydrocarbons such as toluene appear to produce more soot than similar fires with crude oil. Fires of lower molecular weight non-aromatics produce an order of magnitude less soot than crude oil fires. Predictive equations with correlation coefficients are provided for specific crude oils. 50 refs., 5 tabs., 13 figs

  18. The Toxicological Mechanisms of Environmental Soot (Black Carbon and Carbon Black: Focus on Oxidative Stress and Inflammatory Pathways

    Directory of Open Access Journals (Sweden)

    Rituraj Niranjan

    2017-06-01

    Full Text Available The environmental soot and carbon blacks (CBs cause many diseases in humans, but their underlying mechanisms of toxicity are still poorly understood. Both are formed after the incomplete combustion of hydrocarbons but differ in their constituents and percent carbon contents. For the first time, “Sir Percival Pott” described soot as a carcinogen, which was subsequently confirmed by many others. The existing data suggest three main types of diseases due to soot and CB exposures: cancer, respiratory diseases, and cardiovascular dysfunctions. Experimental models revealed the involvement of oxidative stress, DNA methylation, formation of DNA adducts, and Aryl hydrocarbon receptor activation as the key mechanisms of soot- and CB-induced cancers. Metals including Si, Fe, Mn, Ti, and Co in soot also contribute in the reactive oxygen species (ROS-mediated DNA damage. Mechanistically, ROS-induced DNA damage is further enhanced by eosinophils and neutrophils via halide (Cl− and Br− dependent DNA adducts formation. The activation of pulmonary dendritic cells, T helper type 2 cells, and mast cells is crucial mediators in the pathology of soot- or CB-induced respiratory disease. Polyunsaturated fatty acids (PUFAs were also found to modulate T cells functions in respiratory diseases. Particularly, telomerase reverse transcriptase was found to play the critical role in soot- and CB-induced cardiovascular dysfunctions. In this review, we propose integrated mechanisms of soot- and CB-induced toxicity emphasizing the role of inflammatory mediators and oxidative stress. We also suggest use of antioxidants and PUFAs as protective strategies against soot- and CB-induced disorders.

  19. Structural effects on the oxidation of soot particles by O2: Experimental and theoretical study

    KAUST Repository

    Raj, Abhijeet

    2013-09-01

    Soot particles are composed of polycyclic aromatic hydrocarbons (PAHs), which have either planar or curved structures. The oxidation behaviors of soot particles differ depending on their structures, arrangement of PAHs, and the type of surface functional groups. The oxidation rate of curved PAHs in soot is thought to be higher than that of planar ones. To understand the role that PAH structure plays in soot reactivity towards O2, experimental studies are conducted on two types of commercially produced soot, Printex-U and Fullerene soot, using high resolution transmission electron microscopy, electron energy loss spectroscopy, thermo-gravimetric analysis and elemental analysis. The relative concentrations of active sites, oxygenated functional groups, aliphatics and aromatics present in soots are evaluated. The activation energies for soot oxidation at different conversion levels are determined. The average activation energies of the two soots are found to differ by 26kJ/mol. To understand the reason for this difference, quantum calculations using density functional (B3LYP) and Hartree-Fock theories are conducted to study the reaction pathways of the oxidation by O2 of planar and curved PAHs using 4-pyrenyl and 1-corannulenyl as their model molecules, respectively. The energetically preferred channels for curved PAH oxidation differ from the planar one. The addition of O2 on a radical site of a six-membered ring to form a peroxyl radical is found to be barrierless for both the model PAHs. For peroxyl decomposition, three pathways are suggested, each of which involve the activation energies of 108, 170 and 121kJ/mol to form stable molecules in the case of planar PAH, and 94, 155 and 125kJ/mol in the case of curved PAH. During the oxidation of a five-membered ring, to form stable molecules, the activation energies of 90kJ/mol for the curved PAH and 169kJ/mol for the planar PAH relative to the energy of the peroxyl radical are required. The low activation barriers of

  20. Numerical investigation of soot formation and oxidation processes under large two-stroke marine diesel engine-like conditions using integrated CFD-chemical kinetics

    DEFF Research Database (Denmark)

    Pang, Kar Mun; Karvounis, Nikolas; Walther, Jens Honore

    2016-01-01

    n-heptane mechanism and a revised multi-step soot model using laser extinction measurements of diesel soot obtained at different ambient pressure levels in an optical accessible, constant volume chamber experiment. It is revealed that ignition delay times and liftoff lengths generated using the new......In this reported work, multi-dimensional computational fluid dynamics studies of diesel combustion and soot formation processes in a constant volume combustion chamber and a marine diesel engine are carried out. The key interest here is firstly to validate the coupling of a newly developed skeletal...... using the revised soot model agrees reasonably well with the measurements in terms of peak values. The numerical model is subsequently applied to investigate the flame development, soot/nitrogen monoxide formation and heat transfer in a two-stroke, low-speed uniflow-scavenged marine diesel engine...

  1. Spectral Signature of Radiative Forcing by East Asian Dust-Soot Mixture

    Science.gov (United States)

    Zhu, A.; Ramanathan, V.

    2007-12-01

    The Pacific Dust Experiment (PACDEX) provides the first detailed sampling of dust-soot mixtures from the western Pacific to the eastern Pacific Ocean. The data includes down and up spectral irradiance, mixing state of dust and soot, and other aerosol properties. This study attempts to simulate the radiative forcing by dust-soot mixtures during the experimental period. The MODTRAN band model was employed to investigate the spectral signatures of solar irradiance change induced by aerosols at moderate spectral resolutions. For the short wave band (300-1100nm) used in this study, the reduction of downward irradiance at surface by aerosols greatly enhances with increasing wavelength in the UV band (300-400nm), reaches a maximum in the blue band, then gradually decreases toward the red band. In the near-IR band (700-1100nm), irradiance reduction by aerosols shows great fluctuations in the band with center wavelength at around 940nm, 820nm, 720nm, 760nm, 690nm, where the aerosol effect is overwhelmed by the water vapor and O2 absorptions. The spectral pattern of irradiance reduction varies for different aerosol species. The maximum reduction lies at around 450nm for soot, and shifting to about 490nm for East Asian mineral dust. It's worth noting that although soot aerosols reduce more irradiance than East Asian dust in the UV and blue band, the impact of dust to the irradiance exceeds that by soot at the longer wavelength band (i.e. around 550nm). The reduction of irradiance by East Asian dust (soot) in the UV band, visible band, and near-IR accounts for about 6% (10%), 56% (64%), and 38% (26%) of total irradiance reduction. As large amount of soot aerosols are involved during the long range transport of East Asian dust, the optical properties of dust aerosols are modified with different mixing state with soot, the spectral pattern of the irradiance reduction will be changed. The study of aerosol forcing at moderate spectral resolutions has the potential application for

  2. Thermal fragmentation and deactivation of combustion-generated soot particles

    KAUST Repository

    Raj, Abhijeet

    2014-09-01

    The effect of thermal treatment on diesel soot and on a commercial soot in an inert environment under isothermal conditions at intermediate temperatures (400-900°C) is studied. Two important phenomena are observed in both the soot samples: soot fragmentation leading to its mass loss, and loss of soot reactivity towards O2. Several experimental techniques such as high resolution transmission electron microscopy, electron energy loss spectroscopy, thermo-gravimetric analysis with mass spectrometry, elemental analysis, Fourier transform infrared spectroscopy and X-ray diffraction have been used to identify the changes in structures, functional groups such as oxygenates and aliphatics, σ and π bonding, O/C and H/C ratios, and crystallite parameters of soot particles, introduced by heat. A decrease in the size of primary particles and an increase in the average polycyclic aromatic hydrocarbon (PAH) size was observed in soots after thermal treatment. The activation energies of soot oxidation for thermally treated soot samples were found to be higher than those for the untreated ones at most conversion levels. The cyclic or acyclic aliphatics with sp3 hybridization were present in significant amounts in all the soot samples, but their concentration decreased with thermal treatment. Interestingly, the H/C and the O/C ratios of soot particles increased after thermal treatment, and thus, they do not support the decrease in soot reactivity. The increase in the concentration of oxygenates on soot surface indicate that their desorption from soot surface in the form of CO, CO2 and other oxygenated compounds may not be significant at the temperatures (400-900°C) studied in this work. © 2014 The Combustion Institute.

  3. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  4. Combustion and Gasification Collection of Diesel Soot by Means of Microwave Heating

    Directory of Open Access Journals (Sweden)

    Xueshi YAO

    2014-06-01

    Full Text Available The experiment of integrated purification of diesel soot was made by means of microwave heating. The experiment includes combustion and gasification collection. The catalytic effect of ceramic carrier was used in the combustion process. In order to improve the purification efficiency of PM2.5 particles, the surfactants were used in gasification collection. The model of computer control was set up so that the purification course could be controlled. The experimental principle was analyzed. Experiment result indicated that the diesel soot purifying efficiency is more than 90 %. The purification efficiency can be improved further by the optimization design of experimental device.

  5. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  6. Simulation and analysis of the soot particle size distribution in a turbulent nonpremixed flame

    KAUST Repository

    Lucchesi, Marco

    2017-02-05

    A modeling framework based on Direct Simulation Monte Carlo (DSMC) is employed to simulate the evolution of the soot particle size distribution in turbulent sooting flames. The stochastic reactor describes the evolution of soot in fluid parcels following Lagrangian trajectories in a turbulent flow field. The trajectories are sampled from a Direct Numerical Simulation (DNS) of a n-heptane turbulent nonpremixed flame. The DSMC method is validated against experimentally measured size distributions in laminar premixed flames and found to reproduce quantitatively the experimental results, including the appearance of the second mode at large aggregate sizes and the presence of a trough at mobility diameters in the range 3–8 nm. The model is then applied to the simulation of soot formation and growth in simplified configurations featuring a constant concentration of soot precursors and the evolution of the size distribution in time is found to depend on the intensity of the nucleation rate. Higher nucleation rates lead to a higher peak in number density and to the size distribution attaining its second mode sooner. The ensemble-averaged PSDF in the turbulent flame is computed from individual samples of the PSDF from large sets of Lagrangian trajectories. This statistical measure is equivalent to time-averaged, scanning mobility particle size (SMPS) measurements in turbulent flames. Although individual trajectories display strong bimodality as in laminar flames, the ensemble-average PSDF possesses only one mode and a long, broad tail, which implies significant polydispersity induced by turbulence. Our results agree very well with SMPS measurements available in the literature. Conditioning on key features of the trajectory, such as mixture fraction or radial locations does not reduce the scatter in the size distributions and the ensemble-averaged PSDF remains broad. The results highlight and explain the important role of turbulence in broadening the size distribution of

  7. Ice Nucleation of Soot Particles in the Cirrus Regime: Is Pore Condensation and Freezing Relevant for Soot?

    Science.gov (United States)

    Kanji, Z. A.; Mahrt, F.; David, R.; Marcolli, C.; Lohmann, U.; Fahrni, J.; Brühwiler, D.

    2017-12-01

    Heterogeneous ice nucleation (HIN) onto soot particles from previous studies have produced inconsistent results of temperature and relative humidity conditions required for freezing depending on the source of soot particle investigated. The ability of soot to act as HIN depended on the type of soot and size of particle. Often homogenous freezing conditions or water saturation conditions were required to freeze soot particles, rendering HIN irrelevant. Using synthesised mesoporous silica particles, we show pore condensation and freezing works with experiments performed in the Zurich Ice Nucleation Chamber (ZINC). By testing a variety of soot particles in parallel in the Horizontal Ice Nucleation Chamber (HINC), we suggest that previously observed HIN on soot particles is not the responsible mechanism for ice formation. Laboratory generated CAST brown and black soot, commercially available soot and acid treated soot were investigated for their ice nucleation abilities in the mixed-phase and cirrus cloud temperature regimes. No heterogeneous ice nucleation activity is inferred at T > -38 °C (mixed-phase cloud regime), however depending on particle size and soot type, HIN was observed for T nucleation of ice in the pores or cavities that are ubiquitous in soot particles between the primary spherules. The ability of some particles to freeze at lower relative humidity compared to others demonstrates why hydrophobicity plays a role in ice nucleation, i.e. controlling the conditions at which these cavities fill with water. Thus for more hydrophobic particles pore filling occurs at higher relative humidity, and therefore freezing of pore water and ice crystal growth. Future work focusses on testing the cloud processing ability of soot particles and water adsorption isotherms of the different soot samples to support the hydrophobicity inferences from the ice nucleation results.

  8. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  9. Fullerene Soot in Eastern China Air: Results from Soot Particle-Aerosol Mass Spectrometer

    Science.gov (United States)

    Wang, J.; Ge, X.; Chen, M.; Zhang, Q.; Yu, H.; Sun, Y.; Worsnop, D. R.; Collier, S.

    2015-12-01

    In this work, we present for the first time, the observation and quantification of fullerenes in ambient airborne particulate using an Aerodyne Soot Particle - Aerosol Mass Spectrometer (SP-AMS) deployed during 2015 winter in suburban Nanjing, a megacity in eastern China. The laser desorption and electron impact ionization techniques employed by the SP-AMS allow us to differentiate various fullerenes from other aerosol components. Mass spectrum of the identified fullerene soot is consisted by a series of high molecular weight carbon clusters (up to m/z of 2000 in this study), almost identical to the spectral features of commercially available fullerene soot, both with C70 and C60 clusters as the first and second most abundant species. This type of soot was observed throughout the entire study period, with an average mass loading of 0.18 μg/m3, accounting for 6.4% of the black carbon mass, 1.2% of the total organic mass. Temporal variation and diurnal pattern of fullerene soot are overall similar to those of black carbon, but are clearly different in some periods. Combining the positive matrix factorization, back-trajectory and analyses of the meteorological parameters, we identified the petrochemical industrial plants situating upwind from the sampling site, as the major source of fullerene soot. In this regard, our findings imply the ubiquitous presence of fullerene soot in ambient air of industry-influenced area, especially the oil and gas production regions. This study also offers new insights into the characterization of fullerenes from other environmental samples via the advanced SP-AMS technique.

  10. Catalytic oxidation of soot over alkaline niobates

    International Nuclear Information System (INIS)

    Pecchi, G.; Cabrera, B.; Buljan, A.; Delgado, E.J.; Gordon, A.L.; Jimenez, R.

    2013-01-01

    Highlights: ► No previous reported studies about alkaline niobates as catalysts for soot oxidation. ► NaNbO 3 and KNbO 3 perovskite-type oxides show lower activation energy than other lanthanoid perovskite-type oxides. ► The alkaline niobate does not show deactivation by metal loss. - Abstract: The lack of studies in the current literature about the assessment of alkaline niobates as catalysts for soot oxidation has motivated this research. In this study, the synthesis, characterization and assessment of alkaline metal niobates as catalysts for soot combustion are reported. The solids MNbO 3 (M = Li, Na, K, Rb) are synthesized by a citrate method, calcined at 450 °C, 550 °C, 650 °C, 750 °C, and characterized by AAS, N 2 adsorption, XRD, O 2 -TPD, FTIR and SEM. All the alkaline niobates show catalytic activity for soot combustion, and the activity depends basically on the nature of the alkaline metal and the calcination temperature. The highest catalytic activity, expressed as the temperature at which combustion of carbon black occurs at the maximum rate, is shown by KNbO 3 calcined at 650 °C. At this calcination temperature, the catalytic activity follows an order dependent on the atomic number, namely: KNbO 3 > NaNbO 3 > LiNbO 3 . The RbNbO 3 solid do not follow this trend presumably due to the perovskite structure was not reached. The highest catalytic activity shown by of KNbO 3 , despite the lower apparent activation energy of NaNbO 3 , stress the importance of the metal nature and suggests the hypothesis that K + ions are the active sites for soot combustion. It must be pointed out that alkaline niobate subjected to consecutive soot combustion cycles does not show deactivation by metal loss, due to the stabilization of the alkaline metal inside the perovskite structure.

  11. On the Response of Nascent Soot Nanostructure and Oxidative Reactivity to Photoflash Exposure

    Directory of Open Access Journals (Sweden)

    Wei Wang

    2017-07-01

    Full Text Available Soot particles are a kind of major pollutant from fuel combustion. To enrich the understanding of soot, this work focuses on investigating detailed influences of instantaneous external irradiation (conventional photoflash exposure on nanostructure as well as oxidation reactivity of nascent soot particles. By detailed soot characterizations flash can reduce the mass of soot and soot nanostructure can be reconstructed substantially without burning. After flash, the degree of soot crystallization increases while the soot reactive rate decreases and the activation energy increases. In addition, nanostructure and oxidative reactivity of soot in air and Ar after flash are different due to their different thermal conductivities.

  12. Soot oxidation over NOx storage catalysts. Activity and deactivation

    International Nuclear Information System (INIS)

    Krishna, K.; Makkee, M.

    2006-01-01

    Soot oxidation activity and deactivation of NO x storage and reduction (NSR) catalysts containing Pt, K, and Ba supported on Al 2 O 3 , are studied under a variety of reaction conditions. K-containing catalysts decrease soot oxidation temperature with O 2 alone and the presence of Pt further enhance the activity due to synergetic effect. The active species responsible for synergism on Pt/K-Al 2 O 3 are unstable and cannot be regenerated. Soot oxidation temperature decreases by about 150 o C with NO+O 2 exhaust feed gas and under lean conditions NSR system acts as catalysed soot filter (CSF). The reactions that are mainly responsible for decreasing soot oxidation temperature are: (1) soot oxidation with NO 2 followed by NO recycles to NO 2 , and (2) soot oxidation with O 2 assisted by NO 2 . Only a part of the stored NO x that is decomposed at high temperatures under lean conditions is found to be useful for soot oxidation. NO x storage capacity of NSR catalysts decreases upon ageing under soot oxidising conditions. This will lead to a decreased soot oxidation activity on stored nitrate decomposition. Pt/K-Al 2 O 3 catalyst is more active, but least stable compared with Pt/Ba-Al 2 O 3 . (author)

  13. Reduced combustion mechanism for C1-C4 hydrocarbons and its application in computational fluid dynamics flare modeling.

    Science.gov (United States)

    Damodara, Vijaya; Chen, Daniel H; Lou, Helen H; Rasel, Kader M A; Richmond, Peyton; Wang, Anan; Li, Xianchang

    2017-05-01

    Emissions from flares constitute unburned hydrocarbons, carbon monoxide (CO), soot, and other partially burned and altered hydrocarbons along with carbon dioxide (CO 2 ) and water. Soot or visible smoke is of particular concern for flare operators/regulatory agencies. The goal of the study is to develop a computational fluid dynamics (CFD) model capable of predicting flare combustion efficiency (CE) and soot emission. Since detailed combustion mechanisms are too complicated for (CFD) application, a 50-species reduced mechanism, LU 3.0.1, was developed. LU 3.0.1 is capable of handling C 4 hydrocarbons and soot precursor species (C 2 H 2 , C 2 H 4 , C 6 H 6 ). The new reduced mechanism LU 3.0.1 was first validated against experimental performance indicators: laminar flame speed, adiabatic flame temperature, and ignition delay. Further, CFD simulations using LU 3.0.1 were run to predict soot emission and CE of air-assisted flare tests conducted in 2010 in Tulsa, Oklahoma, using ANSYS Fluent software. Results of non-premixed probability density function (PDF) model and eddy dissipation concept (EDC) model are discussed. It is also noteworthy that when used in conjunction with the EDC turbulence-chemistry model, LU 3.0.1 can reasonably predict volatile organic compound (VOC) emissions as well. A reduced combustion mechanism containing 50 C 1 -C 4 species and soot precursors has been developed and validated against experimental data. The combustion mechanism is then employed in the computational fluid dynamics (CFD) of modeling of soot emission and combustion efficiency (CE) of controlled flares for which experimental soot and CE data are available. The validated CFD modeling tools are useful for oil, gas, and chemical industries to comply with U.S. Environmental Protection Agency's (EPA) mandate to achieve smokeless flaring with a high CE.

  14. Two-dimensional quantification of soot and flame-soot interaction in spray combustion at elevated pressures - Final report

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, T.

    2008-07-15

    Single-pulse time-resolved laser-induced incandescence (TiRe-LII) signal transients from soot particulates were acquired during unsteady high pressure Diesel combustion in a constant volume cell near top dead centre conditions typically found in a Diesel engine. Measurements were performed for initial gas pressures between 1 MPa and 3 MPa, injection pressures between 50 MPa and 130 MPa and laser probe timings between 5 ms and 16 ms after start of fuel injection. In separate experiments and for the same cell operating conditions, gas temperatures were deduced from spectrally resolved soot pyrometry measurements. Implementing the LII model of Kock et al. ensemble mean soot particle diameters were evaluated from least-squares fitting of theoretical cooling curves to experimental TiRe-LII signal transients. Since in the experiments the environmental gas temperature and the width of an assumed particle size distribution were not known, the effects of the initial choice of these parameters on retrieved particle diameters were investigated. It is shown that evaluated mean particle diameters are only slightly biased by the choice of typical size distribution widths and gas temperatures. For a fixed combustion phase mean particle diameters are not much affected by gas pressure, however they become smaller at high fuel injection pressure. At a mean chamber pressure of 1.4 MPa evaluated mean particle diameters increased by a factor of two for probe delays between 5 ms and 16 ms after start of injection, irrespective of the choices of first-guess fitting variables, indicating a certain robustness of data analysis procedure. (author)

  15. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  16. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  17. Predictive user modeling with actionable attributes

    NARCIS (Netherlands)

    Zliobaite, I.; Pechenizkiy, M.

    2013-01-01

    Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

  18. A comparative study on the sooting tendencies of various 1-alkene fuels in counterflow diffusion flames

    KAUST Repository

    Wang, Yu

    2018-02-19

    Alkenes are important components in transportation fuels, and are known to have increased sooting tendencies compared to analogous saturated hydrocarbons with the same carbon number. This work aims to understand the sooting tendencies of various 1-alkenes through experiments and numerical simulations for counterflow diffusion flames. Soot and PAH formation tendencies of 1-alkene fuels, including ethylene (C2H4), propene (C3H6), 1-butene (1-C4H8), 1-pentene (1-C5H10), 1-hexene (1-C6H12) and 1-octene (1-C8H16), were experimentally studied using laser induced-incandescence (LII) and laser-induced fluorescence (LIF) techniques, respectively. From the LII results, 1-C4H8 was found to be the most sooting fuel, followed by C3H6 > 1-C5H10 > 1-C6H12 > 1-C8H16 > C2H4. The LIF data with a detection wavelength of 500 nm indicated the PAH formation tendencies followed the order of 1-C4H8 > 1-C5H10 ∼1-C6H12 > C3H6 > 1-C8H16 > C2H4, which were different from the order of sooting tendencies. Numerical simulations with a comprehensive chemical kinetic model including PAH growth chemistry for the tested 1-alkene fuels were conducted to elucidate the aromatic formation pathways and rationalize the experimentally observed trends. The numerical results highlighted the importance of intermediate species with odd carbon numbers in aromatic species formation, such as propargyl, allyl, cyclopentadienyl and indenyl radicals. Their concentration differences, which could be traced back to the parent fuel molecules through rate of production analysis, rationalize the experimentally observed differences in soot and PAH formation tendencies.

