Academic literature on the topic 'Chemical kinetic modeling'
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Journal articles on the topic "Chemical kinetic modeling":
Suleymanov, Yury. "Advancing chemical kinetic modeling." Science 372, no. 6537 (April 1, 2021): 44.2–44. http://dx.doi.org/10.1126/science.372.6537.44-b.
Pitz, W. J., C. K. Westbrook, O. Herbinet, and E. J. Silke. "KS-2: Progress in Chemical Kinetic Modeling for Surrogate Fuels(Keynote Papers)." Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines 2008.7 (2008): 9–15. http://dx.doi.org/10.1299/jmsesdm.2008.7.9.
Boukhalfa, Nora. "Chemical Kinetic Modeling of Methane Combustion." Procedia Engineering 148 (2016): 1130–36. http://dx.doi.org/10.1016/j.proeng.2016.06.561.
ERTEKİN, Özlem. "Example of A Kinetic Mathematical Modeling in Food Engineering." ITM Web of Conferences 22 (2018): 01029. http://dx.doi.org/10.1051/itmconf/20182201029.
Martínez, Haydee, Joaquín Sánchez, José-Manuel Cruz, Guadalupe Ayala, Marco Rivera, and Thomas Buhse. "Modeling of Scale-Dependent Bacterial Growth by Chemical Kinetics Approach." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/820959.
Edeleva, Mariya, Paul H. M. Van Steenberge, Maarten K. Sabbe, and Dagmar R. D’hooge. "Connecting Gas-Phase Computational Chemistry to Condensed Phase Kinetic Modeling: The State-of-the-Art." Polymers 13, no. 18 (September 7, 2021): 3027. http://dx.doi.org/10.3390/polym13183027.
Escanciano, Itziar A., Mateusz Wojtusik, Jesús Esteban, Miguel Ladero, and Victoria E. Santos. "Modeling the Succinic Acid Bioprocess: A Review." Fermentation 8, no. 8 (July 31, 2022): 368. http://dx.doi.org/10.3390/fermentation8080368.
Westbrook, Charles K. "Chemical kinetic modeling of higher hydrocarbon fuels." AIAA Journal 24, no. 12 (December 1986): 2002–9. http://dx.doi.org/10.2514/3.9559.
Silke, Emma J., William J. Pitz, Charles K. Westbrook, and Marc Ribaucour. "Detailed Chemical Kinetic Modeling of Cyclohexane Oxidation†." Journal of Physical Chemistry A 111, no. 19 (May 2007): 3761–75. http://dx.doi.org/10.1021/jp067592d.
Lai, Jason Y. W., Kuang C. Lin, and Angela Violi. "Biodiesel combustion: Advances in chemical kinetic modeling." Progress in Energy and Combustion Science 37, no. 1 (February 2011): 1–14. http://dx.doi.org/10.1016/j.pecs.2010.03.001.
Dissertations / Theses on the topic "Chemical kinetic modeling":
Jalan, Amrit. "Predictive kinetic modeling of low-temperature hydrocarbon oxidation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91059.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 221-235).
