Academic literature on the topic 'Conjugate mixture models'
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Journal articles on the topic "Conjugate mixture models"
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Khalidov, Vasil, Florence Forbes, and Radu Horaud. "Conjugate Mixture Models for Clustering Multimodal Data." Neural Computation 23, no. 2 (February 2011): 517–57. http://dx.doi.org/10.1162/neco_a_00074.
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The problem of multimodal clustering arises whenever the data are gathered with several physically different sensors. Observations from different modalities are not necessarily aligned in the sense there there is no obvious way to associate or compare them in some common space. A solution may consist in considering multiple clustering tasks independently for each modality. The main difficulty with such an approach is to guarantee that the unimodal clusterings are mutually consistent. In this letter, we show that multimodal clustering can be addressed within a novel framework: conjugate mixture models. These models exploit the explicit transformations that are often available between an unobserved parameter space (objects) and each of the observation spaces (sensors). We formulate the problem as a likelihood maximization task and derive the associated conjugate expectation-maximization algorithm. The convergence properties of the proposed algorithm are thoroughly investigated. Several local and global optimization techniques are proposed in order to increase its convergence speed. Two initialization strategies are proposed and compared. A consistent model selection criterion is proposed. The algorithm and its variants are tested and evaluated within the task of 3D localization of several speakers using both auditory and visual data.
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Gustafson, Paul. "The effect of mixing-distribution misspecification in conjugate mixture models." Canadian Journal of Statistics 24, no. 3 (September 1996): 307–18. http://dx.doi.org/10.2307/3315741.
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Song, Yuntao, Anrong Li, Hui Li, Xianfeng Li, Zeao Huang, Junbao Yang, Yi Ding, and Grace Szu. "Abstract 2094: Conjugates of TLR9 and STING agonists achieved profound synergistic effects in vitro and in vivo." Cancer Research 82, no. 12_Supplement (June 15, 2022): 2094. http://dx.doi.org/10.1158/1538-7445.am2022-2094.
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Abstract Introduction: Both Toll-like receptor 9 (TLR9) and STING pathways are two important pathways involved in immune activation. We reasoned that concurrent activation of TLR9 and STING pathways could activate immunity with an efficacy and safety profile that could not be achieved by activating either pathway alone, and we designed a series of conjugates where TLR9 and STING agonists were linked together by a releasable or stable linker. The conjugates have been evaluated in in vitro assays and in vivo mouse models in comparison with TLR9 agonist or STING agonist alone and combination of the two agonists. Methods: Cellular potency was assessed using THP-1 monocyte cells and human PBMC. In vivo efficacy was evaluated in mouse tumor models, where tumor cells were inoculated into either the right flank or both flanks of C57BL/6 or BALB/c mice, test compounds were injected intratumorally into the right flank three times at every three days when tumors reached a volume of 90-100 mm3, muDX400 was dosed via IP injection six times at every four days. In MC38 murine model, compounds-treated mice free from tumor for 30 days were re-challenged with MC38 tumor cells. Results: Conjugates CS-2554, 2571 and 2600 showed five to ten folds improvement in potency over the corresponding STING agonist alone or a mixture of the corresponding STING and TLR9 agonists (1/1molar ratio) in THP1 assay, a similar fold of increase in EC50 was observed in human PBMC assay, where induction of IFNα, IFNβ, TNFα and IL6 were measured. In MC38 murine model, CS-2554 at the dose of 9 ug/injection resulted in CR in all treated mice; whereas no CR was obtained when a mixture of an equivalent amount of the corresponding STING agonist and TLR9 agonist was used. The tumor-free mice remained tumor-free after re-challenge study. In MC38 dual tumor model, when combined with aPD-1, a mixture of 50 ug of TLR9 agonist and 5 ug of STING agonist resulted in CR in 38% treated mice, whereas the same level was achieved with only 4 ug of the corresponding conjugate CS-2571. Comparisons of a conjugate and either the corresponding agonist alone or the two in combination were also carried out in CT26 dual tumor model. On day 13, for the injected tumor, the tumor growth inhibition rate (TGI) of an equivalent amount of a TLR9 agonist, a STING agonist, a mixture of the two, and the corresponding conjugate CS-2600 was 29.65%, 31.3%, 61.00%, and 91.93%, respectively. For the distal tumor, only the conjugate CS-2600 showed significant inhibition of tumor growth with 57% TGI, whereas no tumor growth inhibition was observed with a TLR9 agonist, a STING agonist, or a mixture of the two. Conclusions: The conjugates harnessed significant synergy between TLR9 and STING pathways in vitro and in vivo and resulted in over ten times enhancement of potency in certain assays over either agent alone or a combination of the two. The preclinical studies of the conjugates support clinical evaluation of this class of novel compounds. Citation Format: Yuntao Song, Anrong Li, Hui Li, Xianfeng Li, Zeao Huang, Junbao Yang, Yi Ding, Grace Szu. Conjugates of TLR9 and STING agonists achieved profound synergistic effects in vitro and in vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2094.