  19. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain, which...

  20. Influence of fuel properties on fundamental spray characteristics and soot emissions using different tailor-made fuels from biomass

    International Nuclear Information System (INIS)

    García, Antonio; Monsalve-Serrano, Javier; Heuser, Benedikt; Jakob, Markus; Kremer, Florian; Pischinger, Stefan

    2016-01-01

    Highlights: • TMFB show clear potential to reduce soot emissions under mixing-controlled combustion. • The larger lift-off-length of 2-MTHF and 1-octanol promotes soot emissions reduction. • Oxidation process governs the improved soot emissions of DNBE. - Abstract: This work evaluates the potential of some new biomass-derived fuels as candidates for compression ignition operation. Thus, fundamental spray characteristics related to fuel vaporization and fuel/air mixing process for 2-Methyltetrahydrofuran, Di-n-butyl ether and 1-octanol has been studied and compared with conventional EN590 Diesel fuel. For this purpose, OH"∗ chemiluminescence and shadowgraphy measurements in a high pressure chamber as well as 1D simulations with a spray model have been carried out at different operating conditions representative of the NEDC driving cycle. Finally, measured soot emissions in the single-cylinder engine were presented and discussed. Results from the high pressure chamber presented very good agreement in terms of liquid length and vapor penetration with simulation results. Thus, some analytical expressions related to macroscopic spray characteristics have been proposed and validated experimentally for all four fuels. Finally, the single-cylinder engine results confirmed the relevant role of soot formation on final emissions for 1-octanol and 2-MTHF. In addition, DNBE showed greater soot oxidation potential than diesel and other TMFB candidates.

  1. Dynamics of flow–soot interaction in wrinkled non-premixed ethylene–air flames

    KAUST Repository

    Arias, Paul G.; Lecoustre, Vivien R.; Roy, Somesh; Luo, Zhaoyu; Haworth, Daniel C.; Lu, Tianfeng; Trouvé , Arnaud; Im, Hong G.

    2015-01-01

    A two-dimensional simulation of a non-premixed ethylene–air flame was conducted by employing a detailed gas-phase reaction mechanism considering polycyclic aromatic hydrocarbons, an aerosol-dynamics-based soot model using a method of moments

  2. The Ångström Exponent and Turbidity of Soot Component in the ...

    African Journals Online (AJOL)

    OPAC) using FORTRAN program to model the effect of soot on optical depth, scattering coefficient, absorption coefficient, single scattering albedo, extinction coefficient and asymmetry parameter at spectral range of 0.25 to 1.00 ƒÝm for eight ...

  3. Investigation of soot by two-color four-wave mixing

    Energy Technology Data Exchange (ETDEWEB)

    Hemmerling, B; Stampanoni-Panariello, A [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1999-08-01

    A novel, non-intrusive technique has been used for the temporally resolved investigation of the interaction of laser radiation and soot in a flame. While there is a fairly good agreement between measurement and simulation remaining discrepancies indicate some shortcomings of the model employed. (author) 2 figs., 2 refs.

  4. In-cylinder Combustion and Soot Evolution in the Transition from Conventional CI mode to PPC

    KAUST Repository

    An, Yanzhao; Jaasim, Mohammed; Raman, Vallinayagam; Im, Hong G.; Johansson, Bengt

    2018-01-01

    with gas phase chemical kinetics, turbulence, and particulate size mimic soot model. The simulations were performed under low load conditions (IMEP ~ 2 to 3 bar) at an engine speed of 1200 rpm. The start of injection (SOI) was advanced from late (-10 CAD a

  5. Robust predictions of the interacting boson model

    International Nuclear Information System (INIS)

    Casten, R.F.; Koeln Univ.

    1994-01-01

    While most recognized for its symmetries and algebraic structure, the IBA model has other less-well-known but equally intrinsic properties which give unavoidable, parameter-free predictions. These predictions concern central aspects of low-energy nuclear collective structure. This paper outlines these ''robust'' predictions and compares them with the data

  6. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  7. Candle Soot-Driven Performance Enhancement in Pyroelectric Energy Conversion

    Science.gov (United States)

    Azad, Puneet; Singh, V. P.; Vaish, Rahul

    2018-05-01

    We observed substantial enhancement in pyroelectric output with the help of candle soot coating on the surface of lead zirconate titanate (PZT). Candle soot of varying thicknesses was coated by directly exposing pyroelectric material to the candle flame. The open-circuit pyroelectric voltage and closed-circuit pyroelectric current were recorded while applying infrared heating across the uncoated and candle soot-coated samples for different heating and cooling cycles. In comparison to the uncoated sample, the maximum open-circuit voltage improves seven times for the candle soot-coated sample and electric current increases by eight times across a resistance of 10Å. Moreover, the harvested energy is enhanced by 50 times for candle soot-coated sample. Results indicate that candle soot coating is an effective and economic method to improve infrared sensing performance of pyroelectric materials.

  8. Extracting falsifiable predictions from sloppy models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

    2007-12-01

    Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

  9. The prediction of epidemics through mathematical modeling.

    Science.gov (United States)

    Schaus, Catherine

    2014-01-01

    Mathematical models may be resorted to in an endeavor to predict the development of epidemics. The SIR model is one of the applications. Still too approximate, the use of statistics awaits more data in order to come closer to reality.

  10. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  11. Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

    Science.gov (United States)

    Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

    2017-12-01

    Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

  12. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing

  13. Soot Formation in Freely-Propagating Laminar Premixed Flames

    Science.gov (United States)

    Lin, K.-C.; Hassan, M. I.; Faeth, G. M.

    1997-01-01

    Soot formation within hydrocarbon-fueled flames is an important unresolved problem of combustion science. Thus, the present study is considering soot formation in freely-propagating laminar premixed flames, exploiting the microgravity environment to simplify measurements at the high-pressure conditions of interest for many practical applications. The findings of the investigation are relevant to reducing emissions of soot and continuum radiation from combustion processes, to improving terrestrial and spacecraft fire safety, and to developing methods of computational combustion, among others. Laminar premixed flames are attractive for studying soot formation because they are simple one-dimensional flows that are computationally tractable for detailed numerical simulations. Nevertheless, studying soot-containing burner-stabilized laminar premixed flames is problematical: spatial resolution and residence times are limited at the pressures of interest for practical applications, flame structure is sensitive to minor burner construction details so that experimental reproducibility is not very good, consistent burner behavior over the lengthy test programs needed to measure soot formation properties is hard to achieve, and burners have poor durability. Fortunately, many of these problems are mitigated for soot-containing, freely-propagating laminar premixed flames. The present investigation seeks to extend work in this laboratory for various soot processes in flames by observing soot formation in freely-propagating laminar premixed flames. Measurements are being made at both Normal Gravity (NG) and MicroGravity (MG), using a short-drop free-fall facility to provide MG conditions.

  14. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  15. Technical Note: The single particle soot photometer fails to reliably detect PALAS soot nanoparticles

    Directory of Open Access Journals (Sweden)

    M. Gysel

    2012-12-01

    Full Text Available The single particle soot photometer (SP2 uses laser-induced incandescence (LII for the measurement of atmospheric black carbon (BC particles. The BC mass concentration is obtained by combining quantitative detection of BC mass in single particles with a counting efficiency of 100% above its lower detection limit. It is commonly accepted that a particle must contain at least several tenths of a femtogram BC in order to be detected by the SP2.

    Here we show the result that most BC particles from a PALAS spark discharge soot generator remain undetected by the SP2, even if their BC mass, as independently determined with an aerosol particle mass analyser (APM, is clearly above the typical lower detection limit of the SP2. Comparison of counting efficiency and effective density data of PALAS soot with flame generated soot (combustion aerosol standard burner, CAST, fullerene soot and carbon black particles (Cabot Regal 400R reveals that particle morphology can affect the SP2's lower detection limit. PALAS soot particles are fractal-like agglomerates of very small primary particles with a low fractal dimension, resulting in a very low effective density. Such loosely packed particles behave like "the sum of individual primary particles" in the SP2's laser. Accordingly, most PALAS soot particles remain undetected as the SP2's laser intensity is insufficient to heat the primary particles to their vaporisation temperature because of their small size (Dpp ≈ 5–10 nm. Previous knowledge from pulsed laser-induced incandescence indicated that particle morphology might have an effect on the SP2's lower detection limit, however, an increase of the lower detection limit by a factor of ∼5–10, as reported here for PALAS soot, was not expected.

    In conclusion, the SP2's lower detection limit at a certain laser power depends primarily on the total BC mass per particle for compact particles with sufficiently high effective

  16. Effect of Dimethyl Ether Mixing on Soot Size Distribution in Premixed Ethylene Flame

    KAUST Repository

    Li, Zepeng

    2016-01-01

    As a byproduct of incomplete combustion, soot attracts increasing attentions as extensive researches exploring serious health and environmental effects from soot particles. Soot emission reduction requires a comprehensive understanding

  17. Strain rate effect on sooting characteristics in laminar counterflow diffusion flames

    KAUST Repository

    Wang, Yu; Chung, Suk-Ho

    2016-01-01

    The effects of strain rate, oxygen enrichment and fuel type on the sooting characteristics of counterflow diffusion flames were studied. The sooting structures and relative PAH concentrations were measured with laser diagnostics. Detailed soot

  18. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

    Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

  19. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  20. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  1. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  2. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  3. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  4. Soot volume fraction in a piloted turbulent jet non-premixed flame of natural gas

    Energy Technology Data Exchange (ETDEWEB)

    Qamar, N.H.; Alwahabi, Z.T.; King, K.D. [Fluid Mechanics, Energy and Combustion Group, University of Adelaide, Adelaide, SA 5005 (Australia); School of Chemical Engineering, University of Adelaide, Adelaide, SA 5005 (Australia); Chan, Q.N. [Fluid Mechanics, Energy and Combustion Group, University of Adelaide, Adelaide, SA 5005 (Australia); School of Chemical Engineering, University of Adelaide, Adelaide, SA 5005 (Australia); School of Mechanical Engineering, University of Adelaide, Adelaide, SA 5005 (Australia); Nathan, G.J. [Fluid Mechanics, Energy and Combustion Group, University of Adelaide, Adelaide, SA 5005 (Australia); School of Mechanical Engineering, University of Adelaide, Adelaide, SA 5005 (Australia); Roekaerts, D. [Department of Multi-Scale Physics, Faculty of Applied Sciences, Delft University of Technology, Lorentzweg, 1, NL-2628 CJ Delft (Netherlands)

    2009-07-15

    Planar laser-induced incandescence (LII) has been used to measure soot volume fraction in a well-characterised, piloted, turbulent non-premixed flame known as the ''Delft Flame III''. Simulated Dutch natural gas was used as the fuel to produce a flame closely matching those in which a wide range of previous investigations, both experimental and modelling, have been performed. The LII method was calibrated using a Santoro-style burner with ethylene as the fuel. Instantaneous and time-averaged data of the axial and radial soot volume fraction distributions of the flame are presented here along with the Probability Density Functions (PDFs) and intermittency. The PDFs were found to be well-characterised by a single exponential distribution function. The distribution of soot was found to be highly intermittent, with intermittency typically exceeding 97%, which increases measurement uncertainty. The instantaneous values of volume fraction are everywhere less than the values in strained laminar flames. This is consistent with the soot being found locally in strained flame sheets that are convected and distorted by the flow. (author)

  5. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  6. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

  7. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    OpenAIRE

    David Ebert

    2006-01-01

    One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

  8. Soot blowing methods and soot steam consumption in Swedish recovery boilers; Sotningsmetoder och sotaangfoerbrukning i svenska sodapannor

    Energy Technology Data Exchange (ETDEWEB)

    Svedin, Kristoffer; Wallin, Erik; Ahlroth, Mikael

    2008-09-15

    The aim with the report was to put together a description of the current state of the sootblowing systems at Swedish recovery boilers, and to explain differences in cleanability and sootblowing efficiency. In chapter 4 a summary of new techniques and alternative soot blowing methods is found. The report is intended for persons working in the pulp industry. To facilitate the benchmarking the recovery boilers have been divided into two groups. Group A comprises recovery boilers which only have one stop per year and the remaining recovery boilers with more than one stop are classified into group B. The following conclusions, based on the recovery boiler design specifications, are of importance to achieve high boiler availability: Low furnace load; High recovery boiler, wide furnace bottom area; Modern air ports; Small or no correlation between cross pitch division in heat surfaces and cleanability could be seen. The expectation was to identify such a relation. However there are doubts on the correctness in reported data. The amount of chlorine and potassium is assumed to affect the cleanability for a few recovery boilers, but for the majority the amounts are low and most likely do not impact the operation. Because of the large impact of the recovery boilers design data (furnace area, load etc.) on the sootblowing, it has been hard to identify the relation cleanability contra sootblowing system. The relations that could be seen are: No distinction between normally designed nozzles and 'high efficiency' nozzles could be identified. The operational conditions for the different models differ a lot and the effect of nozzle type could not be distinguished. Only a minority of the soot blowing sequences are known from the study. In the recovery boilers with problematic areas improvements can be made in the soot blowing sequence. Four recovery boilers are using intelligent soot blowing of some kind. Two of these boilers have low availability and the other two have

  9. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  10. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  11. Multi-model analysis in hydrological prediction

    Science.gov (United States)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  12. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  4. Photoacoustic Soot Spectrometer (PASS) Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Dubey, M [Los Alamos National Laboratory; Springston, S [Brookhaven National Laboratory; Koontz, A [Pacific Northwest National Laboratory; Aiken, A [Los Alamos National Laboratory

    2013-01-17

    The photoacoustic soot spectrometer (PASS) measures light absorption by aerosol particles. As the particles pass through a laser beam, the absorbed energy heats the particles and in turn the surrounding air, which sets off a pressure wave that can be detected by a microphone. The PASS instruments deployed by ARM can also simultaneously measure the scattered laser light at three wavelengths and therefore provide a direct measure of the single-scattering albedo. The Operator Manual for the PASS-3100 is included here with the permission of Droplet Measurement Technologies, the instrument’s manufacturer.

  5. Aromatics oxidation and soot formation in flames

    Energy Technology Data Exchange (ETDEWEB)

    Howard, J.B.; Pope, C.J.; Shandross, R.A.; Yadav, T. [Massachusetts Institute of Technology, Cambridge (United States)

    1993-12-01

    This project is concerned with the kinetics and mechanisms of aromatics oxidation and soot and fullerenes formation in flames. The scope includes detailed measurements of profiles of stable and radical species concentrations in low-pressure one-dimensional premixed flames. Intermediate species identifications and mole fractions, fluxes, and net reaction rates calculated from the measured profiles are used to test postulated reaction mechanisms. Particular objectives are to identify and to determine or confirm rate constants for the main benzene oxidation reactions in flames, and to characterize fullerenes and their formation mechanisms and kinetics.

  6. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  7. Fractal-like dimension of nanometer Diesel soot particles

    Energy Technology Data Exchange (ETDEWEB)

    Skillas, G.; Baltensperger, U. [Paul Scherrer Inst. (PSI), Villigen (Switzerland); Siegmann, K. [Eidgenoessische Technische Hochschule, Zurich (Switzerland)

    1997-11-01

    Measurements with a low-pressure impactor and a differential mobility analyser were conducted for Diesel soot at various engine loads. By means of these measurements a fractal-like dimension of Diesel soot particles, with diameters ranging from 55 up to 260 nm, was established. (author) 2 figs., 7 refs.

  8. Presumed PDF modeling of microjet assisted CH4–H2/air turbulent flames

    International Nuclear Information System (INIS)

    Chouaieb, Sirine; Kriaa, Wassim; Mhiri, Hatem; Bournot, Philippe

    2016-01-01

    Highlights: • Microjet assisted CH 4 –H 2 /air turbulent flames are numerically investigated. • Temperature, species and soot are well predicted by the Presumed PDF model. • An inner flame is identified due to the microjet presence. • The addition of hydrogen to the microjet assisted flames enhances mixing. • Soot emission is reduced by 36% for a 10% enriched microjet assisted flame. - Abstract: The characteristics of microjet assisted CH 4 –H 2 /air flames in a turbulent mode are numerically investigated. Simulations are performed using the Computational Fluid Dynamics code Fluent. The Presumed PDF and the Discrete Ordinates models are considered respectively for combustion and radiation modeling. The k–ε Realizable model is adopted as a turbulence closure model. The Tesner model is used to calculate soot particle quantities. In the first part of this paper, the Presumed PDF model is compared to the Eddy Dissipation model and to slow chemistry combustion models from literature. Results show that the Presumed PDF model predicts correctly thermal and species fields, as well as soot formation. The effect of hydrogen enrichment on CH 4 /air confined flames under the addition of an air microjet is investigated in the second part of this work. The found results show that an inner flame was identified due to the air microjet for the CH 4 –H 2 /air flames. Moreover, the increase of hydrogen percentage in the fuel mixture leads to mixing enhancement and consequently to considerable soot emission reduction.

  9. Spent fuel: prediction model development

    International Nuclear Information System (INIS)

    Almassy, M.Y.; Bosi, D.M.; Cantley, D.A.

    1979-07-01

    The need for spent fuel disposal performance modeling stems from a requirement to assess the risks involved with deep geologic disposal of spent fuel, and to support licensing and public acceptance of spent fuel repositories. Through the balanced program of analysis, diagnostic testing, and disposal demonstration tests, highlighted in this presentation, the goal of defining risks and of quantifying fuel performance during long-term disposal can be attained

  10. Navy Recruit Attrition Prediction Modeling

    Science.gov (United States)

    2014-09-01

    have high correlation with attrition, such as age, job characteristics, command climate, marital status, behavior issues prior to recruitment, and the...the additive model. glm(formula = Outcome ~ Age + Gender + Marital + AFQTCat + Pay + Ed + Dep, family = binomial, data = ltraining) Deviance ...0.1 ‘ ‘ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance : 105441 on 85221 degrees of freedom Residual deviance

  11. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  12. Predictive Models and Computational Toxicology (II IBAMTOX)

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  13. Finding furfural hydrogenation catalysts via predictive modelling

    NARCIS (Netherlands)

    Strassberger, Z.; Mooijman, M.; Ruijter, E.; Alberts, A.H.; Maldonado, A.G.; Orru, R.V.A.; Rothenberg, G.

    2010-01-01

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes

  14. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL STRESSES IN ... the transverse residual stress in the x-direction (σx) had a maximum value of 375MPa ... the finite element method are in fair agreement with the experimental results.

  15. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico; Kryshtafovych, Andriy; Tramontano, Anna

    2009-01-01

    established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic

  16. Mental models accurately predict emotion transitions.

    Science.gov (United States)

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  17. Mental models accurately predict emotion transitions

    Science.gov (United States)

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  18. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  19. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  20. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  1. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  2. Studies of propane flame soot acting as heterogeneous ice nuclei in conjunction with single particle soot photometer measurements

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2011-09-01

    Full Text Available The ice nucleation efficiency of propane flame soot particles with and without a sulphuric acid coating was investigated using the aerosol and cloud chamber facility AIDA (Aerosol Interaction and Dynamics in the Atmosphere. The test soot for cloud formation simulations was produced using a propane flame Combustion Aerosol Standard generator (CAST, Jing-CAST Technologies. The organic carbon content (OC of the test soot was altered in a reproducible fashion by changing the fuel/air mixture of the generator. The soot content of ice nuclei was subsequently investigated using a combination of a pumped counterflow virtual impactor (PCVI to separate and evaporate the ice crystals, and a DMT single particle soot photometer (SP2 to examine the mixing state of the BC containing ice residuals.

    Ice nucleation was found to be most efficient for uncoated soot of low organic carbon content (~5 % organic carbon content where deposition freezing occurred at an ice saturation ratio Sice ~ 1.22 at a temperature T = 226.6 K with 25 % of the test soot becoming active as ice nuclei. Propane flame soot of higher organic carbon content (~30 % and ~70 % organic carbon content showed significantly lower ice nucleation efficiency (an activated fraction of the order of a few percent in the experiments than the low organic carbon content soot, with water saturation being required for freezing to occur. Ice nucleation occurred over the range Sice = 1.22–1.70, and T = 223.2–226.6 K. Analysis of the SP2 data showed that the 5 % organic carbon content soot had an undetectable OC coating whereas the 30 % organic carbon content soot had a thicker or less volatile OC coating.

    The application of a sulphuric acid coating to the flame soot shifted the threshold of the onset of freezing towards that of the homogeneous freezing of sulphuric acid; for the minimum OC flame soot this inhibited nucleation since the

  3. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  4. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  5. Finding Furfural Hydrogenation Catalysts via Predictive Modelling.

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-09-10

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.

  6. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  7. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  8. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  9. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  10. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  11. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  12. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

  13. Reductions of PAH and Soot by Center Air Injection

    Directory of Open Access Journals (Sweden)

    Kazuhiro Yamamoto

    2014-07-01

    Full Text Available In this study, to reduce the amount of pollutant PAH and soot in the flame, we examined the burner system equipped with a center air injection. For this purpose, by using PAH-LIF and soot LII, we evaluated relative PAH and soot amounts in both the triple port burner and the conventional co-axial burner (double port burner to discuss effects of center air injection on the formation of PAH and soot. The fuel was propane. In the triple port burner, two different blue flames are observed near the burner rim, followed by bright luminous flames with soot. The flame length is longer when the fuel flow velocity is increased. On the other hand, the flame length is shorter with an increase in internal air flow velocity. As for PAH and soot, these amounts of the triple port burner are much smaller than those of the double port burner. For the triple port burner, due to the center air injection, the fuel consumption occurs in both inner and outer flames. On the other hand, for the double port burner, the oxygen is supplied from one side air, and as a result, the fuel consumption rate is relatively lower. Hence, by the center air injection, the fuel consumption is largely accelerated, resulting in the reduction of PAH and soot.

