Flow Control Problem Research Articles

To Solution of problem of controlling heat carrier flow rate for low-temperature heat supply

The problem of flow control of the heat carrier with a significant reduction of its temperature is studied. Several solutions to this problem are found taking into account the required amount of heat to the consumer. In this case, the heating supply object seems to be an equivalent heating device. An acceptable range of temperature reduction in the heat supply pipe is found, in which the problem of 100 % heat supply can be solved by increasing the flow of the heat carrier. It has been shown that this range can be significantly extended if there can be some decline in the quality of the heating supply – delivered volume of heat. The results can be used in the development of low-temperature heating modes – graphs of quantitative regulation of the heating supply.

Measurements versus Numerical Simulations for Slotted Synthetic Jet Actuator

In many studies concerning synthetic jet flow fields the analysis is usually restricted to simple configurations, such as a single diaphragm oscillating in a cylindrical cavity, which is linked to the external environment with only one orifice/slot. Nonetheless, in many applications the requirement of small sizes and weights leads to many implementation issues, such as asymmetric actuator geometries, presence of several slots and diaphragms and irregular cavity shapes. Therefore, the design of a synthetic jet actuator for a specific flow control problem requires a dedicated study in order to characterize its behavior even in quiescent conditions. The aim of this work is to investigate the behavior of a novel synthetic jet actuator, composed of three independent diaphragms, acting on a single cavity, and linked to the external environment through four slots per diaphragm. The device has been studied in quiescent conditions, both numerically and experimentally. The experimental investigation has been carried out by means of hot-wire measurements. In particular, the distribution of the phase-averaged streamwise velocity along the slot spanwise direction has been detected near the slot exit plane. From the computational side, incompressible direct numerical simulations have been carried out using the open-source OpenFOAM code. The diaphragm motion is mimicked by a inhomogeneous inlet boundary condition, whose amplitude is chosen to match the experimental velocity at the exit plane. A fair agreement between the numerical and the experimental results is achieved for both the velocity field at the slot exit and the main non-dimensional parameters of the synthetic jet. After the validation, the numerical results are finally processed, to obtain information about the vortex motion in the external environment.

Flow Control and Scheduling Algorithm of Air-Space-Ground Integrated Networks

Air-space-ground integrated networks are the combine network of the air, space and ground. The ASG-IIN has the problem of level isolated in Multi-level architecture. This article design an Air-space-ground integrated networks layered independent flow control scheme, based on the Air-space-ground framework, which analyze the problems of satellite network flow control, spacecraft flow control and land mobile communications networks flow control. According to the research of complex networks’ situation of establishment in WIT120, secure campus and sturdy power grid, we obtain a high service flow control demand of blend networks. Basing on the token, game theory and neural network, we put forward a series of new method to control the flow in Air-space-ground integrated networks.

Boundary control in computational haemodynamics

In this work, a data assimilation method is proposed following an optimise-then-discretise approach, and is applied in the context of computational haemodynamics. The methodology aims to make use of phase-contrast magnetic resonance imaging to perform optimal flow control in computational fluid dynamic simulations. Flow matching between observations and model predictions is performed in luminal regions, excluding near-wall areas, improving the near-wall flow reconstruction to enhance the estimation of related quantities such as wall shear stresses. The proposed approach remarkably improves the flow field at the aortic root and reveals a great potential for predicting clinically relevant haemodynamic phenomenology. This work presents model validation against an analytical solution using the standard 3-D Hagen–Poiseuille flow, and validation with real data involving the flow control problem in a glass replica of a human aorta imaged with a 3T magnetic resonance scanner.In vitroexperiments consist of both a numerically generated reference flow solution, which is considered as the ground truth, as well as real flow MRI data obtained from phase-contrast flow acquisitions. The validation against thein vitroflow MRI experiments is performed for different flow regimes and model parameters including different mesh refinements.

