scholarly journals Acoustic Emission investigation for avalanche formation and release: A case study of dry-slab avalanche event in Great Himalaya

2020 ◽  
Author(s):  
Jagdish Kapil ◽  
Sakshi Sharma ◽  
Karmjit Singh ◽  
Jangvir Singh Shahi ◽  
Rama Arora
Keyword(s):  
Acoustic Emission ◽  
High Speed ◽  
Instability Index ◽  
Critical Instability ◽  
Long Time ◽  
Research Challenge ◽  
Avalanche Formation ◽  
Instability Indices ◽  
Release Processes

Abstract. Non-invasive monitoring of avalanche formation and release processes, through the use of Acoustic Emission (AE) technique, has been a research challenge since long time. In present investigation AE technique is implemented to monitor the avalanche formation and release processes through a case study of a natural avalanche event reported in Great Himalaya. The specialized AE sensor-arrestor arrays, established over the avalanche starting zone, in conjunction to a high speed multichannel AE acquisition system have successfully recorded the avalanche event passed through the course of instability development followed by release of avalanche. A new method is devised to compute the AE based instability index, and same has been applied to quantify the instability levels of a snowpack. The prominent AE parameters and instability indices are analyzed for different window scales with respect to different AE sensors. The effect of nivological and meteorological conditions and pit analyses collected during the avalanche formation process is also discussed. The critical instability was triggered possibly due to the excessive loading (during snowfall) of an unstable snowpack consisting of persistent weak layers which led to the avalanche release. An abnormal and abrupt increase in the AE activity was observed prior to the avalanche release. The increasing trends in instability indices have shown a good correlation to the avalanche formation and a sharp jump in instability index is attributed to a particular transition occurring across two different instability states of the snowpack. Thus, five conceptual states of snowpack are identified for instability evolution corresponding to four different transitions during avalanche formation and release processes.

APPLICATION OF THE EARLY DAMAGE DIAGNOSTICS TECHNIQUE TO EXAMINATION OF THE AVIATION PANEL

2019 ◽  
Vol 85 (6) ◽  
pp. 53-63 ◽  
Author(s):  
I. E. Vasil’ev ◽  
Yu. G. Matvienko ◽  
A. V. Pankov ◽  
A. G. Kalinin
Keyword(s):  
Acoustic Emission ◽  
Damage Detection ◽  
High Speed ◽  
Early Stage ◽  
Video Data ◽  
High Speed Video ◽  
Damage Diagnostics ◽  
Subsurface Defect ◽  
Sensitive Coating ◽  
Early Damage

The results of using early damage diagnostics technique (developed in the Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN) for detecting the latent damage of an aviation panel made of composite material upon bench tensile tests are presented. We have assessed the capabilities of the developed technique and software regarding damage detection at the early stage of panel loading in conditions of elastic strain of the material using brittle strain-sensitive coating and simultaneous crack detection in the coating with a high-speed video camera “Video-print” and acoustic emission system “A-Line 32D.” When revealing a subsurface defect (a notch of the middle stringer) of the aviation panel, the general concept of damage detection at the early stage of loading in conditions of elastic behavior of the material was also tested in the course of the experiment, as well as the software specially developed for cluster analysis and classification of detected location pulses along with the equipment and software for simultaneous recording of video data flows and arrays of acoustic emission (AE) data. Synchronous recording of video images and AE pulses ensured precise control of the cracking process in the brittle strain-sensitive coating (tensocoating)at all stages of the experiment, whereas the use of structural-phenomenological approach kept track of the main trends in damage accumulation at different structural levels and identify the sources of their origin when classifying recorded AE data arrays. The combined use of oxide tensocoatings and high-speed video recording synchronized with the AE control system, provide the possibility of definite determination of the subsurface defect, reveal the maximum principal strains in the area of crack formation, quantify them and identify the main sources of AE signals upon monitoring the state of the aviation panel under loading P = 90 kN, which is about 12% of the critical load.

Comparative study on the use of acoustic emission and vibration analyses for the bearing fault diagnosis of high-speed trains

2021 ◽  
pp. 147592172110360
Author(s):  
Dongming Hou ◽  
Hongyuan Qi ◽  
Honglin Luo ◽  
Cuiping Wang ◽  
Jiangtian Yang
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
High Speed ◽  
High Speed Train ◽  
Signal Attenuation ◽  
Transmission Path ◽  
Bearing Fault Diagnosis ◽  
Operation Conditions ◽  
Fault Features ◽  
High Speed Trains