  14. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  15. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  16. Measurement of Soot Volume Fraction and Temperature for Oxygen-Enriched Ethylene Combustion Based on Flame Image Processing

    Directory of Open Access Journals (Sweden)

    Weijie Yan

    2017-05-01

    Full Text Available A method for simultaneously visualizing the two-dimensional distributions of temperature and soot volume fraction in an ethylene flame was presented. A single-color charge-coupled device (CCD camera was used to capture the flame image in the visible spectrum considering the broad-response spectrum of the R and G bands of the camera. The directional emissive power of the R and G bands were calibrated and used for measurement. Slightly increased temperatures and reduced soot concentration were predicted in the central flame without self-absorption effects considered, an iterative algorithm was used for eliminating the effect of self-absorption. Nine different cases were presented in the experiment to demonstrate the effects of fuel mass flow rate and oxygen concentration on temperature and soot concentration in three different atmospheres. For ethylene combustion in pure-air atmosphere, as the fuel mass flow rate increased, the maximum temperature slightly decreased, and the maximum soot volume fraction slightly increased. For oxygen fractions of 30%, 40%, and 50% combustion in O2/N2 oxygen-enhanced atmospheres, the maximum flame temperatures were 2276, 2451, and 2678 K, whereas combustion in O2/CO2 atmospheres were 1916, 2322, and 2535 K. The maximum soot volume fractions were 4.5, 7.0, and 9.5 ppm in oxygen-enriched O2/N2 atmosphere and 13.6, 15.3, and 14.8 ppm in oxygen-enriched O2/CO2 atmosphere. Compared with the O2/CO2 atmosphere, combustion in the oxygen-enriched O2/N2 atmosphere produced higher flame temperature and larger soot volume fraction. Preliminary results indicated that this technique is reliable and can be used for combustion diagnosis.

  17. Characterization of Diesel Soot Aggregates by Scattering and Extinction Methods

    Science.gov (United States)

    Kamimoto, Takeyuki

    2006-07-01

    Characteristics of diesel soot particles sampled from diesel exhaust of a common-rail turbo-charged diesel engine are quantified by scattering and extinction diagnostics using newly build two laser-based instruments. The radius of gyration representing the aggregates size is measured by the angular distribution of scattering intensity, while the soot mass concentration is measured by a two-wavelength extinction method. An approach to estimate the refractive index of diesel soot by an analysis of the extinction and scattering data using an aggregates scattering theory is proposed.

  18. Characterization of Diesel Soot Aggregates by Scattering and Extinction Methods

    International Nuclear Information System (INIS)

    Kamimoto, Takeyuki

    2006-01-01

    Characteristics of diesel soot particles sampled from diesel exhaust of a common-rail turbo-charged diesel engine are quantified by scattering and extinction diagnostics using newly build two laser-based instruments. The radius of gyration representing the aggregates size is measured by the angular distribution of scattering intensity, while the soot mass concentration is measured by a two-wavelength extinction method. An approach to estimate the refractive index of diesel soot by an analysis of the extinction and scattering data using an aggregates scattering theory is proposed

  19. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  20. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  2. Alcator C-Mod predictive modeling

    International Nuclear Information System (INIS)

    Pankin, Alexei; Bateman, Glenn; Kritz, Arnold; Greenwald, Martin; Snipes, Joseph; Fredian, Thomas

    2001-01-01

    Predictive simulations for the Alcator C-mod tokamak [I. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] are carried out using the BALDUR integrated modeling code [C. E. Singer et al., Comput. Phys. Commun. 49, 275 (1988)]. The results are obtained for temperature and density profiles using the Multi-Mode transport model [G. Bateman et al., Phys. Plasmas 5, 1793 (1998)] as well as the mixed-Bohm/gyro-Bohm transport model [M. Erba et al., Plasma Phys. Controlled Fusion 39, 261 (1997)]. The simulated discharges are characterized by very high plasma density in both low and high modes of confinement. The predicted profiles for each of the transport models match the experimental data about equally well in spite of the fact that the two models have different dimensionless scalings. Average relative rms deviations are less than 8% for the electron density profiles and 16% for the electron and ion temperature profiles

  3. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  4. Time-averaged probability density functions of soot nanoparticles along the centerline of a piloted turbulent diffusion flame using a scanning mobility particle sizer

    KAUST Repository

    Chowdhury, Snehaunshu

    2017-01-23

    In this study, we demonstrate the use of a scanning mobility particle sizer (SMPS) as an effective tool to measure the probability density functions (PDFs) of soot nanoparticles in turbulent flames. Time-averaged soot PDFs necessary for validating existing soot models are reported at intervals of ∆x/D∆x/D = 5 along the centerline of turbulent, non-premixed, C2H4/N2 flames. The jet exit Reynolds numbers of the flames investigated were 10,000 and 20,000. A simplified burner geometry based on a published design was chosen to aid modelers. Soot was sampled directly from the flame using a sampling probe with a 0.5-mm diameter orifice and diluted with N2 by a two-stage dilution process. The overall dilution ratio was not evaluated. An SMPS system was used to analyze soot particle concentrations in the diluted samples. Sampling conditions were optimized over a wide range of dilution ratios to eliminate the effect of agglomeration in the sampling probe. Two differential mobility analyzers (DMAs) with different size ranges were used separately in the SMPS measurements to characterize the entire size range of particles. In both flames, the PDFs were found to be mono-modal in nature near the jet exit. Further downstream, the profiles were flatter with a fall-off at larger particle diameters. The geometric mean of the soot size distributions was less than 10 nm for all cases and increased monotonically with axial distance in both flames.

  5. Comparison of two ordinal prediction models

    DEFF Research Database (Denmark)

    Kattan, Michael W; Gerds, Thomas A

    2015-01-01

    system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared...... on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. RESULTS: We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We...... demonstrate our algorithm with a prostate cancer staging system example. CONCLUSION: We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models....

  6. Kinetic study of diesel soot oxidation: application to simulation of diesel particulate filter regeneration; Etude cinetique de la combustion des suies diesel: application a la modelisation de la regeneration du filtre a particule

    Energy Technology Data Exchange (ETDEWEB)

    Huguet, Ch.

    2005-11-15

    Because of their toxicity, soot are considered as the most important pollutant from Diesel engines. The Diesel Particulate Filter (DPF) is widely deployed in Europe to address the significant reductions in particulate emissions required by increasingly stringent emission standards, both for heavy duty vehicles and passenger cars. Such a DPF filtrates above 99% of soot emissions and must be regularly regenerated. The use of additive allows to decrease the soot oxidation temperature to values which can be reached by appropriate engine tuning. The soot addition is a dominant parameter for the development of regeneration strategies. Its influence must be correctly represented by models. This Ph-D was performed at IFP in collaboration with ADEME and was supported by the LCSR at Orleans. The aim of the present research is to develop a kinetic mechanism characteristic of Diesel soot oxidation, which can be integrated into a DPF regeneration model and used for engine control. The oxidation study was based on soot characterisation and reaction kinetics investigations. The samples of Diesel soot were collected, without and with Cerium/Iron additive, by using two engines points representative of two normalized European cycles (ECE and EUDC). Thermal and composition analyses with techniques such as XPS, XRD or TEM were used to determine their physical and chemical properties. Their oxidation kinetics was experimentally studied on a synthetic gas bench (SGB) with a fixed bed reactor. Different tests were performed: temperature-programmed oxidation (TPO), Isothermal oxidation (IO), and sequential oxidation. The results allowed to correlate Diesel soot physical and chemical properties with their oxidation rate. A kinetic model was developed, which is based on global carbon consummation law and distinguishes the oxidation of different soot components. The simulation results agree very well with the experimental results of Diesel soot oxidation. (author)

  7. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  8. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  9. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  10. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  11. Investigating Soot Morphology in Counterflow Flames at Elevated Pressures

    KAUST Repository

    Amin, Hafiz Muhammad Fahid

    2018-01-01

    Practical combustion devices such as gas turbines and diesel engines operate at high pressures to increase their efficiency. Pressure significantly increases the overall soot yield. Morphology of these ultra-fine particles determines their airborne

  12. A stepwise model to predict monthly streamflow

    Science.gov (United States)

    Mahmood Al-Juboori, Anas; Guven, Aytac

    2016-12-01

    In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

  13. Understanding Combustion and Soot Formation in Diesel Engines

    Science.gov (United States)

    2016-09-09

    distributions of PLII signals help understand the soot distributions within diesel/ biodiesel flames. In addition, planar laser-induced Figure 1. Transported ...Prescribed by ANSI Std. Z39.18 Page 1 of 1FORM SF 298 9/14/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll This project investigated biodiesel ...emissions testing. 1 FINAL REPORT Project title: Understanding combustion and soot formation in biodiesel fuelled diesel engines Lead Institute and

  14. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  15. An Intelligent Model for Stock Market Prediction

    Directory of Open Access Journals (Sweden)

    IbrahimM. Hamed

    2012-08-01

    Full Text Available This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP Artificial Neural Networks (ANN. Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.

  16. Measurement of Soot Deposition in Automotive Components Using Neutron Radiography

    Energy Technology Data Exchange (ETDEWEB)

    Zekveld, David; Liu, Liaohui [AMEC NSS, 700 University Ave, Toronto, Ontario, M5G 1X6 (Canada); UOIT, 2000 Simcoe Street North, Oshawa, Ontario, L1H 7K4 (Canada); Harrison, Andrew; Gill, Spencer; Harvel, Glenn [UOIT, 2000 Simcoe Street North, Oshawa, Ontario, L1H 7K4 (Canada); Chang, Jen-Shih [McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4L8 (Canada)

    2008-07-01

    About 40% of air pollution is generated by vehicles and transportation. The particulate matter (PM) emission significantly impacts human health. Fine particles below 2.5 {mu}m (PM2.5) can enter the lungs and lead to respiratory problems. These particles not only influence human health, but also reduce the capability of many automobile exhaust heat exchanging devices. Neutron radiography is a non-destructive method of analyzing carbonaceous PM. While neutron radiography has been demonstrated for soot measurement in the past, the application has not considered the presence of unburned hydrocarbons, significant amounts of moisture nor examined complex geometrical configurations. The purpose of this work is to study a reliable non-destructive testing methodology using neutron radiography for measurement of soot distribution in automotive components. A soot standard (aluminium target) was designed and manufactured as a calibration tool. The standard is radiographed and used to measure the differences between various soot thickness and compositions. The radiograph images are analyzed to determine a calibration curve based upon the composition of the materials which can then be used for analysis of the automotive components. Experiments are performed using a diesel engine to produce soot deposits on exhaust piping. Soot distribution on exhaust piping is measured using neutron radiography. (authors)

  17. Isothermal Kinetics of Catalyzed Air Oxidation of Diesel Soot

    Directory of Open Access Journals (Sweden)

    R. Prasad

    2011-01-01

    Full Text Available To comply with the stringent emission regulations on soot, diesel vehicles manufacturers more and more commonly use diesel particulate filters (DPF. These systems need to be regenerated periodically by burning soot that has been accumulated during the loading of the DPF. Design of the DPF requires rate of soot oxidation. This paper describes the kinetics of catalytic oxidation of diesel soot with air under isothermal conditions. Kinetics data were collected in a specially designed mini-semi-batch reactor. Under the high air flow rate assuming pseudo first order reaction the activation energy of soot oxidation was found to be, Ea = 160 kJ/ mol. ©2010 BCREC UNDIP. All rights reserved(Received: 14th June 2010, Revised: 18th July 2010, Accepted: 9th August 2010[How to Cite: R. Prasad, V.R. Bella. (2010. Isothermal Kinetics of Catalyzed Air Oxidation of Diesel Soot. Bulletin of Chemical Reaction Engineering and Catalysis, 5(2: 95-101. doi:10.9767/bcrec.5.2.796.95-101][DOI:http://dx.doi.org/10.9767/bcrec.5.2.796.95-101 || or local:  http://ejournal.undip.ac.id/index.php/bcrec/article/view/796]Cited by in: ACS 1 |

  18. Measurement of Soot Deposition in Automotive Components Using Neutron Radiography

    International Nuclear Information System (INIS)

    Zekveld, David; Liu, Liaohui; Harrison, Andrew; Gill, Spencer; Harvel, Glenn; Chang, Jen-Shih

    2008-01-01

    About 40% of air pollution is generated by vehicles and transportation. The particulate matter (PM) emission significantly impacts human health. Fine particles below 2.5 μm (PM2.5) can enter the lungs and lead to respiratory problems. These particles not only influence human health, but also reduce the capability of many automobile exhaust heat exchanging devices. Neutron radiography is a non-destructive method of analyzing carbonaceous PM. While neutron radiography has been demonstrated for soot measurement in the past, the application has not considered the presence of unburned hydrocarbons, significant amounts of moisture nor examined complex geometrical configurations. The purpose of this work is to study a reliable non-destructive testing methodology using neutron radiography for measurement of soot distribution in automotive components. A soot standard (aluminium target) was designed and manufactured as a calibration tool. The standard is radiographed and used to measure the differences between various soot thickness and compositions. The radiograph images are analyzed to determine a calibration curve based upon the composition of the materials which can then be used for analysis of the automotive components. Experiments are performed using a diesel engine to produce soot deposits on exhaust piping. Soot distribution on exhaust piping is measured using neutron radiography. (authors)

  19. Durable superhydrophobic carbon soot coatings for sensor applications

    Science.gov (United States)

    Esmeryan, K. D.; Radeva, E. I.; Avramov, I. D.

    2016-01-01

    A novel approach for the fabrication of durable superhydrophobic (SH) carbon soot coatings used in quartz crystal microbalance (QCM) based gas or liquid sensors is reported. The method uses modification of the carbon soot through polymerization of hexamethyldisiloxane (HMDSO) by means of glow discharge RF plasma. The surface characterization shows a fractal-like network of carbon nanoparticles with diameter of ~50 nm. These particles form islands and cavities in the nanometer range, between which the plasma polymerized hexamethyldisiloxane (PPHMDSO) embeds and binds to the carbon chains and QCM surface. Such modified surface structure retains the hydrophobic nature of the soot and enhances its robustness upon water droplet interactions. Moreover, it significantly reduces the insertion loss and dynamic resistance of the QCM compared to the commonly used carbon soot/epoxy resin approach. Furthermore, the PPHMDSO/carbon soot coating demonstrates durability and no aging after more than 40 probing cycles in water based liquid environments. In addition, the surface layer keeps its superhydrophobicity even upon thermal annealing up to 540 °C. These experiments reveal an opportunity for the development of soot based SH QCMs with improved electrical characteristics, as required for high-resolution gas or liquid measurements.

  20. Predictive Models, How good are they?

    DEFF Research Database (Denmark)

    Kasch, Helge

    The WAD grading system has been used for more than 20 years by now. It has shown long-term viability, but with strengths and limitations. New bio-psychosocial assessment of the acute whiplash injured subject may provide better prediction of long-term disability and pain. Furthermore, the emerging......-up. It is important to obtain prospective identification of the relevant risk underreported disability could, if we were able to expose these hidden “risk-factors” during our consultations, provide us with better predictive models. New data from large clinical studies will present exciting new genetic risk markers...

  1. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    SILVA R. G.

    1999-01-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  2. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  3. Reaction mechanism for the free-edge oxidation of soot by O 2

    KAUST Repository

    Raj, Abhijeet; da Silva, Gabriel; Chung, Suk-Ho

    2012-01-01

    The reaction pathways for the oxidation by O 2 of polycyclic aromatic hydrocarbons present in soot particles are investigated using density functional theory at B3LYP/6-311++G(d,p) level of theory. For this, pyrene radical (4-pyrenyl) is chosen as the model molecule, as most soot models present in the literature employ the reactions involving the conversion of 4-pyrenyl to 4-phenanthryl by O 2 and OH to account for soot oxidation. Several routes for the formation of CO and CO 2 are proposed. The addition of O 2 on a radical site to form a peroxyl radical is found to be barrierless and exothermic with reaction energy of 188kJ/mol. For the oxidation reaction to proceed further, three pathways are suggested, each of which involve the activation energies of 104, 167 and 115kJ/mol relative to the peroxyl radical. The effect of the presence of H atom on a carbon atom neighboring the radical site on the energetics of carbon oxidation is assessed. Those intermediate species formed during oxidation with seven-membered rings or with a phenolic group are found to be highly stable. The rate constants evaluated using transition state theory in the temperature range of 300-3000K for the reactions involved in the mechanism are provided. © 2012 The Combustion Institute.

  4. Reaction mechanism for the free-edge oxidation of soot by O 2

    KAUST Repository

    Raj, Abhijeet

    2012-11-01

    The reaction pathways for the oxidation by O 2 of polycyclic aromatic hydrocarbons present in soot particles are investigated using density functional theory at B3LYP/6-311++G(d,p) level of theory. For this, pyrene radical (4-pyrenyl) is chosen as the model molecule, as most soot models present in the literature employ the reactions involving the conversion of 4-pyrenyl to 4-phenanthryl by O 2 and OH to account for soot oxidation. Several routes for the formation of CO and CO 2 are proposed. The addition of O 2 on a radical site to form a peroxyl radical is found to be barrierless and exothermic with reaction energy of 188kJ/mol. For the oxidation reaction to proceed further, three pathways are suggested, each of which involve the activation energies of 104, 167 and 115kJ/mol relative to the peroxyl radical. The effect of the presence of H atom on a carbon atom neighboring the radical site on the energetics of carbon oxidation is assessed. Those intermediate species formed during oxidation with seven-membered rings or with a phenolic group are found to be highly stable. The rate constants evaluated using transition state theory in the temperature range of 300-3000K for the reactions involved in the mechanism are provided. © 2012 The Combustion Institute.

  5. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to

  6. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  7. Characterization and reactivity of soot from fast pyrolysis of lignocellulosic compounds and monolignols

    DEFF Research Database (Denmark)

    Trubetskaya, Anna; Brown, Avery; Tompsett, Geoffrey

    2018-01-01

    spectroscopy. The CO2 reactivity of soot was investigated by thermogravimetric analysis. Soot from cellulose was more reactive than soot produced from extractives, lignin and monolignols. Soot reactivity was correlated with the separation distances between adjacent graphene layers, as measured using...... transmission electron microscopy. Particle size, free radical concentration, differences in a degree of curvature and multi-core structures influenced the soot reactivity less than the interlayer separation distances. Soot yield was correlated with the lignin content of the feedstock. The selection...... of the extraction solvent had a strong influence on the soot reactivity. The Soxhlet extraction of softwood and wheat straw lignin soot using methanol decreased the soot reactivity, whereas acetone extraction had only a modest effect....

  8. Predictive Models for Carcinogenicity and Mutagenicity ...

    Science.gov (United States)

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

  9. Validated predictive modelling of the environmental resistome.

    Science.gov (United States)

    Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

    2015-06-01

    Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

  10. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  11. Baryogenesis model predicting antimatter in the Universe

    International Nuclear Information System (INIS)

    Kirilova, D.

    2003-01-01

    Cosmic ray and gamma-ray data do not rule out antimatter domains in the Universe, separated at distances bigger than 10 Mpc from us. Hence, it is interesting to analyze the possible generation of vast antimatter structures during the early Universe evolution. We discuss a SUSY-condensate baryogenesis model, predicting large separated regions of matter and antimatter. The model provides generation of the small locally observed baryon asymmetry for a natural initial conditions, it predicts vast antimatter domains, separated from the matter ones by baryonically empty voids. The characteristic scale of antimatter regions and their distance from the matter ones is in accordance with observational constraints from cosmic ray, gamma-ray and cosmic microwave background anisotropy data

  12. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    OpenAIRE

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre t...

  13. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  14. Extension of weighted sum of gray gas data to mathematical simulation of radiative heat transfer in a boiler with gas-soot media.

    Science.gov (United States)

    Gharehkhani, Samira; Nouri-Borujerdi, Ali; Kazi, Salim Newaz; Yarmand, Hooman

    2014-01-01

    In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site.

  15. Tectonic predictions with mantle convection models

    Science.gov (United States)

    Coltice, Nicolas; Shephard, Grace E.

    2018-04-01

    Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

  16. In-cylinder Combustion and Soot Evolution in the Transition from Conventional CI mode to PPC

    KAUST Repository

    An, Yanzhao

    2018-01-09

    The present study intends to explore the in-cylinder combustion and evolution of soot emission during the transition from conventional compression ignition (CI) combustion to partially premixed combustion (PPC) at low load conditions. In-cylinder combustion images and engine-out emissions were measured in an optical engine fueled with low octane heavy naphtha fuel (RON = 50). Full cycle engine simulations were performed using a three-dimensional computational fluid dynamics code CONVERGETM, coupled with gas phase chemical kinetics, turbulence, and particulate size mimic soot model. The simulations were performed under low load conditions (IMEP ~ 2 to 3 bar) at an engine speed of 1200 rpm. The start of injection (SOI) was advanced from late (-10 CAD aTDC) to early fuel injection timings (-40 CAD aTDC) to realize the combustion transition from CI combustion to PPC. The simulation results of combustion and emission are compared with the experimental results at both CI and PPC combustion modes. The results of the study show a typical low-temperature stratified lean combustion at PPC mode, while high-temperature spray-driven combustion is evident at CI mode. The in-cylinder small intermediates species such as acetylene (C2H2), propargyl (C3H3), cyclopentadienyl (C5H5) and polycyclic aromatic hydrocarbons (PAHs) were significantly suppressed at PPC mode. Nucleation reaction of PAHs collision contributed to main soot mass production. The distribution of soot mass and particle number density was consistent with the distribution of high-temperature zones at CI and PPC combustion modes.

  17. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  18. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  19. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Predicting extinction rates in stochastic epidemic models

    International Nuclear Information System (INIS)

    Schwartz, Ira B; Billings, Lora; Dykman, Mark; Landsman, Alexandra

    2009-01-01

    We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed

  1. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert F.; Knox, James C.

    2016-01-01

    As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  2. Effects of non-unity Lewis number of gas-phase species in turbulent nonpremixed sooting flames

    KAUST Repository

    Attili, Antonio; Bisetti, Fabrizio; Mueller, Michael E.; Pitsch, Heinz

    2016-01-01

    Turbulence statistics from two three-dimensional direct numerical simulations of planar n-heptane/air turbulent jets are compared to assess the effect of the gas-phase species diffusion model on flame dynamics and soot formation. The Reynolds number based on the initial jet width and velocity is around 15, 000, corresponding to a Taylor scale Reynolds number in the range 100 ≤ Reλ ≤ 150. In one simulation, multicomponent transport based on a mixture-averaged approach is employed, while in the other the gas-phase species Lewis numbers are set equal to unity. The statistics of temperature and major species obtained with the mixture-averaged formulation are very similar to those in the unity Lewis number case. In both cases, the statistics of temperature are captured with remarkable accuracy by a laminar flamelet model with unity Lewis numbers. On the contrary, a flamelet with a mixture-averaged diffusion model, which corresponds to the model used in the multi-component diffusion three-dimensional DNS, produces significant differences with respect to the DNS results. The total mass of soot precursors decreases by 20-30% with the unity Lewis number approximation, and their distribution is more homogeneous in space and time. Due to the non-linearity of the soot growth rate with respect to the precursors' concentration, the soot mass yield decreases by a factor of two. Being strongly affected by coagulation, soot number density is not altered significantly if the unity Lewis number model is used rather than the mixture-averaged diffusion. The dominant role of turbulent transport over differential diffusion effects is expected to become more pronounced for higher Reynolds numbers. © 2016 The Combustion Institute.

