TRAFFIC FLOWS FORECASTING BASED ON MACHINE LEARNING

The article aims to develop a model for forecasting the characteristics of traffic flows in real-time based on the classification of applications using machine learning methods to ensure the quality of service. It is shown that the model can forecast the mean rate and frequency of packet arrival for the entire flow of each class separately. The prediction is based on information about the previous flows of this class and the first 15 packets of the active flow. Thus, the Random Forest Regression method reduces the prediction error by approximately 1.5 times compared to the standard mean estimate for transmitted packets issued at the switch interface.

Optimal sensor and actuator placement for feedback control of vortex shedding

We consider linear feedback control of the two-dimensional flow past a cylinder at low Reynolds numbers, with a particular focus on the optimal placement of a single sensor and a single actuator. To accommodate the high dimensionality of the flow, we compute its leading resolvent forcing and response modes to enable the design of $\mathcal {H}_2$ -optimal estimators and controllers. We then investigate three control problems: (i) optimal estimation (OE) in which we measure the flow at a single location and estimate the entire flow; (ii) full-state information control (FIC) in which we measure the entire flow but actuate at only one location; and (iii) the overall feedback control problem in which a single sensor is available for measurement and a single actuator is available for control. We characterize the performance of these control arrangements over a range of sensor and actuator placements and discuss implications for effective feedback control when using a single sensor and a single actuator. The optimal sensor and actuator placements found for the OE and FIC problems are also compared with those found for the overall feedback control problem over a range of Reynolds numbers. This comparison reveals the key factors and conflicting trade-offs that limit feedback control performance.

Towards bootstrapping RG flows: sine-Gordon in AdS

The boundary correlation functions for a Quantum Field Theory (QFT) in an Anti-de Sitter (AdS) background can stay conformally covariant even if the bulk theory undergoes a renormalization group (RG) flow. Studying such correlation functions with the numerical conformal bootstrap leads to non-perturbative constraints that must hold along the entire flow. In this paper we carry out this analysis for the sine-Gordon RG flows in AdS2, which start with a free (compact) scalar in the UV and end with well-known massive integrable theories that saturate many S-matrix bootstrap bounds. We numerically analyze the correlation functions of both breathers and kinks and provide a detailed comparison with perturbation theory near the UV fixed point. Our bounds are often saturated to one or two orders in perturbation theory, as well as in the flat-space limit, but not necessarily in between.

Revising of the Near Ground Helicopter Hover: The Effect of Ground Boundary Layer Development

The interaction of a helicopter rotor with the ground in hover flight is addressed numerically using a hybrid Eulerian–Lagrangian CFD model. When a helicopter takes off or lands, its wake interferes with the ground. This interaction, depending on the height-to-rotor diameter ratio, causes the altering of the rotor loading and performance as compared to the unconstrained case and gives rise to the development of a complex outwash flow field in the surrounding of the helicopter. The present study aims to characterize the interactional phenomena occurring in the early stages of the rotor wake development and in particular the interference of the starting vortex with the ground boundary layer and the effect of this interaction in the motion of the vortex in the rotor outwash flow. The hybrid CFD method employed combines a standard URANS compressible finite volume solver, the use of which is restricted to confined grids around solid bodies, and a Lagrangian approximation of the entire flow field in which conservation equations are solved in their material form, disctretized using particle representation of the flow quantities. The two methods are strongly coupled to each other through an appropriate iterative scheme. The main advantage of the proposed methodology is that it can conveniently handle complex configurations with several bodies that move independently from one another, with affordable computational cost. In this paper, thrust coefficient predictions of the hybrid model are compared to predictions of a free wake code and to experimental data indicating that consistent prediction of the rotor load requires the inclusion of the ground boundary layer in the analysis. Moreover, detailed comparisons of the rotor wake evolution predicted by the hybrid model are presented.

A Hybrid Methodology Based on Smart Management Energy Consumption in Irrigation Systems

Innovative practices in irrigation systems can bring improvements in terms of economic efficiency and in the same time can reduce environmental impact. Investment in high tech technologies frequently involves additional costs, but an efficient water management can increase the lifetime of the equipment. The main objective of this article is to reduce the energy consumption by one thousand cubic meters pumped and automatically to increase the economic efficiency of the pumping groups. This paper develops a new operating algorithm that ensures the operation of the pumping group at safe operating intervals and in the same time identifies the equivalent pump operating points for the entire flow range and pumping height of the pumping group. This methodology is based on the principles of an Expert System to perform the optimization process of the energy consumption in pumping groups. The resulting methodology avoids the combinatorial explosion of the solutions to be analyzed and determines the point of maximum efficiency without violation of any of the system constraints under any operating condition. The proposed methodology is tested on an irrigation system that includes a pumping group with 5 pumps, showing its effectiveness in obtaining the optimal solution with a relatively low computational burden.

