Experimental Investigation of Solid Particle Erosion in Successive Elbows in Gas Dominated Flows

2018 ◽  
Author(s):  
Alireza Asgharpour ◽  
Peyman Zahedi ◽  
Hadi Arabnejad Khanouki ◽  
Siamack A. Shirazi ◽  
Brenton S. McLaury
Keyword(s):  
Phase Distribution ◽  
State Of The Art ◽  
Flow Direction ◽  
Erosive Wear ◽  
Flow Conditions ◽  
In Series ◽  
Particle Velocities ◽  
Paint Removal ◽  
Impact Region

When a fluid containing erosive particles flows through two or more elbows mounted in series with short distances between them, the downstream elbows which are installed after the first elbow are exposed to erosion from a flow that is not fully developed. Particle velocities and concentration distributions change due to change of flow direction within the first elbow which may cause the characteristics of erosive wear in the second elbow to be different than the first. In the present study, the erosion magnitude and pattern in two 4-inch standard successive elbows installed with 13D distance from each other are examined experimentally. Utilizing a state-of-the-art ultrasonic technique, erosion measurements are performed in gas-sand and gas-liquid-sand annular flows to investigate the effects of particle size and flow rates. A paint removal study is also performed to capture the erosion patterns in two elbows for different flow conditions. Using two clear elbows, a flow visualization is performed which shows the quality of phase distribution in the two elbows in series in annular and stratified flows. Erosion measurements show the results in the second elbow for this geometry and these flow conditions are less than or in a few cases nearly equal to the first elbow. The location of maximum erosion for all the cases considered is around 45 and 65 degrees from the inlet of the elbow in the first and second elbows, respectively. Two areas are identified in erosion patterns of both elbows. One high intensity particle impact region which is affected primarily by first impact of particles, and another pattern is formed due to impacting particles that have rebounded from the first impact.

Experimental Investigation of Solid Particle Erosion in Successive Elbows in Gas Dominated Flows

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Alireza Asgharpour ◽  
Peyman Zahedi ◽  
Hadi Arabnejad Khanouki ◽  
Siamack A. Shirazi ◽  
Brenton S. McLaury
Keyword(s):  
Phase Distribution ◽  
Erosive Wear ◽  
High Impact ◽  
Stratified Flows ◽  
Solid Particle Erosion ◽  
Flow Conditions ◽  
In Series ◽  
Paint Removal ◽  
Impact Region

Abstract When a fluid containing erosive particles flows through two or more elbows mounted in series with short distances between them, the downstream elbows which are installed after the first elbow are exposed to erosion from a flow that is not fully developed, and therefore, the characteristics of erosive wear in the second elbow can be different than the first. In this work, the erosion magnitude and pattern in two standard successive vertical–horizontal and horizontal–vertical elbows are examined experimentally. Utilizing an ultrasonic technique (UT), erosion measurements are performed in gas–sand and gas–liquid–sand annular flows to investigate the effects of particle size and flowrates. A paint removal study is also performed to capture the erosion patterns in two elbows for different flow conditions. Using two clear elbows, a flow visualization is performed which shows the quality of phase distribution in the two elbows in series in annular and stratified flows. Measurements show the erosion in the second elbow for this geometry and these flow conditions are less than or in a few cases nearly equal to the first elbow. The location of maximum erosion for all the cases considered is around 45 and 65 deg from the inlet of the elbow in the first and second elbows, respectively. Two areas of high impact frequencies are identified in both elbows. One high-intensity particle impact region which is affected primarily by first impact of particles, and another pattern is formed due to rebounded particles from the first impact.