  3. Effects of non-unity Lewis number of gas-phase species in turbulent nonpremixed sooting flames

    KAUST Repository

    Attili, Antonio

    2016-02-13

    Turbulence statistics from two three-dimensional direct numerical simulations of planar n-heptane/air turbulent jets are compared to assess the effect of the gas-phase species diffusion model on flame dynamics and soot formation. The Reynolds number based on the initial jet width and velocity is around 15, 000, corresponding to a Taylor scale Reynolds number in the range 100 ≤ Reλ ≤ 150. In one simulation, multicomponent transport based on a mixture-averaged approach is employed, while in the other the gas-phase species Lewis numbers are set equal to unity. The statistics of temperature and major species obtained with the mixture-averaged formulation are very similar to those in the unity Lewis number case. In both cases, the statistics of temperature are captured with remarkable accuracy by a laminar flamelet model with unity Lewis numbers. On the contrary, a flamelet with a mixture-averaged diffusion model, which corresponds to the model used in the multi-component diffusion three-dimensional DNS, produces significant differences with respect to the DNS results. The total mass of soot precursors decreases by 20-30% with the unity Lewis number approximation, and their distribution is more homogeneous in space and time. Due to the non-linearity of the soot growth rate with respect to the precursors\\' concentration, the soot mass yield decreases by a factor of two. Being strongly affected by coagulation, soot number density is not altered significantly if the unity Lewis number model is used rather than the mixture-averaged diffusion. The dominant role of turbulent transport over differential diffusion effects is expected to become more pronounced for higher Reynolds numbers. © 2016 The Combustion Institute.

  4. Data Driven Economic Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Masoud Kheradmandi

    2018-04-01

    Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

  5. Ice nucleation activity of diesel soot particles at cirrus relevant temperature conditions: Effects of hydration, secondary organics coating, soot morphology, and coagulation

    Science.gov (United States)

    Kulkarni, Gourihar; China, Swarup; Liu, Shang; Nandasiri, Manjula; Sharma, Noopur; Wilson, Jacqueline; Aiken, Allison C.; Chand, Duli; Laskin, Alexander; Mazzoleni, Claudio; Pekour, Mikhail; Shilling, John; Shutthanandan, Vaithiyalingam; Zelenyuk, Alla; Zaveri, Rahul A.

    2016-04-01

    Ice formation by diesel soot particles was investigated at temperatures ranging from -40 to -50°C. Size-selected soot particles were physically and chemically aged in an environmental chamber, and their ice nucleating properties were determined using a continuous flow diffusion type ice nucleation chamber. Bare (freshly formed), hydrated, and compacted soot particles, as well as α-pinene secondary organic aerosol (SOA)-coated soot particles at high relative humidity conditions, showed ice formation activity at subsaturation conditions with respect to water but below the homogeneous freezing threshold conditions. However, SOA-coated soot particles at dry conditions were observed to freeze at homogeneous freezing threshold conditions. Overall, our results suggest that heterogeneous ice nucleation activity of freshly emitted diesel soot particles are sensitive to some of the aging processes that soot can undergo in the atmosphere.

  6. Plant control using embedded predictive models

    International Nuclear Information System (INIS)

    Godbole, S.S.; Gabler, W.E.; Eschbach, S.L.

    1990-01-01

    B and W recently undertook the design of an advanced light water reactor control system. A concept new to nuclear steam system (NSS) control was developed. The concept, which is called the Predictor-Corrector, uses mathematical models of portions of the controlled NSS to calculate, at various levels within the system, demand and control element position signals necessary to satisfy electrical demand. The models give the control system the ability to reduce overcooling and undercooling of the reactor coolant system during transients and upsets. Two types of mathematical models were developed for use in designing and testing the control system. One model was a conventional, comprehensive NSS model that responds to control system outputs and calculates the resultant changes in plant variables that are then used as inputs to the control system. Two other models, embedded in the control system, were less conventional, inverse models. These models accept as inputs plant variables, equipment states, and demand signals and predict plant operating conditions and control element states that will satisfy the demands. This paper reports preliminary results of closed-loop Reactor Coolant (RC) pump trip and normal load reduction testing of the advanced concept. Results of additional transient testing, and of open and closed loop stability analyses will be reported as they are available

  7. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  8. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  9. Prediction of Chemical Function: Model Development and ...

    Science.gov (United States)

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  10. Evaluating Predictive Models of Software Quality

    Science.gov (United States)

    Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

    2014-06-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  11. Predicting FLDs Using a Multiscale Modeling Scheme

    Science.gov (United States)

    Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.

    2017-09-01

    The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.

  12. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  13. Evaluating predictive models of software quality

    International Nuclear Information System (INIS)

    Ciaschini, V; Canaparo, M; Ronchieri, E; Salomoni, D

    2014-01-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  14. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  15. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  16. Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

    Science.gov (United States)

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

  17. 3-D simulation of soot formation in a direct-injection diesel engine based on a comprehensive chemical mechanism and method of moments

    Science.gov (United States)

    Zhong, Bei-Jing; Dang, Shuai; Song, Ya-Na; Gong, Jing-Song

    2012-02-01

    Here, we propose both a comprehensive chemical mechanism and a reduced mechanism for a three-dimensional combustion simulation, describing the formation of polycyclic aromatic hydrocarbons (PAHs), in a direct-injection diesel engine. A soot model based on the reduced mechanism and a method of moments is also presented. The turbulent diffusion flame and PAH formation in the diesel engine were modelled using the reduced mechanism based on the detailed mechanism using a fixed wall temperature as a boundary condition. The spatial distribution of PAH concentrations and the characteristic parameters for soot formation in the engine cylinder were obtained by coupling a detailed chemical kinetic model with the three-dimensional computational fluid dynamic (CFD) model. Comparison of the simulated results with limited experimental data shows that the chemical mechanisms and soot model are realistic and correctly describe the basic physics of diesel combustion but require further development to improve their accuracy.

  18. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  19. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  20. An Anisotropic Hardening Model for Springback Prediction

    International Nuclear Information System (INIS)

    Zeng, Danielle; Xia, Z. Cedric

    2005-01-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test

  1. Soot in the air may have serious climatic consequences

    International Nuclear Information System (INIS)

    Seip, Hans Martin

    2002-01-01

    Emissions of soot in China and India may be an important cause of changed summer weather in China, with increasing floods in the south-east and increasing droughts in the north-east. In addition to the greenhouse gases, the particulate matter (aerosols) in the air has an important effect on the climate. Most particles have a cooling effect since they reflect solar radiation. However, some particles are dark as they contain soot ('black carbon'). Such particles, which are formed by incomplete combustion of coal, oil and biomass, absorb solar radiation and thus have a warming effect, even if they reduce the solar irradiation on the ground. Soot particles do not have quite the same effect as the greenhouse gases. The soot particles absorb solar radiation, while the greenhouse gases absorb terrestrial heat radiation. In addition, the residence time of the soot particles in the atmosphere is shorter than that of, say, carbon dioxide. The concentration is therefore much higher in areas close to emission sources than elsewhere

  2. Effects of self-absorption on simultaneous estimation of temperature distribution and concentration fields of soot and metal-oxide nanoparticles in nanofluid fuel flames using a spectrometer

    Science.gov (United States)

    Liu, Guannan; Liu, Dong

    2018-06-01

    An improved inverse reconstruction model with consideration of self-absorption effect for the temperature distribution and concentration fields of soot and metal-oxide nanoparticles in nanofluid fuel flames was proposed based on the flame emission spectrometry. The effects of self-absorption on the temperature profile and concentration fields were investigated for various measurement errors, flame optical thicknesses and detecting lines numbers. The model neglecting the self-absorption caused serious reconstruction errors especially in the nanofluid fuel flames with large optical thicknesses, while the improved model was used to successfully recover the temperature distribution and concentration fields of soot and metal-oxide nanoparticles for the flames regardless of the optical thickness. Through increasing detecting lines number, the reconstruction accuracy can be greatly improved due to more flame emission information received by the spectrometer. With the adequate detecting lines number, the estimations for the temperature distribution and concentration fields of soot and metal-oxide nanoparticles in flames with large optical thicknesses were still satisfying even from the noisy radiation intensities with signal to noise ratio (SNR) as low as 46 dB. The results showed that the improved reconstruction model was effective and robust to concurrently retrieve the temperature distribution and volume fraction fields of soot and metal-oxide nanoparticles for the exact and noisy data in nanofluid fuel sooting flames with different optical thicknesses.

  3. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  4. Chinese Soot on a Vietnamese Soup

    Science.gov (United States)

    Mari, X.

    2015-12-01

    Black Carbon (BC) is an aerosol emitted as soot during biomass burning and fossil fuels combustion together with other carbonaceous aerosols such as organic carbon (OC) and polyaromatic hydrocarbons (PAHs). While the impacts of BC on health and climate have been studied for many years, studies about its deposition and impact on marine ecosystems are scares. This is rather surprising considering that a large fraction of atmospheric BC deposits on the surface of the ocean via dry or wet deposition. On a global scale, deposition on the ocean is about 45 Tg C per year, with higher fluxes in the northern hemisphere and in inter-tropical regions, following the occurrence of the hot-spots of concentration. In the present study conducted on shore, in Haiphong and Halong cities, North Vietnam, we measured the seasonal variations of atmospheric BC, OC and PAHs during a complete annual cycle. The presentation will discuss the atmospheric results in terms of seasonal variability and sources. Inputs to the marine system are higher during the dry season, concomitantly with the arrival of air masses enriched in BC coming from the North. However, the carbon fingerprint can significantly differ at shorter time periods depending on the air mass pathway and speed. Our work leads to the characterization and the determination of the relative contribution of more specific sources like local traffic, which includes tourism and fishing boats, coal dust emitted from the nearby mine, and long-range transported aerosols. This variable input of carbonaceous aerosols might have consequences for the cycling and the repartition of carbon and nutrients in the marine ecosystem of Halong Bay.

  5. Predictions of models for environmental radiological assessment

    International Nuclear Information System (INIS)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa; Mahler, Claudio Fernando

    2011-01-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for 137 Cs and 60 Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  6. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...

  7. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  8. Investigations of the long-term effects of LII on soot and bath gas

    KAUST Repository

    Cenker, Emre; Bennett, A.; Roberts, William L.

    2017-01-01

    A combination of high-repetition rate imaging, laser extinction measurements, two-colour soot pyrometry imaging, and high-resolution transmission electron microscopy of thermophoretically sampled soot is used to investigate the long

  9. Effects of Fuel Quantity on Soot Formation Process for Biomass-Based Renewable Diesel Fuel Combustion

    KAUST Repository

    Jing, Wei; Wu, Zengyang; Roberts, William L.; Fang, Tiegang

    2016-01-01

    Soot formation process was investigated for biomass-based renewable diesel fuel, such as biomass to liquid (BTL), and conventional diesel combustion under varied fuel quantities injected into a constant volume combustion chamber. Soot measurement

  10. A computational study of soot formation in opposed-flow diffusion flame interacting with vortices

    KAUST Repository

    Selvaraj, Prabhu; Im, Hong G.

    2017-01-01

    ethylene-air flame is simulated. A reduced mechanism with PAH pathways that includes until coronene and method of moments with interpolative closure (MOMIC) has been employed to calculate the soot characteristics. Interaction of sooting flame with a

  11. Effective modelling for predictive analytics in data science ...

    African Journals Online (AJOL)

    Effective modelling for predictive analytics in data science. ... the nearabsence of empirical or factual predictive analytics in the mainstream research going on ... Keywords: Predictive Analytics, Big Data, Business Intelligence, Project Planning.

  12. The immersion freezing behavior of size-segregated soot and kaolinite particles

    Science.gov (United States)

    Hartmann, S.; Augustin, S.; Clauss, T.; Niedermeier, D.; Raddatz, M.; Wex, H.; Shaw, R. A.; Stratmann, F.

    2011-12-01

    Heterogeneous ice nucleation plays a crucial role for ice formation in mixed-phase and cirrus clouds and has an important impact on precipitation formation, global radiation balances, and therefore Earth's climate (Cantrell and Heymsfield, 2005). Mineral dust and soot particles are found to be a major component of ice crystal residues (e.g., Pratt et al., 2009) so these substances are potential sources of atmospheric ice nuclei (IN). Experimental studies investigating the immersion freezing behavior of size-segregated soot and kaolinite particles conducted at the Leipzig Aerosol Cloud Interaction Simulator (LACIS) are presented. In our measurements only one aerosol particle is immersed in an air suspended water droplet which can trigger ice nucleation. The method facilitates very precise examinations with respect to temperature, ice nucleation time and ice nucleus size. Considering laboratory studies, the picture of the IN ability of soot particles is quite heterogeneous. Our studies show that submicron flame, spark soot particles and optionally coated with sulfuric acid to simulate chemically aging do not act as IN at temperatures higher than homogeneous freezing taking place. Therefore soot particles might not be an important source of IN for immersion freezing in the atmosphere. In contrast, kaolinite being representative for natural mineral dust with a well known composition and structure is found to be very active in forming ice for all freezing modes (e.g., Mason and Maybank, 1958). Analyzing the immersion freezing behavior of different sized kaolinite particles (300, 500 and 700 nm in diameter) the size effect was clearly observed, i.e. the ice fraction (number of frozen droplets per total number) scales with particle surface, i.e. the larger the ice nucleus surface the higher the ice fraction. The slope of the logarithm of the ice fraction as function of temperature is similar for all particle sizes investigated and fits very well with the results of L

  13. Combining GPS measurements and IRI model predictions

    International Nuclear Information System (INIS)

    Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

    2002-01-01

    The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

  14. Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

    Science.gov (United States)

    Strack, John E.; Pielke, Roger A.; Liston, Glen E.

    2007-12-01

    Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season by converting incoming solar radiation to longwave radiation and sensible heat. Soot deposition lowers the albedo of the snow, allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 2.2°C warming of 3 m air temperatures and a 108 m increase in boundary layer depth during the melt period. The snow-free date also occurred 11 d earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, owing to soot pollution, caused the snow-free date to occur 5 d earlier. The soot pollution caused a 1.0°C warming of 3 m air temperatures and a 25 m average deepening of the boundary layer.

  15. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  16. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  17. Towards predictive models for transitionally rough surfaces

    Science.gov (United States)

    Abderrahaman-Elena, Nabil; Garcia-Mayoral, Ricardo

    2017-11-01

    We analyze and model the previously presented decomposition for flow variables in DNS of turbulence over transitionally rough surfaces. The flow is decomposed into two contributions: one produced by the overlying turbulence, which has no footprint of the surface texture, and one induced by the roughness, which is essentially the time-averaged flow around the surface obstacles, but modulated in amplitude by the first component. The roughness-induced component closely resembles the laminar steady flow around the roughness elements at the same non-dimensional roughness size. For small - yet transitionally rough - textures, the roughness-free component is essentially the same as over a smooth wall. Based on these findings, we propose predictive models for the onset of the transitionally rough regime. Project supported by the Engineering and Physical Sciences Research Council (EPSRC).

  18. Resource-estimation models and predicted discovery

    International Nuclear Information System (INIS)

    Hill, G.W.

    1982-01-01

    Resources have been estimated by predictive extrapolation from past discovery experience, by analogy with better explored regions, or by inference from evidence of depletion of targets for exploration. Changes in technology and new insights into geological mechanisms have occurred sufficiently often in the long run to form part of the pattern of mature discovery experience. The criterion, that a meaningful resource estimate needs an objective measure of its precision or degree of uncertainty, excludes 'estimates' based solely on expert opinion. This is illustrated by development of error measures for several persuasive models of discovery and production of oil and gas in USA, both annually and in terms of increasing exploration effort. Appropriate generalizations of the models resolve many points of controversy. This is illustrated using two USA data sets describing discovery of oil and of U 3 O 8 ; the latter set highlights an inadequacy of available official data. Review of the oil-discovery data set provides a warrant for adjusting the time-series prediction to a higher resource figure for USA petroleum. (author)

  19. Prediction of pipeline corrosion rate based on grey Markov models

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Peng Guichu; Wang Yuemin

    2009-01-01

    Based on the model that combined by grey model and Markov model, the prediction of corrosion rate of nuclear power pipeline was studied. Works were done to improve the grey model, and the optimization unbiased grey model was obtained. This new model was used to predict the tendency of corrosion rate, and the Markov model was used to predict the residual errors. In order to improve the prediction precision, rolling operation method was used in these prediction processes. The results indicate that the improvement to the grey model is effective and the prediction precision of the new model combined by the optimization unbiased grey model and Markov model is better, and the use of rolling operation method may improve the prediction precision further. (authors)

  20. An Operational Model for the Prediction of Jet Blast

    Science.gov (United States)

    2012-01-09

    This paper presents an operational model for the prediction of jet blast. The model was : developed based upon three modules including a jet exhaust model, jet centerline decay : model and aircraft motion model. The final analysis was compared with d...

  1. New Nanotech from an Ancient Material: Chemistry Demonstrations Involving Carbon-Based Soot

    Science.gov (United States)

    Campbell, Dean J.; Andrews, Mark J.; Stevenson, Keith J.

    2012-01-01

    Carbon soot has been known since antiquity, but has recently been finding new uses as a robust, inexpensive nanomaterial. This paper describes the superhydrophobic properties of carbon soot films prepared by combustion of candle wax or propane gas and introduces some of the optical absorption and fluorescence properties of carbon soot particles.…

  2. Data driven propulsion system weight prediction model

    Science.gov (United States)

    Gerth, Richard J.

    1994-10-01

    The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

  3. Predictive modeling of emergency cesarean delivery.

    Directory of Open Access Journals (Sweden)

    Carlos Campillo-Artero

    Full Text Available To increase discriminatory accuracy (DA for emergency cesarean sections (ECSs.We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTREE, and analyzed a random forest model (RFM. We used the areas under the receiver-operating-characteristic (ROC curves (AUCs to assess their DA.The magnitude of the LR+ for all putative individual RFs and ORs in the logistic regression models was low to moderate. Except for parity, all putative RFs were positively associated with ECS, including hospital fixed-effects and night-shift delivery. The DA of all logistic models ranged from 0.74 to 0.81. The most relevant RFs (pH, induction, and previous C-section in the CTREEs showed the highest ORs in the logistic models. The DA of the RFM and its most relevant interaction terms was even higher (AUC = 0.94; 95% CI: 0.93-0.95.Putative fetal, maternal, and contextual RFs alone fail to achieve reasonable DA for ECS. It is the combination of these RFs and the interactions between them at each hospital that make it possible to improve the DA for the type of delivery and tailor interventions through prediction to improve the appropriateness of ECS indications.

  4. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  5. Methodology for Designing Models Predicting Success of Infertility Treatment

    OpenAIRE

    Alireza Zarinara; Mohammad Mahdi Akhondi; Hojjat Zeraati; Koorsh Kamali; Kazem Mohammad

    2016-01-01

    Abstract Background: The prediction models for infertility treatment success have presented since 25 years ago. There are scientific principles for designing and applying the prediction models that is also used to predict the success rate of infertility treatment. The purpose of this study is to provide basic principles for designing the model to predic infertility treatment success. Materials and Methods: In this paper, the principles for developing predictive models are explained and...

  6. Finite Unification: Theory, Models and Predictions

    CERN Document Server

    Heinemeyer, S; Zoupanos, G

    2011-01-01

    All-loop Finite Unified Theories (FUTs) are very interesting N=1 supersymmetric Grand Unified Theories (GUTs) realising an old field theory dream, and moreover have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N=1 GUTs is achieved by searching for renormalization group invariant (RGI) relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensional couplings that guarantee the vanishing of all beta-functions in certain N=1 GUTs even to all orders. Furthermore developments in the soft supersymmetry breaking sector of N=1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory, too. Based on the above theoretical framework phenomenologically consistent FUTs have been constructed. Here we review FUT models based on the SU(5) and SU(3)^3 gauge groups and their predictions. Of particular interest is the Hig...

  7. Revised predictive equations for salt intrusion modelling in estuaries

    NARCIS (Netherlands)

    Gisen, J.I.A.; Savenije, H.H.G.; Nijzink, R.C.

    2015-01-01

    For one-dimensional salt intrusion models to be predictive, we need predictive equations to link model parameters to observable hydraulic and geometric variables. The one-dimensional model of Savenije (1993b) made use of predictive equations for the Van der Burgh coefficient $K$ and the dispersion

  8. Neutrino nucleosynthesis in supernovae: Shell model predictions

    International Nuclear Information System (INIS)

    Haxton, W.C.

    1989-01-01

    Almost all of the 3 · 10 53 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7 Li, 11 B, 19 F, 138 La, and 180 Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab

  9. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  10. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  11. Model predictive control of a wind turbine modelled in Simpack

    International Nuclear Information System (INIS)

    Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

    2014-01-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

  12. Model predictive control of a wind turbine modelled in Simpack

    Science.gov (United States)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  13. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  14. Potassium and soot interaction in fast biomass pyrolysis at high temperatures

    DEFF Research Database (Denmark)

    Trubetskaya, Anna; Hofmann Larsen, Flemming; Shchukarev, Andrey

    2018-01-01

    2 reactivity was studied by thermogravimetric analysis. The XPS results showed that potassium incorporation with oxygen-containing surface groups in the soot matrix did not occur during high temperature pyrolysis. The potassium was mostly found as water-soluble salts such as KCl, KOH, KHCO3 and K2CO...... potassium amount was incorporated in the soot matrix during pyrolysis. Raman spectroscopy results showed that the carbon chemistry of biomass soot also affected the CO2 reactivity. The less reactive pinewood soot was more graphitic than herbaceous biomass soot samples with the disordered carbon structure...

  15. Predictive integrated modelling for ITER scenarios

    International Nuclear Information System (INIS)

    Artaud, J.F.; Imbeaux, F.; Aniel, T.; Basiuk, V.; Eriksson, L.G.; Giruzzi, G.; Hoang, G.T.; Huysmans, G.; Joffrin, E.; Peysson, Y.; Schneider, M.; Thomas, P.

