Method For Computation Of Flows Research Articles

Physics-informed deep learning for traffic state estimation based on the traffic flow model and computational graph method

Traffic state estimation (TSE) is a critical task for intelligent transportation systems. However, it is extremely challenging because the traffic data quality is often affected by the installation position of devices, data collection frequency, interference during the transmission process, etc., thus causing the problem of data sparsity or data missing. To address the issue of traffic state estimation under the scenario of data sparsity, we propose a TSE model that combines the computational graph with physics-informed deep learning (PIDL) methods. Firstly, we apply the computational graph method to determine the parameters of the traffic fundamental diagram. These parameters are embedded into the computational graph framework, and their values are determined through the forward propagation of variables and the backward propagation of errors. Next, we employ the PIDL method to realize TSE (taking the LWR model based on the Greenshields fundamental diagram as an example). The PIDL leverages the advantages of data-driven and model-driven approaches to achieve accurate traffic state estimation. Case studies are conducted using the NGSIM dataset under two sparse data scenarios: loop detectors and probe vehicles. Experimental results demonstrate that PIDL can accurately reconstruct the traffic state of the entire road segment based on partially observed data. Furthermore, compared to pure deep learning methods and other baseline models, PIDL performs better in situations with sparse data, thereby proving the feasibility of integrating domain knowledge with deep learning frameworks. This paper fully acknowledges the issue of data sparsity in TSE and effectively addresses it by applying the PIDL method to achieve precise TSE, which holds significant implications for the control and management of real traffic flow.

Comparative Studies of Aerodynamic Drag Using Inviscid Flow Computation and Newtonian Method at High Speed

The flow field analysis over various reentry configurations is studied numerically by solving time-dependent compressible Euler equations. The governing fluid flow equations are discretized in spatial coordinates employing a finite volume approach, which reduces the equations to semi-discretized ordinary differential equations. Temporal integration is performed using multi-stage Runge-Kutta time stepping scheme. A local time step is used to achieve steady state solution. The numerical computation is carried out for freestream Mach number of 10.0 and angle of attack of 10.0 degree. The flow features around the blunt body are characterized by a bow shock wave, expansion wave and base flow region. The numerical scheme captures all the flow field features well. Comparisons of the flow field and surface pressure distribution results are made between different configurations of the blunt body capsules such as ARD (ESA’ s Atmospheric Reentry Demonstrator), Apollo II, MUSES-C, OREX (Orbital Reentry Experiments) with and without shoulder curvature and spherically blunted cone with flare angle of 30 and 35 degree. The inviscid analysis takes into consideration centrifugal force and expansion fan at the shoulder of the reentry capsules. The effects of the capsule geometry on the flow field may be useful for optimization of the reentry capsule. The Newtonian flow assumptions are used to calculate forebody aerodynamic drag for various blunt- bodies in conjunction with the NISA software. A comparison between CFD and the Newtonian flow assumptions for various reentry modules are made, and comparison shows an agreement between them.

Flow velocity computation using a single ERT sensor

Flow velocity is an important parameter in the multi-phase flow detection field. Electrical resistance tomography (ERT) is an advanced and non-invasive measuring technique for velocity estimation that has received considerable interest in the past decade. The process involves using two adjacent ERT sensors to collect measurements in a cross-sectional pipe, and the application of the cross-correlation (CC) principle for computing flow velocity. Currently, however, inaccurate assumptions, uncertain parameters, and noisy data greatly limit ERT efficiency and accuracy in practice. A new flow velocity computation method is presented that uses a single ERT sensor to replace two adjacent ERT sensors. According to the measurements of the single sensor and the corresponding ERT images, two key variables are computed that tightly align with the flow velocity. The proposed method overcomes the limitations of existing flow computation methods to some extents. Moreover, it can compute flow velocities in not only solid-liquid but also gas-liquid two-phase flows. Finally, experiments are conducted to validate the proposed method, and demonstrate its accuracy and reliability over existing methods.

A high-dimensional cytometry atlas of peripheral blood over the human life span.