Low temperature oxidation in the gas and condensed phases has been the subject of experimental investigations for many decades owing to applications in many areas of practical significance like thermal stability, combustion, atmospheric chemistry and industrial syntheses. Owing to several practical limitations it has proven difficult to understand these processes at a mechanistic level from experiments alone. Developments in scientific computing have opened up computational chemistry and cheminformatics based tools as an attractive option for exploring and elucidating the kinetics of these complex processes through detailed kinetic modeling and requires efforts in three key areas: single reaction kinetics, reaction networks and coupling kinetics with mass/momentum/energy balance models. This thesis presents several contributions employing high-level electronic structure calculations, reaction rate theory, automated kinetic modeling and empirical correlations to further our mechanistic understanding of low-temperature oxidation in the gas and liquid phase. First, an extensible framework for automatic estimation of species thermochemistry in the solution phase is presented and validated. This framework uses the Linear Solvation Energy Relationship (LSER) formalism of Abraham/Mintz and co-workers for high-throughput estimation of [delta]G°solv(T) in over 30 solvents using solute descriptors estimated from group additivity. The performance of scaled particle theory (SPT) expressions for enthalpic-entropic decomposition of [delta]G°solv(T) is also discussed along with the associated computational issues. Second, the importance of solvent effects on free-radical kinetics is explored using tetralin oxidation as a case study. The solvent dependence for the main propagation and termination reactions are determined using the Polarizable Continuum (PCM) family of solvation models. Incorporating these kinetic solvent effects in detailed kinetic models suggest oxidation rates increase with solvent polarity, consistent with experiment. Following this, electronic structure methods and reaction rate theory are used elucidate mechanistic details of new pathways in liquid-phase and atmospheric oxidation. The first of these studies focuses on pathways that establish [gamma]-ketohydroperoxides (KHP), well-known products in low-temperature alkane oxidation, as precursors to acids through a two-step process. Ab initio calculations are used to identify pathways leading from KHP to a cyclic peroxide isomer which decomposes through novel concerted reactions into carbonyl and carboxylic acid products. High-level gas phase rate coefficients are obtained using DFT/WFT methods coupled with VTST/SCT calculations and multi-structural partition functions (QMs-T). Solvent effects are included using continuum dielectric solvation models and the predicted rate coefficients found to be in excellent agreement with experiment lending theoretical support to the 30-year old Korcek hypothesis. Next, insights from the Korcek reaction are extended to atmospheric chemistry where similar cyclic peroxides are formed by reactions of the Criegee Intermediate (*CH₂OO*) with double bonds. More specifically, the role of chemical activation in reactions between *CH₂OO* and C=O/C=C species is explored using master equation calculations to obtain phenomenological rate coefficients k(T,P). In the case of reactions with C=O, the yield of collisionally stabilized SOZ at atmospheric pressure was found to increase in the order HCHO < CH₃CHO < CH₃COCH₃ - At low pressures, chemically activated formation of organic acids was found to be the major product channel in agreement with recent direct measurements. Epoxide and CH₂=CHOH are predicted to be the major products for *CH₂OO* + C₂H₄ under atmospheric conditions. Finally, as a case study in coupling detailed chemical and physical models, the improved understanding of liquid phase oxidation developed above is used to build multi-physics models of diesel injector deposit formation that adversely affects fuel spray characteristics and engine efficiency. Octane is used as a model liquid fuel for detailed kinetic modeling of oxidative aging leading to deposit precursors. In addition to fuel chemistry, the immiscibility of polar oxidation products leading to 'soft deposit' is modeled using linear solvation energy relationships. The chemistry and phase separation models are coupled with physical processes like washing. The resulting framework is used to explore the sensitivity of deposit formation to various model parameters.
by Amrit Jalan.
Ph. D.
Moore, Jason Stuart. "Kinetic modeling and automated optimization in microreactor systems." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79195.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 127-138).