Product flows and decision models in Internet fulfillment warehouses

Internet Fulfillment Warehouses (IFWs) present a new operational model in the design and control of warehouses. IFWs operate with new paradigms, specifically, the use of an explosive storage policy combined with commingled storage are key features in achieving fast fulfillment. We document and present the process, data, and decision flows of IFW operations. The flows were synthesised from an observational study at the largest IFW operator. Detailed flows are presented for: (i) receiving and stocking (ii) order picking and consolidation and (iii) truck assignment and loading. The key contribution of this paper is introducing new warehousing models that are unique to fulfillment facilities which stock thousands of different products and process a very large number of small quantity customer orders. Multiple flow control and decision optimisation problems can be formulated from the operational models. Five specific problems are introduced, each focuses on the online retailing objective of fast fulfillment.

Passenger flow control with multi-station coordination in subway networks: algorithm development and real-world case study

ABSTRACTThis paper addresses the problem of passenger flow control in a multi-line subway network during peak hours. A new multi-station coordinated passenger flow control model is proposed to simultaneously adjust the number of inbound and transfer passengers entering multiple stations or lines. The implementation of passenger flow control governs the redundant passengers to queue at given facilities, which is similar to ramp metering that regulates the number of vehicles entering a highway segment. The proposed model is a bi-level programming, whose upper level aims to optimize the system performance with different passenger flow control strategies, while the lower level is a logit-based stochastic user equilibrium assignment problem under a given strategy, considering passenger flow evolution, dynamic path cost, and route choice. An algorithm, integrating the method of successive averages with genetic algorithm, is developed to solve the model. A real-world case study is conducted to examine the validity.

Exploiting Hidden Convexity in Queueing Networks: A Novel Approach to Optimal Control of Flows

Optimal flow control in queueing networks is a challenging problem occurring in many contexts, such as data centers, cloud computing, healthcare, revenue management, and distributed networks, etc. The traditional approach has been to adopt heuristic solutions or consider infinite-horizon fluid or diffusion approximations. Motivated by emerging techniques in Robust Optimization, we propose a framework, termed Pipeline Queues, which tracks the dynamics of a queue simultaneously in terms of its queue length and waiting time. We begin by showing that the dynamics of a traditional queueing system can be equivalently modeled using this approach. Our key contribution is the uncovering of the hidden convexity resulting from our modeling approach. This leads us to tractable optimization formulations for generic flow control problems of obtaining performance guarantees on average and quantiles of waiting time, under arbitrary arrival and service distributions with non-zero initial conditions. Our model is flexible enough to capture partial observability and uncertainty of the initial state, as well as various constraints on the control policy. We apply our approach to multiple examples from the literature and numerically illustrate their application. Finally, we implemented our model on a real dataset at a major hospital in India. Our proposed policies are near optimal and perform significantly better than present heuristics.

NOVEL CONTROL APPROACH FOR OPTIMAL POWER FLOW IN HYBRID WIND-PHOTOVOLTAIC-DIESEL GENERATION SYSTEMS

The paper deals with a formulation of an analytical control model for optimal power flow in an islanded microgrid (MG). In an MG with load change, wind power fluctuation, sun irradiation power disturbance, that can significant influence the power flow, and hence the power flow control problem in real life system faces some new challenges. In order to maintain the balance of power flow, a diesel engine generator (DEG) needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation, which depends on time and system states, and ultimately, leads to a feedback control or to the so called energy management to be implemented in a SCADA system

Non-Smooth Optimization for Robust Control of Infinite-Dimensional Systems

We use a non-smooth trust-region method for $H_\infty$-control of infinite-dimensional systems. Our method applies in particular to distributed and boundary control of partial differential equations. It is computationally attractive as it avoids the use of system reduction or identification. For illustration the method is applied to control a reaction-convection-diffusion system, a Van de Vusse reactor, and to a cavity flow control problem.

