The Performance of Air-Air Ejectors With Triangular Tabbed Driving Nozzles

Author(s):  
S. F. McBean ◽  
A. M. Birk

This paper describes an experimental investigation into the effects of geometrical variations on ejector system performance when the driving nozzle includes delta mixing tabs. Mixing tabs have been shown to provide good mixing performance with comparable back-pressure penalties to other types of enhanced mixing nozzles. The performance parameters of most interest are pumping, mixing, and back-pressure. Geometric parameters studied include standoff distance, mixing-tube diameter, and tab angle. Experimental testing showed significant performance improvements in mixing and pumping with a decrease in tab angle. Maximum mixing was found to occur with tab angles positioned at 120°. Exceptional mixing was also observed with increased standoff. Back-pressure was shown to increase with increasing standoff and decreasing tab angle, but was not affected by mixing-tube diameter. In addition, a zone of recirculation was identified at the entrance to the mixing-tube. This zone is thought to have an influence on ejector performance.

Crystals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 388 ◽  
Author(s):  
Sithara P. Sreenilayam ◽  
Dermot Brabazon ◽  
Yuri P. Panarin

The present work explains simulation and experimental investigation of the most significant performance parameters of a ferroelectric liquid crystal (FLC) optical switch. The measurements were carried out with commercially available FLC mixture (θ = 22.5°), having a very fast response time within the range of 1–10 μs. The best achieved cross talk was ~19 dB, which is an exact match with the theoretical result.


Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1639
Author(s):  
Seungmin Jung ◽  
Jihoon Moon ◽  
Sungwoo Park ◽  
Eenjun Hwang

Recently, multistep-ahead prediction has attracted much attention in electric load forecasting because it can deal with sudden changes in power consumption caused by various events such as fire and heat wave for a day from the present time. On the other hand, recurrent neural networks (RNNs), including long short-term memory and gated recurrent unit (GRU) networks, can reflect the previous point well to predict the current point. Due to this property, they have been widely used for multistep-ahead prediction. The GRU model is simple and easy to implement; however, its prediction performance is limited because it considers all input variables equally. In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can achieve significant performance improvements, especially when the input sequence of RNN is long. Through extensive experiments, we show that the proposed model outperforms other recent multistep-ahead prediction models in the building-level power consumption forecasting.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Aadel M. Alatwi ◽  
Ahmed Nabih Zaki Rashed ◽  
Eman Mohsen El-Gammal

AbstractSystem performance, which depends on the data transmission rates and propagation distances between two satellites in low Earth orbit (LEO) based on wavelength division multiplexing (WDM) techniques, is thoroughly studied. This study demonstrates the effect of WDM techniques on multi transceiver inter-satellite wireless optical communications. The system performance parameters with propagation distance at a multiple transceiver system are discussed using two previous models. The system performance parameters are investigated with 250 Gb/s transmission bit rates and 5000 km propagation distances for 16 transceiver systems. The maximum quality factor (Q factor), light peak signal per noise ratio, and signal peak per noise ratio are the primary important performance parameters in this study.


Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5748
Author(s):  
Zhibo Zhang ◽  
Qing Chang ◽  
Na Zhao ◽  
Chen Li ◽  
Tianrun Li

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.


2011 ◽  
Vol 44 (6) ◽  
pp. 1272-1276 ◽  
Author(s):  
Koichi Momma ◽  
Fujio Izumi

VESTAis a three-dimensional visualization system for crystallographic studies and electronic state calculations. It has been upgraded to the latest version,VESTA 3, implementing new features including drawing the external morphology of crystals; superimposing multiple structural models, volumetric data and crystal faces; calculation of electron and nuclear densities from structure parameters; calculation of Patterson functions from structure parameters or volumetric data; integration of electron and nuclear densities by Voronoi tessellation; visualization of isosurfaces with multiple levels; determination of the best plane for selected atoms; an extended bond-search algorithm to enable more sophisticated searches in complex molecules and cage-like structures; undo and redo in graphical user interface operations; and significant performance improvements in rendering isosurfaces and calculating slices.


2017 ◽  
Vol 107 (04) ◽  
pp. 301-305
Author(s):  
E. Prof. Uhlmann ◽  
F. Kaulfersch

Partikelverstärkte Titanmatrix-Verbundwerkstoffe erlauben erhebliche Leistungssteigerungen im Bereich hochtemperaturbeanspruchter Struktur- und Funktionsbauteile. Die durch die Partikelverstärkung gesteigerte Verschleißbeständigkeit, Festigkeit und Härte bedeuten eine große Herausforderung an die spanende Bearbeitung derartiger Hochleistungswerkstoffe. Mittels Zerspanuntersuchungen beim Fräsen konnten unter Variation der Werkzeuggeometrie, der Schneidstoffe und der Prozessstrategie Parameterbeiche identifiziert werden, mit denen die prozesssichere Zerspanung partikelverstärkter Titanmatrix-Verbundwerkstoffe möglich ist.   Particle-reinforced titanium matrix composites ensure significant performance improvements of structural and functional high-temperature components. However, the high wear resistance, toughness and hardness due to particle reinforcement is a major challenge in machining these high performance materials. By conducting milling experiments with a variation of tool geometry, cutting material and process strategy, process parameters could be identified that enable efficient machining of particle-reinforced titanium matrix composites.


2017 ◽  
Vol 21 (9) ◽  
pp. 4841-4859 ◽  
Author(s):  
Sean W. D. Turner ◽  
James C. Bennett ◽  
David E. Robertson ◽  
Stefano Galelli

Abstract. Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.


2020 ◽  
Vol 70 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Goran Marković ◽  
Vlada Sokolović

Networks with distributed sensors, e.g. cognitive radio networks or wireless sensor networks enable large-scale deployments of cooperative automatic modulation classification (AMC). Existing cooperative AMC schemes with centralised fusion offer considerable performance increase in comparison to single sensor reception. Previous studies were generally focused on AMC scenarios in which multipath channel is assumed to be static during a signal reception. However, in practical mobile environments, time-correlated multipath channels occur, which induce large negative influence on the existing cooperative AMC solutions. In this paper, we propose two novel cooperative AMC schemes with the additional intra-sensor fusion, and show that these offer significant performance improvements over the existing ones under given conditions.


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