The optimization, kinetic investigation, or scale-up of a reaction often requires significant time and materials. Silicon microreactor systems have been shown advantageous for studying chemical reactions due to their small volume, rapid mixing, tight temperature control, large range of operating conditions, and increased safety. The primary goal of this thesis is to expand the capabilities of automated microreactor systems to increase their scope and efficiency. An automated optimization platform is built utilizing continuous inline IR analysis at the reactor exit, and a Paal-Knorr reaction is chosen as the first example chemistry. This reaction, where both the first and second reaction steps affect the overall rate, leads to a more complex conversion profile. A steepest descent algorithm is first used to optimize conversion and production rates. The steepest descent algorithm tends to move slowly up the production rate ridge, significantly reducing efficiency. This issue is overcome by using a Fletcher-Reeves conjugate gradient method, which finds the constrained optimum in much fewer experiments. The conjugate gradient algorithm is then further improved upon by incorporating a hybrid Armijo line search and bisection contraction method. However, the conversion is only about 40% at the maximum in production rate. A further optimization is performed using a quadratic loss function to penalize conversions of less than 85%. This optimization of production rate led to an optimum at higher residence time, where a conversion of 81% is achieved. In the conventional view of reaction analysis, batch reactions are thought to be significantly more efficient in generating time-course reaction data than flow reactions, which are generally limited to steady-state studies. By taking advantage of the low dispersion in microreactors, successive fluid elements of the reactor may be treated as separate batch reactors. By continuously manipulating the reaction flow rate and tracking the total reaction time of each fluid element, time-course data analogous to that conventionally derived from batch reactors are generated and shown to be in agreement with steady-state results. Palladium-catalyzed carbonylation and CN-coupling reactions are used extensively in laboratory synthesis and industrial processes. The primary reaction studied involves the coupling of bromobenzene and morpholene with the addition of one or two carbonyl groups. The dependence of reaction conversion and selectivity on temperature, CO pressure, and Pd concentration are investigated using GC and IR analysis. A temperature ramp method is employed to rapidly investigate temperature effects on reaction rate and selectivity. The experiments reveal a change in the rate determining step at approximately 120 °C and corresponded well with GC data taken at several setpoints. In addition, the activation energy of the lower temperature regime as determined by this IR analysis is found to be very similar to that found by GC analysis, the experiments for which took significantly longer both to perform and analyze. Furthermore, the data collected from these experiments are used to fit a kinetic model. Multicomponent reactions (MCRs) are important to drug discovery by affording complex products in only a single step. By linking two of these MCRs, a Petasis boronic acid-Mannich reaction and an Ugi reaction, six different components could be incorporated in a relatively short time. The kinetics of each reaction are investigated with online UPLC analysis, allowing for quantification of a number of reaction components, including monitoring the formation of side products that were unknown prior to experimentation. A simple microcalorimeter is built using thermoelectric elements and a silicon microreactor to experimentally determine the heats of reaction during flow to allow for understanding the heat transfer needs for scale up. The result from the nitration of benzene, which has a heat of reaction of -117 kJ/mol, is -118.6 +/- 2.4 kJ/mol. The experimentally determined values are close to the known values; however, there is significant noise in the output during the reaction due to the two-phase nature of the reaction. The Paal-Knorr reaction is further investigated to determine the limits of sensitivity of the microcalorimetry system. A continuous concentration ramp experiment is performed with online IR analysis, enabling the thermoelectric output to be adjusted for reaction rate to determine the sensitivity to the heat of reaction. Below approximately 2 M, the sensitivity decreases rapidly, largely due to noise in the temperature control and concentration. To attempt to correct for the former, a calorimetry system with larger thermal mass is constructed and shown to decrease the sensitivity limit to 1 M, corresponding to a heat flow of approximately 0.05 W.
by Jason Stuart Moore.
Ph.D.
Akih, Kumgeh Benjamin. "Shock tube studies and chemical kinetic modeling of oxygenated hydrocarbon ignition." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103701.
