scholarly journals A Robust Adiabatic Model for a Quasi-Steady Prediction of Far-Off Non-Measured Performance in Vaneless Twin-Entry or Dual-Volute Radial Turbines

2020 ◽  
Vol 10 (6) ◽  
pp. 1955
Author(s):  
José Ramón Serrano ◽  
Francisco J. Arnau ◽  
Luis Miguel García-Cuevas ◽  
Vishnu Samala
Keyword(s):  
Mass Flow ◽  
Performance Parameters ◽  
Flow Conditions ◽  
Fitting Procedure ◽  
Radial Turbine ◽  
Novel Approach ◽  
Proposed Model ◽  
Double Entry ◽  
Radial Turbines ◽  
Fitting Parameters

The current investigation describes in detail a mass flow oriented model for extrapolation of reduced mass flow and adiabatic efficiency of double entry radial inflow turbines under any unequal and partial flow admission conditions. The model is based on a novel approach, which proposes assimilating double entry turbines to two variable geometry turbines (VGTs) using the mass flow ratio ( MFR ) between the two entries as the discriminating parameter. With such an innovative approach, the model can extrapolate performance parameters to non-measured MFR s, blade-to-jet speed ratios, and reduced speeds. Therefore, the model can be used in a quasi-steady method for predicting double entry turbines performance instantaneously. The model was validated against a dataset from two different double entry turbine types: a twin-entry symmetrical turbine and a dual-volute asymmetrical turbine. Both were tested under steady flow conditions. The proposed model showed accurate results and a coherent set of fitting parameters with physical meaning, as discussed in this paper. The obtained parameters showed very similar figures for the aforementioned turbine types, which allows concluding that they are an adequate set of values for initializing the fitting procedure of any type of double entry radial turbine.

The Feasibility of Using an Air Turbine to Drive an Afterburner Fuel Pump

2003 ◽  
Author(s):  
N. E. Backus ◽  
K. W. Ramsden ◽  
M. K. Yates ◽  
P. Laskaridis ◽  
P. Pilidis
Keyword(s):  
Mass Flow ◽  
Engine Speed ◽  
Performance Data ◽  
Fuel Pump ◽  
Radial Turbine ◽  
Air Turbine ◽  
Fixed Proportion ◽  
Mass Flows ◽  
Electric Engine ◽  
Radial Turbines

Current fighter engine designs extract power to drive the afterburner fuel pump through the use of a gearbox. The presence of the gearbox only allows the fuel pump to operate at a fixed proportion of engine speed. In addition the fuel pump is continually rotating, although not pumping fuel, even when the afterburner is not engaged. This article investigates the feasibility of using an air turbine to drive the afterburner fuel pump in preparation for supporting an all-electric engine. Utilising performance data for a typical modern military engine, 1-dimensional design techniques were used to design several radial turbines to power the afterburner fuel pump. A choice of an axial or a radial air turbine is possible. Both were reviewed and it was determined that a radial turbine is optimum based on manufacturability and (theoretical) efficiency. Several design iterations were completed to determine the estimated weight and size based on various air off-take locations, mass flows, and rotational speeds. These iterations showed that increasing mass flow allows for lower rotational speeds and/or smaller diameter rotors, but with a corresponding increases in thrust penalties.

W-MMP2Vec: Topic-driven network embedding model for link prediction in content-based heterogeneous information network

2021 ◽  
Vol 25 (3) ◽  
pp. 711-738
Author(s):  
Phu Pham ◽  
Phuc Do
Keyword(s):  
Link Prediction ◽  
Representation Learning ◽  
Information Network ◽  
Network Embedding ◽  
Heterogeneous Information Network ◽  
Heterogeneous Information ◽  
Learning Framework ◽  
Novel Approach ◽  
Proposed Model ◽  
Meta Path