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Ali, Sajid, Muhammad Aslam, and Mohsin Ali. "Heterogeneous data analysis using a mixture of Laplace models with conjugate priors." International Journal of Systems Science 45, no. 12 (March 4, 2013): 2619–36. http://dx.doi.org/10.1080/00207721.2013.775381.
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Jun-Uk Chu and Yun-Jung Lee. "Conjugate-Prior-Penalized Learning of Gaussian Mixture Models for Multifunction Myoelectric Hand Control." IEEE Transactions on Neural Systems and Rehabilitation Engineering 17, no. 3 (June 2009): 287–97. http://dx.doi.org/10.1109/tnsre.2009.2015177.
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Ali, Abdullah Masoud, Matteo Angelino, and Aldo Rona. "Physically Consistent Implementation of the Mixture Model for Modelling Nanofluid Conjugate Heat Transfer in Minichannel Heat Sinks." Applied Sciences 12, no. 14 (July 11, 2022): 7011. http://dx.doi.org/10.3390/app12147011.
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As much as two-phase mixture models resolve more physics than single-phase homogeneous models, their inconsistent heat transfer predictions have limited their use in modelling nanofluid cooled minichannel heat sinks. This work investigates, addresses, and solves this key shortcoming, enabling reliable physically sound predictions of minichannel nanoflows, using the two-phase mixture model. It does so by applying the single-phase and the two-phase mixture model to a nine-passages rectangular minichannel, 3 mm deep and 1 mm wide, cooled by a 1% by volume suspension of Al2O3 nanoparticles in water, over the Reynolds number range 92 to 455. By varying the volume fraction αnf of the second phase between 2% and 50%, under a constant heat flux of 16.67 W/cm2 and 30 Celsius coolant inflow, it is shown that the two-phase mixture model predicts heat transfer coefficient, pressure loss, friction factor, exergy destruction rate, exergy expenditure rate, and second law efficiency values converging to the single-phase model ones at increasing αnf. A two-phase mixture model defined with 1% second phase volume fraction and 100% nanoparticles volume fraction in the second phase breaks the Newtonian fluid assumption within the model and produces outlier predictions. By avoiding this unphysical regime, the two-phase mixture model matched experimental measurements of average heat transfer coefficient to within 1.76%. This has opened the way for using the two-phase mixture model with confidence to assess and resolve uneven nanoparticle dispersion effects and increase the thermal and mass transport performance of minichannels.
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Colichio, Gabriela B. C., Giuliana S. Oliveira, Tasson C. Rodrigues, Maria Leonor S. Oliveira, and Eliane N. Miyaji. "Efficacy of a Protein Vaccine and a Conjugate Vaccine Against Co-Colonization with Vaccine-Type and Non-Vaccine Type Pneumococci in Mice." Pathogens 9, no. 4 (April 10, 2020): 278. http://dx.doi.org/10.3390/pathogens9040278.
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Widespread use of pneumococcal conjugate vaccines (PCVs) has led to substitution of vaccine-type (VT) strains by non-vaccine type (NVT) strains in nasopharyngeal carriage. We compared the efficacy of PCV13 and a nasal protein formulation containing pneumococcal surface protein A (PspA) adjuvanted with the whole-cell pertussis vaccine (wP) in the protection against co-colonization challenge models in mice with VT and NVT strains expressing different PspAs. Immunized mice were challenged with two different mixtures: i. VT4 (PspA3) + NVT33 (PspA1) and ii. VT23F (PspA2) + NVT15B/C (PspA4). Results from the first mixture showed a reduction in loads of VT4 strain in the nasopharynx of mice immunized with PCV13. A statistical difference between the loads of the VT and NVT strains was observed, indicating a competitive advantage for the NVT strain in PCV13-immunized animals. In the second mixture, no reduction was observed for the VT23F strain, probably due to low levels of anti-23F polysaccharide IgG induced by PCV13. Interestingly, a combination of the PspA formulation containing wP with PCV13 led to a reduction in colonization with both strains of the two mixtures tested, similar to the groups immunized nasally with wP or PspA plus wP. These results indicate that a combination of vaccines may be a useful strategy to overcome pneumococcal serotype replacement.