En tant que contribution à la compréhension, la modélisation et le contrôle de la combustion des hydrocarbures oxygénés tels que les biocarburants, l'auto-allumage à haute température d'une série de molécules a été étudiée avec la méthode de tube a onde de choc pour les pressions entre 1 atm et 13 atm. Les molécules représentatives du biodiésel, c'est à dire des esters méthyliques et éthyliques, ont été étudiées. Les esters méthyliques d'acide formique jusqu'à butanoique ont été étudiés afin de découvrir l'influence de leurs structures sur l'auto-allumage. Cette relation a aussi été examinée avec les calculs de la chimique quantique. Alors que la pluparts de ces esters sont marqués par des délais d'auto-allumage similaires, les influences des groupes méthyliques terminales, et la présence ou absence des liaisons secondaires de C-H, ont été identifiées, comme dans le cas d'acétate de méthyle, caractérisé par les plus longs délais. Le rôle du groupe alkyle sur la réactivité d'ester a été étudié en comparant des esters méthyliques avec les esters éthyliques. Les esters éthyliques sont généralement plus réactifs que les esters méthyliques du même acide. De la même manière, sont investigués quelques hydrocarbures oxygénés, dont leur cinétique d'oxydation est impliquée dans la combustion des biocarburants et carburants pétrolifères. Un mécanisme de la cinétique chimique pour la combustion du propanal à haute température a été développé et validé. Le propanal, comme d'autres aldéhydes, appartient au groupe des espèces intermédiaires qui se forment pendant la combustion de presque tous les hydrocarbures, mais leur modélisation reste imprécise. Des études consacrées à la compréhension des sous-modèles de ces molécules devraient contribuer à la modélisation avancée de la cinétique chimique de la combustion. Le mécanisme proposé prédit aussi les délais d'auto-allumage d'acétaldéhyde, dont le sous-mécanisme est inclus. L'éthanol est un biocarburant largement utilisé dans les moteurs à allumage commandé. Il y a également intérêt à utiliser ce carburant dans les moteurs à allumage par compression. Ceci est en accord avec la nécessité de développer des carburants flexibles pour des moteurs divers. La modification de l'auto-allumage de l'éthanol par des additifs chimiques comme le nitrate d'isopropyle (IPN), le formiate d'isopropyle (IPF) et l'eau a été investiguée. Il se trouve que, alors que l'IPN améliore la tendance à l'auto-allumage de l'éthanol (délais plus courts), l'IPF augmente sa résistance à l'autoallumage, de sorte que ce dernier peut être utilisé comme additif pour supprimer l'autoallumage. Pour une même température, l'auto-allumage de l'éthanol contenant de l'eau se révèle accélérée. Un mécanisme pour la combustion des mélanges de diesel et du biodiesel est également proposé. Le mécanisme est dérivé de la réduction des mécanismes détaillés pour le n-heptane et le butanoate de méthyle obtenus sur la base de l'analyse de sensitivité de l'auto-allumage. Cette méthode comparative systématique et innovatrice cherche à caractériser les propriétés des carburants oxygénés en vue de révéler les similitudes et les différences. Les résultats servent à l'optimisation des modèles cinétiques chimiques ainsi qu'à la compréhension de la cinétique de combustion d'une série d'espèces oxygénées. Des corrélations de délais d'auto-allumage sont également proposées pour l'application pratique. Le mécanisme proposé pour les mélanges diesel et biodiesel se prête à l'étude de la combustion dans les écoulements turbulents.
Alecu, Ionut M. Marshall Paul. "Kinetic studies and computational modeling of atomic chlorine reactions in the gas phase." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12071.
Alecu, Ionut M. "Kinetic studies and computational modeling of atomic chlorine reactions in the gas phase." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12071/.
Castaneda-Lopez, Luis Carlos. "Kinetic modeling of the hydrotreatment of light cycle oil/diesel." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1061.
Wu, Kuo-chʻun 1968. "Chemical kinetic modeling of oxidation of hydrocarbon emissions in spark ignition engines." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35377.
Boddapati, Aparna. "Modeling cure depth during photopolymerization of multifunctional acrylates." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33934.
Lee, Chuang-Chung. "Kinetic modeling of amyloid fibrillation and synaptic plasticity as memory loss and formation mechanisms." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/49893.
Includes bibliographical references (p. 141-150).