Age can profoundly affect susceptibility to a broad range of human diseases. Children are more susceptible to some infectious diseases such as diphtheria and pertussis, while in others, such as coronavirus disease 2019 and hepatitis A, they are more protected compared with adults. One explanation is that the composition of the immune system is a major contributing factor to disease susceptibility and severity. While most studies of the human immune system have focused on adults, how the immune system changes after birth remains poorly understood. Here, using high-dimensional spectral flow cytometry and computational methods for data integration, we analyzed more than 50 populations of immune cells in the peripheral blood, generating an immune cell atlas that defines the healthy human immune system from birth up to 75 years of age. We focused our efforts on children under 18 years old, revealing major changes in immune cell populations after birth and in children of schooling age. Specifically, CD4+ T effector memory cells, Vδ2+ gamma delta (γδ)T cells, memory B cells, plasmablasts, CD11c+ B cells and CD16+ CD56bright natural killer (NK) cells peaked in children aged 5-9 years old, whereas frequencies of T helper 1, T helper 17, dendritic cells and CD16+ CD57+ CD56dim NK cells were highest in older children (10-18 years old). The frequency of mucosal-associated invariant T cells was low in the first several years of life and highest in adults between 19 and 30 years old. Late adulthood was associated with fewer mucosal-associated invariant T cells and Vδ2+ γδT cells but with increased frequencies of memory subsets of B cells, CD4+ and CD8+ T cells and CD57+ NK cells. This human immune cell atlas provides a critical resource to understand changes to the immune system during life and provides a reference for investigating the immune system in the context of human disease. This work may also help guide future therapies that target specific populations of immune cells to protect at-risk populations.

Carrier-Domain Method for high-resolution computation of time-periodic long-wake flows

We are introducing the Carrier-Domain Method (CDM) for high-resolution computation of time-periodic long-wake flows, with cost-effectives that makes the computations practical. The CDM is closely related to the Multidomain Method, which was introduced 24 years ago, originally intended also for cost-effective computation of long-wake flows and later extended in scope to cover additional classes of flow problems. In the CDM, the computational domain moves in the free-stream direction, with a velocity that preserves the outflow nature of the downstream computational boundary. As the computational domain is moving, the velocity at the inflow plane is extracted from the velocity computed earlier when the plane’s current position was covered by the moving domain. The inflow data needed at an instant is extracted from one or more instants going back in time as many periods. Computing the long-wake flow with a high-resolution moving mesh that has a reasonable length would certainly be far more cost-effective than computing it with a fixed mesh that covers the entire length of the wake. We are also introducing a CDM version where the computational domain moves in a discrete fashion rather than a continuous fashion. To demonstrate how the CDM works, we compute, with the version where the computational domain moves in a continuous fashion, the 2D flow past a circular cylinder at Reynolds number 100. At this Reynolds number, the flow has an easily discernible vortex shedding frequency and widely published lift and drag coefficients and Strouhal number. The wake flow is computed up to 350 diameters downstream of the cylinder, far enough to see the secondary vortex street. The computations are performed with the Space–Time Variational Multiscale method and isogeometric discretization; the basis functions are quadratic NURBS in space and linear in time. The results show the power of the CDM in high-resolution computation of time-periodic long-wake flows.

Real-Time Optical Flow for Vehicular Perception With Low- and High-Resolution Event Cameras

Event cameras capture changes of illumination in the observed scene rather than accumulating light to create images. Thus, they allow for applications under high-speed motion and complex lighting conditions, where traditional frame-based sensors show their limits with blur and over- or under-exposed pixels. Thanks to these unique properties, they represent nowadays an highly attractive sensor for ITS-related applications. Event-based optical flow (EBOF) has been studied following the rise in popularity of these neuromorphic cameras. The recent arrival of high-definition neuromorphic sensors, however, challenges the existing approaches, because of the increased resolution of the events pixel array and a much higher throughput. As an answer to these points, we propose an optimized framework for computing optical flow in real-time with both low- and high-resolution event cameras. We formulate a novel dense representation for the sparse events flow, in the form of the “inverse exponential distance surface”. It serves as an interim frame, designed for the use of proven, state-of-the-art frame-based optical flow computation methods. We evaluate our approach on both low- and high-resolution driving sequences, and show that it often achieves better results than the current state of the art, while also reaching higher frame rates, 250Hz at 346 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times260$ </tex-math></inline-formula> pixels and 77Hz at 1280 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times720$ </tex-math></inline-formula> pixels.