A wheel set bearing is an important supporting component of a high-speed train. Its quality and performance directly determine the overall safety of the train. Therefore, monitoring a wheel set bearing’s conditions for an early fault diagnosis is vital to ensure the safe operation of high-speed trains. However, the collected signals are often contaminated by environmental noise, transmission path, and signal attenuation because of the complexity of high-speed train systems and poor operation conditions, making it difficult to extract the early fault features of the wheel set bearing accurately. Vibration monitoring is most widely used for bearing fault diagnosis, with the acoustic emission (AE) technology emerging as a powerful tool. This article reports a comparison between vibration and AE technology in terms of their applicability for diagnosing naturally degraded wheel set bearings. In addition, a novel fault diagnosis method based on the optimized maximum second-order cyclostationarity blind deconvolution (CYCBD) and chirp Z-transform (CZT) is proposed to diagnose early composite fault defects in a wheel set bearing. The optimization CYCBD is adopted to enhance the fault-induced impact response and eliminate the interference of environmental noise, transmission path, and signal attenuation. CZT is used to improve the frequency resolution and match the fault features accurately under a limited data length condition. Moreover, the efficiency of the proposed method is verified by the simulated bearing signal and the real datasets. The results show that the proposed method is effective in the detection of wheel set bearing faults compared with the minimum entropy deconvolution (MED) and maximum correlated kurtosis deconvolution (MCKD) methods. This research is also the first to compare the effectiveness of applying AE and vibration technologies to diagnose a naturally degraded high-speed train bearing, particularly close to actual line operation conditions.

scholarly journals Analysis of Dangerous Sea States in the Northwestern Mediterranean Area

2021 ◽  
Vol 9 (4) ◽  
pp. 422
Author(s):  
Alessio Innocenti ◽  
Miguel Onorato ◽  
Carlo Brandini
Keyword(s):  
Extreme Events ◽  
Mediterranean Area ◽  
Rayleigh Distribution ◽  
Surface Elevation ◽  
Wave Steepness ◽  
Sea Waves ◽  
Operational Forecasts ◽  
Long Time ◽  
Simulated Field

Extreme sea waves, although rare, can be notably dangerous when associated with energetic sea states and can generate risks for the navigation. In the last few years, they have been the object of extensive research from the scientific community that helped with understanding the main physical aspects; however, the estimate of extreme waves probability in operational forecasts is still debated. In this study, we analyzed a number of sea-states that occurred in a precise area of the Mediterranean sea, near the location of a reported accident, with the objective of relating the probability of extreme events with different sea state conditions. For this purpose, we performed phase-resolving simulations of wave spectra obtained from a WaveWatch III hindcast, using a Higher Order Spectral Method. We produced statistics of the sea-surface elevation field, calculating crest distributions and the probability of extreme events from the analysis of a long time-series of the surface elevation. We found a good matching between the distributions of the numerically simulated field and theory, namely Tayfun second- and third- order ones, in contrast with a significant underestimate given by the Rayleigh distribution. We then related spectral quantities like angular spreading and wave steepness to the probability of occurrence of extreme events finding an enhanced probability for high mean steepness seas and narrow spectra, in accordance with literature results, finding also that the case study of the reported accident was not amongst the most dangerous. Finally, we related the skewness and kurtosis of the surface elevation to the wave steepness to explain the discrepancy between theoretical and numerical distributions.

scholarly journals Influence of Hydrogeochemistry on Tunnel Drainage in Evaporitic Formations: El Regajal Tunnel Case Study (Aranjuez, Spain)

2021 ◽  
Vol 13 (3) ◽  
pp. 1505
Author(s):  
Ignacio Menéndez Pidal ◽  
Jose Antonio Mancebo Piqueras ◽  
Eugenio Sanz Pérez ◽  
Clemente Sáenz Sanz
Keyword(s):  
High Speed ◽  
Civil Engineering ◽  
Saturation Index ◽  
The Subject ◽  
Under Construction ◽  
Underground Flow ◽  
Very High ◽  
Over Time

Many of the large number of underground works constructed or under construction in recent years are in unfavorable terrains facing unusual situations and construction conditions. This is the case of the subject under study in this paper: a tunnel excavated in evaporitic rocks that experienced significant karstification problems very quickly over time. As a result of this situation, the causes that may underlie this rapid karstification are investigated and a novel methodology is presented in civil engineering where the use of saturation indices for the different mineral specimens present has been crucial. The drainage of the rock massif of El Regajal (Madrid-Toledo, Spain, in the Madrid-Valencia high-speed train line) was studied and permitted the in-situ study of the hydrogeochemical evolution of water flow in the Miocene evaporitic materials of the Tajo Basin as a full-scale testing laboratory, that are conforms as a whole, a single aquifer. The work provides a novel methodology based on the calculation of activities through the hydrogeochemical study of water samples in different piezometers, estimating the saturation index of different saline materials and the dissolution capacity of the brine, which is surprisingly very high despite the high electrical conductivity. The circulating brine appears unsaturated with respect to thenardite, mirabilite, epsomite, glauberite, and halite. The alteration of the underground flow and the consequent renewal of the water of the aquifer by the infiltration water of rain and irrigation is the cause of the hydrogeochemical imbalance and the modification of the characteristics of the massif. These modifications include very important loss of material by dissolution, altering the resistance of the terrain and the increase of the porosity. Simultaneously, different expansive and recrystallization processes that decrease the porosity of the massif were identified in the present work. The hydrogeochemical study allows the evolution of these phenomena to be followed over time, and this, in turn, may facilitate the implementation of preventive works in civil engineering.

