Pressure and velocity measurements in a three-dimensional wall jet

The effects on the flow fields of varying the ratio of the velocity at the exit plane of the nozzle to the outer tunnel flow are reported. The pressure-velocity correlations are taken and some trends are discussed. Emphasis is placed on comparing the coherence between the fluctuating pressure and velocity fields at various locations in the different flow configurations

An experimental investigation of an axisymmetric jet in a coflowing airstream

The flow development of an axisymmetric jet exhausting into a moving airstream has been studied. The jet has a Reynolds number of 22,600, and the ratio of the jet velocity to the wind tunnel velocity is 5.1 to 1. The flow field of the axisymmetric jet was examined at locations varying from approximately zero to eight diameters downstream of the orifice. Of primary concern at each downstream location was the mapping of the one point statistical properties of the flow, including mean velocity, turbulent intensity, and intermittency. Autocorrelations and power spectral density curves were determined for both the fluctuating velocity field and the concentration signal at various distances from the jet's center line for different downstream locations. A laser Doppler velocimeter, using a phase locked loop processor, was used to make the desired velocity field measurements which were compared with hot wire anemometer and pressure probe data

11th European Headache Federation Congress jointly with 31st Congress of the Italian Society for the Study of Headaches : Rome, Italy. 01-03 December 2017

. Aims of the study were explore the relationship between peripheral chromatic and central visual dysfunction evaluating also the presence of functional receptor impairment in patients with migraine, with and without aura examined interictally

Investigations of scaling laws for jet impingement

The statistical properties of tangential flows over surfaces were investigated by two techniques. In one, a laser-Doppler velocimeter was used in a smoke-laden jet to measure one-point statistical properties, including mean velocities, turbulent intensities, intermittencies, autocorrelations, and power spectral densities. In the other technique, free stream and surface pressure probes connected to 1/8 inch microphones were used to obtain single point rms and 1/3 octave pressures, as well as two point cross correlations, the latter being converted to auto spectra, amplitude ratios, phase lags, and coherences. The results of these studies support the vortex model of jets, give some insights into the effects of surface impingement, and confirm that jet diameter and velocity are the scaling parameters for circular jets, while Reynolds number is relatively unimportant

Microscopic black hole detection in UHECR: the double bang signature

According to recent conjectures on the existence of large extra dimensions in our universe, black holes may be produced during the interaction of Ultra High Energy Cosmic Rays with the atmosphere. However, and so far, the proposed signatures are based on statistical effects, not allowing identification on an event by event basis, and may lead to large uncertainties. In this note, events with a double bang topology, where the production and instantaneous decay of a microscopic black hole (first bang) is followed, at a measurable distance, by the decay of an energetic tau lepton (second bang) are proposed as an almost background free signature. The characteristics of these events and the capability of large cosmic ray experiments to detect them are discussed.Comment: revised version, 5 figure

A new tool for food industrial plant simulation and IoT control

The general objective of this research is to create a Simulation Software allowing the Optimization and Control of an IoT system for food industry applications. An industrial plant is today considered a complex system as it is often composed of many types of machines characterized by a strong temporal variation of the productions. The three missing factors to accomplish what above are: • Simulation; • Implementation of communicating objects also called IoT (Internet of Things) systems. • Intelligent control; In this paper, we show the tools developed and implemented in the Simulation software used to model a physical industrial process by mean of a user-friendly graphic interface allowing interactively defining different plant configurations, through the selection of basic graphic elements and their appropriate connection. The software has been developed in Unity, a cross-platform engine used to create three-dimensional, twodimensional, virtual reality, and augmented reality, as well as simulations. The software consists of the following main sections: • library; • creation and management of the process scheme; • simulation. The "library" section contains the elements (blocks) used in the process scheme, to be completed with functions describing their specific behaviour. These elements represent physical components and logical connectors that allow connecting the different blocks generating an oriented graph.The "creation and management of the process scheme" section is the graphical interface through which new configurations can be created. In particular, the connectors correspond to a flow of information from one block to another and contain the output variables determined by the function of the starting block. These values are used as input in the arrival block. The "simulation" section allows simulating of previously designed configurations

Dynamic simulation driven design and management of production facilities in agricultural/food industry

An industrial plant in the agro-food sector can be considered a complex system as it is composed of numerous types of machines and it is characterized by a strong variation (seasonality) in the agricultural production. Whenever the dynamic behavior of the plants during operation is considered, system and design complexities increase. Reliable operation of food processing farms is primarily dependent on perfect balance between variable supply and product storage at each given time. To date, the classical modus operandi of food processing management systems is carried out under stationary and average conditions. Moreover, most of the systems installed for agricultural and food industries are sized using average production data. This often results in a mismatch between the actual operation and the expected operation. Consequently, the system is not optimized for the needs of a specific company. Also, the system is not flexible to the evolution that the production process could possibly have in the future. Promising techniques useful to solve the above-described problems could possibly be borrowed from demand side management (DSM) in smart grid systems. Such techniques allow customers to make dynamically informed decisions regarding their energy demand and help the energy providers in reducing the peak load demand and reshape the load profile. DSM is successfully used to improve the energy management system and we conjecture that DSM could be suitably adapted to food processing management. In this paper we describe how DSM could be exploited in the intelligent management of production facilities serving agricultural and food industry. The main objective is, indeed, to present how methods for modelling and implementing the dynamic simulation used for the optimization of the energy management in smart grid systems can be applied to a fruit and vegetables processing plant through a suitable adaptation

A pore-scale hydro-mechanical coupled model for geomaterials

We present a model for fluid-saturated granular media coupled flow and mechanical deformation. The fluid is assumed to be incompressible and the solid part is assumed to be a cohesive granular material. Forces exerted by the fluid in motion are determinated and applied to solid particles. We derive a finite volumes formulation of the flow problem and we couple it to a discrete element method (DEM) formulation of the solid deformation. The ability of the algorithm to solve transient problems is tested by simulating an oedometer test on a soil sample. The numerical solution of our model is in good agreement with Terzaghi’s analytical solution