Link prediction on heterogeneous information network (HIN) is considered as a challenge problem due to the complexity and diversity in types of nodes and links. Currently, there are remained challenges of meta-path-based link prediction in HIN. Previous works of link prediction in HIN via network embedding approach are mainly focused on exploiting features of node rather than existing relations in forms of meta-paths between nodes. In fact, predicting the existence of new links between non-linked nodes is absolutely inconvincible. Moreover, recent HIN-based embedding models also lack of thorough evaluations on the topic similarity between text-based nodes along given meta-paths. To tackle these challenges, in this paper, we proposed a novel approach of topic-driven multiple meta-path-based HIN representation learning framework, namely W-MMP2Vec. Our model leverages the quality of node representations by combining multiple meta-paths as well as calculating the topic similarity weight for each meta-path during the processes of network embedding learning in content-based HINs. To validate our approach, we apply W-TMP2Vec model in solving several link prediction tasks in both content-based and non-content-based HINs (DBLP, IMDB and BlogCatalog). The experimental outputs demonstrate the effectiveness of proposed model which outperforms recent state-of-the-art HIN representation learning models.

Food waste treatment option selection through spherical fuzzy AHP

2021 ◽  
pp. 1-11
Author(s):  
Aysu Melis Buyuk ◽  
Gul T. Temur
Keyword(s):  
Treatment Option ◽  
Food Waste ◽  
Waste Treatment ◽  
Fuzzy Ahp ◽  
Treatment Options ◽  
Analytic Hierarchy ◽  
Food Treatment ◽  
Novel Approach ◽  
Proposed Model ◽  
Option Selection

In line with the increase in consciousness on sustainability in today’s global world, great emphasis has been attached to food waste management. Food waste is a complex issue to manage due to uncertainties on quality, quantity, location, and time of wastes, and it involves different decisions at many stages from seed to post-consumption. These ambiguities re-quire that some decisions should be handled in a linguistic and ambiguous environment. That forces researchers to benefit from fuzzy sets mostly utilized to deal with subjectivity that causes uncertainty. In this study, as a novel approach, the spherical fuzzy analytic hierarchy process (SFAHP) was used to select the best food treatment option. In the model, four main criteria (infrastructural, governmental, economic, and environmental) and their thirteen sub-criteria are considered. A real case is conducted to show how the proposed model can be used to assess four food waste treatment options (composting, anaerobic digestion, landfilling, and incineration). Also, a sensitivity analysis is generated to check whether the evaluations on the main criteria can change the results or not. The proposed model aims to create a subsidiary tool for decision makers in relevant companies and institutions.

scholarly journals Estimating PQoS of Video Conferencing on Wi-Fi Networks Using Machine Learning

2021 ◽  
Vol 13 (3) ◽  
pp. 63
Author(s):  
Maghsoud Morshedi ◽  
Josef Noll
Keyword(s):  
Machine Learning ◽  
Network Performance ◽  
Service Providers ◽  
Video Conferencing ◽  
Machine Learning Algorithms ◽  
Performance Parameters ◽  
High Definition ◽  
Internet Service ◽  
Novel Approach ◽  
5 Ghz

Video conferencing services based on web real-time communication (WebRTC) protocol are growing in popularity among Internet users as multi-platform solutions enabling interactive communication from anywhere, especially during this pandemic era. Meanwhile, Internet service providers (ISPs) have deployed fiber links and customer premises equipment that operate according to recent 802.11ac/ax standards and promise users the ability to establish uninterrupted video conferencing calls with ultra-high-definition video and audio quality. However, the best-effort nature of 802.11 networks and the high variability of wireless medium conditions hinder users experiencing uninterrupted high-quality video conferencing. This paper presents a novel approach to estimate the perceived quality of service (PQoS) of video conferencing using only 802.11-specific network performance parameters collected from Wi-Fi access points (APs) on customer premises. This study produced datasets comprising 802.11-specific network performance parameters collected from off-the-shelf Wi-Fi APs operating at 802.11g/n/ac/ax standards on both 2.4 and 5 GHz frequency bands to train machine learning algorithms. In this way, we achieved classification accuracies of 92–98% in estimating the level of PQoS of video conferencing services on various Wi-Fi networks. To efficiently troubleshoot wireless issues, we further analyzed the machine learning model to correlate features in the model with the root cause of quality degradation. Thus, ISPs can utilize the approach presented in this study to provide predictable and measurable wireless quality by implementing a non-intrusive quality monitoring approach in the form of edge computing that preserves customers’ privacy while reducing the operational costs of monitoring and data analytics.

