A Cole-Hopf transformation based fourth-order multiple-relaxation-time lattice Boltzmann model for the coupled Burgers' equations

In this work, a Cole-Hopf transformation based fourth-order multiple-relaxation-time lattice Boltzmann (MRT-LB) model for d-dimensional coupled Burgers' equations is developed. We first adopt the Cole-Hopf transformation where an intermediate variable \theta is introduced to eliminate the nonlinear convection terms in the Burgers' equations on the velocity u=(u_1,u_2,...,u_d). In this case, a diffusion equation on the variable \theta can be obtained, and particularly, the velocity u in the coupled Burgers' equations is determined by the variable \theta and its gradient term \nabla\theta. Then we develop a general MRT-LB model with the natural moments for the d-dimensional transformed diffusion equation and present the corresponding macroscopic finite-difference scheme. At the diffusive scaling, the fourth-order modified equation of the developed MRT-LB model is derived through the Maxwell iteration method. With the aid of the free parameters in the MRT-LB model, we find that not only the consistent fourth-order modified equation can be obtained, but also the gradient term $\nabla\theta$ can be calculated locally by the non-equilibrium distribution function with a fourth-order accuracy, this indicates that theoretically, the MRT-LB model for $d$-dimensional coupled Burgers' equations can achieve a fourth-order accuracy in space. Finally, some simulations are conducted to test the MRT-LB model, and the numerical results show that the proposed MRT-LB model has a fourth-order convergence rate, which is consistent with our theoretical analysis

A consistent and conservative diffuse-domain lattice Boltzmann method for multiphase flows in complex geometries

Modeling and simulation of multiphase flows in complex geomerties are challenging due to the complexity in describing the interface topology changes among different phases and the difficulty in implementing the boundary conditions on the irregular solid surface. In this work, we first developed a diffuse-domain (DD) based phase-field model for multiphase flows in complex geometries. In this model, the irregular fluid region is embedded into a larger and regular domain by introducing a smooth characteristic function. Then, the reduction-consistent and conservative phase-field equation for the multiphase field and the consistent and conservative Navier-Stokes equations for the flow field are reformulated as the diffuse-domain based consistent and conservative (DD-CC) equations where some additional source terms are added to reflect the effects of boundary conditions. In this case, there is no need to directly treat the complex boundary conditions on the irregular solid surface, and additionally, based on a matched asymptotic analysis, it is also shown that the DD-CC equations can converge to the original governing equations as the interface width parameter tends to zero. Furthermore, to solve the DD-CC equations, we proposed a novel and simple lattice Boltzmann (LB) method with a Hermite-moment-based collision matrix which can not only keep consistent and conservation properties, but also improve the numerical stability with a flexible parameter. With the help of the direct Taylor expansion, the macroscopic DD-CC equations can be recovered correctly from the present LB method. Finally, to test the capacity of LB method, several benchmarks and complex problems are considered, and the numerical results show that the present LB method is accurate and efficient for the multiphase flows in complex geomerties.Comment: 22 pages, 9 figure

