355 research outputs found
Global solutions and large time behavior for some Oldroyd-B type models in
In this paper, we are concerned with global solutions to the co-rotation
Oldroyd-B type model and large time behavior for the general Oldroyd-B type
model. We first establish the energy estimate and B-K-M criterion for the 2-D
co-rotation Oldroyd-B type model. Then, we obtain global solutions by proving
the boundedness of vorticity. In general case, we apply Fourier spiltting
method to prove the decay rate for global solutions constructed by
T.M.Elgindi and F.Rousset
Large time behavior to a 2D micro-macro model for compressible polymeric fluids near equilibrium
In this paper, we mainly study the large time behavior to a 2D micro-macro
model for compressible polymeric fluids with small initial data. This model is
a coupling of isentropic compressible Navier-Stokes equations with a nonlinear
Fokker-Planck equation. Firstly the Fourier splitting method yields that the
logarithmic decay rate. By virtue of the time weighted energy estimate, we can
improve the decay rate to . Under the low-frequency
condition and by the Littlewood-Paley theory, we show that the solutions belong
to some Besov spaces with negative index and obtain the optimal decay
rate. Finally, we obtain the decay rate by establishing a new
Fourier splitting estimate
Global strong solutions and large time behavior to a micro-macro model for compressible polymeric fluids near equilibrium
In this paper, we mainly study the global strong solutions and its long time
decay rates of all order spatial derivatives to a micro-macro model for
compressible polymeric fluids with small initial data. This model is a coupling
of isentropic compressible Navier-Stokes equations with a nonlinear
Fokker-Planck equation. We first prove that the micro-macro model admits a
unique global strong solution provided the initial data are close to
equilibrium state for . Moreover, for , we also show a new
critical Fourier estimation that allow us to give the long time decay rates of
norm for all order spatial derivatives
Global existence and optimal decay rate of weak solutions to the co-rotation Hooke dumbbell model
In this paper, we mainly study global existence and optimal decay rate
of weak solutions to the co-rotation Hooke dumbbell model. This micro-macro
model is a coupling of the Navier-Stokes equation with a nonlinear
Fokker-Planck equation. Based on the defect measure propagation method, we
prove that the co-rotation Hooke dumbbell model admits a global weak solution
provided the initial data under different integrability conditions. Moreover,
we obtain optimal long time decay rate in for the weak solutions obtained
by the Fourier splitting method
Global existence and optimal decay rate of weak solutions to some inviscid Oldroyd-B models
This paper is devoted to global existence and optimal decay rate of weak
solutions to some inviscid Oldroyd-B models with center diffusion. By virtue of
the properties of Calderon-Zygmund operator and the Littlewood-Paley
decomposition theory, we firstly prove that the 2-D co-rotation inviscid
Oldroyd-B model admits global weak solutions with some large data under
different integrability conditions. Furthermore, we prove the energy
conservation of weak solutions for the co-rotation case. These obtained results
generalize and cover the classical results for the Euler equation. Moreover, we
establish global weak solutions with small data for the 2-D noncorotation
inviscid Oldroyd-B model without damping. Finally, we prove optimal decay rate
of global weak solutions for the noncorotation case by the improved Fourier
splitting method.Comment: 44 page
CFD Simulation of the Influence of Viscosity on an Electrical Submersible Pump
Electrical Submersible Pump (ESP) is a multi-stage centrifugal pump used in the petroleum industry. Due to the high efficiency and adaptivity, ESPs are widely employed in offshore oil wells. Viscous fluid pumping can result in degradation of ESP performance. Improving the efficiency and maintaining the performance of ESPs are of great significance to oil production economic benefit.
To better understand the influence of viscosity on electrical submersible pumps, this work uses a CFD method to study the flow behaviors inside ESPs. Commercial software ANSYS Fluent is adopted to simulate the flow field inside the pump. A single stage of an ESP WJE-1000, manufactured by Baker Hughes Ltd., is modelled and investigated. 3-D single phase flow numerical simulation is performed to study the pump performance. Several sets of fluids of different viscosities and densities are tested under various operation conditions. A wide range of inlet flow rates are calculated for every set of fluids.