The principles of biochemical kinetics and system engineering are applied to explain memory-related neuroscientific phenomena. Amyloid fibrillation and synaptic plasticity have been our focus of research due to their significance. The former is related to the pathology of many neurodegenerative diseases and the later is regarded as the principal mechanism underlying learning and memory. Claimed to be the number one cause of senile dementia, Alzheimer's disease (AD) is one of the disorders that involve misfolding of amyloid protein and formation of insoluble fibrils. Although a variety of time dependent fibrillation data in vitro are available, few mechanistic models have been developed. To bridge this gap we used chemical engineering concepts from polymer dynamics, particle mechanics and population balance models to develop a mathematical formulation of amyloid growth dynamics. A three-stage mechanism consisting of natural protein misfolding, nucleation, and fibril elongation phases was proposed to capture the features of homogeneous fibrillation responses. While our cooperative laboratory provided us with experimental findings, we guided them with experimental design based on modeling work. It was through the iterative process that the size of fibril nuclei and concentration profiles of soluble proteins were elucidated. The study also reveals further experiments for diagnosing the evolution of amyloid coagulation and probing desired properties of potential fibrillation inhibitors. Synaptic plasticity at various time ranges has been studied experimentally to elucidate memory formation mechanism. By comparison, the theoretical work is underdeveloped and insufficient to explain some experiments. To resolve the issue, we developed models for short-term, long-term, and spike timing dependent synaptic plasticity, respectively.
(cont.) First, presynaptic vesicle trafficking that leads to the release of glutamate as neurotransmitter was taken into account to explain short-term plasticity data. Second, long-term plasticity data lasting for hours after tetanus stimuli has been matched by a calcium entrapment model we developed. Model differentiation was done to demonstrate the better performance of calcium entrapment model than an alternative bistable theory in fitting graded long-term potentiation responses. Finally, to decipher spike timing dependent plasticity (STDP), we developed a systematic model incorporating back propagation of action potential, dual requirement of NMDA receptors, and calcium dependent plasticity. This built model is supported by five different types of STDP experimental data. The accumulation of amyloid beta has been found to disrupt the sustainable modification of long-term synaptic plasticity which might explain the inability of AD patients to form new memory at early stage of the disease. Yet the linkage between the existence of amyloid beta species and failure of long-term plasticity was unclear. We suggest that the abnormality of calcium entrapment function caused by amyloid oligomers is the intermediate step that eventually leads to memory loss. Unsustainable calcium level and decreased postsynaptic activities result into the removal or internalization of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. The number of AMPA receptors as the indicators of synaptic strength may result into disconnection between neurons and even neuronal apoptosis. New experiments have been suggested to validate this hypothesis and to elucidate the pathology of Alzheimer's disease.
by Chuang-Chung (Justin) Lee.
Ph.D.
Bandstra, Joel Zachary. "Kinetic modeling of heterogeneous chemical reactions with applications to the reduction of environmental contaminants on iron metal." Full text open access at:, 2005. http://content.ohsu.edu/u?/etd,280.
Books on the topic "Chemical kinetic modeling":
H, Galina, ed. Grafting, characterization techniques, kinetic modeling. Berlin: Springer, 1998.
M. A. J. S. van Boekel. Kinetic modeling of reactions in foods. Boca Raton: Taylor & Francis, 2008.
G, Compton R., and Hancock G, eds. Applications of kinetic modelling. Amsterdam: Elsevier, 1999.
Prof, Carr Robert W., ed. Modeling of chemical reactions. Amsterdam: Elsevier, 2007.
Coker, A. Kayode. Modeling of chemical kinetics and reactor design. Boston, MA: Gulf Professional Pub., 2001.
United States. Federal Highway Administration. Exploring cement hydration kinetics: International summit on cement hydration kinetics and modeling. Washington, D.C.]: U.S. Dept. of Transportation, Federal Highway Administration, 2010.
Boekel, Tiny Van. Kinetic modelling of reactions in foods. Boca Raton: Taylor & Francis, 2008.
B, DeMore W., NASA Panel for Data Evaluation., and Jet Propulsion Laboratory (U.S.), eds. Chemical kinetics and photochemical data for use in stratospheric modeling. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1992.
Kopin, Liu, and Wagner Albert 1945-, eds. The chemical dynamics and kinetics of small radicals. Singapore: World Scientific, 1995.
