Localized Damage Detection Algorithm and Implementation on a Large-Scale Steel Beam-to-Column Moment Connection

2015 ◽  
Vol 31 (3) ◽  
pp. 1543-1566 ◽  
Author(s):  
Siavash Dorvash ◽  
Shamim N. Pakzad ◽  
Elizabeth L. LaCrosse ◽  
James M. Ricles ◽  
Ian C. Hodgson
Keyword(s):  
Damage Detection ◽  
Large Scale ◽  
Structural Changes ◽  
Structural Model ◽  
Detection Algorithm ◽  
Steel Beam ◽  
Extreme Loads ◽  
Moment Connection ◽  
Significant Research ◽  
Increasing Cyclic Loading

Civil structures experience loading scenarios ranging from typical ambient excitations to extreme loads induced by natural events that, depending on their intensity, cause damage. It is important to detect damage before it propagates to become detrimental to integrity and functionality of the structure. Significant research efforts are focused on developing damage detection algorithms to diagnose damage from performance and response of the structure. A major challenge in many existing algorithms is in their validation and absence of real-scale implementation. This paper presents implementation of influence-based damage detection algorithm by implementation on a large-scale structural model (steel beam-to-column moment connection) which experiences progressive damage towards collapse of the system through increasing cyclic loading. IDDA utilizes statistical analysis of correlation functions between the structural responses at different locations. It is shown through this implementation that IDDA, accompanied by a statistical framework, can accurately identify structural changes and indicate the intensity of the damage.

Lamb Waves Signal Analysis in Structural Health Monitoring Systems

2011 ◽  
Vol 368-373 ◽  
pp. 2402-2405
Author(s):  
Nai Zhi Zhao ◽  
Chang Tie Huang ◽  
Xin Chen
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Changes ◽  
Lamb Waves ◽  
Detection Algorithm ◽  
Operational Conditions ◽  
Structural Health ◽  
Detection Algorithms ◽  
Baseline Subtraction

Many of the wave propagation based structural health monitoring techniques rely on some knowledge of the structure in a healthy state in order to identify damage. Baseline measurements are recorded when a structure is pristine and are stored for comparison to future data. A concern with the use of baseline subtraction methods is the ability to discern structural changes from the effects of varying environmental and operational conditions when analyzing the vibration response of a system. The use of a standard baseline subtraction technique may falsely indicate damage when environmental or operational variations are present between baseline measurements and new measurements. A procedure was outlined for the method, including excitation and recording of Lamb waves, and the use of damage detection algorithms. In this paper, several tests are performed and the results are used to help develop the damage detection algorithms previously described, and to evaluate the performance of the instantaneous baseline SHM technique. Analytical testing is first performed by feeding known input signals into each damage detection algorithm and analyzing the output data. The results of the analytical testing are used to help develop the damage detection algorithms.

Automotive Wire Control Steering Sensor Fault Detection Algorithm Research

2015 ◽  
Vol 727-728 ◽  
pp. 708-711
Author(s):  
Zhi Ping Liu
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Large Scale ◽  
Structural Changes ◽  
Detection Algorithm ◽  
Steering System ◽  
Steering Wheel ◽  
Detection Accuracy ◽  
Sensor Fault ◽  
Sensor Fault Detection

This article to cancel after the mechanical connections between steering wheel and steering, wire control steering system security and reliability problems, put forward on the basis of the analytical redundancy software sensor method of wire control steering system. In order to solve the compared with the traditional steering system in terms of reliability and safety of the problems of structural changes, the wire control steering system of the main sensor fault diagnosis methods are studied. In wire control steering system associated with the vehicle dynamics model is established under the premise of hypothesis testing to double adaptive fading Kalman filtering technology as a platform, combined with according to the working state of each sensors to determine fault feature vector, to build the main sensor wire control steering automobile fault diagnosis method of residual error threshold. For fault diagnosis of automobile EPS sensor, the BP neural network is put forward to EPS sensor for auto are introduced in the fault diagnosis. For large-scale wireless sensor networks (WSN), reduce the fault detection accuracy, and larger load of communication problems, according to the spatial and temporal correlation characteristics of sensor nodes, proposes a distributed sensor fault detection algorithm based on cluster. These algorithms for sensor fault detection is of great significance.

scholarly journals Topological Determinants of Epileptogenesis in Large-Scale Structural and Functional Models of the Dentate Gyrus Derived From Experimental Data

2007 ◽  
Vol 97 (2) ◽  
pp. 1566-1587 ◽  
Author(s):  
Jonas Dyhrfjeld-Johnsen ◽  
Vijayalakshmi Santhakumar ◽  
Robert J. Morgan ◽  
Ramon Huerta ◽  
Lev Tsimring ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
Network Architecture ◽  
Large Scale ◽  
Structural Changes ◽  
Structural Model ◽  
Small World ◽  
Long Distance ◽  
General Importance

In temporal lobe epilepsy, changes in synaptic and intrinsic properties occur on a background of altered network architecture resulting from cell loss and axonal sprouting. Although modeling studies using idealized networks indicated the general importance of network topology in epilepsy, it is unknown whether structural changes that actually take place during epileptogenesis result in hyperexcitability. To answer this question, we built a 1:1 scale structural model of the rat dentate gyrus from published in vivo and in vitro cell type–specific connectivity data. This virtual dentate gyrus in control condition displayed globally and locally well connected (“small world”) architecture. The average number of synapses between any two neurons in this network of over one million cells was less than three, similar to that measured for the orders of magnitude smaller C. elegans nervous system. To study how network architecture changes during epileptogenesis, long-distance projecting hilar cells were gradually removed in the structural model, causing massive reductions in the number of total connections. However, as long as even a few hilar cells survived, global connectivity in the network was effectively maintained and, as a result of the spatially restricted sprouting of granule cell axons, local connectivity increased. Simulations of activity in a functional dentate network model, consisting of over 50,000 multicompartmental single-cell models of major glutamatergic and GABAergic cell types, revealed that the survival of even a small fraction of hilar cells was enough to sustain networkwide hyperexcitability. These data indicate new roles for fractionally surviving long-distance projecting hilar cells observed in specimens from epilepsy patients.