Efficient SVV stabilized triangular spectral element methods for incompressible flows of high Reynolds numbers

In this paper, we propose a spectral vanishing viscosity method for the triangular spectral element computation of high Reynolds number incompressible flows. This can be regarded as an extension of a similar stabilization technique for the standard spectral element method. The difficulty of this extension lies in the fact that a suitable definition of spectral vanishing viscosity operator in non-structured elements does not exist, and it is not clear that if a suitably defined spectral vanishing viscosity provides desirable dissipation for the artificially accumulated energy. The main contribution of the paper includes: 1) a well-defined spectral vanishing viscosity operator is proposed for non-standard spectral element methods for the Navier-Stokes equations based on triangular or tetrahedron partitions; 2) an evaluation technique is introduced to efficiently implement the stabilization term without extra computational cost; 3) the accuracy and efficiency of the proposed method is carefully examined through several numerical examples. Our numerical results show that the proposed method not only preserves the exponential convergence, but also produces improved accuracy when applied to the unsteady Navier-Stokes equations having smooth solutions. Especially, the stabilized triangular spectral element method efficiently stabilizes the simulation of high Reynolds incompressible flows.

Self-Attention-Based Multiscale Feature Learning Optical Flow With Occlusion Feature Map Prediction

Even though optical flow approaches based on convolutional neural networks have achieved remarkable performance with respect to both accuracy and efficiency, large displacements and motion occlusions remain challenges for most existing learning-based models. To address the abovementioned issues, we propose in this paper a self-attention-based multiscale feature learning optical flow computation method with occlusion feature map prediction. First, we exploit a self-attention mechanism-based multiscale feature learning module to compensate for large displacement optical flows, and the presented module is able to capture long-range dependencies from the input frames. Second, we design a simple but effective self-learning module to acquire an occlusion feature map, in which the predicted occlusion map is utilized to correct the optical flow estimation in occluded areas. Third, we explore a hybrid loss function that integrates the photometric and smoothness losses into the classical endpoint error (EPE)-based loss to ensure the accuracy and robustness of the presented network. Finally, we compare the proposed method with some state-of-the-art approaches using the MPI-Sintel and KITTI test databases. The experimental results demonstrate that the proposed method achieved competitive performance with respect to both accuracy and robustness, and it produced the better results compared to other methods under large displacements and motion occlusions.

Lattice Boltzmann Computations of the Fluid Flow in the Wake of a Wind Turbine Modelled by a Porous Disk Lattice Boltzmann Computations of the Fluid Flow in the Wake of a Wind Turbine Modelled by a Porous Disk

The study of wind turbine wakes was the subject of numerous papers. However, most computational studies were based on Reynolds Averaged Navier Stokes (RANS) equations or on large eddy simulations (LES) technique. In this work, a different technique based on Lattice Boltzmann method (LBM) is applied. This approach allows the numerical investigations of the flow field in the wake of a wind turbine modelled by a solid porous disk. The LBM is a mesoscopic simulation method for fluid flow computations. The applied model is based on the Regularized Bhatnagar-Groos-Krook (R-BGK) model and an LBM-LES method is used to solve the turbulent flow at a Reynolds number Re = 40000. Three-dimensional computations are performed using the open source Palabos code. The effects of the lattice velocity schemes D3Q19 and D3Q27, the value of Smagorinsky’s constant and the type of boundary conditions on the solid porous disk are investigated. The potential of 3D LBM computations to describe the far wake of an horizontal axis wind turbine is also shown‎.