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Hamadani, Mehdi, Christopher N. Graham, Laura Liao, Katherine H. Zhang, Hannah Strat, David Ungar, Weiyun Z. Ai, Lei Chen, and Carmelo Carlo-Stella. "Long-term survival projections of loncastuximab tesirine-treated patients in relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL)." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e19551-e19551. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e19551.
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e19551 Background: Loncastuximab tesirine (loncastuximab tesirine-lpyl; Lonca) is an FDA approved CD19-directed antibody-drug conjugate for R/R DLBCL. From the LOTIS-2 trial primary data cut (April 6, 2020), overall response rate was 48.3% and median overall survival (OS) was 9.9 months. The OS Kaplan-Meier (KM) plot displayed a survival plateau suggesting the presence of long-term survivors (LTS). Survival analyses were conducted on a more mature data cut (March 1, 2021; median follow-up = 1.7 years, follow-up completeness at median = 81%) to estimate the percentage of LTS and expected lifetime survival (mean OS) for lonca-treated patients. Methods: Consistent with studies of other R/R DLBCL treatments, identified through a literature review, parametric and mixture cure models were fit utilizing multiple distributions. Flexible cubic spline (hazard scale 1-3 knots) and non-mixture cure analyses were also conducted. Age- and gender-matched United States life table hazards were used in projections for LTS and to ensure modeled hazards were not less than the general population. Best-fit models were determined through fit statistics, KM and fitted curve overlays, and clinical plausibility. The best-fit model from each method was a candidate for overall best fit. A hybrid model following the best-fit parametric/spline model to a defined time point and switching to general population mortality was also constructed. Results: Mixture and non-mixture cure models fit best (individual best fits gamma and Weibull, respectively). Parametric and spline models (individual best fits log-normal and 2 knot models, respectively) did not fit the observed data well nor fit the clinical expectation of long-term survival. Due to better fit, spline models were used in the hybrid model. LTS from the mixture cure and non-mixture cure models were 24-26%. Mixture cure, non-mixture cure, and hybrid model with a 2-year switch point were consistent in survival predictions (6.11-6.23 years). In a sensitivity analysis with 3-year switch point in the hybrid model, the estimated survival was shorter due to the switch point being below the observed survival plateau. Table presents full survival results and fit statistics. Conclusions: The observed survival plateau suggests lonca-treated patients may include LTS. Mixture cure, non-mixture cure, and hybrid models fit the trial data well and align on survival projections (6.11-6.23 years). Additional follow-up may help refine the switch point of the hybrid model and confirm presence of LTS.[Table: see text]
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Hamadani, Mehdi, Christopher N. Graham, Laura Liao, Katherine H. Zhang, Hannah Strat, David Ungar, Weiyun Z. Ai, Lei Chen, and Carmelo Carlo-Stella. "Long-term survival projections of loncastuximab tesirine-treated patients in relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL)." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): e19551-e19551. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e19551.
