Analysis of process variables via CFD to evaluate the performance of a FCC riser

Feedstock conversion and yield products are studied through a 3D model simulating the main reactor of the fluid catalytic cracking (FCC) process. Computational fluid dynamic (CFD) is used with Eulerian-Eulerian approach to predict the fluid catalytic cracking behavior. The model considers 12 lumps with catalyst deactivation by coke and poisoning by alkaline nitrides and polycyclic aromatic adsorption to estimate the kinetic behavior which, starting from a given feedstock, produces several cracking products. Different feedstock compositions are considered. The model is compared with sampling data at industrial operation conditions. The simulation model is able to represent accurately the products behavior for the different operating conditions considered. All the conditions considered were solved using a solver ANSYS CFX 14.0. The different operation process variables and hydrodynamic effects of the industrial riser of a fluid catalytic cracking (FCC) are evaluated. Predictions from the model are shown and comparison with experimental conversion and yields products are presented; recommendations are drawn to establish the conditions to obtain higher product yields in the industrial process

Pseudospectral Model Predictive Control under Partially Learned Dynamics

Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underlying parametric model. In the field of robotics, a lack of model knowledge can be overcome with machine learning techniques, utilizing measurements to build a dynamical model from the data. This paper aims to take the middle ground between these two approaches by introducing a semi-parametric representation of the underlying system dynamics. Our goal is to leverage the considerable information contained in a traditional physics based model and combine it with a data-driven, non-parametric regression technique known as a Gaussian Process. Integrating this semi-parametric model with model predictive pseudospectral control, we demonstrate this technique on both a cart pole and quadrotor simulation with unmodeled damping and parametric error. In order to manage parametric uncertainty, we introduce an algorithm that utilizes Sparse Spectrum Gaussian Processes (SSGP) for online learning after each rollout. We implement this online learning technique on a cart pole and quadrator, then demonstrate the use of online learning and obstacle avoidance for the dubin vehicle dynamics.Comment: Accepted but withdrawn from AIAA Scitech 201

Monitoring luminous yellow massive stars in M33: new yellow hypergiant candidates

The evolution of massive stars surviving the red supergiant (RSG) stage remains unexplored due to the rarity of such objects. The yellow hypergiants (YHGs) appear to be the warm counterparts of post-RSG classes located near the Humphreys-Davidson upper luminosity limit, which are characterized by atmospheric instability and high mass-loss rates. We aim to increase the number of YHGs in M33 and thus to contribute to a better understanding of the pre-supernova evolution of massive stars. Optical spectroscopy of five dust-enshrouded YSGs selected from mid-IR criteria was obtained with the goal of detecting evidence of extensive atmospheres. We also analyzed BVI photometry for 21 of the most luminous YSGs in M33 to identify changes in the spectral type. To explore the properties of circumstellar dust, we performed SED-fitting of multi-band photometry of the 21 YSGs. We find three luminous YSGs in our sample to be YHG candidates, as they are surrounded by hot dust and are enshrouded within extended, cold dusty envelopes. Our spectroscopy of star 2 shows emission of more than one H$\alpha$ component, as well as emission of CaII, implying an extended atmospheric structure. In addition, the long-term monitoring of the star reveals a dimming in the visual light curve of amplitude larger than 0.5 mag that caused an apparent drop in the temperature that exceeded 500 K. We suggest the observed variability to be analogous to that of the Galactic YHG $\rho$ Cas. Five less luminous YSGs are suggested as post-RSG candidates showing evidence of hot or/and cool dust emission. We demonstrate that mid-IR photometry, combined with optical spectroscopy and time-series photometry, provide a robust method for identifying candidate YHGs. Future discovery of YHGs in Local Group galaxies is critical for the study of the late evolution of intermediate-mass massive stars.Comment: 24 pages, 12 figures, 7 Tables. A&A in pres

Comparison of the extended linear sigma model and chiral perturbation theory

The pion-nucleon scattering amplitudes are calculated in tree approximation with the use of the extended linear sigma model (ELSM) as well as heavy baryon chiral perturbation theory (HB$\chi$PT), and the non-relativistic forms of the ELSM results are compared with those of HB$\chi$PT. We find that the amplitudes obtained in ELSM do not agree with those derived from the more fundamental effective approach, HB$\chi$PT.Comment: 7 page

Cirrus cloud properties derived from coincident GOES and lidar data during the 1986 FIRE Cirrus Intensive Field Observations (IFO)