    2005-01-01

    The uncertainty on the prediction of ITER scenarios is evaluated. 2 transport models which have been extensively validated against the multi-machine database are used for the computation of the transport coefficients. The first model is GLF23, the second called Kiauto is a model in which the profile of dilution coefficient is a gyro Bohm-like analytical function, renormalized in order to get profiles consistent with a given global energy confinement scaling. The package of codes CRONOS is used, it gives access to the dynamics of the discharge and allows the study of interplay between heat transport, current diffusion and sources. The main motivation of this work is to study the influence of parameters such plasma current, heat, density, impurities and toroidal moment transport. We can draw the following conclusions: 1) the target Q = 10 can be obtained in ITER hybrid scenario at I p = 13 MA, using either the DS03 two terms scaling or the GLF23 model based on the same pedestal; 2) I p = 11.3 MA, Q = 10 can be reached only assuming a very peaked pressure profile and a low pedestal; 3) at fixed Greenwald fraction, Q increases with density peaking; 4) achieving a stationary q-profile with q > 1 requires a large non-inductive current fraction (80%) that could be provided by 20 to 40 MW of LHCD; and 5) owing to the high temperature the q-profile penetration is delayed and q = 1 is reached about 600 s in ITER hybrid scenario at I p = 13 MA, in the absence of active q-profile control. (A.C.)

  16. Visualizing the mobility of silver during catalytic soot oxidation

    DEFF Research Database (Denmark)

    Gardini, Diego; Christensen, Jakob M.; Damsgaard, Christian Danvad

    2016-01-01

    The catalytic activity and mobility of silver nanoparticles used as catalysts in temperature programmed oxidation of soot:silver (1:5 wt:wt) mixtures have been investigated by means of flow reactor experiments and in situ environmental transmission electron microscopy (ETEM). The carbon oxidation...

  17. Sooting behavior of oxygenated fuels in a diffusion burner

    NARCIS (Netherlands)

    Boot, M.D.; Luijten, C.C.M.; Baert, R.S.G.; Edenhofer, R.; Dirks, H.; Lucka, K.; Köhne, H.

    2009-01-01

    Different strategies are being investigated towards reducing engine-out emission levels of soot and NOx of modern Diesel engines. A fuel-based strategy currently under investigation, entails the use of low cetane number (CN; i.e.low reactive) oxygenates. Previous research has shown that low CN

  18. Nanoparticle production by UV irradiation of combustion generated soot particles

    International Nuclear Information System (INIS)

    Stipe, Christopher B.; Choi, Jong Hyun; Lucas, Donald; Koshland, Catherine P.; Sawyer, Robert F.

    2004-01-01

    Laser ablation of surfaces normally produce high temperature plasmas that are difficult to control. By irradiating small particles in the gas phase, we can better control the size and concentration of the resulting particles when different materials are photofragmented. Here, we irradiate soot with 193 nm light from an ArF excimer laser. Irradiating the original agglomerated particles at fluences ranging from 0.07 to 0.26 J/cm 2 with repetition rates of 20 and 100 Hz produces a large number of small, unagglomerated particles, and a smaller number of spherical agglomerated particles. Mean particle diameters from 20 to 50 nm are produced from soot originally having a mean electric mobility diameter of 265nm. We use a non-dimensional parameter, called the photon/atom ratio (PAR), to aid in understanding the photofragmentation process. This parameter is the ratio of the number of photons striking the soot particles to the number of the carbon atoms contained in the soot particles, and is a better metric than the laser fluence for analyzing laser-particle interactions. These results suggest that UV photofragmentation can be effective in controlling particle size and morphology, and can be a useful diagnostic for studying elements of the laser ablation process

  19. Soot and short-lived pollutants provide political opportunity

    Science.gov (United States)

    Victor, David G.; Zaelke, Durwood; Ramanathan, Veerabhadran

    2015-09-01

    Cutting levels of soot and other short-lived pollutants delivers tangible benefits and helps governments to build confidence that collective action on climate change is feasible. After the Paris climate meeting this December, actually reducing these pollutants will be essential to the credibility of the diplomatic process.

  20. The Ice Nucleation Activity of Surface Modified Soot

    Science.gov (United States)

    Häusler, Thomas; Witek, Lorenz; Felgitsch, Laura; Hitzenberger, Regina; Grothe, Hinrich

    2017-04-01

    The ice nucleation efficiency of many important atmospheric particles remains poorly understood. Since soot is ubiquitous in the Earth's troposphere, they might have the potential to significantly impact the Earth's climate (Finlayson-Pitts and Pitts, 2000; Seinfeld and Pandis, 1998). Here we present the ice nucleation activity (INA) in immersion freezing mode of different types of soot. Therefor a CAST (combustion aerosol standard) generator was used to produce different kinds of soot samples. The CAST generator combusts a propane-air-mixture and deposits thereby produced soot on a polyvinyl fluoride filter. By varying the propane to air ratio, the amount of organic portion of the soot can be varied from black carbon (BC) with no organic content to brown carbon (BrC) with high organic content. To investigate the impact of functional sites of ice nuclei (IN), the soot samples were exposed to NO2 gas for a certain amount of time (30 to 360 minutes) to chemically modify the surface. Immersion freezing experiments were carried out in a unique reaction gadget. In this device a water-in-oil suspension (with the soot suspended in the aqueous phase) was cooled till the freezing point and was observed through a microscope (Pummer et al., 2012; Zolles et al., 2015) It was found that neither modified nor unmodified BC shows INA. On the contrary, unmodified BrC shows an INA at -32˚ C, which can be increased up to -20˚ C. The INA of BrC depends on the duration of NO2- exposure. To clarify the characteristics of the surface modifications, surface sensitive analysis like infrared spectroscopy and X-ray photoelectron spectroscopy were carried out. Finlayson-Pitts, B. J. and Pitts, J. N. J.: Chemistry of the Upper and Lower Atmosphere, Elsevier, New York, 2000. Pummer, B. G., Bauer, H., Bernardi, J., Bleicher, S., and Grothe, H.: Suspendable macromolecules are responsible for ice nucleation activity of birch and conifer pollen, Atmos Chem Phys, 12, 2541-2550, 2012. Seinfeld, J

  1. Fragmentation and bond strength of airborne diesel soot agglomerates

    Directory of Open Access Journals (Sweden)

    Messerer Armin

    2008-06-01

    Full Text Available Abstract Background The potential of diesel soot aerosol particles to break up into smaller units under mechanical stress was investigated by a direct impaction technique which measures the degree of fragmentation of individual agglomerates vs. impact energy. Diesel aerosol was generated by an idling diesel engine used for passenger vehicles. Both the aerosol emitted directly and aerosol that had undergone additional growth by Brownian coagulation ("aging" was investigated. Optionally a thermo-desoption technique at 280°C was used to remove all high-volatility and the majority of low-volatility HC adsorbates from the aerosol before aging. Results It was found that the primary soot agglomerates emitted directly from the engine could not be fragmented at all. Soot agglomerates permitted to grow additionally by Brownian coagulation of the primary emitted particles could be fragmented to a maximum of 75% and 60% respectively, depending on whether adsorbates were removed from their surface prior to aging or not. At most, these aged agglomerates could be broken down to roughly the size of the agglomerates from the primary emission. The energy required for a 50% fragmentation probability of all bonds within an agglomerate was reduced by roughly a factor of 2 when aging "dry" agglomerates. Average bond energies derived from the data were 0.52*10-16 and 1.2*10-16 J, respectively. This is about 2 orders of magnitude higher than estimates for pure van-der-Waals agglomerates, but agrees quite well with other observations. Conclusion Although direct conclusions regarding the behavior of inhaled diesel aerosol in contact with body fluids cannot be drawn from such measurements, the results imply that highly agglomerated soot aerosol particles are unlikely to break up into units smaller than roughly the size distribution emitted as tail pipe soot.

  2. Fragmentation and bond strength of airborne diesel soot agglomerates

    Science.gov (United States)

    Rothenbacher, Sonja; Messerer, Armin; Kasper, Gerhard

    2008-01-01

    Background The potential of diesel soot aerosol particles to break up into smaller units under mechanical stress was investigated by a direct impaction technique which measures the degree of fragmentation of individual agglomerates vs. impact energy. Diesel aerosol was generated by an idling diesel engine used for passenger vehicles. Both the aerosol emitted directly and aerosol that had undergone additional growth by Brownian coagulation ("aging") was investigated. Optionally a thermo-desoption technique at 280°C was used to remove all high-volatility and the majority of low-volatility HC adsorbates from the aerosol before aging. Results It was found that the primary soot agglomerates emitted directly from the engine could not be fragmented at all. Soot agglomerates permitted to grow additionally by Brownian coagulation of the primary emitted particles could be fragmented to a maximum of 75% and 60% respectively, depending on whether adsorbates were removed from their surface prior to aging or not. At most, these aged agglomerates could be broken down to roughly the size of the agglomerates from the primary emission. The energy required for a 50% fragmentation probability of all bonds within an agglomerate was reduced by roughly a factor of 2 when aging "dry" agglomerates. Average bond energies derived from the data were 0.52*10-16 and 1.2*10-16 J, respectively. This is about 2 orders of magnitude higher than estimates for pure van-der-Waals agglomerates, but agrees quite well with other observations. Conclusion Although direct conclusions regarding the behavior of inhaled diesel aerosol in contact with body fluids cannot be drawn from such measurements, the results imply that highly agglomerated soot aerosol particles are unlikely to break up into units smaller than roughly the size distribution emitted as tail pipe soot. PMID:18533015

  3. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  4. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  5. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  6. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  7. Predictive Modelling of Heavy Metals in Urban Lakes

    OpenAIRE

    Lindström, Martin

    2000-01-01

    Heavy metals are well-known environmental pollutants. In this thesis predictive models for heavy metals in urban lakes are discussed and new models presented. The base of predictive modelling is empirical data from field investigations of many ecosystems covering a wide range of ecosystem characteristics. Predictive models focus on the variabilities among lakes and processes controlling the major metal fluxes. Sediment and water data for this study were collected from ten small lakes in the ...

  8. An investigation of late-combustion soot burnout in a DI diesel engine using simultaneous planar imaging of soot and OH radical

    Energy Technology Data Exchange (ETDEWEB)

    John E. Dec; Peter L. Kelly-Zion

    1999-10-01

    Diesel engine design continues to be driven by the need to improve performance while at the same time achieving further reductions in emissions. The development of new designs to accomplish these goals requires an understanding of how the emissions are produced in the engine. Laser-imaging diagnostics are uniquely capable of providing this information, and the understanding of diesel combustion and emissions formation has been advanced considerably in recent years by their application. However, previous studies have generally focused on the early and middle stages of diesel combustion. These previous laser-imaging studies do provide important insight into the soot formation and oxidation processes during the main combustion event. They indicate that prior to the end of injection, soot formation is initiated by fuel-rich premixed combustion (equivalence ratio > 4) near the upstream limit of the luminous portion of the reacting fuel jet. The soot is then oxidized at the diffusion flame around the periphery of the luminous plume. Under typical diesel engine conditions, the diffusion flame does not burn the remaining fuel and soot as rapidly as it is supplied, resulting in an expanding region of rich combustion products and soot. This is evident in natural emission images by the increasing size of the luminous soot cloud prior to the end of injection. Hence, the amount of soot in the combustion chamber typically increases until shortly after the end of fuel injection, at which time the main soot formation period ends and the burnout phase begins. Sampling valve and two-color pyrometry data indicate that the vast majority (more than 90%) of the soot formed is oxidized before combustion ends; however, it is generally thought that a small fraction of this soot from the main combustion zones is not consumed and is the source of tail pipe soot emissions.

  9. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  10. Simultaneous measurement of the concentrations of soot particles and gas species in light hydrocarbon flames using mass spectrometry

    International Nuclear Information System (INIS)

    Li, Qingxun; Liu, Fang; Wang, Dezheng; Wang, Tiefeng

    2014-01-01

    Besides gas species concentrations, soot volume fractions are also important data in the study of flames. This work describes the simultaneous measurement of the concentrations of soot and gas species in light hydrocarbon flames by in situ sampling and mass spectrometry (MS).The reaction medium was frozen by sampling into a very low-pressure tube, and the soot selectivity (proportion of carbon atoms in the reactant converted to soot) was determined from the C and H mass balances using the measured concentrations of the gas species and the mass of soot present per unit gas volume. The H/C ratio of the soot was measured by a thermogravimetry–mass spectrometry combination. The soot volume fraction was calculated from the soot selectivity and density of the soot. The soot selectivity measured by this reduced pressure sampling mass spectrometry (RPSMS) method was verified by measurements using the gravimetric sampling technique where the mass of soot collected in a volume of gas was weighed by a high precision balance. For most of the measurements, the uncertainty in the soot volume fraction was ±5%, but this would be larger when the soot volume fractions are less than 1 ppm. For demonstration, the RPSMS method was used to study a methane fuel-rich flame where the soot volume fractions were 1–5 ppm. The simultaneous measurement of concentrations of soot and gas species is useful for the quantitative study of flames. (paper)

  11. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  12. Incipient Soot Formation in Rich Partially Premixed Flames under High Pressure Conditions of Relevance to Compression-Ignition Engines

    Science.gov (United States)

    2017-09-09

    a Laminar Premixed Flame, Aerosol Reaction Engineering , Center for Aerosol science and Engineering (CASE) Workshop 2016, Saint Louis, Missouri, May...Publication Type: Conference Paper or Presentation Conference Name: Aerosol Reaction Engineering , Center for Aerosol science and Engineering (CASE...measurements of critical soot precursors up to 3-ring aromatics is available online to modelers to improve the chemical reaction mechanism [24]. To give a

  13. MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

    Science.gov (United States)

    Son, S. W.; Lim, Y.; Kim, D.

    2017-12-01

    The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

  14. Effect of Dimethyl Ether Mixing on Soot Size Distribution in Premixed Ethylene Flame

    KAUST Repository

    Li, Zepeng

    2016-04-21

    As a byproduct of incomplete combustion, soot attracts increasing attentions as extensive researches exploring serious health and environmental effects from soot particles. Soot emission reduction requires a comprehensive understanding of the mechanism for polycyclic aromatic hydrocarbons and of soot formation and aging processes. Therefore, advanced experimental techniques and numerical simulations have been conducted to investigate this procedure. In order to investigate the effects of dimethyl ether (DME) mixing on soot particle size distribution functions (PSDFs), DME was mixed in premixed ethylene/oxygen/argon at flames at the equivalence ratio of 2.0 with a range of mixing ratio from 0% to 30% of the total carbon fed. Two series of atmospheric pressure flames were tested in which cold gas velocity was varied to obtain different flame temperatures. The evolution of PSDFs along the centerline of the flame was determined by burner stabilized stagnation probe and scanning mobility particle sizer (SMPS) techniques, yielding the PSDFs for various separation distances above the burner surface. Meanwhile, the flame temperature profiles were carefully measured by a thermocouple and the comparison to that of simulated laminar premixed burner-stabilized stagnation flame was satisfactory. Additionally, to understand the chemical role of DME mixing in soot properties, characterization measurements were conducted on soot samples using thermo-gravimetric analysis (TGA) and elemental analysis (EA). Results of the evolution of PSDFs and soot volume fraction showed that adding DME into ethylene flame could reduce soot yield significantly. The addition of DME led to the decrease of both the soot nucleation rate and the particle mass growth rate. To explain the possible mechanism for the observation, numerical simulations were performed. Although DME addition resulted in the slight increase of methyl radicals from pyrolysis, the decrease in acetylene and propargyl radicals

  15. The effect of mineral dust and soot aerosols on ice microphysics near the foothills of the Himalayas: A numerical investigation

    Science.gov (United States)

    Hazra, Anupam; Padmakumari, B.; Maheskumar, R. S.; Chen, Jen-Ping

    2016-05-01

    This study investigates the influence of different ice nuclei (IN) species and their number concentrations on cloud ice production. The numerical simulation with different species of ice nuclei is investigated using an explicit bulk-water microphysical scheme in a Mesoscale Meteorological Model version 5 (MM5). The species dependent ice nucleation parameterization that is based on the classical nucleation theory has been implemented into the model. The IN species considered include dust and soot with two different concentrations (Low and High). The simulated cloud microphysical properties like droplet number concentration and droplet effective radii as well as macro-properties (equivalent potential temperature and relative humidity) are comparable with aircraft observations. When higher dust IN concentrations are considered, the simulation results showed good agreement with the cloud ice and cloud water mixing ratio from aircraft measurements during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. Relative importance of IN species is shown as compared to the homogeneous freezing nucleation process. The tendency of cloud ice production rates is also analyzed and found that dust IN is more efficient in producing cloud ice when compared to soot IN. The dust IN with high concentration can produce more surface precipitation than soot IN at the same concentration. This study highlights the need to improve the ice nucleation parameterization in numerical models.

  16. Effects of Fuel Quantity on Soot Formation Process for Biomass-Based Renewable Diesel Fuel Combustion

    KAUST Repository

    Jing, Wei

    2016-12-01

    Soot formation process was investigated for biomass-based renewable diesel fuel, such as biomass to liquid (BTL), and conventional diesel combustion under varied fuel quantities injected into a constant volume combustion chamber. Soot measurement was implemented by two-color pyrometry under quiescent type diesel engine conditions (1000 K and 21% O2 concentration). Different fuel quantities, which correspond to different injection widths from 0.5 ms to 2 ms under constant injection pressure (1000 bar), were used to simulate different loads in engines. For a given fuel, soot temperature and KL factor show a different trend at initial stage for different fuel quantities, where a higher soot temperature can be found in a small fuel quantity case but a higher KL factor is observed in a large fuel quantity case generally. Another difference occurs at the end of combustion due to the termination of fuel injection. Additionally, BTL flame has a lower soot temperature, especially under a larger fuel quantity (2 ms injection width). Meanwhile, average soot level is lower for BTL flame, especially under a lower fuel quantity (0.5 ms injection width). BTL shows an overall low sooting behavior with low soot temperature compared to diesel, however, trade-off between soot level and soot temperature needs to be carefully selected when different loads are used.

  17. Butterfly, Recurrence, and Predictability in Lorenz Models

    Science.gov (United States)

    Shen, B. W.

    2017-12-01

    Over the span of 50 years, the original three-dimensional Lorenz model (3DLM; Lorenz,1963) and its high-dimensional versions (e.g., Shen 2014a and references therein) have been used for improving our understanding of the predictability of weather and climate with a focus on chaotic responses. Although the Lorenz studies focus on nonlinear processes and chaotic dynamics, people often apply a "linear" conceptual model to understand the nonlinear processes in the 3DLM. In this talk, we present examples to illustrate the common misunderstandings regarding butterfly effect and discuss the importance of solutions' recurrence and boundedness in the 3DLM and high-dimensional LMs. The first example is discussed with the following folklore that has been widely used as an analogy of the butterfly effect: "For want of a nail, the shoe was lost.For want of a shoe, the horse was lost.For want of a horse, the rider was lost.For want of a rider, the battle was lost.For want of a battle, the kingdom was lost.And all for the want of a horseshoe nail."However, in 2008, Prof. Lorenz stated that he did not feel that this verse described true chaos but that it better illustrated the simpler phenomenon of instability; and that the verse implicitly suggests that subsequent small events will not reverse the outcome (Lorenz, 2008). Lorenz's comments suggest that the verse neither describes negative (nonlinear) feedback nor indicates recurrence, the latter of which is required for the appearance of a butterfly pattern. The second example is to illustrate that the divergence of two nearby trajectories should be bounded and recurrent, as shown in Figure 1. Furthermore, we will discuss how high-dimensional LMs were derived to illustrate (1) negative nonlinear feedback that stabilizes the system within the five- and seven-dimensional LMs (5D and 7D LMs; Shen 2014a; 2015a; 2016); (2) positive nonlinear feedback that destabilizes the system within the 6D and 8D LMs (Shen 2015b; 2017); and (3

  18. Auditing predictive models : a case study in crop growth

    NARCIS (Netherlands)

    Metselaar, K.

    1999-01-01

    Methods were developed to assess and quantify the predictive quality of simulation models, with the intent to contribute to evaluation of model studies by non-scientists. In a case study, two models of different complexity, LINTUL and SUCROS87, were used to predict yield of forage maize

  19. Models for predicting compressive strength and water absorption of ...

    African Journals Online (AJOL)

    This work presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using augmented Scheffe's simplex lattice design. The statistical models developed can predict the mix proportion that will yield the desired property. The models were tested for lack of ...

  20. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  1. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  2. Impacts of fuel formulation and engine operating parameters on the nanostructure and reactivity of diesel soot

    Science.gov (United States)

    Yehliu, Kuen

    This study focuses on the impacts of fuel formulations on the reactivity and nanostructure of diesel soot. A 2.5L, 4-cylinder, turbocharged, common rail, direct injection light-duty diesel engine was used in generating soot samples. The impacts of engine operating modes and the start of combustion on soot reactivity were investigated first. Based on preliminary investigations, a test condition of 2400 rpm and 64 Nm, with single and split injection strategies, was chosen for studying the impacts of fuel formulation on the characteristics of diesel soot. Three test fuels were used: an ultra low sulfur diesel fuel (BP15), a pure soybean methyl-ester (B100), and a synthetic Fischer-Tropsch fuel (FT) produced in a gas-to-liquid process. The start of injection (SOI) and fuel rail pressures were adjusted such that the three test fuels have similar combustion phasing, thereby facilitating comparisons between soots from the different fuels. Soot reactivity was investigated by thermogravimetric analysis (TGA). According to TGA, B100 soot exhibits the fastest oxidation on a mass basis followed by BP15 and FT derived soots in order of apparent rate constant. X-ray photoelectron spectroscopy (XPS) indicates no relation between the surface oxygen content and the soot reactivity. Crystalline information for the soot samples was obtained using X-ray diffraction (XRD). The basal plane diameter obtained from XRD was inversely related to the apparent rate constants for soot oxidation. For comparison, high resolution transmission electron microscopy (HRTEM) provided images of the graphene layers. Quantitative image analysis proceeded by a custom algorithm. B100 derived soot possessed the shortest mean fringe length and greatest mean fringe tortuosity. This suggests soot (nano)structural disorder correlates with a faster oxidation rate. Such results are in agreement with the X-ray analysis, as the observed fringe length is a measure of basal plane diameter. Moreover the relation

  3. Accurate and dynamic predictive model for better prediction in medicine and healthcare.

    Science.gov (United States)

    Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

    2018-05-01

    Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

  4. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

  5. Testing the predictive power of nuclear mass models

    International Nuclear Information System (INIS)

    Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

    2008-01-01

    A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

  6. From Predictive Models to Instructional Policies

    Science.gov (United States)

    Rollinson, Joseph; Brunskill, Emma

    2015-01-01

    At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

  7. Soot in the atmosphere and snow surface of Antarctica

    International Nuclear Information System (INIS)

    Warren, S.G.; Clarke, A.D.