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e19551 Background: Loncastuximab tesirine (loncastuximab tesirine-lpyl; Lonca) is an FDA approved CD19-directed antibody-drug conjugate for R/R DLBCL. From the LOTIS-2 trial primary data cut (April 6, 2020), overall response rate was 48.3% and median overall survival (OS) was 9.9 months. The OS Kaplan-Meier (KM) plot displayed a survival plateau suggesting the presence of long-term survivors (LTS). Survival analyses were conducted on a more mature data cut (March 1, 2021; median follow-up = 1.7 years, follow-up completeness at median = 81%) to estimate the percentage of LTS and expected lifetime survival (mean OS) for lonca-treated patients. Methods: Consistent with studies of other R/R DLBCL treatments, identified through a literature review, parametric and mixture cure models were fit utilizing multiple distributions. Flexible cubic spline (hazard scale 1-3 knots) and non-mixture cure analyses were also conducted. Age- and gender-matched United States life table hazards were used in projections for LTS and to ensure modeled hazards were not less than the general population. Best-fit models were determined through fit statistics, KM and fitted curve overlays, and clinical plausibility. The best-fit model from each method was a candidate for overall best fit. A hybrid model following the best-fit parametric/spline model to a defined time point and switching to general population mortality was also constructed. Results: Mixture and non-mixture cure models fit best (individual best fits gamma and Weibull, respectively). Parametric and spline models (individual best fits log-normal and 2 knot models, respectively) did not fit the observed data well nor fit the clinical expectation of long-term survival. Due to better fit, spline models were used in the hybrid model. LTS from the mixture cure and non-mixture cure models were 24-26%. Mixture cure, non-mixture cure, and hybrid model with a 2-year switch point were consistent in survival predictions (6.11-6.23 years). In a sensitivity analysis with 3-year switch point in the hybrid model, the estimated survival was shorter due to the switch point being below the observed survival plateau. Table presents full survival results and fit statistics. Conclusions: The observed survival plateau suggests lonca-treated patients may include LTS. Mixture cure, non-mixture cure, and hybrid models fit the trial data well and align on survival projections (6.11-6.23 years). Additional follow-up may help refine the switch point of the hybrid model and confirm presence of LTS.[Table: see text]
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Ruiz, A., P. E. Lopez-de-Teruel, and M. C. Garrido. "Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians." Journal of Artificial Intelligence Research 9 (October 1, 1998): 167–217. http://dx.doi.org/10.1613/jair.533.
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This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of finite mixture models, conjugate families and factorization. Both the joint probability density of the variables and the likelihood function of the (objective or subjective) observation are approximated by a special mixture model, in such a way that any desired conditional distribution can be directly obtained without numerical integration. We have developed an extended version of the expectation maximization (EM) algorithm to estimate the parameters of mixture models from uncertain training examples (indirect observations). As a consequence, any piece of exact or uncertain information about both input and output values is consistently handled in the inference and learning stages. This ability, extremely useful in certain situations, is not found in most alternative methods. The proposed framework is formally justified from standard probabilistic principles and illustrative examples are provided in the fields of nonparametric pattern classification, nonlinear regression and pattern completion. Finally, experiments on a real application and comparative results over standard databases provide empirical evidence of the utility of the method in a wide range of applications.
Dissertations / Theses on the topic "Conjugate mixture models"
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Khalidov, Vasil. "Modèles de mélanges conjugués pour la modélisation de la perception visuelle et auditive." Grenoble, 2010. http://www.theses.fr/2010GRENM064.
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Dans cette thèse, nous nous intéressons à la modélisation de la perception audio-visuelle avec une tête robotique. Les problèmes associés, notamment la calibration audio-visuelle, la détection, la localisation et le suivi d'objets audio-visuels sont étudiés. Une approche spatio-temporelle de calibration d'une tête robotique est proposée, basée sur une mise en correspondance probabiliste multimodale des trajectoires. Le formalisme de modèles de mélange conjugué est introduit ainsi qu'une famille d'algorithmes d'optimisation efficaces pour effectuer le regroupement multimodal. Un cas particulier de cette famille d'algorithmes, notamment l'algorithme EM conjugue, est amélioré pour obtenir des propriétés théoriques intéressantes. Des méthodes de détection d'objets multimodaux et d'estimation du nombre d'objets sont développées et leurs propriétés théoriques sont étudiées. Enfin, la méthode de regroupement multimodal proposée est combinée avec des stratégies de détection et d'estimation du nombre d'objets ainsi qu'avec des techniques de suivi pour effectuer le suivi multimodal de plusieurs objets. La performance des méthodes est démontrée sur des données simulées et réelles issues d'une base de données de scénarios audio-visuels réalistes (base de données CAVA)In this thesis, the modelling of audio-visual perception with a head-like device is considered. The related problems, namely audio-visual calibration, audio-visual object detection, localization and tracking are addressed. A spatio-temporal approach to the head-like device calibration is proposed based on probabilistic multimodal trajectory matching. The formalism of conjugate mixture models is introduced along with a family of efficient optimization algorithms to perform multimodal clustering. One instance of this algorithm family, namely the conjugate expectation maximization (ConjEM) algorithm is further improved to gain attractive theoretical properties. The multimodal object detection and object number estimation methods are developed, their theoretical properties are discussed. Finally, the proposed multimodal clustering method is combined with the object detection and object number estimation strategies and known tracking techniques to perform multimodal multiobject tracking. The performance is demonstrated on simulated data and the database of realistic audio-visual scenarios (CAVA database)
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Dahl, David Boyack. "Conjugate dirichlet process mixture models : efficient sampling, gene expression, and clustering /." 2004. http://www.library.wisc.edu/databases/connect/dissertations.html.