The contribution of erosive wear to the performance degradation of sliding spool servovalves

1998 ◽  
Vol 212 (6) ◽  
pp. 437-451 ◽  
Author(s):  
N. D. Vaughan ◽  
P. E. Pomeroy ◽  
D. G. Tilley
Keyword(s):  
Flow Direction ◽  
Surface Hardness ◽  
Erosive Wear ◽  
Central Position ◽  
Flow Conditions ◽  
Controlled System ◽  
Particle Contamination ◽  
Contaminant Particle ◽  
Spool Valves ◽  
Fluid Characteristics

Flow conditions for sliding spool valves around their central position may be critical in terms of the resulting system performance. In-service changes that occur can cause a degradation of the performance of both the valve and the controlled system. The degradation due to erosive wear arising from solid particle contamination in the fluid flow is examined in detail in this paper. It reports the details of a test rig and methodology that has been carefully established to examine the effect of various factors on erosion wear. These factors include the contaminant particle size and concentration, differential pressure across the metering land, spool opening, spool surface hardness and flow direction, as well as fluid characteristics.

Status of nondestructive control of transport function metal products at JSC EVRAZ NTMK

2020 ◽  
Vol 76 (6) ◽  
pp. 586-590
Author(s):  
S. P. Bersenev ◽  
E. M. Slobtsova
Keyword(s):  
Crack Detection ◽  
Middle Part ◽  
Control Line ◽  
Magnetic Powder ◽  
Nondestructive Control ◽  
Automated Control ◽  
Ultrasonic Control ◽  
Acoustic Contact ◽  
In Series

Achievements in the area of automated ultrasonic control of quality of rails, solid-rolled wheels and tyres, wheels magnetic powder crack detection, carried out at JSC EVRAZ NTMK. The 100% nondestructive control is accomplished by automated control in series at two ultrasonic facilities RWI-01 and four facilities УМКК-1 of magnetic powder control, installed into the exit control line in the wheel-tyre shop. Diagram of location, converters displacement and control operations in the process of control at the facility RWI-01 presented, as well as the structural diagram of the facility УМКК-1. The automated ultrasonic control of rough tyres is made in the tyres control line of the wheel-tyre shop at the facility УКБ-1Д. The facility enables to control internal defects of tyres in radial, axis and circular directions of radiation. Possibilities of the facility УКБ-1Д software were shown. Nondestructive control of railway rails is made at two facilities, comprising the automated control line of the rail and structural shop. The УКР-64Э facility of automated ultrasonic rails control is intended to reveal defects in the area of head, web and middle part of rail foot by pulse echo-method with a immersion acoustic contact. The diagram of rail P65 at the facility УКР-64Э control presented. To reveal defects of the macrostructure in the area of rail head and web by mirror-shadow method, an ultrasonic noncontact electromagnetic-acoustic facility is used. It was noted, that implementation of the 100% nondestructive control into the technology of rolled stuff production enabled to increase the quality of products supplied to customers and to increase their competiveness.

Data science in economics: comprehensive review of advanced machine learning and deep learning methods

2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Data Science ◽  
State Of The Art ◽  
Science Methods ◽  
Learning Models ◽  
Diverse Range ◽  
Hybrid Machine ◽  
Economics Research

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.

State-of-the-Art: A Systematic Literature Review on Image Segmentation in Latent Fingerprint Forensics

2019 ◽  
Vol 12 ◽  
Author(s):  
Megha Chhabra ◽  
Manoj Kumar Shukla ◽  
Kiran Kumar Ravulakollu
Keyword(s):  
Image Segmentation ◽  
Background Noise ◽  
State Of The Art ◽  
Recognition Rate ◽  
Poor Quality ◽  
Latent Fingerprint ◽  
In The Beginning ◽  
The Comparative Study ◽  
Finger Skin

: Latent fingerprints are unintentional finger skin impressions left as ridge patterns at crime scenes. A major challenge in latent fingerprint forensics is the poor quality of the lifted image from the crime scene. Forensics investigators are in permanent search of novel outbreaks of the effective technologies to capture and process low quality image. The accuracy of the results depends upon the quality of the image captured in the beginning, metrics used to assess the quality and thereafter level of enhancement required. The low quality of the image collected by low quality scanners, unstructured background noise, poor ridge quality, overlapping structured noise result in detection of false minutiae and hence reduce the recognition rate. Traditionally, Image segmentation and enhancement is partially done manually using help of highly skilled experts. Using automated systems for this work, differently challenging quality of images can be investigated faster. This survey amplifies the comparative study of various segmentation techniques available for latent fingerprint forensics.