A conservative multirate explicit time integration method for computation of compressible flows

In the context of high fidelity simulation of compressible flows (LES and DNS) at extreme scale (small time steps) on massively parallel supercomputers, explicit time integration methods are widely used since they both have a good computational cost trade-off at small time scales and require a small number of parallel communications, thus having little impact on the parallel strategy compared to their implicit counterpart. However, the synchronous nature of the time integration of the governing equations can be a severe constraint when the stability condition is applied globally since the time scales are related to the flow properties and the mesh resolution, which may show strong variations throughout the computational domain. We propose to further improve the efficiency (CPU wall-time reduction) of explicit Runge–Kutta methods by developing a multirate explicit time integration method, by means of flux interpolation at the boundary between cells evolving with different time-steps, which enforces the conservation properties. In terms of computational efficiency, the presented multirate time integration method is easy to implement in pre-existing Eulerian compressible Navier–Stokes codes, requires less additional memory storage, and provides a considerable speed-up while being robust and preserving the order of accuracy of the legacy explicit Runge–Kutta time integration method. The multirate time integration method is implemented in the massively parallel finite volume and high-order (spectral difference) IC3 code (Bodart et al., 2016) (fork of the solver CharLESX), but it can also be applied to any flux-based spatial method such as discontinuous Galerkin or others. For a targeted y+=0.2 on the developed turbulent channel flow test case at Reτ=392; a 2.48 effective speedup is obtained versus an expected theoretical speedup of 2.53.

Probabilistic Load Flow Analysis for Power System Containing Wind Farms Based on Cumulant Method

In this paper, a probabilistic load flow computation method based on the cumulants and Edgeworth expansion theory is put forward, and is used in the analysis of system containing wind farms composed of doubly-fed induction generator. Firstly a 2-parameter Weibull function is adopted to fit the random distribution of wind speed, and then the probabilistic model for wind power generator can be established based on active power output characteristic of wind power generator. Based on the linearized AC load flow model, analysis for IEEE 30-node system with wind farm is carried out. Finally the method is compared with Monte-Carlo simulation method, and the effects of wind farms integrated to the operation of power system is analysed in detail.

Monthly river flows in Texas for natural and developed conditions

River flow characteristics and computational methods for converting sequences of monthly flows between natural and regulated conditions are explored based on experience in assessing water availability throughout the state of Texas in the United States. Diverse climate, hydrology, economic development, and water management practices across the state combined with continual population growth and implementation of a statewide water availability modeling system makes Texas an excellent case study of stream flow characteristics and modeling and analysis methods that are relevant worldwide. Stream flow is extremely variable, subject to severe multiple-year droughts, intense floods, seasonality, and continuous fluctuation. The effects of population and economic growth, water resources development and management, and climatic variability on river flows vary with different conditions found across the state. The modeling system provides capabilities for adjusting observed river flows to represent natural conditions, simulating regulated flows representing specified conditions of development, and performing statistical frequency and reliability analyses.

High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations

Background and ObjectiveHigh-quality vascular modeling is crucial for blood flow simulations, i.e., computational fluid dynamics (CFD). As without an accurate geometric representation of the smooth vascular surface, it is impossible to make meaningful blood flow simulations. The purpose of this work is to develop high-quality vascular modeling and modification method for blood flow computations. MethodsWe develop a new technique for the accurate geometric modeling and modification of vasculatures using implicit extrusion surfaces (IES). In the proposed method, the skeleton of the vascular structure is subdivided into short curve segments, each of which is then represented implicitly locally as the intersection of two mutually orthogonal implicit surfaces defined by distance functions. A set of contour points is extracted and fitted with an implicit curve for accurately specifying the vessel cross-section profile, which is then extruded locally along the skeleton to fill the gaps between two vascular tube cross sections. We also present a new implicit geometric editing technique to modify the constructed vascular model with pathology for virtual stenting. ResultsExperimental results and validations show that accurate vascular models with highly smooth surfaces can be generated by the proposed method. In addition, we conduct some blood flow simulations to indicate the effectiveness of proposed method for hemodynamic simulations. ConclusionsThe proposed technique can achieve precise geometric models of vasculatures with any required degree of smoothness for reliable blood flow simulations.