Full textConference papers on the topic "Conjugate mixture models"
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Jun-Uk Chu and Yun-Jung Lee. "Conjugate prior penalized learning of Gaussian mixture models for EMG pattern recognition." In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iros.2007.4399330.
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Fontanesi, Stefano, Simone Malaguti, and E. V. McAssey. "CFD Methodology Assessment for the Investigation of Convective Heat Transfer Properties of Engine Coolants Under Boiling Conditions." In ASME 2009 Internal Combustion Engine Division Spring Technical Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/ices2009-76056.
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The paper presents a combined experimental and numerical program directed at defining a cost/effective methodology for conjugate heat transfer CFD simulations of engine water cooling jackets. As a first step in the process, deficiencies in current numerical strategies for the analysis of conjugate heat transfer problems under typical engine operating conditions are exposed and commented. Results are shown form a wide validation program based on the comparison between experimental measurements from a test facility at Villanova University and CFD predictions at the University of Modena. On the experimental side, the test apparatus consists of a test section, pump, accumulator tank, rejection heat exchanger and required pumping. The test section is provided with a constant volumetric flow rate, and consists of a cylindrical aluminum body with a drilled horizontal flow channel. The section is heated by ten cartridge heaters located at a constant radial distance from the cylinder axis. The test section is connected to the flow loop by means of two calming sections, respectively at the cylinder inlet and exit. Twenty thermocouples are used to measure the test section local temperature along a radial plane cutting the cylinder. Water / ethylene-glycol binary mixture and pure water are tested and compared during the experimental program, in order to reproduce a set of thermal situations as close as possible to actual engine cooling system operation. On the CFD side, an extensive program reproducing the experiments is carried out in order to assess the predictive capabilities of some of the most commonly used eddy viscosity models available in literature. Both non-evaporating and evaporating conditions are tested, showing severe limitations to the use of simplified boiling models to correctly capture the complex interaction between turbulent boundary layer and vapor bubble dynamics. In order to overcome the above stated deficiencies under boiling conditions, a methodology is then proposed to both improve the accuracy of the CFD forecasts and reduce the computational costs of the simulations. A few preliminary results from the validation process are shown and briefly discussed at the end of the paper.
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Cai, D., L. L. Zheng, H. Zhang, Y. Wan, A. V. Hariharan, and M. Chandra. "CFD-Aided Design for Polysilicon Production System." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33077.
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This paper presents the CFD-aided design for polysilicon production system that utilizes an innovative technique of silicon tube-based CVD process. Virtual experiment has been conducted, which involves the development of a complex computational model capable of describing multi-component fluid flow, gas/surface chemistry, conjugate heat transfer, thermal radiation, and species transport. Theoretical analysis has been conducted and a desirable velocity regime for silane and hydrogen mixture has been found. The simulations of the flow field, temperature and species transport have been performed for various reactor geometries, operating conditions (e.g., flow rates of primary silane and secondary hydrogen gases), and heating power design. The deposition rate of polysilicon has been derived analytically as well as computationally. The effects of various conditions on deposition rate have been investigated, and optimal geometry and operating conditions have been obtained for the targeted deposition rate.
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Vashishtha, Ashish, Sajjad Yousefian, Graham Goldin, Karin Frojd, Sandeep Jella, Gilles Bourque, and Rory F. D. Monaghan. "CFD-CRN Study of NOx Formation in a High-Pressure Combustor Fired With Lean Premixed CH4 / H2 - Air Mixtures." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14819.