Identification-Based Closed-Loop Control Strategies for a Cylinder Wake Flow

Four closed-loop control strategies are discussed to reduce the drag of a cylinder wake flow: Linear Quadratic Gaussian (LQG) control, gain-scheduled LQG (GS-LQG) control, gain-scheduled PI control, and multimodel predictive control (M-MPC). The control models are obtained in an input–output framework through ARMAX (for LQG control), multi-ARMAX (for GS-LQG control and M-MPC), and multi-ARX (for gain-scheduled PI control). The use of system identification for the underlying flow control problem gets rid of the difficult task of developing accurate and robust reduced-order models for the Navier–Stokes (NS) equations. The control is introduced through sucking of fluid through the cylinder surface. The drag on the cylinder is reduced for all control methods. The robustness of all control strategies is tested against unmodeled disturbances and/or dynamics through a detailed simulation of an NS equation-based model by varying in time the Reynolds number around its nominal value 200. For the considered cylinder wake, the M-MPC approach is the best solution. The application of the presented closed-loop control algorithms for the cylinder drag control as a benchmark problem constitutes promising solutions for other related flow control problems in industries.

Distributed LPV State-Feedback Control Under Control Input Saturation

Developed in this note is a scheduled state-feedback controller synthesis method for discrete-time Linear Parameter Varying (LPV) systems subjected to control input saturation constraints. The static state-feedback gain is scheduled with an exact replica of the parameter matrix. The saturation effect is modeled by introducing time-varying parameters as functions of the control inputs, which are also used to schedule the controller. The synthesis method is then specialized to distributed state-feedback by imposing a particular structure on the feedback gain matrix. An explicit formula is also derived for the computation of the distributed control input from a nonlinear equation. The viability of the proposed method is tested in a simulation environment, for a ramp meter traffic flow control problem.

Finite element approximation of Dirichlet control using boundary penalty method for unsteady Navier–Stokes equations

This paper is concerned with the analysis of the finite element approximations of Dirichlet control problem using boundary penalty method for unsteady Navier–Stokes equations. Boundary penalty method has been used as a computationally convenient approach alternative to Dirichlet boundary control problems governed by Navier−Stokes equations due to its variational properties. Analysis of the mixed Galerkin finite element method applied to the spatial semi-discretization of the optimality system, from which optimal control can be computed, is presented. An optimal L ∞ (L 2 ) error estimate of the numerical approximations of the optimality system is derived. Feasibility and applicability of the approach are illustrated by numerically solving a canonical flow control problem.

ОБЛІКОВО-АНАЛІТИЧНІ АСПЕКТИ ФОРМУВАННЯ ІНФОРМАЦІЙНОГО ЗАБЕЗПЕЧЕННЯ УПРАВЛІННЯ ГРОШОВИМИ ПОТОКАМИ

The article is devoted to the study of the essence of cash flows and their accounting and analytical support. The urgency of solving issues of information support for cash flow management is substantiated, taking into account the current conditions of economic development and factors influencing the movement of cash resources. Using previous work, the authors of the article proposed their vision for the definition of «cash flows» as a set of all types of cash assets that serve the enterprise, are transformed and ensure its continuous operation. Classification is improved taking into account modern business conditions on the basis of non-cash. Accounting and analytical support for the formation of information in the cash flow management system is developed, which has a separate accounting and analytical component. The necessity of carrying out the administrative analysis of cash flows of the enterprise on the basis of a technique based on implementation of analytical procedures of the relevant information and acceptance of the corresponding administrative decisions is proved. According to the authors, accounting and analytical support of cash flows is a system that is based on financial and management accounting data as an informative basis for their analysis, is part of the overall process of managing the activities of the enterprise. The proposed system of accountingиand analytical support is focused on solving problems of cash flow management and control, which are the subject of interest of opportunistic managers. When developing forms of management reporting and methods of analysis, the tasks to be solved should take into account the interests of the owners. Further research is proposed to develop a methodological approach to management analysis of cash flows and search for key indicators to assess the level of efficiency of generating cash resources of the enterprise to avoid agency conflicts.