Improved probabilistic load flow method based on D‐vine copulas and Latin hypercube sampling in distribution network with multiple wind generators

In this study, a D-vine copulas modelling based probabilistic load flow (PLF) computation method is proposed, which considers the dependence among multiple wind generators. Furthermore, this method is not restricted by the type of wind speed distribution, i.e. allow random variables to comply with any types of distribution model. Copula theory plays an important role on dependency modelling. However, when high-dimensional correlation is taken into account, standard multivariate copula suffers from the problems of inflexible structure. Vine copula is flexible to build high-dimensional dependence and able to construct complicated dependence structure by applying bivariate copulas. For marginal distributions of wind speed, non-parametric model can provide a better estimation than those parametric models. An improved Latin hypercube sampling based Monte Carlo simulation method is utilised to solve PLF problems. A modified IEEE 33-node distribution system is used to conduct the numerical experiments for the accuracy and efficiency verification of the proposed PLF method, under the MatlabR2016a platform. The simulation results verify the outstanding accuracy, efficiency and robustness of the proposed PLF method.

A new exchange flow computational method of quasi-one-dimensional flow between matrix and fractures in Fractured Reservoirs

Natural fractured reservoirs exist widely in the world. The heterogeneous porous medium was idealized to be a uniform system of the fracture and matrix for the convenience of numerical simulation. The traditional method to describe the flow exchange between the matrix and fracture is using a function related to shape factor and the pressure difference between the matrix and fracture. However, this classical model cannot be applied for the incompressible fluid. A new exchange flow computational method between matrix and fractures of quasi-one-dimensional flow in fractured reservoirs is proposed in this article. Numerical simulations are performed to demonstrate that the proposed method can provide more accurate results.

Fast flow computation methods on unstructured tetrahedral meshes for rapid reservoir modelling

Subsurface reservoir models have a high degree of uncertainty regarding reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how fluids-in-place, reservoir dynamics, and development decisions are affected by such uncertainty. The rapid reservoir modelling (RRM) workflow has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. A tracing algorithm is reviewed and implemented to compute time-of-flight and tracer concentrations efficiently on unstructured grids. Numerical well testing (NWT) is adopted in RRM to further interrogate the reservoir model. A new edge-based fast marching method is developed and implemented to solve the diffusive time-of-flight for approximating pressure transients efficiently on unstructured tetrahedral meshes. We demonstrate that an implementation of the workflow consisting of integrated sketch-based interface modelling, unstructured mesh generation, flow diagnostics, and numerical well testing is possible.

Ship Stability in a Seastate by the State-Space Fokker–Planck Method

The development of a new methodology for the modeling of the nonlinear responses and stability of ships in stochastic steep waves is presented. The radiation and diffraction hydrodynamic forces are cast in a state-space form by using a panel method followed by the implementation of the estimation of signal parameters via rotational invariance techniques algorithm. Strong free-surface nonlinearities present in the hydrostatic restoring and Froude-Krylov exciting forces are modeled by the fluid impulse theory. The ambient seastate is represented by a state-space diffusion modeled after a given wave spectrum. This enables the study of the nonlinear seakeeping and stability of ships in a seastate by invoking the methods of stochastic calculus. A state-space stochastic differential equation is derived for the states governing the vessel nonlinear responses, and a linear Fokker-Planck partial differential equation is obtained for the joint probability density function of the vessel motions. 1. Introduction Ships advancing in steep random waves may experience large responses and loss of stability. The need exists for the development of rational stability criteria that will enable the derivation of the safe operation envelope of vessels operating in severe seastates. The past several decades have witnessed significant progress toward the development of potential and viscous flow computational methods for the treatment of the seakeeping hydrodynamics of ships. These methods combined with experiments have been the primary tools for the treatment of ship stability in realistic environments (Umeda et al. 2008). A comprehensive list of articles is contained in the previous reference. Yet, we still lack a general-purpose theoretical framework that may be applied for the assessment of the stability properties of ships. The study of ship stability in a seastate requires the explicit account of nonlinearities of potential and viscous origin, the coupling of all modes of motion, and the development of statistical models for the nonlinear ship responses and their extreme statistics in a stochastic seastate. The study of the stability of ships by the methods described previously is typically carried out by Monte-Carlo simulations for the determination of the safe operating envelope. This approach may, however, be very time consuming when the treatment of the six-degree-of-freedom seakeeping problem is necessary and in conditions where nonlinear coupling between the vessel responses lead to loss of stability (e.g. parametric rolling, broaching).