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Abstract The main motivation of this study is to investigate detailed NOx and CO formation in high-pressure dump combustor fired with lean premixed methane-air mixture using CFD-CRN hybrid approach. Further, this study is extended to investigate the effect of H2 enrichment on emission formation in the same combustor. Three-dimensional steady RANS CFD simulations have been performed using a Flamelet Generated Manifold (FGM) model in Simcenter STAR-CCM+ 2019.2 with the DRM22 reduced mechanism. The CFD simulations have been modelled along with all three heat transfers modes: conduction, convection and radiation. The conjugate heat transfer (CHT) approach and participating media radiation modelling have been used here. Initially, CFD simulations are performed for five lean equivalence ratios (ϕ = 0.43–0.55, Tinlet = 673 K, Vinlet = 40 m/s) of pure methane-air mixture operating at 5 bar. The exit temperature and flame-length are compared with available experimental data. The automatic chemical reactor network has been constructed from CFD data and solved using the recently developed reactor network module of Simcenter STAR-CCM+ 2019.2 in a single framework for each cases. It is found out that the CRNs up to 10,000 PSRs can provide adequate accuracy in exit NOx predictions compared to experiments for pure methane cases. The contribution of NOx formation pathway, changes from N2O intermediate to thermal NO as equivalence ratio increases. Further studies are performed for two equivalence ratios (ϕ = 0.43 and 0.50 to simulate the impact of H2 addition (up to 40% by volume) on NOx formation pathways and CO emission. It is found out here that the contribution from NNH pathway increases for leaner equivalence ratio cases (ϕ = 0.43), while thermal pathway slightly increases for ϕ = 0.50 with increase in H2 content from 0% to 40%.
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Hu, Xizhuo, Zhi Tao, Jianqin Zhu, and Haiwang Li. "Numerical Study of Pyrolysis Effects on Supercritical-Pressure Flow and Conjugate Heat Transfer of N-Decane in the Square Channel." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-63970.
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Regenerative cooling has become the most effective and practical method of thermal protection to the high temperature structures of scramjet engines. Pyrolytic reactions of endothermic hydrocarbon fuel have significant influence on the regenerative cooling process at high temperature due to a large amount of heat absorption and fluid components change. In this paper, a three-dimensional (3D) model is developed for numerically investigating the flow and heat transfer of pyrolytic reacted n-decane in the square engine cooling channel under supercritical pressure with asymmetrical heating imposed on the bottom channel surface. The one-step global pyrolytic reaction mechanism consisting of 18 species is adopted to simulate the pyrolysis process of n-decane. The governing equations for species continuum, momentum, energy and the k-ω turbulence equation are properly solved, with accurate computations of the thermophysical and transport properties of fluid mixture, which undergo drastic variations and exert strong impact on fluid flow and heat transfer process in the channel. The numerical method is validated based on the good agreement between the current predictions and the experimental data. Numerical studies of the pyrolysis effects on the characteristics of flow resistance and conjugate heat transfer under various operating conditions have been conducted. Results reveal that pyrolysis intensively takes place in high temperature regions. The pressure drop along the channel steeply rise due to the further fluid acceleration caused by pyrolysis. It is found that the variations of heat flux at the bottom, top and side fluid-solid-interface walls are totally different. Pyrolysis could lead to greater heat transfer enhancement at the bottom interface, consequently, more heat is transferred into the fluid region through the bottom interface. The dual effects of heat absorption and enhanced heat transfer caused by pyrolysis produce strong influence on the wall temperature. The mechanism of these physicochemical phenomena are also analyzed in detail, which is conducive to fundamentally understand the complicated physicochemical process of regenerative cooling. The present work has profound significance for the development of regenerative cooling technology.
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Samale, Anil P., and El Mostafa El Ghazzani. "Investigation of Coupling Guard Temperature Rise Using Advanced CFD Analysis." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14110.
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Abstract Increasingly, the turbomachinery industry is facing issues related to high temperatures and oil misting inside coupling guards. This leads to machinery downtimes and loss of revenue. Many in the turbomachinery industry are investing significant time and effort to reduce heat generation inside coupling guards. The present computational fluid dynamics (CFD) investigation of Air+Oil flow and heat transfer in the coupling guard was conducted to investigate these issues. In prior investigations, the emphasis has been mostly placed on predicting temperature by modeling pure airflow in the coupling guard. This paper presents CFD simulations completed under two conditions: 1) with pure AIR -in a Single phase and 2) a multi-phase fluid combining Air+Oil. The coupling guard geometry is cylindrical in nature. Given the symmetry in the geometry, a 90-degree sector was modeled, allowing significantly smaller meshes and lower run times without compromising quality. In this paper, the modeled geometry includes both Fluid + Solid domains that do not contain an inlet or outlet. This work explains the CFD methodology for multiphase and conjugate heat transfer analysis. The objective of this paper is to predict the temperature on the coupling guard considering Air + Oil flow and heat transfer. The domain evaluated consists of several stationary and rotating components. The CFD domain used for the conjugate heat transfer analysis consists of fluid between the rotating shaft and the stationary cover. The solid domain includes the coupling guard cover. The commercially available software ANSYS CFX 18.1 was used. The mesh was created using Tetrahedral/Prism elements. Both steady-state and unsteady CFD analyses were completed. As noted, multiphase CFD analyses were carried out using Air and Oil VG68 as a homogenous type of mixture. Detailed flow field characteristics (total and static temperature, pressure, streamlines colored by Mach number, etc.) and CFD-predicted temperatures are compared between the Pure Air and Air+Oil simulations. Also, available measurements were used to validate the CFD results. Temperature results obtained from the CFD simulations were found to be in good agreement with the experimental data. The CFD modeling approach developed can be used to design coupling guards with lower surface temperatures.