    1990-01-01

    Samples of snow collected near the south pole during January and February 1986 were analyzed for the presence of light-absorbing particles by passing the melted snow through a nuclepore filter. Transmission of light through the filter showed that snow far from the station contains the equivalent of 0.1-0.3 ng of carbon per gram of snow (ng/g). Samples of ambient air were filtered and found to contain about 1-2 ng of carbon per kilogram of air, giving a scavenging ratio of about 150. The snow downwind of the station exhibited a well-defined plume of soot due to the burning of diesel fuel, but even in the center of the plume 1 km downwind, the soot concentration was only 3 ng/g, too small to affect snow albedo significantly. Measurements of snow albedo near large inland stations are therefore probably representative of their surrounding regions

  8. Single Particle Soot Photometer intercomparison at the AIDA chamber

    Directory of Open Access Journals (Sweden)

    M. Laborde

    2012-12-01

    Full Text Available Soot particles, consisting of black carbon (BC, organic carbon (OC, inorganic salts, and trace elements, are emitted into the atmosphere during incomplete combustion. Accurate measurements of atmospheric BC are important as BC particles cause adverse health effects and impact the climate.

    Unfortunately, the accurate measurement of the properties and mass concentrations of BC particles remains difficult. The Single Particle Soot Photometer (SP2 can contribute to improving this situation by measuring the mass of refractory BC in individual particles as well as its mixing state.

    Here, the results of the first detailed SP2 intercomparison, involving 6 SP2s from 6 different research groups, are presented, including the most evolved data products that can presently be calculated from SP2 measurements.

    It was shown that a detection efficiency of almost 100% down to 1 fg BC per particle can readily be achieved, and that this limit can be pushed down to ∼0.2 fg BC with optimal SP2 setup. Number and mass size distributions of BC cores agreed within ±5% and ±10%, respectively, in between the SP2s, with larger deviations in the range below 1 fg BC.

    The accuracy of the SP2's mass concentration measurement depends on the calibration material chosen. The SP2 has previously been shown to be equally sensitive to fullerene soot and ambient BC from sources where fossil fuel was dominant and less sensitive to fullerene soot than to Aquadag. Fullerene soot was therefore chosen as the standard calibration material by the SP2 user community; however, many data sets rely solely on Aquadag calibration measurements. The difference in SP2 sensitivity was found to be almost equal (fullerene soot to Aquadag response ratio of ∼0.75 at 8.9 fg BC for all SP2s. This allows the calculation of a fullerene soot equivalent calibration curve from a measured Aquadag calibration, when no fullerene soot calibration is available. It could be

  9. Application of the direct simulation Monte Carlo method to nanoscale heat transfer between a soot particle and the surrounding gas

    International Nuclear Information System (INIS)

    Yang, M.; Liu, F.; Smallwood, G.J.

    2004-01-01

    Laser-Induced Incandescence (LII) technique has been widely used to measure soot volume fraction and primary particle size in flames and engine exhaust. Currently there is lack of quantitative understanding of the shielding effect of aggregated soot particles on its conduction heat loss rate to the surrounding gas. The conventional approach for this problem would be the application of the Monte Carlo (MC) method. This method is based on simulation of the trajectories of individual molecules and calculation of the heat transfer at each of the molecule/molecule collisions and the molecule/particle collisions. As the first step toward calculating the heat transfer between a soot aggregate and the surrounding gas, the Direct Simulation Monte Carlo (DSMC) method was used in this study to calculate the heat transfer rate between a single spherical aerosol particle and its cooler surrounding gas under different conditions of temperature, pressure, and the accommodation coefficient. A well-defined and simple hard sphere model was adopted to describe molecule/molecule elastic collisions. A combination of the specular reflection and completely diffuse reflection model was used to consider molecule/particle collisions. The results obtained by DSMC are in good agreement with the known analytical solution of heat transfer rate for an isolated, motionless sphere in the free-molecular regime. Further the DSMC method was applied to calculate the heat transfer in the transition regime. Our present DSMC results agree very well with published DSMC data. (author)

  10. Lanthanum-promoted copper-based hydrotalcites derived mixed oxides for NO{sub x} adsorption, soot combustion and simultaneous NO{sub x}-soot removal

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zhongpeng [School of Resources and Environment, University of Jinan, 106 Jiwei Road, Jinan 250022 (China); Inorganic Chemistry Laboratory, University of Oxford, South Parks Road, Oxford OX1 3QR (United Kingdom); Yan, Xiaotong; Bi, Xinlin; Wang, Liguo [School of Resources and Environment, University of Jinan, 106 Jiwei Road, Jinan 250022 (China); Zhang, Zhaoliang, E-mail: chm_zhangzl@ujn.edu.cn [School of Resources and Environment, University of Jinan, 106 Jiwei Road, Jinan 250022 (China); Jiang, Zheng; Xiao, Tiancun [Inorganic Chemistry Laboratory, University of Oxford, South Parks Road, Oxford OX1 3QR (United Kingdom); Umar, Ahmad [Department of Chemistry, College of Science and Arts, Najran University, P.O. Box 1988, Najran 11001 (Saudi Arabia); Promising Centre for Sensors and Electronic Devices (PCSED), Najran University, P.O. Box 1988, Najran 11001 (Saudi Arabia); Wang, Qiang, E-mail: qiang.wang.ox@gmail.com [College of Environmental Science and Engineering, Beijing Forestry University, 35 Tsinghua East Road, Beijing 100083 (China)

    2014-03-01

    Graphical abstract: - Highlights: • The addition of La in Cu-based oxides increased the types of active oxygen. • NO{sub x} adsorption, soot oxidation and simultaneous NO{sub x}-soot removal were enhanced. • The possible catalytic mechanism was studied via in situ FTIR analysis. • Soot oxidation was promoted by the NO{sub 2} intermediate. - Abstract: La-promoted Cu-based hydrotalcites derived mixed oxides were prepared and their catalytic activities for NO{sub x} adsorption, soot oxidation, and simultaneous NO{sub x}-soot removal were investigated. The catalysts were characterized by XRD, DTG, BET, FTIR, H2-TPR, TPD and TPO techniques. The oxides catalysts exhibited mesoporous properties with specific surface area of 45–160 m{sup 2}/g. The incorporation of La and Cu decreased the amount of basic sites due to the large decrease in surface areas. Under O{sub 2} atmosphere, La incorporation is dominant for soot oxidation activity, while Cu favors high selectivity to CO{sub 2} formation. A synergetic effect between La and Cu for catalyzed soot oxidation lies in the improved redox property and suitable basicity. The presence of NO in O{sub 2} significantly promoted soot oxidation on the catalysts with the ignition temperature decreased to about 300 °C. In O{sub 2}/NO atmosphere, NO{sub 2} acts as an intermediate which oxidizes soot to CO{sub 2} at a lower temperature with itself reduced to NO or N{sub 2}, contributing to the high catalytic performance in simultaneous removal of NO{sub x} and soot.

  11. Effect of relative humidity on soot - secondary organic aerosol mixing: A case study from the Soot Aerosol Aging Study (PNNL-SAAS)

    Science.gov (United States)

    Sharma, N.; China, S.; Zaveri, R. A.; Shilling, J. E.; Pekour, M. S.; Liu, S.; Aiken, A. C.; Dubey, M. K.; Wilson, J. M.; Zelenyuk, A.; OBrien, R. E.; Moffet, R.; Gilles, M. K.; Gourihar, K.; Chand, D.; Sedlacek, A. J., III; Subramanian, R.; Onasch, T. B.; Laskin, A.; Mazzoleni, C.

    2014-12-01

    Atmospheric processing of fresh soot particles emitted by anthropogenic as well as natural sources alters their physical and chemical properties. For example, fresh and aged soot particles interact differently with incident solar radiation, resulting in different overall radiation budgets. Varying atmospheric chemical and meteorological conditions can result in complex soot mixing states. The Soot Aerosol Aging Study (SAAS) was conducted at the Pacific Northwest National Laboratory in November 2013 and January 2014 as a step towards understanding the evolution of mixing state of soot and its impact on climate-relevant properties. Aging experiments on diesel soot were carried out in a controlled laboratory chamber, and the effects of condensation and coagulation processes were systematically explored in separate sets of experiments. In addition to online measurement of aerosol properties, aerosol samples were collected for offline single particle analysis to investigate the evolution of the morphology, elemental composition and fine structure of sample particles from different experiments. Condensation experiments focused on the formation of α-pinene secondary organic aerosol on diesel soot aerosol seeds. Experiments were conducted to study the aging of soot under dry (RH < 2%) and humid conditions (RH ~ 80%). We present an analysis of the morphology of soot, its evolution, and its correlation with optical properties, as the condensation of α-pinene SOA is carried out for the two different RH conditions. The analysis was performed by using scanning electron microscopy, transmission electron microscopy, scanning transmission x-ray microscopy and atomic force microscopy for single particle characterization. In addition, particle size, mass, composition, shape, and density were characterized in-situ, as a function of organics condensed on soot seeds, using single particle mass spectrometer.

  12. The Complexity of Developmental Predictions from Dual Process Models

    Science.gov (United States)

    Stanovich, Keith E.; West, Richard F.; Toplak, Maggie E.

    2011-01-01

    Drawing developmental predictions from dual-process theories is more complex than is commonly realized. Overly simplified predictions drawn from such models may lead to premature rejection of the dual process approach as one of many tools for understanding cognitive development. Misleading predictions can be avoided by paying attention to several…

  13. Sweat loss prediction using a multi-model approach.

    Science.gov (United States)

    Xu, Xiaojiang; Santee, William R

    2011-07-01

    A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

  14. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  15. Effects of morphology and wavelength on the measurement accuracy of soot volume fraction by laser extinction

    Science.gov (United States)

    Wang, Ya-fei; Huang, Qun-xing; Wang, Fei; Chi, Yong; Yan, Jian-hua

    2018-01-01

    A novel method to evaluate the quantitative effects of soot morphology and incident wavelength on the measurement accuracy of soot volume fraction, by the laser extinction (LE) technique is proposed in this paper. The results indicate that the traditional LE technique would overestimate soot volume fraction if the effects of morphology and wavelength are not considered. Before the agglomeration of isolated soot primary particles, the overestimation of the LE technique is in the range of 2-20%, and rises with increasing primary particle diameter and with decreasing incident wavelength. When isolated primary particles are agglomerated into fractal soot aggregates, the overestimation would exceed 30%, and rise with increasing primary particle number per soot aggregate, fractal dimension and fractal prefactor and with decreasing incident wavelength to a maximum value of 55%. Finally, based on these results above, the existing formula of the LE technique gets modified, and the modification factor is 0.65-0.77.

  16. Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines

    Science.gov (United States)

    Feulner, Markus; Hagen, Gunter; Müller, Andreas; Schott, Andreas; Zöllner, Christian; Brüggemann, Dieter; Moos, Ralf

    2015-01-01

    Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the “engine-out” soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS) agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content. PMID:26580621

  17. Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines.

    Science.gov (United States)

    Feulner, Markus; Hagen, Gunter; Müller, Andreas; Schott, Andreas; Zöllner, Christian; Brüggemann, Dieter; Moos, Ralf

    2015-11-13

    Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the "engine-out" soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS) agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content.

  18. Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines

    Directory of Open Access Journals (Sweden)

    Markus Feulner

    2015-11-01

    Full Text Available Soot sensors are required for on-board diagnostics (OBD of automotive diesel particulate filters (DPF to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the “engine-out” soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content.

  19. Modeling of Complex Life Cycle Prediction Based on Cell Division

    Directory of Open Access Journals (Sweden)

    Fucheng Zhang

    2017-01-01

    Full Text Available Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.

  20. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  1. Predictive modeling and reducing cyclic variability in autoignition engines

    Science.gov (United States)

    Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

    2016-08-30

    Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

  2. Dynamic Simulation of Human Gait Model With Predictive Capability.

    Science.gov (United States)

    Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

    2018-03-01

    In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

  3. Intelligent soot blowing for boilers co-firing waste and biofuel; Behovsstyrd sotblaasning foer bio- och avfallseldade pannor - inventering och teknikval

    Energy Technology Data Exchange (ETDEWEB)

    Kjoerk, Anders [S.E.P. Scandinavian Energy Project AB, Goeteborg (Sweden)

    2003-11-01

    To achieve optimum boiler operation and performance it is necessary to control the cleanliness and limit the fouling of the heat transfer surfaces. Historically, the heating surfaces in boilers firing biomass and waste are cleaned by steamblowing soot blowers on scheduled time-based and/or parameter-based intervals or by mechanical methods. With the advent of fuel switching strategies and use of mixed-in industrial waste, the control of heating surface cleanliness has become even more crucial for these boilers. Scheduled and/or parameter based approaches do not easily address operational changes. As plant operators push to achieve greater efficiency and performance from their boilers, the ability to more effectively optimize cleaning cycles has become increasingly important. If soot blowing is done only when and where it is required rather than at set intervals, unit performance can be maintained with reduced blowing, which saves steam. Two philosophical approaches toward intelligent soot blowing are currently being applied in the industry. One incorporates heat flux monitors to gather real-time heat transfer data to determine which areas of the furnace need cleaning. The other uses indirect temperature and pressure data to infer locations where soot blowing is needed, and is mainly applied for controlling soot blowers in the superheater and economiser area. The heat flux monitors are so fare used for control of the furnace wall blowers. A system using temperature, pressure and flow data does not require much additional instrumentation as compared with what is available on a standard boiler. However the blower control system must be capable of operating blowers on an individual basis. For advanced options it should also be possible to adjust the speed of the soot blower and the steam pressure. The control program could be more or less advanced but the ability to model heating surfaces and determine real-time cleanliness is crucial for an intelligent soot blowing

  4. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  5. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  6. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  7. Ocean wave prediction using numerical and neural network models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...

  8. A mathematical model for predicting earthquake occurrence ...

    African Journals Online (AJOL)

    We consider the continental crust under damage. We use the observed results of microseism in many seismic stations of the world which was established to study the time series of the activities of the continental crust with a view to predicting possible time of occurrence of earthquake. We consider microseism time series ...

  9. Model for predicting the injury severity score.

    Science.gov (United States)

    Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

    2015-07-01

    To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

  10. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  11. An assessment of radiation modeling strategies in simulations of laminar to transitional, oxy-methane, diffusion flames

    International Nuclear Information System (INIS)

    Abdul-Sater, Hassan; Krishnamoorthy, Gautham

    2013-01-01

    Twenty four, laboratory scale, laminar to transitional, diffusion oxy-methane flames were simulated employing different radiation modeling options and their predictions compared against experimental measurements of: temperature, flame length and radiant fraction. The models employed were: gray and non-gray formulations of a recently proposed weighted-sum-of-gray gas model, non-adiabatic extension of the equilibrium based mixture fraction model and investigations into the effects of: the thermal boundary conditions, soot and turbulence radiation interactions (TRI). Predictions of gas, wall temperatures and flame lengths were in good agreement with experimental measurements. Flame lengths determined through the axial profiles of OH confirmed with the experimental trends by increasing with increase in fuel-inlet Reynolds numbers and decreasing with the increase in O 2 composition in oxidizer. The temperature and flame length predictions were not sensitive to the radiative property model employed. There were significant variations between the gray and non-gray model radiant fraction predictions with the variations in general increasing with decrease in Reynolds numbers possibly attributed to shorter flames and steeper temperature gradients. The inclusion of soot model and TRI model did not affect our predictions as a result of low soot volume fractions and the radiation emission enhancement to the temperature fluctuations being localized to the flame sheet. -- Highlights: • Twenty four, lab scale, laminar to transitional, diffusion, oxy-methane flames were simulated. • Equilibrium model adequately predicted the temperature and flame lengths. • The experimental trends in radiant fractions were replicated. • Gray and non-gray model differences in radiant fractions were amplified at low Re. • Inclusion of soot and TRI models did not affect our predictions

  12. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  13. A predictive pilot model for STOL aircraft landing

    Science.gov (United States)

    Kleinman, D. L.; Killingsworth, W. R.

    1974-01-01

    An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

  14. Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

    Science.gov (United States)

    Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

    2016-01-01

    Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

  15. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

  16. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  17. Testing and analysis of internal hardwood log defect prediction models

    Science.gov (United States)

    R. Edward Thomas

    2011-01-01

    The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

  18. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  19. Models for predicting fuel consumption in sagebrush-dominated ecosystems

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

  20. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  1. A new, accurate predictive model for incident hypertension

    DEFF Research Database (Denmark)

    Völzke, Henry; Fung, Glenn; Ittermann, Till

    2013-01-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....

  2. Prediction models for successful external cephalic version: a systematic review

    NARCIS (Netherlands)

    Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M.; Molkenboer, Jan F. M.; van der Post, Joris A. M.; Mol, Ben W.; Kok, Marjolein

    2015-01-01

    To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015.

  3. Hidden Markov Model for quantitative prediction of snowfall

    Indian Academy of Sciences (India)

    A Hidden Markov Model (HMM) has been developed for prediction of quantitative snowfall in Pir-Panjal and Great Himalayan mountain ranges of Indian Himalaya. The model predicts snowfall for two days in advance using daily recorded nine meteorological variables of past 20 winters from 1992–2012. There are six ...

  4. Mathematical model for dissolved oxygen prediction in Cirata ...

    African Journals Online (AJOL)

    This paper presents the implementation and performance of mathematical model to predict theconcentration of dissolved oxygen in Cirata Reservoir, West Java by using Artificial Neural Network (ANN). The simulation program was created using Visual Studio 2012 C# software with ANN model implemented in it. Prediction ...

  5. Econometric models for predicting confusion crop ratios

    Science.gov (United States)

    Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)

    1979-01-01

    Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

  6. Isothermal Kinetics of Diesel Soot Oxidation over La0.7K0.3ZnOy Catalysts

    Directory of Open Access Journals (Sweden)

    Ram Prasad

    2014-10-01

    Full Text Available This paper describes the kinetics of catalytic oxidation of diesel soot with air under isothermal conditions (320-350 oC. Isothermal kinetics data were collected in a mini-semi-batch reactor. Experiments were performed over the best selected catalyst composition La0.7K0.3ZnOy prepared by sol-gel method. Characterization of the catalyst by XRD and FTIR confirmed that La1-xKxZnOy did not exhibit perovskite phase but formed mixed metal oxides. 110 mg of the catalyst-soot mixture in tight contact (10:1 ratio was taken in order to determine the kinetic model, activation energy and Arrhenius constant of the oxidation reaction under the high air flow rate assuming pseudo first order reaction. The activation energy and Arrhenius constant were found to be 138 kJ/mol and 6.46x1010 min-1, respectively. © 2014 BCREC UNDIP. All rights reservedReceived: 26th April 2014; Revised: 27th May 2014; Accepted: 28th June 2014How to Cite: Prasad, R., Kumar, A., Mishra, A. (2014. Isothermal Kinetics of Diesel Soot Oxidation over La0.7K0.3ZnOy Catalysts. Bulletin of Chemical Reaction Engineering & Catalysis, 9(3: 192-200. (doi: 10.9767/bcrec.9.3.6773.192-200Permalink/DOI: http://dx.doi.org/10.9767/bcrec.9.3.6773.192-200

  7. PEEX Modelling Platform for Seamless Environmental Prediction

    Science.gov (United States)

    Baklanov, Alexander; Mahura, Alexander; Arnold, Stephen; Makkonen, Risto; Petäjä, Tuukka; Kerminen, Veli-Matti; Lappalainen, Hanna K.; Ezau, Igor; Nuterman, Roman; Zhang, Wen; Penenko, Alexey; Gordov, Evgeny; Zilitinkevich, Sergej; Kulmala, Markku

    2017-04-01

    The Pan-Eurasian EXperiment (PEEX) is a multidisciplinary, multi-scale research programme stared in 2012 and aimed at resolving the major uncertainties in Earth System Science and global sustainability issues concerning the Arctic and boreal Northern Eurasian regions and in China. Such challenges include climate change, air quality, biodiversity loss, chemicalization, food supply, and the use of natural resources by mining, industry, energy production and transport. The research infrastructure introduces the current state of the art modeling platform and observation systems in the Pan-Eurasian region and presents the future baselines for the coherent and coordinated research infrastructures in the PEEX domain. The PEEX modeling Platform is characterized by a complex seamless integrated Earth System Modeling (ESM) approach, in combination with specific models of different processes and elements of the system, acting on different temporal and spatial scales. The ensemble approach is taken to the integration of modeling results from different models, participants and countries. PEEX utilizes the full potential of a hierarchy of models: scenario analysis, inverse modeling, and modeling based on measurement needs and processes. The models are validated and constrained by available in-situ and remote sensing data of various spatial and temporal scales using data assimilation and top-down modeling. The analyses of the anticipated large volumes of data produced by available models and sensors will be supported by a dedicated virtual research environment developed for these purposes.

  8. Impact of modellers' decisions on hydrological a priori predictions

    Science.gov (United States)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  9. Role of soot in the transport of chlorine in hydrocarbon-air diffusion flames

    International Nuclear Information System (INIS)

    Venkatesh, S.; Saito, K.; Stencel, J.M.; Majidi, V.; Owens, M.