Regularities of vortex motion in gas-vortex bioreactor

Regularities of the vortex motion in an industrial glass bioreactor with a volume of 12 liters with a reactor vessel diameter D = 190 mm and with a filling of 50% was studied. A 65% water solution of glycerin was used as a model culture medium (density ρ g = 1150 kg/m3 and kinematic viscosity Vg = 15 mm2/s). Methods of particle image velocimetry and adaptive track visualization were used to observe the vortex pattern. The regularities of the vortex motion of the cultural medium were determined. It was found that, similar to the case of two rotating immiscible liquids, a strongly swirling jet was formed near the axis, and the entire flow took on the structure of a miniature gas-liquid tornado. The aerating gas interacted with the liquid only through the free surface, without mixing with it. As a result, the intensification of interphase mass transfer was provided due to the high speed of motion of the aerating gas.

Quantitative Phase Velocimetry for Label-Free Measurement of Intracellular Mass Transport Velocity

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle. Finally, based on the known effective particle size, we show that QPV is an accessible method to measure intracellular viscosity.

Bubble PIV technique to measure the velocity field of a free-swimming California sea lion

Fish et al. (2014) adapted laboratory PIV for safe use on larger animals. As opposed to seeding the entire flow with reflective particles and illuminating a plane of the flow with a laser, they produced a sheet of small bubbles and used sunlight for global illumination. Underwater cameras imaged the flow in a method similar to traditional PIV. This technique was used to measure the flow around a swimming dolphin and estimate the thrust produced during a tail stand maneuver (Fish et al. (2014, 2018)). In the current work, we will extend the modification of PIV of Fish et al. to measure the flow produced by a swimming sea lion also using bubbles as seeding particles and sunlight as illumination. This is the first time that the flowfield of a swimming sea lion has been directly measured. We will present an extensive extension to the image processing required to measure flow under field conditions. Finally, we will present the flow generated by propulsive strokes of an adult female (Cali) sea lion freely swimming through a pool of stationary water.

Combining shallow-water and analytical wake models for tidal array micro-siting

Array optimisation is critical for improving power performance and reducing infrastructure costs thereby helping enable tidal-stream energy to become a competitive renewable energy source. However, ascertaining an optimal array layout is a highly complex problem, subject to the specific site hydrodynamics characterisation and multiple inter-disciplinary constrains. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated with applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for 24 turbines with a rated speed of 3.05 m/s, demonstrating practical implications whilst also considering the temporal variability of the tide. Micro-siting using this technique generated an array 12% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was further evaluated through assessment of the optimised layout within the ocean model that represents the turbines through a discrete turbine representation.Used iteratively, this methodology could be applied to deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

In-building heat recovery mitigates adverse temperature effects on biological wastewater treatment: a network-scale analysis of thermal-hydraulics in sewers

Heat recovery from wastewater is a robust and straightforward strategy to reduce water-related energy consumption. Its implementation, though, requires a careful assessment of its impacts across the entire wastewater system as adverse effects on the water and resource recovery facility and competition among heat recovery strategies may arise.A model-based assessment of heat recovery from wastewater therefore implies extending the current simulation spatial scope, enabling thermal-hydraulic simulations from the household tap along its entire flow path down to the wastewater resource recovery facility. With this aim in mind, we propose a new modelling framework interfacing thermal-hydraulic simulations of (i) households, (ii) private lateral connections, and (iii) the main public sewer network.Applying this framework to analyse the fate of wastewater heat budgets in a Swiss catchment, we find that heat losses in lateral connections are large and cannot be overlooked in any thermal-hydraulic analysis, due to the high-temperature, low-flow wastewater characteristics maximizing heat losses to the environment. Further, we find that implementing shower drain heat recovery devices in 50% of the catchment’s households lower the wastewater temperature at the wastewater resource recovery facility significantly less – only 0.3 K – than centralized in-sewer heat recovery, due to a significant thermal damping effect induced by lateral connections and secondary sewer lines. In-building technologies are thus less likely to adversely affect biological wastewater treatment processes. The proposed open-source modelling framework can be applied to any other catchment. We thereby hope to enable more efficient heat recovery strategies, maximizing energy harvesting while minimising impacts on biological wastewater treatment.