Metro passenger flow control with station-to-station cooperation based on stop-skipping and boarding limiting

Metro passenger flow control problem is studied under given total inbound demand in this work, which considers passenger demand control and train capacity supply. Relevant connotations are analyzed and a mathematical model is developed. The decision variables are boarding limiting and stop-skipping strategies and the objective is the maximal passenger profit. And a passenger original station choice model based on utility theory is built to modify the inbound passenger distribution among stations. Algorithm of metro passenger flow control scheme is designed, where two key technologies of stopping-station choice and headway adjustment are given and boarding limiting and train stopping-station scheme are optimized. Finally, a real case of Beijing metro is taken for example to verify validity. The results show that in the three scenarios with different ratios of normal trains to stop-skipping trains, the total limited passenger volume is the smallest and the systematic profit is the largest in scenario 3.

Mathematical Models of Unsteady Flow Distribution in Gas Transport Systems

The paper considers the multilevel methods of unsteady gas flow modeling in gas transport systems of arbitrary configuration, i.e., containing internal and external closed loops. Computational modeling relies on a generalized solution to initial boundary value problem for nonlinear partial differential equations with discontinuous coefficients describing the unsteady pressure and flow distribution in the gas transport system. Considered methods are focused on the use of different variants of finite volume (balance), finite-element (variational) and multigrid approximations of generalized solutions of parabolic equations. The number of levels of the hierarchy of calculations determined by the structure of gas transport system. Proposed methods are vital for solutions of the main gas flow control problems for gas transport systems and ready for use with parallel computing application programming interfaces.

Fuzzy TOPSIS method with ordered fuzzy numbers for flow control in a manufacturing system

The aim of the paper is to present a practical solution to a particular real-life problem of discrete flow control in a manufacturing system. For this purpose a fuzzy Multi-Criteria Decision Making (MCDM) method, which is an extension of the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) approach using Ordered Fuzzy Numbers (OFNs), is used. The paper includes a case study of the application of this method as a flow controller for the transport trolley in a flexible manufacturing system. The immediate aim of control is to choose the transport trolley’s destination (production line). A set of criteria (parameters) for the evaluation of the flow’s destination is suggested, related to time efficiency and equal workload of machines. The advantage of the proposed method is its ability to distinguish the type of criteria (benefit, cost) by using the orientation of ordered fuzzy numbers. An example of calculations using the presented method is shown and the results of the method, based on the simulation of a manufacturing system, are presented. The results thus obtained are compatible with flexible automation. In order to test the FTOPSIS method with OFNs the proposed flow control method is compared with the TOPSIS method and other simple control methods (dispatching rules). The proposed method is more efficient than the methods used for comparison and can be effective and efficient for diversified production and fast, automatic changeovers on production lines.

Distributed model predictive control for cooperative synchromodal freight transport

This paper investigates cooperative synchromodal freight transport planning among multiple intermodal freight transport operators in different and interconnected service networks. The cooperative planning is formulated as a cooperative model predictive container flow control problem, and solved with three Distributed Model Predictive Flow Control (DMPFC) approaches: the parallel and serial Augmented Lagrangian Relaxation (ALR) based DMPFC approaches, and the Alternating Direction Method of Multipliers (ADMM) based DMPFC approach. The simulation results show that the serial ALR-based DMPFC approach requires the least iterations and information exchanges while the ADMM-based DMPFC approach takes the least amount of actual computation time.