scholarly journals Net-exergetic, hydraulic and thermal optimization of coaxial heat exchangers using fixed flow conditions instead of fixed flow rates

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Tobias Blanke ◽  
Markus Hagenkamp ◽  
Bernd Döring ◽  
Joachim Göttsche ◽  
Vitali Reger ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Laminar Flow ◽  
Mass Flow ◽  
Flow Rate ◽  
Heat Exchangers ◽  
Circular Ring ◽  
Flow Conditions ◽  
Flow Rates ◽  
Mass Flow Rates ◽  
Pipe Radius

AbstractPrevious studies optimized the dimensions of coaxial heat exchangers using constant mass flow rates as a boundary condition. They show a thermal optimal circular ring width of nearly zero. Hydraulically optimal is an inner to outer pipe radius ratio of 0.65 for turbulent and 0.68 for laminar flow types. In contrast, in this study, flow conditions in the circular ring are kept constant (a set of fixed Reynolds numbers) during optimization. This approach ensures fixed flow conditions and prevents inappropriately high or low mass flow rates. The optimization is carried out for three objectives: Maximum energy gain, minimum hydraulic effort and eventually optimum net-exergy balance. The optimization changes the inner pipe radius and mass flow rate but not the Reynolds number of the circular ring. The thermal calculations base on Hellström’s borehole resistance and the hydraulic optimization on individually calculated linear loss of head coefficients. Increasing the inner pipe radius results in decreased hydraulic losses in the inner pipe but increased losses in the circular ring. The net-exergy difference is a key performance indicator and combines thermal and hydraulic calculations. It is the difference between thermal exergy flux and hydraulic effort. The Reynolds number in the circular ring is instead of the mass flow rate constant during all optimizations. The result from a thermal perspective is an optimal width of the circular ring of nearly zero. The hydraulically optimal inner pipe radius is 54% of the outer pipe radius for laminar flow and 60% for turbulent flow scenarios. Net-exergetic optimization shows a predominant influence of hydraulic losses, especially for small temperature gains. The exact result depends on the earth’s thermal properties and the flow type. Conclusively, coaxial geothermal probes’ design should focus on the hydraulic optimum and take the thermal optimum as a secondary criterion due to the dominating hydraulics.

scholarly journals A NOVEL APPROACH TO OPTIMIZE THE RIDESHARING PROBLEM USING GENETIC ALGORITHM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 875-878
Author(s):  
S. Rangriz ◽  
M. Davoodi ◽  
J. Saberian
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Public Transportation ◽  
Noise Pollution ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Jam ◽  
Novel Approach ◽  
Proposed Model ◽  
Public Transportation Systems

Abstract. The enormous increase in the number of vehicles in the cities makes plenty of problems including air pollution, noise pollution, and traffic jam. Overcoming these annoying issues needs a significant plan in urban management such as using modern techniques in public transportation systems. Sharing either cars or taxies is one of the most interesting ways that has been used in some countries recently. In this phenomenon, 2 or 3 people use other’s car or taxi. In this article, an innovative approach to share taxies is proposed, and it uses a Genetic Algorithm to determine the placement of travelers in taxies. Therefore, some taxis will be switched off, and this helps to decrease urban traffic jam in cities. The results present that the proposed model turns off 69.8 % of taxies, and also 27.8 % of them carry more than one passenger; hence, this confirms the performance of the proposed model.

scholarly journals A Novel Method to Detect Inner Emotion States of Human using Artificial Neural Networks

2020 ◽  
Vol 8 (6) ◽  
pp. 5820-5825
Keyword(s):  
Physiological Signals ◽  
Classification Rate ◽  
Discrete Emotion ◽  
Novel Approach ◽  
Proposed Model ◽  
Depression Detection ◽  
Novel Method ◽  
Artificial Neural ◽  
Ann Classifier ◽  
Performance Rate