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Wang, Bing, Jinhua Wang, and Haijun Jia. "CFD Simulation of Natural Ventilation Performance of the Interim Region in Spent Fuel Dry-Storage System of HTR-PM." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-60238.
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The spent fuel dry-storage system of High Temperature Reactor-Pebble bed Modules (HTR-PM) in China is designed to consist of 3 separate regions, with each composed of multiple storage wells. Cold air is distributed to 8 parallel wells in the interim region from a bifurcation chamber, and then heated by vertical placed canisters in each well before gathering in a mixture chamber. In accident condition, the decay heat in interim region will be discharged by open-cycle natural ventilation. In this paper, thermal performance of the interim region by natural ventilation was investigated by a step-by-step scheme. Firstly, the resistance characteristics of wells loaded with different numbers of canisters and bifurcation chamber were studied with CFD code, and were formulated into momentum sources of porous media. Then, equivalent model of the system with porous media regions was employed to simulate the flow distribution of the system. Two different operation conditions (half-loaded condition and full-loaded condition) were studied in this step and hottest well were located. Finally, a refined model of the hottest well with minimized and necessary assumption was employed to investigate the conjugate heat transfer coupled with thermal radiation process, and to obtain the internal temperature profile of the hottest well. The results showed that the total mass flow of natural ventilation is 5.53 kg/s under half-loaded condition (20 canisters, 156.72 kW of decay heat) and 4.83 kg/s under full-loaded condition (40 canisters, 192.37 kW of decay heat). Hottest well was the well-1th under half-loaded condition, where maximal temperatures of concrete walls, steel barrel, canisters and spent fuel pebble bed inside the canister were 86.5 °C, 142.2 °C, 279.5 °C, 484.9 °C, respectively. The results demonstrate that the interim region of dry-storage system satisfies the temperature limitation of component materials in accident condition.
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Yadav, Rakesh, Ishan Verma, Abhijit Modak, and Shaoping Li. "A Fully Non-Adiabatic Flamelet Generated Manifold Model for High Fidelity Modeling of Turbulent Combustion in Gas Turbine Like Conditions." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15814.
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Abstract Flamelet Generated Manifold (FGM) has proven to be an efficient approach to model turbulent combustion across different regimes of combustion. The manifolds are generally created by solving laminar premixed or opposed flow configurations. Gas turbine combustors often involve many strong non-adiabatic events such as multiple temperature boundaries, quenching from cooling and effusion holes, conjugate heat transfer, soot radiation interaction, phase change from spray and the modulation of inlet conditions. The adiabatic assumption of the underlying flamelet generation in the FGM is, therefore, prone to errors in the prediction of flame speed, liner temperatures, and pollutant formation. In this work, a novel approach to generate fully non-adiabatic manifold is proposed and validated. The FGM manifold is created using a series of non-adiabatic flamelets, each flamelet is solved in one-dimensional physical space. The non-adiabatic flamelets are generated with an optimal combination of freely propagating and burner stabilized flames. This hybrid method of the flamelet configuration allows modeling large heat gain and loss without encountering any unrealistic temperature in the flamelet solution. Such fully non-adiabatic flamelets are then convoluted to generate a five-dimensional Non-adiabatic Flamelet Generated Manifold (NFGM) Probability Density Function (PDF.). The average properties such as temperature, mixture density, species concentration, rate of reaction, etc. from PDF are then coupled with the CFD solution. The non-adiabatic flamelets and corresponding NFGM is implemented into ANSYS Fluent software version 2020R1. This approach is validated first for canonical cases, followed by gas turbine like conditions of swirl stabilized methane fueled turbulent flame, developed at DLR Stuttgart as the PRECCINSTA combustor. The experimental data for this combustor is available for multiple operating conditions. A stable operating point (φ = 0.83, P = 30 kW) is chosen. The proposed nonadiabatic NFGM is used with Stress blended eddy simulation (SBES). The current NFGM-SBES results are compared with experimental data as well as the previously published works. The impact of modeling heat release in flamelet is used to analyze the M-shape versus V-shape flame transition and the peaks of the carbon monoxide in mixing shear layers. The findings from the current work, in terms of accuracy, validity and best practices while modeling NFGM-SBES are discussed and summarized. The improved results of NFGM compared to adiabatic FGM are encouraging and provides a potential high-fidelity tool for accurate, yet efficient modeling of turbulent combustion inside gas turbines.