One of the main difficulties in detecting cirrus clouds and determining their correct altitude using satellite measurements is their nonblackness. In the present algorithm (Rossow et al., 1985) used by the International Satellite Cloud Climatology Project (ISCCP), the cirrus cloud emissivity is estimated from the derived cloud reflectance using a theoretical model relating visible (VIS, 0.65 micron) optical depth to infrared (IR, 10.5 micron) emissivity. At this time, it is unknown how accurate this approach is or how the derived cloud altitude relates to the physical properties of the cloud. The First ISCCP Regional Experiment (FIRE) presents opportunities for determining how the observed radiances depend on the cloud properties. During the FIRE Cirrus Intensive Field Observations (IFO, see Starr, 1987), time series of cloud thickness, height, and relative optical densities were measured from several surface-based lidars. Cloud microphysics and radiances at various wavelengths were also measured simultaneously over these sites from aircraft at specific times during the IFO (October 19 to November 2, 1986). Satellite-observed radiances taken simultaneously can be matched with these data to determine their relationships to the cirrus characteristics. The first step is taken toward relating all of these variables to the satellite observations. Lidar-derived cloud heights are used to determine cloud temperatures which are used to estimate cloud emissivities from the satellite IR radiances. These results are then correlated to the observed VIS reflectances for various solar zenith angles

Massive Hyper-Kahler Sigma Models and BPS Domain Walls

With the non-Abelian Hyper-Kahler quotient by U(M) and SU(M) gauge groups, we give the massive Hyper-Kahler sigma models that are not toric in the N=1 superfield formalism. The U(M) quotient gives N!/[M! (N-M)!] (N is a number of flavors) discrete vacua that may allow various types of domain walls, whereas the SU(M) quotient gives no discrete vacua. We derive BPS domain wall solution in the case of N=2 and M=1 in the U(M) quotient model.Comment: 16 pages, 1 figure, contribution to the Proceedings of the International Conference on "Symmetry Methods in Physics (SYM-PHYS10)" held at Yerevan, Armenia, 13-19 Aug. 200

The entropy of randomized network ensembles

Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same degree-correlations or the same community structure of any given real network. We characterize these randomized network ensembles by their entropy, i.e. the normalized logarithm of the total number of networks which are part of these ensembles. We estimate the entropy of randomized ensembles starting from a large set of real directed and undirected networks. We propose entropy as an indicator to assess the role of each structural feature in a given real network.We observe that the ensembles with fixed scale-free degree distribution have smaller entropy than the ensembles with homogeneous degree distribution indicating a higher level of order in scale-free networks.Comment: (6 pages,1 figure,2 tables

Condensates and quasiparticles in inflationary cosmology: mass generation and decay widths

During de Sitter inflation massless particles of minimally coupled scalar fields acquire a mass and a decay width thereby becoming \emph{quasiparticles}. For bare massless particles non-perturbative infrared radiative corrections lead to a self-consistent generation of mass, for a quartic self interaction $M \propto \lambda^{1/4} H$, and for a cubic self-interaction the mass is induced by the formation of a non-perturbative \emph{condensate} leading to $M \propto \lambda^{1/3} H^{2/3}$. These radiatively generated masses restore de Sitter invariance and result in anomalous scaling dimensions of superhorizon fluctuations. We introduce a generalization of the non-perturbative Wigner-Weisskopf method to obtain the time evolution of quantum states that include the self-consistent generation of mass and regulate the infrared behavior. The infrared divergences are manifest as poles in $\Delta=M^2/3H^2$ in the single particle self-energies, leading to a re-arrangement of the perturbative series non-analytic in the couplings. A set of simple rules that yield the leading order infrared contributions to the decay width are obtained and implemented. The lack of kinematic thresholds entail that all particle states acquire a decay width, dominated by the emission and absorption of superhorizon quanta $\propto (\lambda/H)^{4/3}\,[H/k_{ph}(\eta)]^6 ; \lambda\,[H/k_{ph}(\eta)]^6$ for cubic and quartic couplings respectively to leading order in $M/H$. The decay of single particle quantum states hastens as their wavevectors cross the Hubble radius and their width is related to the highly squeezed limit of the bi- or tri-spectrum of scalar fluctuations respectively.Comment: 31 pages, 7 figures. Comments and references, matches published versio

Detection of a Moving Rigid Solid in a Perfect Fluid

In this paper, we consider a moving rigid solid immersed in a potential fluid. The fluid-solid system fills the whole two dimensional space and the fluid is assumed to be at rest at infinity. Our aim is to study the inverse problem, initially introduced in [3], that consists in recovering the position and the velocity of the solid assuming that the potential function is known at a given time. We show that this problem is in general ill-posed by providing counterexamples for which the same potential corresponds to different positions and velocities of a same solid. However, it is also possible to find solids having a specific shape, like ellipses for instance, for which the problem of detection admits a unique solution. Using complex analysis, we prove that the well-posedness of the inverse problem is equivalent to the solvability of an infinite set of nonlinear equations. This result allows us to show that when the solid enjoys some symmetry properties, it can be partially detected. Besides, for any solid, the velocity can always be recovered when both the potential function and the position are supposed to be known. Finally, we prove that by performing continuous measurements of the fluid potential over a time interval, we can always track the position of the solid.Comment: 19 pages, 14 figure