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

scholarly journals Ensemble-Based Out-of-Distribution Detection

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 567
Author(s):  
Donghun Yang ◽  
Kien Mai Mai Ngoc ◽  
Iksoo Shin ◽  
Kyong-Ha Lee ◽  
Myunggwon Hwang
Keyword(s):  
Detection Method ◽  
State Of The Art ◽  
Metric Learning ◽  
Feature Space ◽  
Confidence Score ◽  
Distance Metric Learning ◽  
Current State ◽  
Overall Performance ◽  
Deep Learning Model

To design an efficient deep learning model that can be used in the real-world, it is important to detect out-of-distribution (OOD) data well. Various studies have been conducted to solve the OOD problem. The current state-of-the-art approach uses a confidence score based on the Mahalanobis distance in a feature space. Although it outperformed the previous approaches, the results were sensitive to the quality of the trained model and the dataset complexity. Herein, we propose a novel OOD detection method that can train more efficient feature space for OOD detection. The proposed method uses an ensemble of the features trained using the softmax-based classifier and the network based on distance metric learning (DML). Through the complementary interaction of these two networks, the trained feature space has a more clumped distribution and can fit well on the Gaussian distribution by class. Therefore, OOD data can be efficiently detected by setting a threshold in the trained feature space. To evaluate the proposed method, we applied our method to various combinations of image datasets. The results show that the overall performance of the proposed approach is superior to those of other methods, including the state-of-the-art approach, on any combination of datasets.

A Simulation Software for the Evaluation of Vulnerabilities in Reputation Management Systems

2021 ◽  
Vol 37 (1-4) ◽  
pp. 1-30
Author(s):  
Vincenzo Agate ◽  
Alessandra De Paola ◽  
Giuseppe Lo Re ◽  
Marco Morana
Keyword(s):  
Quality Of Service ◽  
Distributed Systems ◽  
State Of The Art ◽  
Simulation Software ◽  
Reputation Management ◽  
Management Systems ◽  
Security Attacks ◽  
Vulnerability Evaluation ◽  
Multi Agent

Multi-agent distributed systems are characterized by autonomous entities that interact with each other to provide, and/or request, different kinds of services. In several contexts, especially when a reward is offered according to the quality of service, individual agents (or coordinated groups) may act in a selfish way. To prevent such behaviours, distributed Reputation Management Systems (RMSs) provide every agent with the capability of computing the reputation of the others according to direct past interactions, as well as indirect opinions reported by their neighbourhood. This last point introduces a weakness on gossiped information that makes RMSs vulnerable to malicious agents’ intent on disseminating false reputation values. Given the variety of application scenarios in which RMSs can be adopted, as well as the multitude of behaviours that agents can implement, designers need RMS evaluation tools that allow them to predict the robustness of the system to security attacks, before its actual deployment. To this aim, we present a simulation software for the vulnerability evaluation of RMSs and illustrate three case studies in which this tool was effectively used to model and assess state-of-the-art RMSs.

scholarly journals ART-UP: A Novel Method for Generating Scanning-Robust Aesthetic QR Codes

2021 ◽  
Vol 17 (1) ◽  
pp. 1-23
Author(s):  
Mingliang Xu ◽  
Qingfeng Li ◽  
Jianwei Niu ◽  
Hao Su ◽  
Xiting Liu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Qr Code ◽  
Quick Response ◽  
Estimation Model ◽  
Qr Codes ◽  
Excellent Performance ◽  
Novel Method ◽  
Coarse To Fine

Quick response (QR) codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this article, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.

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