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Chahine, Nadeen O., Eric G. Lima, Clark T. Hung, and Gerard A. Ateshian. "Effect of Dynamic Deformational Loading on the Transport of Dextran Molecules Into Agarose Gels." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-61368.
Full textAbstract:
The poor intrinsic healing capacity of articular cartilage has led to a number of attempts to engineer a replacement tissue [1]. One of these approaches, termed functional tissue engineering, suggests that the application of mechanical preconditioning, mimicking the in vivo loading environment, may enhance the development of material properties in these constructs [2,3]. Using this approach, our previous studies have demonstrated that dynamic loading (DL) increases the mechanical properties of chondrocyte-seeded agarose hydrogels relative to free swelling (FS) controls [4–6]. One mechanism by which the increase in mechanical properties occurs is hypothesized to be due to enhanced transport of nutrients and/or growth factors under dynamic loading [7]. The goal of the current study is to determine the effect of dynamic loading on the transport of neutral dextran molecules into agarose gels. Dextran, a neutral and generally inert solute commonly used in diffusion and transport studies, is used in its fluorophore-conjugated form thus making it possible to track the solute and quantify its content inside a hydrogel. We hypothesize that the uptake of dextran molecules into the agarose gels will be significantly enhanced under the influence of physiological dynamic deformation loading. Two varying molecular weights of dextran, 3 kDa and 70 kDa, were chosen in this study to ascertain a wide range of transport behaviors, and to interpret the experimental results in the context of a recently developed mixture theory model for the transport of neutral solutes in a neutrally charged gel, such as agarose [8].
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Ugarte, Sergio, Mohamad Metghalchi, and James C. Keck. "Methanol Oxidation Induction Times Using the Rate-Controlled Constrained-Equilibrium Method." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55289.
Full textAbstract:
Methanol oxidation has been modeled using the Rate-Controlled Constrained-Equilibrium method (RCCE). In this method, composition of the system is determined by constraints rather than by species. Since the number of constraints can be much smaller than the number of species present, the number of rate equations required to describe the time evolution of the system can be considerably reduced. In the present paper, C1 chemistry with 29 species and 140 reactions has been used to investigate the oxidation of stoichiometric methanol/oxygen mixture at constant energy and volume. Three fixed elemental constraints: elemental carbon, elemental oxygen and elemental hydrogen and from one to nine variable constraints: moles of fuel, total number of moles, moles of free oxygen, moles of free oxygen, moles of free valence, moles of fuel radical, moles of formaldehyde H2CO, moles of HCO, moles of CO and moles of CH3O were used. The four to twelve rate equations for the constraint potentials (LaGrange multipliers conjugate to the constraints) were integrated for a wide range of initial temperatures and pressures. As expected, the RCCE calculations gave correct equilibrium values in all cases. Only 8 constraints were required to give reasonable agreement with detailed calculations. Results of using 9 constraints showed compared very well to those of the detailed calculations at all conditions. For this system, ignition delay times and major species concentrations were within 0.5% to 5% of the values given by detailed calculations. Adding up to 12 constraints improved the accuracy of the minor species mole fractions at early times, but only had a little effect on the ignition delay times. RCCE calculations reduced the time required for input and output of data in 25% and 10% when using 8 and 9 constraints respectively. In addition, RCCE calculations gave valuable insight into the important reaction paths and rate-limiting reactions involved in methanol oxidation.