B, DeMore W., and Jet Propulsion Laboratory (U.S.), eds. Chemical kinetics and photochemical data for use in stratospheric modeling: Evaluation number 11. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1994.
Book chapters on the topic "Chemical kinetic modeling":
Jakobsen, Hugo A. "Elementary Kinetic Theory of Gases." In Chemical Reactor Modeling, 183–365. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05092-8_2.
Grünfeld, Cecil P. "Nonlinear Kinetic Models with Chemical Reactions." In Modeling in Applied Sciences, 173–224. Boston, MA: Birkhäuser Boston, 2000. http://dx.doi.org/10.1007/978-1-4612-0513-5_6.
Campbell, Jerry L., Kannan Krishnan, Harvey J. Clewell, and Melvin E. Andersen. "Modeling Kinetic Interactions of Chemical Mixtures." In Principles and Practice of Mixtures Toxicology, 125–57. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2010. http://dx.doi.org/10.1002/9783527630196.ch5.
Froment, G. F. "Fundamental Kinetic Modeling of Complex Processes." In Chemical Reactions in Complex Mixtures, 77–100. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-6530-3_5.
Sapre, A. V. "Kinetic Modeling at Mobil: An Historical Perspective." In Chemical Reactions in Complex Mixtures, 222–53. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-6530-3_12.
Tolsma, John E., Brian Simpson, Taeshin Park, and Jason Mustakis. "Modeling, Optimization, and Applications of Kinetic Mechanisms with OpenChem." In Chemical Engineering in the Pharmaceutical Industry, 137–53. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470882221.ch10.
Varfolomeev, Sergey, Viktor Bykov, and Svetlana Tsybenova. "Kinetic modelling of processes in the cholinergic synapse. Mechanisms of functioning and control methods." In ORGANOPHOSPHORUS NEUROTOXINS, 127–39. ru: Publishing Center RIOR, 2020. http://dx.doi.org/10.29039/22_127-139.
Varfolomeev, Sergey, Viktor Bykov, and Svetlana Tsybenova. "Kinetic modelling of processes in the cholinergic synapse. Mechanisms of functioning and control methods." In Organophosphorous Neurotoxins, 121–33. ru: Publishing Center RIOR, 2020. http://dx.doi.org/10.29039/chapter_5e4132b600e1c6.27895580.
Froment, G. F. "Kinetic Modeling of Complex Processes. Thermal Cracking and Catalytic Hydrocracking." In Chemical Reactor Technology for Environmentally Safe Reactors and Products, 409–24. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2747-9_16.
Knoth, Oswald, and Ralf Wolke. "A Comparison of Fast Chemical Kinetic Solvers in a Simple Vertical Diffusion Model." In Air Pollution Modeling and Its Application X, 287–94. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-1817-4_32.
Conference papers on the topic "Chemical kinetic modeling":
WESTBROOK, C. "Chemical kinetic modeling of higher hydrocarbon fuels." In 24th Aerospace Sciences Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1986. http://dx.doi.org/10.2514/6.1986-139.
Tamura, Todd, and Simone Hochgreb. "Chemical Kinetic Modeling of the Oxidation of Unburned Hydrocarbons." In International Fuels & Lubricants Meeting & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1992. http://dx.doi.org/10.4271/922235.
Westbrook, Charles K., and William J. Pitz. "Chemical Kinetic Modeling of Combustion of Practical Hydrocarbon Fuels." In 40th Annual Earthmoving Industry Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1989. http://dx.doi.org/10.4271/890990.
Slavinskaya, N. A. "Chemical Kinetic Modeling in Coal Gasification Processes: An Overview." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23362.
Ateka, Ainara, Ander Portillo, Miguel Sanchez-Contador, Javier Bilbao, and Andrés T. Aguayo. "Core-shell catalysts for the direct synthesis of DME. Kinetic modeling." In 14th Mediterranean Congress of Chemical Engineering (MeCCE14). Grupo Pacífico, 2020. http://dx.doi.org/10.48158/mecce-14.dg.05.01.