    1991-01-01

    Soot is an inevitable product of incomplete combustion in many practical combustion systems such as automobiles, incinerators and furnaces. Recent studies on chlorinated hydrocarbon combustion have shown that soot and other praticulates (eg. fly ash) play an important role in secondary reactions leading to the formation of chlorine substituted polyaromatic hydrocarbons (PAHs). In order to attain very high destruction efficiencies the fundamental chemical and physical processes that are associated with combustion, and post-combustion cleanup must be well understood. In order to understand the effect of chlorine on the soot formed in a combustion system, fundamental studies using a coflow laminar hydrocarbon-air diffusion flame have been carried out. Phenomenological studies have revealed the effect of chlorine on the visible structure of the flame. Soot inception activation energies were estimated for methane, ethane and ethylene diffusion flames for the case of with and without chlorine addition. No significant difference in the activation energy was estimated for either case. The effect of chlorine on the soot escape rate of an acetylene diffusion flame was estimated. The soot formed in these diffusion flames was analyzed for chlorine using scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS) and by laser induced plasma spectroscopy (LIPS). REsults from these techniques indicate the presence of chlorine in the soot formed. In this paper a chemical scheme to explain the chlorine found in the soot is proposed based on known theories of soot formation

  10. Comparative Study of Different Methods for Soot Sensing and Filter Monitoring in Diesel Exhausts

    Science.gov (United States)

    Feulner, Markus; Hagen, Gunter; Hottner, Kathrin; Redel, Sabrina; Müller, Andreas; Moos, Ralf

    2017-01-01

    Due to increasingly tighter emission limits for diesel and gasoline engines, especially concerning particulate matter emissions, particulate filters are becoming indispensable devices for exhaust gas after treatment. Thereby, for an efficient engine and filter control strategy and a cost-efficient filter design, reliable technologies to determine the soot load of the filters and to measure particulate matter concentrations in the exhaust gas during vehicle operation are highly needed. In this study, different approaches for soot sensing are compared. Measurements were conducted on a dynamometer diesel engine test bench with a diesel particulate filter (DPF). The DPF was monitored by a relatively new microwave-based approach. Simultaneously, a resistive type soot sensor and a Pegasor soot sensing device as a reference system measured the soot concentration exhaust upstream of the DPF. By changing engine parameters, different engine out soot emission rates were set. It was found that the microwave-based signal may not only indicate directly the filter loading, but by a time derivative, the engine out soot emission rate can be deduced. Furthermore, by integrating the measured particulate mass in the exhaust, the soot load of the filter can be determined. In summary, all systems coincide well within certain boundaries and the filter itself can act as a soot sensor. PMID:28218700

  11. Soot reduction under DC electric fields in counterflow non-premixed laminar ethylene flames

    KAUST Repository

    Park, Daegeun

    2014-04-23

    The effects of DC electric fields on non-premixed ethylene flames in a counterflow burner were studied experimentally with a focus on the reduction of soot particles. The experiment was conducted by connecting a high voltage terminal and a ground terminal to a lower (fuel) and upper (oxidizer) nozzle, respectively. We applied direct current (DC) potentials in a range of -5 kV < Vdc < 5 kV. Uniform electric fields were then generated in the gap between the two nozzles. The experimental conditions were selected to cover both soot formation (SF) and soot formation oxidation (SFO) flames. The flames subjected to the negative electric fields moved toward the fuel nozzle because of an ionic wind due to the Lorentz force acting on the positive ions in the flames. In addition, the yellow luminosity significantly decreased, indicating changes in the sooting characteristics. To analyze the sooting characteristics under the electric fields, planar laser induced incandescence (PLII) and fluorescence (PLIF) techniques were used to visualize the soot, polycyclic aromatic hydrocarbons (PAHs), and OH radicals. The sooting limits in terms of the fuel and oxygen mole fractions were measured. No substantial soot formation due to the effects of the DC electric fields for the tested range of voltages and reactant mole fractions could be identified. The detailed flame behaviors and sooting characteristics under the DC electric fields are discussed. Copyright © Taylor & Francis Group, LLC.

  12. A computational study of soot formation in opposed-flow diffusion flame interacting with vortices

    KAUST Repository

    Selvaraj, Prabhu

    2017-01-05

    The flame-vortex interaction enables the study of basic phenomena that control the coupling between combustion and turbulence. Employing a gas phase reaction mechanism considering polycyclic aromatic hydrocarbons (PAH), a two dimensional counterflow ethylene-air flame is simulated. A reduced mechanism with PAH pathways that includes until coronene and method of moments with interpolative closure (MOMIC) has been employed to calculate the soot characteristics. Interaction of sooting flame with a prescribed decaying random velocity field is being investigated. Counterflow nonpremixed flames at low strain rate sooting conditions are considered. Effects of vortices are studied on the flame structures and its sensitivity on the soot formation characteristics. As the vortex rolls up the flame, integrated soot volume fraction is found to be larger for the air-side vortex. A detailed analysis on the flame structure and its influence on the formation of soot were carried out. The results indicate that the larger PAH species contributes to the soot formation in the airside perturbation regimes, whereas the soot formation is dominated by the soot transport in fuel-side perturbation.

  13. Source identification of individual soot agglomerates in Arctic air by transmission electron microscopy

    Science.gov (United States)

    Weinbruch, S.; Benker, N.; Kandler, K.; Schütze, K.; Kling, K.; Berlinger, B.; Thomassen, Y.; Drotikova, T.; Kallenborn, R.

    2018-01-01

    Individual soot agglomerates collected at four different locations on the Arctic archipelago Svalbard (Norway) were characterised by transmission electron microscopy and energy-dispersive X-ray microanalysis. For source identification of the ambient soot agglomerates, samples from different local sources (coal burning power plants in Longyearbyen and Barentsburg, diesel and oil burning for power generation in Sveagruva and Ny Ålesund, cruise ship) as well as from other sources which may contribute to Arctic soot concentrations (biomass burning, aircraft emissions, diesel engines) were investigated. Diameter and graphene sheet separation distance of soot primary particles were found to be highly variable within each source and are not suited for source identification. In contrast, concentrations of the minor elements Si, P, K, Ca and Fe showed significant differences which can be used for source attribution. The presence/absence of externally mixed particle groups (fly ashes, tar balls, mercury particles) gives additional hints about the soot sources. Biomass/wood burning, ship emissions and coal burning in Barentsburg can be excluded as major source for ambient soot at Svalbard. The coal power plant in Longyearbyen is most likely a major source of soot in the settlement of Longyearbyen but does not contribute significantly to soot collected at the Global Atmosphere Watch station Zeppelin Mountain near Ny Ålesund. The most probable soot sources at Svalbard are aircraft emissions and diesel exhaust as well as long range transport of coal burning emissions.

  14. Comparative Study of Different Methods for Soot Sensing and Filter Monitoring in Diesel Exhausts.

    Science.gov (United States)

    Feulner, Markus; Hagen, Gunter; Hottner, Kathrin; Redel, Sabrina; Müller, Andreas; Moos, Ralf

    2017-02-18

    Due to increasingly tighter emission limits for diesel and gasoline engines, especially concerning particulate matter emissions, particulate filters are becoming indispensable devices for exhaust gas after treatment. Thereby, for an efficient engine and filter control strategy and a cost-efficient filter design, reliable technologies to determine the soot load of the filters and to measure particulate matter concentrations in the exhaust gas during vehicle operation are highly needed. In this study, different approaches for soot sensing are compared. Measurements were conducted on a dynamometer diesel engine test bench with a diesel particulate filter (DPF). The DPF was monitored by a relatively new microwave-based approach. Simultaneously, a resistive type soot sensor and a Pegasor soot sensing device as a reference system measured the soot concentration exhaust upstream of the DPF. By changing engine parameters, different engine out soot emission rates were set. It was found that the microwave-based signal may not only indicate directly the filter loading, but by a time derivative, the engine out soot emission rate can be deduced. Furthermore, by integrating the measured particulate mass in the exhaust, the soot load of the filter can be determined. In summary, all systems coincide well within certain boundaries and the filter itself can act as a soot sensor.

  15. Comparative Study of Different Methods for Soot Sensing and Filter Monitoring in Diesel Exhausts

    Directory of Open Access Journals (Sweden)

    Markus Feulner

    2017-02-01

    Full Text Available Due to increasingly tighter emission limits for diesel and gasoline engines, especially concerning particulate matter emissions, particulate filters are becoming indispensable devices for exhaust gas after treatment. Thereby, for an efficient engine and filter control strategy and a cost-efficient filter design, reliable technologies to determine the soot load of the filters and to measure particulate matter concentrations in the exhaust gas during vehicle operation are highly needed. In this study, different approaches for soot sensing are compared. Measurements were conducted on a dynamometer diesel engine test bench with a diesel particulate filter (DPF. The DPF was monitored by a relatively new microwave-based approach. Simultaneously, a resistive type soot sensor and a Pegasor soot sensing device as a reference system measured the soot concentration exhaust upstream of the DPF. By changing engine parameters, different engine out soot emission rates were set. It was found that the microwave-based signal may not only indicate directly the filter loading, but by a time derivative, the engine out soot emission rate can be deduced. Furthermore, by integrating the measured particulate mass in the exhaust, the soot load of the filter can be determined. In summary, all systems coincide well within certain boundaries and the filter itself can act as a soot sensor.

  16. Effect of Morphology and Composition on the Hygroscopicity of Soot Aerosols

    Science.gov (United States)

    Williams, L.; Slowik, J.; Davidovits, P.; Jayne, J.; Kolb, C.; Worsnop, D.; Rudich, Y.

    2003-12-01

    Freshly generated soot aerosols are initially hydrophobic and unlikely to act as cloud condensation nuclei (CCN). However, during combustion many low vapor pressure gas products are formed that may then condense on existing soot aerosols. Additionally, soot particles may acquire coatings as they age, such as acids, salts, and oxygenated organics. An understanding of this aging process and its effect on soot hygroscopicity is necessary to address the potential of soot to act as a CCN. The transformation of soot from hydrophobic to hydrophilic is the focus of this work. An aim here is to determine the minimum coating required for hygroscopic growth. Soot particles produced by combustion of mixtures of fuel and air are size selected by a Differential Mobility Analyzer (DMA) and entrained in a laminar flow passing through a flow tube. The size selected soot particles are mixed with a controlled amount of the gas phase precursors to produce the coatings to be studied. Initial studies are focused on coatings of H2SO4, NH4NO3, and selected organics. The number of particles per unit volume of air is counted by a Condensation Particle Counter (CPC) and the particles are isokinetically sampled into an Aerosol Mass Spectrometer (AMS). Two distinct types of soot aerosols have been observed depending on the type of fuel and air mixture. With soot produced by the combustion of propane and air, the AMS shows a polydisperse particle size distribution with aerodynamic diameters ranging from 100 nm to 400 nm. The aerodynamic diameter is linearly related to the DMA-determined mobility diameter with the product density x shape factor = 1.2. The organic molecules in this soot are mostly PAH compounds. However, when kerosene is added to the propane flame, the soot particle morphology and composition is strikingly altered. While the DMA shows an essentially unchanged mobility diameter distribution, in the range 100 nm to 400, aerodynamic particle diameter is constant at about 100 nm

  17. Effect of NO2 and water on the catalytic oxidation of soot

    DEFF Research Database (Denmark)

    Christensen, Jakob Munkholt; Grunwaldt, Jan-Dierk; Jensen, Anker Degn

    2017-01-01

    The influence of adding NO2 to 10 vol% O2/N2 on non-catalytic soot oxidation and soot oxidation in intimate or loose contact with a catalyst has been investigated. In non-catalytic soot oxidation the oxidation rate is increased significantly at lower temperatures by NO2. For soot oxidation in tig...... exhibited a volcano-curve dependence on the heat of oxygen chemisorption, and among the tested pure metals and oxides Cr2O3 was the most active catalyst. Further improvements were achieved with a FeaCrbOx binary oxide catalyst....

  18. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  19. NOx PREDICTION FOR FBC BOILERS USING EMPIRICAL MODELS

    Directory of Open Access Journals (Sweden)

    Jiří Štefanica

    2014-02-01

    Full Text Available Reliable prediction of NOx emissions can provide useful information for boiler design and fuel selection. Recently used kinetic prediction models for FBC boilers are overly complex and require large computing capacity. Even so, there are many uncertainties in the case of FBC boilers. An empirical modeling approach for NOx prediction has been used exclusively for PCC boilers. No reference is available for modifying this method for FBC conditions. This paper presents possible advantages of empirical modeling based prediction of NOx emissions for FBC boilers, together with a discussion of its limitations. Empirical models are reviewed, and are applied to operation data from FBC boilers used for combusting Czech lignite coal or coal-biomass mixtures. Modifications to the model are proposed in accordance with theoretical knowledge and prediction accuracy.

  20. Complex versus simple models: ion-channel cardiac toxicity prediction.

    Science.gov (United States)

    Mistry, Hitesh B

    2018-01-01

    There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B net was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B net model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  1. Complex versus simple models: ion-channel cardiac toxicity prediction

    Directory of Open Access Journals (Sweden)

    Hitesh B. Mistry

    2018-02-01

    Full Text Available There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the Bnet model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  2. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

    Science.gov (United States)

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

    2012-01-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  3. [Application of ARIMA model on prediction of malaria incidence].

    Science.gov (United States)

    Jing, Xia; Hua-Xun, Zhang; Wen, Lin; Su-Jian, Pei; Ling-Cong, Sun; Xiao-Rong, Dong; Mu-Min, Cao; Dong-Ni, Wu; Shunxiang, Cai

    2016-01-29

    To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA). SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation. The model of ARIMA (1, 1, 1) (1, 1, 0) 12 was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of the model. The prediction effect of the model was acceptable. The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

  4. Spectral reflectance of solar light from dirty snow: a simple theoretical model and its validation

    OpenAIRE

    A. Kokhanovsky

    2013-01-01

    A simple analytical equation for the snow albedo as the function of snow grain size, soot concentration, and soot mass absorption coefficient is presented. This simple equation can be used in climate models to assess the influence of snow pollution on snow albedo. It is shown that the squared logarithm of the albedo (in the visible) is directly proportional to the soot concentration. A new method of the determination of the soot mass absorption coefficient in snow is proposed. The equations d...

  5. Mobility Modelling through Trajectory Decomposition and Prediction

    OpenAIRE

    Faghihi, Farbod

    2017-01-01

    The ubiquity of mobile devices with positioning sensors make it possible to derive user's location at any time. However, constantly sensing the position in order to track the user's movement is not feasible, either due to the unavailability of sensors, or computational and storage burdens. In this thesis, we present and evaluate a novel approach for efficiently tracking user's movement trajectories using decomposition and prediction of trajectories. We facilitate tracking by taking advantage ...

  6. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  7. Predicting birth weight with conditionally linear transformation models.

    Science.gov (United States)

    Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

    2016-12-01

    Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

  8. Prediction of hourly solar radiation with multi-model framework

    International Nuclear Information System (INIS)

    Wu, Ji; Chan, Chee Keong

    2013-01-01

    Highlights: • A novel approach to predict solar radiation through the use of clustering paradigms. • Development of prediction models based on the intrinsic pattern observed in each cluster. • Prediction based on proper clustering and selection of model on current time provides better results than other methods. • Experiments were conducted on actual solar radiation data obtained from a weather station in Singapore. - Abstract: In this paper, a novel multi-model prediction framework for prediction of solar radiation is proposed. The framework started with the assumption that there are several patterns embedded in the solar radiation series. To extract the underlying pattern, the solar radiation series is first segmented into smaller subsequences, and the subsequences are further grouped into different clusters. For each cluster, an appropriate prediction model is trained. Hence a procedure for pattern identification is developed to identify the proper pattern that fits the current period. Based on this pattern, the corresponding prediction model is applied to obtain the prediction value. The prediction result of the proposed framework is then compared to other techniques. It is shown that the proposed framework provides superior performance as compared to others

  9. Heterogeneous reaction of SO2 with soot: The roles of relative humidity and surface composition of soot in surface sulfate formation

    Science.gov (United States)

    Zhao, Yan; Liu, Yongchun; Ma, Jinzhu; Ma, Qingxin; He, Hong

    2017-03-01

    The conversion of SO2 to sulfates on the surface of soot is still poorly understood. Soot samples with different fractions of unsaturated hydrocarbons and oxygen-containing groups were prepared by combusting n-hexane under well-controlled conditions. The heterogeneous reaction of SO2 with soot was investigated using in situ attenuated total internal reflection infrared (ATR-IR) spectroscopy, ion chromatography (IC) and a flow tube reactor at the ambient pressure and relative humidity (RH). Water promoted SO2 adsorption and sulfate formation at the RH range from 6% to 70%, while exceeded water condensed on soot was unfavorable for sulfate formation due to inhibition of SO2 adsorption when RH was higher than 80%. The surface composition of soot, which was governed by combustion conditions, also played an important role in the heterogeneous reaction of SO2 with soot. This effect was found to greatly depend on RH. At low RH of 6%, soot with the highest fuel/oxygen ratio of 0.162 exhibited a maximum uptake capacity for SO2 because it contained a large amount of aromatic Csbnd H groups, which acted as active sites for SO2 adsorption. At RH of 54%, soot produced with a fuel/oxygen ratio of 0.134 showed the highest reactivity toward SO2 because it contained appropriate amounts of aromatic Csbnd H groups and oxygen-containing groups, subsequently leading to the optimal surface concentrations of both SO2 and water. These results suggest that variation in the surface composition of soot from different sources and/or resulting from chemical aging in the atmosphere likely affects the conversion of SO2 to sulfates.

  10. Validation and sensitivity analysis of a two zone Diesel engine model for combustion and emissions prediction

    International Nuclear Information System (INIS)

    Rakopoulos, C.D.; Rakopoulos, D.C.; Giakoumis, E.G.; Kyritsis, D.C.

    2004-01-01

    The present two zone model of a direct injection (DI) Diesel engine divides the cylinder contents into a non-burning zone of air and another homogeneous zone in which fuel is continuously supplied from the injector and burned with entrained air from the air zone. The growth of the fuel spray zone, which comprises a number of fuel-air conical jets equal to the injector nozzle holes, is carefully modelled by incorporating jet mixing, thus determining the amount of oxygen available for combustion. The mass, energy and state equations are applied in each of the two zones to yield local temperatures and cylinder pressure histories. The concentration of the various constituents in the exhaust gases are calculated by adopting a chemical equilibrium scheme for the C-H-O system of the 11 species considered, together with chemical rate equations for the calculation of nitric oxide (NO). A model for evaluation of the soot formation and oxidation rates is included. The theoretical results from the relevant computer program are compared very favourably with the measurements from an experimental investigation conducted on a fully automated test bed, standard 'Hydra', DI Diesel engine installed at the authors' laboratory. In-cylinder pressure and temperature histories, nitric oxide concentration and soot density are among the interesting quantities tested for various loads and injection timings. As revealed, the model is sensitive to the selection of the constants of the fuel preparation and reaction sub-models, so that a relevant sensitivity analysis is undertaken. This leads to a better understanding of the physical mechanisms governed by these constants and also paves the way for construction of a reliable and relatively simple multi-zone model, which incorporates in each zone (packet) the philosophy of the present two zone model

  11. Validation and sensitivity analysis of a two zone diesel engine model for combustion and emissions prediction

    Energy Technology Data Exchange (ETDEWEB)

    Rakopoulos, C.D.; Rakopoulos, D.C.; Giakoumis, E.G. [National Technical University of Athens (Greece). Mechanical Engineering Dept.; Kyritsis, D.C. [University of Illinois at Urbana-Champaign, Urbana, IL (United States). Dept. of Mechanical and Industrial Engineering

    2004-06-01

    The present two zone model of a direct injection (DI) diesel engine divides the cylinder contents into a non-burning zone of air and another homogeneous zone in which fuel is continuously supplied from the injector and burned with entrained air from the air zone. The growth of the fuel spray zone, which comprises a number of fuel-air conical jets equal to the injector nozzle holes, is carefully modelled by incorporating jet mixing, thus determining the amount of oxygen available for combustion. The mass, energy and state equations are applied in each of the two zones to yield local temperatures and cylinder pressure histories. The concentration of the various constituents in the exhaust gases are calculated by adopting a chemical equilibrium scheme for the C-H-O system of the 11 species considered, together with chemical rate equations for the calculation of nitric oxide (NO). A model for evaluation of the soot formation and oxidation rates is included. The theoretical results from the relevant computer program are compared very favourably with the measurements from an experimental investigation conducted on a fully automated test bed, standard ''Hydra'', DI diesel engine installed at the authors' laboratory. In-cylinder pressure and temperature histories, nitric oxide concentration and soot density are among the interesting quantities tested for various loads and injection timings. As revealed, the model is sensitive to the selection of the constants of the fuel preparation and reaction sub-models, so that a relevant sensitivity analysis is undertaken. This leads to a better understanding of the physical mechanisms governed by these constants and also paves the way for construction of a reliable and relatively simple multi-zone model, which incorporates in each zone (packet) the philosophy of the present two zone model. (author)

  12. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  13. Variation of diesel soot characteristics by different types and blends of biodiesel in a laboratory combustion chamber

    Energy Technology Data Exchange (ETDEWEB)

    Omidvarborna, Hamid; Kumar, Ashok [Department of Civil Engineering, The University of Toledo, Toledo, OH (United States); Kim, Dong-Shik, E-mail: dong.kim@utoledo.edu [Department of Chemical and Environmental Engineering, The University of Toledo, Toledo, OH (United States)

    2016-02-15

    Very little information is available on the physical and chemical properties of soot particles produced in the combustion of different types and blends of biodiesel fuels. A variety of feedstock can be used to produce biodiesel, and it is necessary to better understand the effects of feedstock-specific characteristics on soot particle emissions. Characteristics of soot particles, collected from a laboratory combustion chamber, are investigated from the blends of ultra-low sulfur diesel (ULSD) and biodiesel with various proportions. Biodiesel samples were derived from three different feedstocks, soybean methyl ester (SME), tallow oil (TO), and waste cooking oil (WCO). Experimental results showed a significant reduction in soot particle emissions when using biodiesel compared with ULSD. For the pure biodiesel, no soot particles were observed from the combustion regardless of their feedstock origins. The overall morphology of soot particles showed that the average diameter of ULSD soot particles is greater than the average soot particles from the biodiesel blends. Transmission electron microscopy (TEM) images of oxidized soot particles are presented to investigate how the addition of biodiesel fuels may affect structures of soot particles. In addition, inductively coupled plasma mass spectrometry (ICP-MS), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) were conducted for characterization of soot particles. Unsaturated methyl esters and high oxygen content of biodiesel are thought to be the major factors that help reduce the formation of soot particles in a laboratory combustion chamber. - Highlights: • The unsaturation of biodiesel fuel was correlated with soot characteristics. • Average diameters of biodiesel soot were smaller than that of ULSD. • Eight elements were detected as the marker metals in biodiesel soot particles. • As the degree of unsaturation increased, the oxygen content in FAMEs increased. • Biodiesel

  14. Model predictive control of a crude oil distillation column

    Directory of Open Access Journals (Sweden)

    Morten Hovd

    1999-04-01

    Full Text Available The project of designing and implementing model based predictive control on the vacuum distillation column at the Nynäshamn Refinery of Nynäs AB is described in this paper. The paper describes in detail the modeling for the model based control, covers the controller implementation, and documents the benefits gained from the model based controller.

  15. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre

    2005-07-01

    Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.

  16. Questioning the Faith - Models and Prediction in Stream Restoration (Invited)

    Science.gov (United States)

    Wilcock, P.

    2013-12-01

    River management and restoration demand prediction at and beyond our present ability. Management questions, framed appropriately, can motivate fundamental advances in science, although the connection between research and application is not always easy, useful, or robust. Why is that? This presentation considers the connection between models and management, a connection that requires critical and creative thought on both sides. Essential challenges for managers include clearly defining project objectives and accommodating uncertainty in any model prediction. Essential challenges for the research community include matching the appropriate model to project duration, space, funding, information, and social constraints and clearly presenting answers that are actually useful to managers. Better models do not lead to better management decisions or better designs if the predictions are not relevant to and accepted by managers. In fact, any prediction may be irrelevant if the need for prediction is not recognized. The predictive target must be developed in an active dialog between managers and modelers. This relationship, like any other, can take time to develop. For example, large segments of stream restoration practice have remained resistant to models and prediction because the foundational tenet - that channels built to a certain template will be able to transport the supplied sediment with the available flow - has no essential physical connection between cause and effect. Stream restoration practice can be steered in a predictive direction in which project objectives are defined as predictable attributes and testable hypotheses. If stream restoration design is defined in terms of the desired performance of the channel (static or dynamic, sediment surplus or deficit), then channel properties that provide these attributes can be predicted and a basis exists for testing approximations, models, and predictions.