The effects of viscosity on ESP performance is identified and studied thoroughly. The flow field inside the pump channels is explored by post processing software. To understand how pump performance changes under different testing conditions, dimensionless analysis is performed. Shaft power, hydraulic power and drag power are discussed and calculated by dimensionless numbers
Control de producción en invernadero mediante aprendizaje por refuerzo
En este proyecto, se estudia, diseña y simula agentes de aprendizaje profundo por refuerzo para controlar el clima interior de un invernadero en un modelo de invernadero de lechugas que tiene incertidumbre en la predicción del clima externo futuro. El objetivo del proyecto es diseñar y entrenar un agente que pueda controlar de forma estable y robusta el clima interior y maximizar el uso de los recursos aportados por clima exterior, encontrando asà un equilibrio que permita el crecimiento saludable de las lechugas sin consumir demasiada energÃa. Para ello, en este trabajo se hablará del algoritmo de aprendizaje profundo por refuerzo, el proceso de diseño y ajuste del agente, la evaluación del agente entrenado y la comparación de los resultados con el control predictivo por model
Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models
Data-driven and controllable human motion synthesis and prediction are active
research areas with various applications in interactive media and social
robotics. Challenges remain in these fields for generating diverse motions
given past observations and dealing with imperfect poses. This paper introduces
MoDiff, an autoregressive probabilistic diffusion model over motion sequences
conditioned on control contexts of other modalities. Our model integrates a
cross-modal Transformer encoder and a Transformer-based decoder, which are
found effective in capturing temporal correlations in motion and control
modalities. We also introduce a new data dropout method based on the diffusion
forward process to provide richer data representations and robust generation.
We demonstrate the superior performance of MoDiff in controllable motion
synthesis for locomotion with respect to two baselines and show the benefits of
diffusion data dropout for robust synthesis and reconstruction of high-fidelity
motion close to recorded data
Individual heat map assessments demonstrate vestronidase alfa treatment response in a highly heterogeneous mucopolysaccharidosis VII study population.
Mucopolysaccharidosis (MPS) VII is an ultra-rare, progressively debilitating, life-threatening lysosomal disease caused by deficiency of the enzyme, β-glucuronidase. Vestronidase alfa is an approved enzyme replacement therapy for MPS VII. UX003-CL301 was a phase 3, randomized, placebo-controlled, blind-start study examining the efficacy and safety of vestronidase alfa 4 mg/kg intravenously administered every 2 weeks to 12 patients with MPS VII. Due to the rarity of disease, broad eligibility criteria resulted in a highly heterogeneous population with variable symptoms. For an integrated view of the diverse data, the changes from baseline (or randomization for the placebo period) in clinical endpoints were grouped into three functional domains (mobility, fatigue, and fine motor + self-care) and analyzed post-hoc as subject-level heat maps. Mobility assessments included the 6-minute walk test, 3-minute stair climb test, Bruininks-Oseretsky test (BOT-2) gross motor function subtests, and patient-reported outcome assessments (PROs) related to movement, pain, and ambulation. Fatigue assessments included the Pediatric Quality of Life Multidimensional Fatigue Scale and other fatigue-related PROs. Fine motor + self-care assessments included BOT-2 fine motor function subtests and PROs for eating, dressing, hygiene, and caregiver assistance. Most subjects showed improvement in at least one domain. Two subjects improved in two or more domains and two subjects did not show clear improvement in any domain. Both severely and mildly affected subjects improved with vestronidase alfa in clinical assessments, PRO results, or both. Heat map analysis demonstrates how subjects responded to treatment across multiple domains, providing a useful visual tool for studying rare diseases with variable symptoms
Component attention network for multimodal dance improvisation recognition
Dance improvisation is an active research topic in the arts. Motion analysis
of improvised dance can be challenging due to its unique dynamics. Data-driven
dance motion analysis, including recognition and generation, is often limited
to skeletal data. However, data of other modalities, such as audio, can be
recorded and benefit downstream tasks. This paper explores the application and
performance of multimodal fusion methods for human motion recognition in the
context of dance improvisation. We propose an attention-based model, component
attention network (CANet), for multimodal fusion on three levels: 1) feature
fusion with CANet, 2) model fusion with CANet and graph convolutional network
(GCN), and 3) late fusion with a voting strategy. We conduct thorough
experiments to analyze the impact of each modality in different fusion methods
and distinguish critical temporal or component features. We show that our
proposed model outperforms the two baseline methods, demonstrating its
potential for analyzing improvisation in dance.Comment: Accepted to 25th ACM International Conference on Multimodal
Interaction (ICMI 2023
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