Human computer interaction is a fast growing area of research where in the physiological signals are used to identify human emotion states. Identifying emotion states can be done using various approaches. One such approach which gained interest of research is through physiological signals using EEG. In the present work, a novel approach is proposed to elicit emotion states using 3-D Video-audio stimuli. Around 66 subjects were involved during data acquisition using 32 channel Enobio device. FIR filter is used to preprocess the acquired raw EEG signals. The desired frequency bands like alpha, delta, beta and theta are extracted using 8-level DWT. The statistical features, Hurst exponential, entropy, power, energy, differential entropy of each bands are computed. Artificial Neural network is implemented using Sequential Keras model and applied on the extracted features to classify in to four classes (HVLA, HVHA, LVHA and LVLA) and eight discrete emotion states like clam, relax, happy, joy, sad, fear, tensed and bored. The performance of ANN classifier found to perform better for 4- classes than 8-classes with a classification rate of 90.835% and 74.0446% respectively. The proposed model achieved better performance rate in detecting discrete emotion states. This model can be used to build applications on health like stress / depression detection and on entertainment to build emotional DJ.

On the Effect of the Incident Mach’s Wave on the Pulsation Level in Boundary Layer of the Plane Delta Wing

2014 ◽  
Vol 9 (1) ◽  
pp. 29-38
Author(s):  
Aleksandr Vaganov ◽  
Yuri Yermolaev ◽  
Gleb Kolosov ◽  
Aleksandr Kosinov ◽  
Aleksandra Panina ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Mass Flow ◽  
Delta Wing ◽  
Level Fluctuation ◽  
Flow Pulsation ◽  
Flow Conditions ◽  
Wing Model ◽  
Maximum Value ◽  
Leading Edges ◽  
High Level

The experimental results of high level fluctuation excitation by external Mach’s wave in the boundary layer of delta wing model with blunt leading edges at Mach numbers M = 2, 2.5, 4 are presented. The exitation areas and mass flow pulsation levels in the conditions of subsonic, sonic and supersonic leading edges have been defined. It was found that the maximum value of the pulsations is 12–15 % and varies only slightly from the flow conditions around of the delta wing

Radial Turbine Rotor Response to Pulsating Inlet Flows

2013 ◽  
Vol 136 (7) ◽  
Author(s):  
Teng Cao ◽  
Liping Xu ◽  
Mingyang Yang ◽  
Ricardo F. Martinez-Botas
Keyword(s):  
Numerical Method ◽  
Time Lag ◽  
Turbine Rotor ◽  
Pulsating Flow ◽  
Navier Stokes ◽  
Transient Effects ◽  
Flow Conditions ◽  
Radial Turbine ◽  
Reduced Frequency ◽  
Integrated Performance

The performance of automotive turbocharger turbines has long been realized to be quite different under pulsating flow conditions compared to that under the equivalent steady and quasi-steady conditions on which the conventional design concept is based. However, the mechanisms of this phenomenon are still intensively investigated nowadays. This paper presents an investigation of the response of a stand-alone rotor to inlet pulsating flow conditions by using a validated unsteady Reynolds-averaged Navier–Stokes solver (URANS). The effects of the frequency, the amplitude, and the temporal gradient of pulse waves on the instantaneous and cycle integrated performance of a radial turbine rotor in isolation were studied, decoupled from the upstream turbine volute. A numerical method was used to help gain the physical understanding of these effects. A validation of the numerical method against the experiments on a full configuration of the turbine was performed prior to the numerical tool being used in the investigation. The rotor was then taken out to be studied in isolation. The results show that the turbine rotor alone can be treated as a quasi-steady device only in terms of cycle integrated performance; however, instantaneously, the rotor behaves unsteadily, which increasingly deviates from the quasi-steady performance as the local reduced frequency of the pulsating wave is increased. This deviation is dominated by the effect of quasi-steady time lag; at higher local reduced frequency, the transient effects also become significant. Based on this study, an interpretation and a model of estimating the quasi-steady time lag have been proposed; a criterion for unsteadiness based on the temporal local reduced frequency concept is developed, which reduces to the Λ criterion proposed in the published literature when cycle averaged. This in turn emphasizes the importance of the pressure wave gradient in time.

Sign in / Sign up

Export Citation Format

Share Document