  17. Predicting Magazine Audiences with a Loglinear Model.

    Science.gov (United States)

    1987-07-01

    TITLE (InciudeSecuirty Clauificalson, Predicting !iagaz:ine Atidiences with a Loglinvar \\lode] * 12. PERSONAL AUTHOR(S) * Peter J.1 .:)anahel 1 3&. TYPE...important use of e.d. estimates is in media selection ( Aaker 1975; Lee 1962, 1963; Little and Lodish 1969). All advertising campaigns have a budget. It...BBD we obtain the modified BBD (MBBD). Let X be the number of exposures a person has to k insertions in a single magazine. The mass function of the

  18. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  19. Predicting Error Bars for QSAR Models

    International Nuclear Information System (INIS)

    Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Mueller, Klaus-Robert

    2007-01-01

    Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D 7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches

  20. Prediction models for successful external cephalic version: a systematic review.

    Science.gov (United States)

    Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

    2015-12-01

    To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

  1. Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

    Science.gov (United States)

    Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

    2018-01-12

    Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

  2. AN EFFICIENT PATIENT INFLOW PREDICTION MODEL FOR HOSPITAL RESOURCE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Kottalanka Srikanth

    2017-07-01

    Full Text Available There has been increasing demand in improving service provisioning in hospital resources management. Hospital industries work with strict budget constraint at the same time assures quality care. To achieve quality care with budget constraint an efficient prediction model is required. Recently there has been various time series based prediction model has been proposed to manage hospital resources such ambulance monitoring, emergency care and so on. These models are not efficient as they do not consider the nature of scenario such climate condition etc. To address this artificial intelligence is adopted. The issues with existing prediction are that the training suffers from local optima error. This induces overhead and affects the accuracy in prediction. To overcome the local minima error, this work presents a patient inflow prediction model by adopting resilient backpropagation neural network. Experiment are conducted to evaluate the performance of proposed model inter of RMSE and MAPE. The outcome shows the proposed model reduces RMSE and MAPE over existing back propagation based artificial neural network. The overall outcomes show the proposed prediction model improves the accuracy of prediction which aid in improving the quality of health care management.

  3. Prediction Model for Gastric Cancer Incidence in Korean Population.

    Directory of Open Access Journals (Sweden)

    Bang Wool Eom

    Full Text Available Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea.Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell's C-statistics, and the calibration was evaluated using a calibration plot and slope.During a median of 11.4 years of follow-up, 19,465 (1.4% and 5,579 (0.7% newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women.In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance.

  4. Stage-specific predictive models for breast cancer survivability.

    Science.gov (United States)

    Kate, Rohit J; Nadig, Ramya

    2017-01-01

    Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Predictive modeling of pedestal structure in KSTAR using EPED model

    Energy Technology Data Exchange (ETDEWEB)

    Han, Hyunsun; Kim, J. Y. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Kwon, Ohjin [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)

    2013-10-15

    A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.

  6. Model predictions for auxiliary heating in spheromaks

    International Nuclear Information System (INIS)

    Fauler, T.K.; Khua, D.D.

    1997-01-01

    Calculations are presented of the plasma temperature waited for under auxiliary heating in spheromaks. A model, ensuring good agreement of earlier experiments with joule heating results, is used. The model includes heat losses due to magnetic fluctuations and shows that the plasma temperatures of the kilo-electron-volt order may be achieved in a small device with the radius of 0.3 m only

  7. Validating predictions from climate envelope models.

    Directory of Open Access Journals (Sweden)

    James I Watling

    Full Text Available Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species' distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967-1971 (t1 and evaluated using occurrence data from 1998-2002 (t2. Model sensitivity (the ability to correctly classify species presences was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on

  8. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  9. Evaluation of wave runup predictions from numerical and parametric models

    Science.gov (United States)

    Stockdon, Hilary F.; Thompson, David M.; Plant, Nathaniel G.; Long, Joseph W.

    2014-01-01

    Wave runup during storms is a primary driver of coastal evolution, including shoreline and dune erosion and barrier island overwash. Runup and its components, setup and swash, can be predicted from a parameterized model that was developed by comparing runup observations to offshore wave height, wave period, and local beach slope. Because observations during extreme storms are often unavailable, a numerical model is used to simulate the storm-driven runup to compare to the parameterized model and then develop an approach to improve the accuracy of the parameterization. Numerically simulated and parameterized runup were compared to observations to evaluate model accuracies. The analysis demonstrated that setup was accurately predicted by both the parameterized model and numerical simulations. Infragravity swash heights were most accurately predicted by the parameterized model. The numerical model suffered from bias and gain errors that depended on whether a one-dimensional or two-dimensional spatial domain was used. Nonetheless, all of the predictions were significantly correlated to the observations, implying that the systematic errors can be corrected. The numerical simulations did not resolve the incident-band swash motions, as expected, and the parameterized model performed best at predicting incident-band swash heights. An assimilated prediction using a weighted average of the parameterized model and the numerical simulations resulted in a reduction in prediction error variance. Finally, the numerical simulations were extended to include storm conditions that have not been previously observed. These results indicated that the parameterized predictions of setup may need modification for extreme conditions; numerical simulations can be used to extend the validity of the parameterized predictions of infragravity swash; and numerical simulations systematically underpredict incident swash, which is relatively unimportant under extreme conditions.

  10. A neighborhood statistics model for predicting stream pathogen indicator levels.

    Science.gov (United States)

    Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

    2015-03-01

    Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

  11. Prediction skill of rainstorm events over India in the TIGGE weather prediction models

    Science.gov (United States)

    Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

    2017-12-01

    Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

  12. Numerical prediction of heat-flux to massive calorimeters engulfed in regulatory fires with the cask analysis fire environment (CAFE) model

    International Nuclear Information System (INIS)

    Koski, Jorman A.; Suo-Antitla, Ahti; Kramer M, Alex; Greiner, Miles

    2000-01-01

    Recent observations show that the thermal boundary conditions within large-scale fires are significantly affected by the presence of thermally massive objects. These objects cool the soot and gas near their surfaces, and these effects reduce the incoming radiant heat-flux to values lower than the levels expected from simple σT fire 4 models. They also affect the flow and temperature fields in the fire far from their surfaces. The Cask Analysis Fire Environment (CAFE) code has been developed at Sandia National Laboratories to provide an enhanced fire boundary condition for the design of radioactive material packages. CAFE is a set of computer subroutines that use computational fluid mechanics methods to predict convective heat transfer and mixing. It also includes models for fuel and oxygen transport, chemical reaction, and participating-media radiation heat transfer. This code uses two-dimensional computational models so that it has reasonably short turnaround times on standard workstations and is well suited for design and risk studies. In this paper, CAFE is coupled with a commercial finite-element program to model a large cylindrical calorimeter fully engulfed in a pool fire. The time-dependent heat-flux to the calorimeter and the calorimeter surface temperature are determined for several locations around the calorimeter circumference. The variation of heat-flux with location is determined for calorimeters with different diameters and wall thickness, and the observed effects discussed

  13. Preclinical models used for immunogenicity prediction of therapeutic proteins.

    Science.gov (United States)

    Brinks, Vera; Weinbuch, Daniel; Baker, Matthew; Dean, Yann; Stas, Philippe; Kostense, Stefan; Rup, Bonita; Jiskoot, Wim

    2013-07-01

    All therapeutic proteins are potentially immunogenic. Antibodies formed against these drugs can decrease efficacy, leading to drastically increased therapeutic costs and in rare cases to serious and sometimes life threatening side-effects. Many efforts are therefore undertaken to develop therapeutic proteins with minimal immunogenicity. For this, immunogenicity prediction of candidate drugs during early drug development is essential. Several in silico, in vitro and in vivo models are used to predict immunogenicity of drug leads, to modify potentially immunogenic properties and to continue development of drug candidates with expected low immunogenicity. Despite the extensive use of these predictive models, their actual predictive value varies. Important reasons for this uncertainty are the limited/insufficient knowledge on the immune mechanisms underlying immunogenicity of therapeutic proteins, the fact that different predictive models explore different components of the immune system and the lack of an integrated clinical validation. In this review, we discuss the predictive models in use, summarize aspects of immunogenicity that these models predict and explore the merits and the limitations of each of the models.

  14. Development of Interpretable Predictive Models for BPH and Prostate Cancer.

    Science.gov (United States)

    Bermejo, Pablo; Vivo, Alicia; Tárraga, Pedro J; Rodríguez-Montes, J A

    2015-01-01

    Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. Statistical dependence with PC and BPH was found for prostate volume (P-value BPH prediction. PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced.

  15. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing so...... decisions need to be made in terms of statistical distributions of walking parameters and in terms of the parameters describing the statistical distributions. The paper explores how sensitive computations of bridge response are to some of the decisions to be made in this respect. This is useful...

  16. A COMPARISON BETWEEN THREE PREDICTIVE MODELS OF COMPUTATIONAL INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    DUMITRU CIOBANU

    2013-12-01

    Full Text Available Time series prediction is an open problem and many researchers are trying to find new predictive methods and improvements for the existing ones. Lately methods based on neural networks are used extensively for time series prediction. Also, support vector machines have solved some of the problems faced by neural networks and they began to be widely used for time series prediction. The main drawback of those two methods is that they are global models and in the case of a chaotic time series it is unlikely to find such model. In this paper it is presented a comparison between three predictive from computational intelligence field one based on neural networks one based on support vector machine and another based on chaos theory. We show that the model based on chaos theory is an alternative to the other two methods.

  17. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Directory of Open Access Journals (Sweden)

    Saerom Park

    Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  18. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Science.gov (United States)

    Park, Saerom; Lee, Jaewook; Son, Youngdoo

    2016-01-01

    Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  19. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering

    2006-05-15

    Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.

  20. Bayesian Age-Period-Cohort Modeling and Prediction - BAMP

    Directory of Open Access Journals (Sweden)

    Volker J. Schmid

    2007-10-01

    Full Text Available The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.

  1. Modeling for prediction of restrained shrinkage effect in concrete repair

    International Nuclear Information System (INIS)

    Yuan Yingshu; Li Guo; Cai Yue

    2003-01-01

    A general model of autogenous shrinkage caused by chemical reaction (chemical shrinkage) is developed by means of Arrhenius' law and a degree of chemical reaction. Models of tensile creep and relaxation modulus are built based on a viscoelastic, three-element model. Tests of free shrinkage and tensile creep were carried out to determine some coefficients in the models. Two-dimensional FEM analysis based on the models and other constitutions can predict the development of tensile strength and cracking. Three groups of patch-repaired beams were designed for analysis and testing. The prediction from the analysis shows agreement with the test results. The cracking mechanism after repair is discussed

  2. Evaluation of two models for predicting elemental accumulation by arthropods

    International Nuclear Information System (INIS)

    Webster, J.R.; Crossley, D.A. Jr.

    1978-01-01

    Two different models have been proposed for predicting elemental accumulation by arthropods. Parameters of both models can be quantified from radioisotope elimination experiments. Our analysis of the 2 models shows that both predict identical elemental accumulation for a whole organism, though differing in the accumulation in body and gut. We quantified both models with experimental data from 134 Cs and 85 Sr elimination by crickets. Computer simulations of radioisotope accumulation were then compared with actual accumulation experiments. Neither model showed exact fit to the experimental data, though both showed the general pattern of elemental accumulation

  3. Uncertainties in model-based outcome predictions for treatment planning

    International Nuclear Information System (INIS)

    Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

    2001-01-01

    Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment

  4. Geospatial application of the Water Erosion Prediction Project (WEPP) Model

    Science.gov (United States)

    D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

    2011-01-01

    The Water Erosion Prediction Project (WEPP) model is a process-based technology for prediction of soil erosion by water at hillslope profile, field, and small watershed scales. In particular, WEPP utilizes observed or generated daily climate inputs to drive the surface hydrology processes (infiltration, runoff, ET) component, which subsequently impacts the rest of the...

  5. Techniques for discrimination-free predictive models (Chapter 12)

    NARCIS (Netherlands)

    Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.; Custers, B.H.M.; Calders, T.G.K.; Schermer, B.W.; Zarsky, T.Z.

    2013-01-01

    In this chapter, we give an overview of the techniques developed ourselves for constructing discrimination-free classifiers. In discrimination-free classification the goal is to learn a predictive model that classifies future data objects as accurately as possible, yet the predicted labels should be

  6. A model to predict the beginning of the pollen season

    DEFF Research Database (Denmark)

    Toldam-Andersen, Torben Bo

    1991-01-01

    for fruit trees are generally applicable, and give a reasonable description of the growth processes of other trees. This type of model can therefore be of value in predicting the start of the pollen season. The predicted dates were generally within 3-5 days of the observed. Finally the possibility of frost...

  7. Statistical models to predict flows at monthly level in Salvajina

    International Nuclear Information System (INIS)

    Gonzalez, Harold O

    1994-01-01

    It thinks about and models of lineal regression evaluate at monthly level that they allow to predict flows in Salvajina, with base in predictions variable, like the difference of pressure between Darwin and Tahiti, precipitation in Piendamo Cauca), temperature in Port Chicama (Peru) and pressure in Tahiti

  8. Validation of a tuber blight (Phytophthora infestans) prediction model

    Science.gov (United States)

    Potato tuber blight caused by Phytophthora infestans accounts for significant losses in storage. There is limited published quantitative data on predicting tuber blight. We validated a tuber blight prediction model developed in New York with cultivars Allegany, NY 101, and Katahdin using independent...

  9. Global vegetation change predicted by the modified Budyko model

    Energy Technology Data Exchange (ETDEWEB)

    Monserud, R.A.; Tchebakova, N.M.; Leemans, R. (US Department of Agriculture, Moscow, ID (United States). Intermountain Research Station, Forest Service)

    1993-09-01

    A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO[sub 2] doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favouring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50-100 y needed for CO[sub 2] doubling, it is not clear if projected global warming will result in drastic or benign vegetation change. 72 refs., 3 figs., 3 tabs.

  10. Moment based model predictive control for systems with additive uncertainty

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.

    2017-01-01

    In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We

  11. Microwave-assisted in-situ regeneration of a perovskite coated diesel soot filter

    NARCIS (Netherlands)

    Zhang-Steenwinkel, Y.; van der Zande, L.M.; Castricum, H.L.; Bliek, A.; van den Brink, R.W.; Elzinga, G.D.

    2005-01-01

    Dielectric heating may be used as an in situ technique for the periodic regeneration of soot filters, as those used in Diesel engines. As generally the Diesel exhaust temperatures are below the soot light-off temperature, passive regeneration is not possible. Presently, we have investigated the

  12. Soot measurements for diesel and biodiesel spray combustion under high temperature highly diluted ambient conditions

    KAUST Repository

    Zhang, Ji; Jing, Wei; Roberts, William L.; Fang, Tiegang

    2014-01-01

    This paper presents the soot temperature and KL factor for biodiesel, namely fatty acid methyl ester (FAME) and diesel fuel combustion in a constant volume chamber using a two-color technique. The KL factor is a parameter for soot concentration

  13. Experimental study of the interaction of HO2 radicals with soot surface.

    Science.gov (United States)

    Bedjanian, Yuri; Lelièvre, Stéphane; Le Bras, Georges

    2005-01-21

    The reaction of HO2 with toluene and kerosene flame soot was studied over the temperature range 240-350 K and at P = 0.5-5 Torr of helium using a discharge flow reactor coupled to a modulated molecular beam mass spectrometer. A flat-flame burner was used for the preparation and deposition of soot samples from premixed flames of liquid fuels under well controlled and adjustable combustion conditions. The independent of temperature in the range 240-350 K value of gamma = (7.5 +/- 1.5) x 10(-2) (calculated with geometric surface area) was found for the uptake coefficient of HO2 on kerosene and toluene soot. No significant deactivation of soot surface during its reaction with HO2 was observed. Experiments on soot ageing under ambient conditions showed that the reactivity of aged soot is similar to that of freshly prepared soot samples. The results show that the HO2 + soot reaction could be a significant loss process for HOx in the urban atmosphere with a potential impact on photochemical ozone formation. In contrast this process will be negligible in the upper troposphere even in flight corridors.

  14. Simulation and analysis of the soot particle size distribution in a turbulent nonpremixed flame

    KAUST Repository

    Lucchesi, Marco; Abdelgadir, Ahmed Gamaleldin; Attili, Antonio; Bisetti, Fabrizio

    2017-01-01

    to the simulation of soot formation and growth in simplified configurations featuring a constant concentration of soot precursors and the evolution of the size distribution in time is found to depend on the intensity of the nucleation rate. Higher nucleation rates

  15. Soot Reactivity in Conventional Combustion and Oxy-fuel Combustion Environments

    DEFF Research Database (Denmark)

    Abián, María; Jensen, Anker D.; Glarborg, Peter

    2012-01-01

    A study of the reactivity of soot produced from ethylene pyrolysis at different temperatures and CO2 atmospheres toward O2 and CO2 has been carried out using a thermogravimetric analyzer. The purpose was to quantify how soot reactivity is affected by the gas environment and temperature history of...

  16. Risk predictive modelling for diabetes and cardiovascular disease.

    Science.gov (United States)

    Kengne, Andre Pascal; Masconi, Katya; Mbanya, Vivian Nchanchou; Lekoubou, Alain; Echouffo-Tcheugui, Justin Basile; Matsha, Tandi E

    2014-02-01

    Absolute risk models or clinical prediction models have been incorporated in guidelines, and are increasingly advocated as tools to assist risk stratification and guide prevention and treatments decisions relating to common health conditions such as cardiovascular disease (CVD) and diabetes mellitus. We have reviewed the historical development and principles of prediction research, including their statistical underpinning, as well as implications for routine practice, with a focus on predictive modelling for CVD and diabetes. Predictive modelling for CVD risk, which has developed over the last five decades, has been largely influenced by the Framingham Heart Study investigators, while it is only ∼20 years ago that similar efforts were started in the field of diabetes. Identification of predictive factors is an important preliminary step which provides the knowledge base on potential predictors to be tested for inclusion during the statistical derivation of the final model. The derived models must then be tested both on the development sample (internal validation) and on other populations in different settings (external validation). Updating procedures (e.g. recalibration) should be used to improve the performance of models that fail the tests of external validation. Ultimately, the effect of introducing validated models in routine practice on the process and outcomes of care as well as its cost-effectiveness should be tested in impact studies before wide dissemination of models beyond the research context. Several predictions models have been developed for CVD or diabetes, but very few have been externally validated or tested in impact studies, and their comparative performance has yet to be fully assessed. A shift of focus from developing new CVD or diabetes prediction models to validating the existing ones will improve their adoption in routine practice.

  17. Consensus models to predict endocrine disruption for all ...

    Science.gov (United States)

    Humans are potentially exposed to tens of thousands of man-made chemicals in the environment. It is well known that some environmental chemicals mimic natural hormones and thus have the potential to be endocrine disruptors. Most of these environmental chemicals have never been tested for their ability to disrupt the endocrine system, in particular, their ability to interact with the estrogen receptor. EPA needs tools to prioritize thousands of chemicals, for instance in the Endocrine Disruptor Screening Program (EDSP). Collaborative Estrogen Receptor Activity Prediction Project (CERAPP) was intended to be a demonstration of the use of predictive computational models on HTS data including ToxCast and Tox21 assays to prioritize a large chemical universe of 32464 unique structures for one specific molecular target – the estrogen receptor. CERAPP combined multiple computational models for prediction of estrogen receptor activity, and used the predicted results to build a unique consensus model. Models were developed in collaboration between 17 groups in the U.S. and Europe and applied to predict the common set of chemicals. Structure-based techniques such as docking and several QSAR modeling approaches were employed, mostly using a common training set of 1677 compounds provided by U.S. EPA, to build a total of 42 classification models and 8 regression models for binding, agonist and antagonist activity. All predictions were evaluated on ToxCast data and on an exte

  18. Mixed models for predictive modeling in actuarial science

    NARCIS (Netherlands)

    Antonio, K.; Zhang, Y.

    2012-01-01

    We start with a general discussion of mixed (also called multilevel) models and continue with illustrating specific (actuarial) applications of this type of models. Technical details on (linear, generalized, non-linear) mixed models follow: model assumptions, specifications, estimation techniques

  19. A multivariate model for predicting segmental body composition.

    Science.gov (United States)

    Tian, Simiao; Mioche, Laurence; Denis, Jean-Baptiste; Morio, Béatrice

    2013-12-01

    The aims of the present study were to propose a multivariate model for predicting simultaneously body, trunk and appendicular fat and lean masses from easily measured variables and to compare its predictive capacity with that of the available univariate models that predict body fat percentage (BF%). The dual-energy X-ray absorptiometry (DXA) dataset (52% men and 48% women) with White, Black and Hispanic ethnicities (1999-2004, National Health and Nutrition Examination Survey) was randomly divided into three sub-datasets: a training dataset (TRD), a test dataset (TED); a validation dataset (VAD), comprising 3835, 1917 and 1917 subjects. For each sex, several multivariate prediction models were fitted from the TRD using age, weight, height and possibly waist circumference. The most accurate model was selected from the TED and then applied to the VAD and a French DXA dataset (French DB) (526 men and 529 women) to assess the prediction accuracy in comparison with that of five published univariate models, for which adjusted formulas were re-estimated using the TRD. Waist circumference was found to improve the prediction accuracy, especially in men. For BF%, the standard error of prediction (SEP) values were 3.26 (3.75) % for men and 3.47 (3.95)% for women in the VAD (French DB), as good as those of the adjusted univariate models. Moreover, the SEP values for the prediction of body and appendicular lean masses ranged from 1.39 to 2.75 kg for both the sexes. The prediction accuracy was best for age < 65 years, BMI < 30 kg/m2 and the Hispanic ethnicity. The application of our multivariate model to large populations could be useful to address various public health issues.

  20. The Selection of Turbulence Models for Prediction of Room Airflow

    DEFF Research Database (Denmark)

    Nielsen, Peter V.

    This paper discusses the use of different turbulence models and their advantages in given situations. As an example, it is shown that a simple zero-equation model can be used for the prediction of special situations as flow with a low level of turbulence. A zero-equation model with compensation...