Havstad, Mark, Salvador M. Aceves, Matthew McNenly, William Piggott, K. Dean Edwards, Robert Wagner, C. Stuart Daw, and Charles E. A. Finney. "Detailed Chemical Kinetic Modeling of Iso-octane SI-HCCI Transition." In SAE 2010 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2010. http://dx.doi.org/10.4271/2010-01-1087.
Curran, H. J., E. M. Fisher, P. A. Glaude, N. M. Marinov, W. J. Pitz, C. K. Westbrook, D. W. Layton, et al. "Detailed Chemical Kinetic Modeling of Diesel Combustion with Oxygenated Fuels." In SAE 2001 World Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-0653.
Mawid, M. A., T. W. Park, B. Sekar, and C. Arana. "Detailed Chemical Kinetic Modeling of JP-8/Jet-A Ignition and Combustion." In ASME Turbo Expo 2005: Power for Land, Sea, and Air. ASMEDC, 2005. http://dx.doi.org/10.1115/gt2005-68829.
Paschkewitz, J., J. Shang, J. Miller, and T. Madden. "An assessment of COIL physical property and chemical kinetic modeling methodologies." In 31st Plasmadynamics and Lasers Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-2574.
Kitamura, Takaaki, Takayuki Ito, Jiro Senda, and Hajime Fujimoto. "Detailed Chemical Kinetic Modeling of Diesel Spray Combustion with Oxygenated Fuels." In SAE 2001 World Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-1262.
Reports on the topic "Chemical kinetic modeling":
PItz, W., C. Westbrook, and O. Herbinet. Chemical Kinetic Modeling of Advanced Transportation Fuels. Office of Scientific and Technical Information (OSTI), January 2009. http://dx.doi.org/10.2172/947237.
Pitz, W., and C. Westbrook. Chemical Kinetic Modeling of Hydrogen Combustion Limits. Office of Scientific and Technical Information (OSTI), April 2008. http://dx.doi.org/10.2172/928549.
Olsen, Mitchell, and Willson. L52248 Investigation of Formaldehyde Chemical Kinetics. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 2004. http://dx.doi.org/10.55274/r0011246.
Pitz, W., C. Westbrook, and E. Silke. Chemical Kinetic Modeling of Combustion of Automotive Fuels. Office of Scientific and Technical Information (OSTI), November 2006. http://dx.doi.org/10.2172/897957.
Koert, D. N., W. J. Pitz, J. W. Bozzelli, and N. P. Cernansky. Chemical kinetic modeling of high pressure propane oxidation and comparison to experimental results. Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/179187.
Koert, D. N., W. J. Pitz, J. W. Bozzelli, and N. P. Cernansky. Chemical kinetic modeling of high pressure propane oxidation and comparison to experimental results. Revision 1. Office of Scientific and Technical Information (OSTI), February 1996. http://dx.doi.org/10.2172/244540.
Linker, Taylor, and Timothy Jacobs. PR-457-18204-R01 Variable Fuel Effects on Legacy Compressor Engines Phase IV - Predictive NOx Modeling. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), May 2019. http://dx.doi.org/10.55274/r0011584.
Maranas, Costas D. Ensemble cell-wide kinetic modeling of anaerobic organisms to support fuels and chemicals production. Office of Scientific and Technical Information (OSTI), November 2018. http://dx.doi.org/10.2172/1481196.
Waganet, R. J., John Duxbury, Uri Mingelgrin, John Hutson, and Zev Gerstl. Consequences of Nonequilibrium Pesticide Fate Processes on Probability of Leaching from Agricultural Lands. United States Department of Agriculture, January 1994. http://dx.doi.org/10.32747/1994.7568769.bard.
Committee on Toxicology. COT FSA PBPK for Regulators Workshop Report 2021. Food Standards Agency, April 2024. http://dx.doi.org/10.46756/sci.fsa.tyy821.