An ALE/embedded boundary method for two-material flow simulations

We present a computational framework that combines an embedded boundary method and an arbitrary Lagrangian–Eulerian (ALE) method for multi-material flow computations of compressible fluids. The methodology is presented for two-material flows and one-material flow with moving boundaries, whereas the concept extends easily to multiple immiscible fluids. The proposed method is capable of handling geometrically complex material interfaces on moving grids and is suitable for multi-material flow computations in the context of ALE shock hydrodynamics. Furthermore, it can serve as the underlying framework for multi-fluid/structure interaction, where a portion of the boundary of a computational domain for a fluid mixture deforms according to the solid domain motion. Specifically, we use a variational multiscale stabilized finite element method to update the fluid state of each material, and define ghost values to enforce the transmission condition at the embedded material interface, which is captured using a level-set approach. Two different strategies to populate ghost values are considered and compared in extensive benchmark numerical tests: simple constant extrapolation and a multi-material Riemann solver, respectively.

Multi-Core CPU Parallel Power Flow Computation in AC/DC System Considering DC Control

In order to integrated the control mode of the High-Voltage Direct Current (HVDC) into the power flow solution method and make it applicable to large-scale AC/DC hybrid system, a multi-core CPU parallel power flow computation method was proposed. First, the mathematical model of HVDC system and the frequently-used control methods of converter are introduced, and then models that have not been considered by conventional power flow programs, such as the adjustment of converter transformer tap and reactive power control management of the converting station, are built. Next, the loop-iteration algorithm is proposed to simulate the conversion of the HVDC control modes, and the AC/DC sequential solution is adopted to solve the AC/DC hybrid power flow. To solve the low speed problem of power flow solution for large-scale systems containing multi-circuit two-terminal DC, this paper handles each circuit separately so that the parallel computation capability of multi-core CPU can be used to improve the computation speed. Finally, the accuracy of the algorithms is validated in a small-scale hybrid system with 5-node and 2-circuit DC, and the excellent convergence and computation efficiency of the algorithms are proved by a large-scale hybrid system with 9241-node and 60-circuit DC as well.

Heart valve flow computation with the integrated Space–Time VMS, Slip Interface, Topology Change and Isogeometric Discretization methods

Heart valve flow computation requires accurate representation of boundary layers near moving solid surfaces, including the valve leaflet surfaces, even when the leaflets come into contact. It also requires dealing with a high level of geometric complexity. We address these computational challenges with a Space–Time (ST) method developed by integrating three special ST methods in the framework of the ST Variational Multiscale (ST-VMS) method. The special methods are the ST Slip Interface (ST-SI) and ST Topology Change (ST-TC) methods and ST Isogeometric Analysis (ST-IGA). The computations are for a realistic aortic-valve model with prescribed valve leaflet motion and actual contact between the leaflets. The ST-VMS method functions as a moving-mesh method, which maintains high-resolution boundary layer representation near the solid surfaces, including leaflet surfaces. The ST-TC method was introduced for moving-mesh computation of flow problems with TC, such as contact between the leaflets of a heart valve. It deals with the contact while maintaining high-resolution representation near the leaflet surfaces. The ST-SI method was originally introduced to have high-resolution representation of the boundary layers near spinning solid surfaces. The mesh covering a spinning solid surface spins with it, and the SI between the spinning mesh and the rest of the mesh accurately connects the two sides. In the context of heart valves, the SI connects the sectors of meshes containing the leaflets, enabling a more effective mesh moving. In that context, integration of the ST-SI and ST-TC methods enables high-resolution representation even when the contact is between leaflets that are covered by meshes with SI. It also enables dealing with contact location change or contact and sliding on the SI. By integrating the ST-IGA with the ST-SI and ST-TC methods, in addition to having a more accurate representation of the surfaces and increased accuracy in the flow solution, the element density in the narrow spaces near the contact areas is kept at a reasonable level. Furthermore, because the flow representation in the contact area has a wider support in IGA, the flow computation method becomes more robust. The computations we present for an aortic-valve model with two different modes of prescribed leaflet motion show the effectiveness of the ST-SI-TC-IGA method.