Flow behavior control in immersion lithography

Over the past decade, immersion lithography has been the primary technology for exposure process in semiconductor manufacturing. Compared with traditional dry lithography method, this technology improves the exposure resolution greatly by inserting a high index liquid into the gap between lens and wafer surface. Keeping the immersion liquid pure and uniform as well as avoiding residual droplets during high speed scanning motion are two challenges faced by the development of immersion lithography. Contaminations, particles, bubbles, heating and stress in the liquid will destroy the continuity of the refractive index. High speed motion of the wafer during scanning may break the meniscus stability on the interface between the liquid and the gas surrounding it, and then generate residual droplets on the wafer. All above phenomena will affect the exposure performance of immersion lithography and corresponding flow behavior control methods are required to solve the problems. This paper gives a review of the studies on flow behavior control in immersion lithography, which contains two parts: studies for liquid purity and uniformity and studies for meniscus stability. In each part, the mechanism and character of the flow behaviors as well as their effects to exposure performance are presented firstly. Then, control approaches adopted by now, including material and surface modifications as well as immersion head utilization, are introduced. In addition, the challenges faced in future studies are also pointed out. The purpose of this review paper is to help the researchers to understand the flow control problems in immersion lithography and to provide better control approaches for exposure performance improvement.

Uncertainty propagation in model extraction by system identification and its implication for control design

In data-based control design, system-identification techniques are used to extract low-dimensional representations of the input–output map between actuators and sensors from observed data signals. Under realistic conditions, noise in the signals is present and is expected to influence the identified system representation. For the subsequent design of the controller, it is important to gauge the sensitivity of the system representation to noise in the observed data; this information will impact the robustness of the controller and influence the stability margins for a closed-loop configuration. Commonly, full Monte Carlo analysis has been used to quantify the effect of data noise on the system identification and control design, but in fluid systems, this approach is often prohibitively expensive, due to the high dimensionality of the data input space, for both numerical simulations and physical experiments. Instead, we present a framework for the estimation of statistical properties of identified system representations given an uncertainty in the processed data. Our approach consists of a perturbative method, relating noise in the data to identified system parameters, which is followed by a Monte Carlo technique to propagate uncertainties in the system parameters to error bounds in Nyquist and Bode plots. This hybrid approach combines accuracy, by treating the system-identification part perturbatively, and computational efficiency, by applying Monte Carlo techniques to the low-dimensional input space of the control design and performance/stability evaluation part. This combination makes the proposed technique affordable and efficient even for large-scale flow-control problems. The ARMarkov/LS identification procedure has been chosen as a representative system-identification technique to illustrate this framework and to obtain error bounds on the identified system parameters based on the signal-to-noise ratio of the input–output data sequence. The procedure is illustrated on the control design for flow over an idealized aerofoil with a trailing-edge splitter plate.

Optimal Energy and Data Routing in Networks With Energy Cooperation

We consider the delay minimization problem in an energy harvesting communication network with energy cooperation. In this network, nodes harvest energy from nature for use in data transmission, and may transfer a portion of their harvested energies to neighboring nodes through energy cooperation. For fixed data and energy routing topologies, we determine the optimum data rates, transmit powers and energy transfers, subject to flow and energy conservation constraints, in order to minimize the network delay. We start with a simplified problem with fixed data flows and optimize energy management at each node for the case of a single energy harvest per node. This is tantamount to distributing each node's available energy over its outgoing data links and energy transfers to neighboring nodes. For this case, with no energy cooperation, we show that each node should allocate more power to links with more noise and/or more data flow. In addition, when there is energy cooperation, our numerical results indicate that, energy is routed from nodes with lower data loads to nodes with higher data loads. We extend this setting to the case of multiple energy harvests per node over time. In this case, we optimize each node's energy management over its outgoing data links and its energy transfers to neighboring nodes, over multiple time slots. For this case, with no energy cooperation, we show that, for any given node, the sum of powers on the outgoing links is equal to the single-link optimal power over time. Finally, we consider the problem of joint flow control and energy management for the entire network. We determine the necessary conditions for joint optimality of a power control, energy transfer and routing policy. We provide an iterative algorithm that updates the data and energy flows, and power distribution over outgoing data links. We show convergence to a Pareto-optimal operating point.