Removing W Polymer Residue from BEOL Structures Using DSP+ (Dilute Sulfuric-Peroxide-HF) Mixture – A Case Study

2012 ◽  
Vol 195 ◽  
pp. 128-131 ◽  
Author(s):  
Hun Hee Lee ◽  
Min Sang Yun ◽  
Hyun Wook Lee ◽  
Jin Goo Park
Keyword(s):  
High Speed ◽  
Semiconductor Device ◽  
Environmental Issues ◽  
Low Power Consumption ◽  
Device Performance ◽  
Metal Gate ◽  
Feature Size ◽  
High K ◽  
Removal Of Metal

As the feature size of semiconductor device shrinks continuously, various high-K metals for 3-D structures have been applied to improve the device performance, such as high speed and low power consumption. Metal gate fabrication requires the removal of metal and polymer residues after etching process without causing any undesired etching and corrosion of metals. The conventional sulfuric-peroxide mixture (SPM) has many disadvantages like the corrosion of metals, environmental issues etc., DSP+(dilute sulfuric-peroxide-HF mixture) chemical is currently used for the removal of post etch residues on device surface, to replace the conventional SPM cleaning [. Due to the increased usage of metal gate in devices in recent times, the application of DSP+chemicals for cleaning processes also increases [.

HFTViz: Visualization for the exploration of high frequency trading data

2021 ◽  
pp. 147387162110649
Author(s):  
Javad Yaali ◽  
Vincent Grégoire ◽  
Thomas Hurtut
Keyword(s):  
Portfolio Management ◽  
High Frequency ◽  
High Speed ◽  
High Frequency Trading ◽  
Domain Experts ◽  
Risk Return ◽  
Visualization Tools ◽  
Liquidity Measures ◽  
Trading Volumes

High Frequency Trading (HFT), mainly based on high speed infrastructure, is a significant element of the trading industry. However, trading machines generate enormous quantities of trading messages that are difficult to explore for financial researchers and traders. Visualization tools of financial data usually focus on portfolio management and the analysis of the relationships between risk and return. Beside risk-return relationship, there are other aspects that attract financial researchers like liquidity and moments of flash crashes in the market. HFT researchers can extract these aspects from HFT data since it shows every detail of the market movement. In this paper, we present HFTViz, a visualization tool designed to help financial researchers explore the HFT dataset provided by NASDAQ exchange. HFTViz provides a comprehensive dashboard aimed at facilitate HFT data exploration. HFTViz contains two sections. It first proposes an overview of the market on a specific date. After selecting desired stocks from overview visualization to investigate in detail, HFTViz also provides a detailed view of the trading messages, the trading volumes and the liquidity measures. In a case study gathering five domain experts, we illustrate the usefulness of HFTViz.

Machine Learning Acoustic Emission Based Monitoring of Cold Forging for Smart Manufacturing: A Review

2021 ◽  
Vol 2 (3) ◽  
Keyword(s):  
Machine Learning ◽  
Acoustic Emission ◽  
Product Quality ◽  
High Speed ◽  
High Rate ◽  
Cold Forging ◽  
Smart Manufacturing ◽  
Forming Process ◽  
Cold Forming ◽  
Effective Manner

Cold forging is a high-speed forming technique used to shape metals at near room temperature. and it allows high-rate production of high strength metal-based products in a consistent and cost-effective manner. However, cold forming processes are characterized by complex material deformation dynamics which makes product quality control difficult to achieve. There is no well defined mathematical model that governs the interactions between a cold forming process, material properties, and final product quality. The goal of this work is to provide a review for the state of research in the field of using acoustic emission (AE) technology in monitoring cold forging process. The integration of AE with machine learning (ML) algorithms to monitor the quality is also reviewed and discussed. It is realized that this promising technology didn’t receive the deserving attention for its implementation in cold forging and that more work is needed.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

2021 ◽  
pp. 095440972110421
Author(s):  
Minling Feng ◽  
Chaoxian Wu ◽  
Shaofeng Lu ◽  
Yihui Wang
Keyword(s):  
High Speed ◽  
Applied Force ◽  
Mixed Integer ◽  
High Speed Railway ◽  
Train Operation ◽  
Train Speed ◽  
Automatic Train Operation ◽  
The Impact ◽  
Trajectory Optimisation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.

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