Автоматизированные системы управления процессом бурения

Автоматизация технологических процессов на основе современной техники должна обеспечить интенсификацию производства, повышение качества и снижение себестоимости продукции. Рассмотрены автоматизированные системы управления процессом бурения: САОПБ-1, Карат-2, АСУТП-Б, АЛМАЗ и др., что позволило привести классификацию данных систем по функциональному назначению: стабилизация скорости подачи, управление параметрами режима бурения и гибкая производственная система. Выделено четыре класса систем управления в зависимости от сложности геолого-технических условий бурения скважин. В первый класс отнесены системы стабилизации скорости подачи, второй - предназначенные для реализации сравнительно простых алгоритмов управления процессом бурения, третий - ориентированные на работу в сложных и слабо изученных геолого-технических условиях, четвертый - способных работать в автоматических режимах при углубке скважины и при проведении спускоподъемных операций. Показано что наиболее технологичным является реализация комплекса технических средств способных работать в автоматических режимах при углубке скважины и проведении спускоподъемных операций.Автоматизація технологічних процесів на основі сучасної техніки повинна забезпечити інтенсифікацію виробництва, підвищення якості та зниження собівартості продукції. Розглянуто автоматизовані системи управління процесом буріння: САОПБ-1, Карат-2, АСУТП-Б, АЛМАЗ та ін. Це дозволило привести класифікацію даних систем за функціональним призначенням: стабілізація швидкості подачі, керування параметрами режиму буріння та гнучка виробничої системи. Виділено чотири класу систем управління залежно від складності геолого-технічних умов буріння свердловин. В перший клас віднесено системи стабілізації швидкості подачі, до другого - призначені для реалізації порівняно простих алгоритмів керування буровий процесом, у третій- орієнтовані на роботу в складних та слабо вивчених геолого-технічних умовах, четвертий - здатні працювати в автоматичних режимах при подовжувачі свердловин і при проведенні спускопідіймальних операцій. Показано, що найбільш технологічним є реалізація комплексу технічних засобів, здатних працювати в автоматичних режимах при поглибленні колодязів та проведення спускопідіймальних операцій.Automation of technological processes based on modern technics should ensure the intensification of production, improving the quality and reducing the cost of production. The automated drilling control systems as are SAOPB-1, Karat-2, ASUTP-B, ALMAZ, etc. were considered. This allowed to classify these systems according to their functional purpose: stabilization of feed rate, control of drilling parameters and flexible production system. Four classes of control systems are distinguished depending on the complexity of geological and technical conditions for drilling boreholes. The first class includes the systems for stabilization of the feed rate, the second - designed to implement relatively simple algorithms for controlling the drilling process, the third - oriented to work in complex and poorly studied geological and technical conditions, the fourth - capable of operating in automatic modes for deepening the borehole and for tripping operations. It is shown that the most technological is the implementation of a set of technical facilities capable of operating in automatic modes during borehole deepening and carrying out tripping operations

Q-YOLO: Efficient Inference for Real-time Object Detection

Real-time object detection plays a vital role in various computer vision applications. However, deploying real-time object detectors on resource-constrained platforms poses challenges due to high computational and memory requirements. This paper describes a low-bit quantization method to build a highly efficient one-stage detector, dubbed as Q-YOLO, which can effectively address the performance degradation problem caused by activation distribution imbalance in traditional quantized YOLO models. Q-YOLO introduces a fully end-to-end Post-Training Quantization (PTQ) pipeline with a well-designed Unilateral Histogram-based (UH) activation quantization scheme, which determines the maximum truncation values through histogram analysis by minimizing the Mean Squared Error (MSE) quantization errors. Extensive experiments on the COCO dataset demonstrate the effectiveness of Q-YOLO, outperforming other PTQ methods while achieving a more favorable balance between accuracy and computational cost. This research contributes to advancing the efficient deployment of object detection models on resource-limited edge devices, enabling real-time detection with reduced computational and memory overhead

Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation

The advancement of deep convolutional neural networks (DCNNs) has driven significant improvement in the accuracy of recognition systems for many computer vision tasks. However, their practical applications are often restricted in resource-constrained environments. In this paper, we introduce projection convolutional neural networks (PCNNs) with a discrete back propagation via projection (DBPP) to improve the performance of binarized neural networks (BNNs). The contributions of our paper include: 1) for the first time, the projection function is exploited to efficiently solve the discrete back propagation problem, which leads to a new highly compressed CNNs (termed PCNNs); 2) by exploiting multiple projections, we learn a set of diverse quantized kernels that compress the full-precision kernels in a more efficient way than those proposed previously; 3) PCNNs achieve the best classification performance compared to other state-of-the-art BNNs on the ImageNet and CIFAR datasets