scholarly journals Rayleigh’s quotient–based damage detection algorithm: Theoretical concepts, computational techniques, and field implementation strategies

2017 ◽  
Vol 17 (2) ◽  
pp. 285-297 ◽  
Author(s):  
Wilfried Njomo Wandji
Keyword(s):  
Damage Detection ◽  
Structural Changes ◽  
Implementation Strategies ◽  
Optimization Methods ◽  
Detection Algorithm ◽  
Computational Techniques ◽  
Energy Principle ◽  
Theoretical Concepts ◽  
Operational Conditions ◽  
Rayleigh’S Quotient

This article proposes a Rayleigh’s quotient–based damage detection algorithm. It aims at efficiently revealing nascent structural changes on a given structure with the capability to differentiate between an actual damage and a change in operational conditions. The first three damage detection levels are targeted: existence, location, and severity. The proposed algorithm is analytically developed from the dynamics theory and the virtual energy principle. Some computational techniques are proposed for carrying out computations, including discretization, integration, derivation, and suitable optimization methods. Field implementation strategies are also considered for the purpose of online damage monitoring. In order to prove the efficiency of this strategy, one experimental and three numerical case studies were conducted. The proposed algorithm successfully detected the damage in all simulated cases and estimated the damage severity with acceptable accuracy. The conclusion is that the proposed algorithm was able to efficiently detect damage appearance in a range of structures for various damage levels and locations, and under different operational conditions.

Do Lower Foreign Flows and Higher Domestic Flows Reduce Indian Equity Market Volatility?

2021 ◽  
pp. 097226292199098
Author(s):  
Vaibhav Aggarwal ◽  
Adesh Doifode ◽  
Mrityunjay Kumar Tiwary
Keyword(s):  
Stock Market ◽  
Mutual Fund ◽  
Stock Markets ◽  
Large Scale ◽  
Structural Changes ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Equity Investments ◽  
Net Equity ◽  
Indian Stock Market

This study examines the relationship that both domestic and foreign institutional net equity flows have with the India stock markets. The motivation behind is the study to examine whether increased net equity investments from domestic institutional investors has reduced the influence of foreign equity flows on the Indian stock market volatility. Our results indicate that only during periods in which domestic equity inflows surpass foreign flows by a significant margin, as seen during 2015–2018, is the Indian stock market volatility not significantly influenced by foreign equity investments. However, during periods of re-emergence of strong foreign net inflows, the Indian market volatility is still being impacted significantly, as has been observed since 2019. Furthermore, we find that both large-scale net buying and net selling by domestic funds increased the stock market volatility as observed during 2015–2018 and COVID-impacted year 2020 respectively. The implications of this study are multi-fold. First, the regulators should discuss with industry bodies before enforcing major structural changes like reconstituting of mutual fund investment mandate in 2017 which forced domestic funds to quickly change portfolio allocation amongst large-cap, mid-cap and small-cap stocks resulting in higher stock market volatility. Second, adequate investor educational and awareness programmes need to be conducted regularly for retail investors to minimize herd behaviour of investing during market rise and heavy redemptions at times of fall. Third, the economic policies should be stable and forward-looking to ensure foreign investors remain attracted to the Indian stock markets at all times.

scholarly journals Secondary Structural Model of MALAT1 Becomes Unstructured in Chronic Myeloid Leukemia and Undergoes Structural Rearrangement in Cervical Cancer

2021 ◽  
Vol 7 (1) ◽  
pp. 6
Author(s):  
Matthew C. Wang ◽  
Phillip J. McCown ◽  
Grace E. Schiefelbein ◽  
Jessica A. Brown
Keyword(s):  
Cervical Cancer ◽  
Chronic Myeloid Leukemia ◽  
Hela Cells ◽  
Binding Sites ◽  
Myeloid Leukemia ◽  
Structural Changes ◽  
Structural Model ◽  
Dimethyl Sulfate ◽  
K562 Cells ◽  
Cancer Types

Long noncoding RNAs (lncRNAs) influence cellular function through binding events that often depend on the lncRNA secondary structure. One such lncRNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), is upregulated in many cancer types and has a myriad of protein- and miRNA-binding sites. Recently, a secondary structural model of MALAT1 in noncancerous cells was proposed to form 194 hairpins and 13 pseudoknots. That study postulated that, in cancer cells, the MALAT1 structure likely varies, thereby influencing cancer progression. This work analyzes how that structural model is expected to change in K562 cells, which originated from a patient with chronic myeloid leukemia (CML), and in HeLa cells, which originated from a patient with cervical cancer. Dimethyl sulfate-sequencing (DMS-Seq) data from K562 cells and psoralen analysis of RNA interactions and structure (PARIS) data from HeLa cells were compared to the working structural model of MALAT1 in noncancerous cells to identify sites that likely undergo structural alterations. MALAT1 in K562 cells is predicted to become more unstructured, with almost 60% of examined hairpins in noncancerous cells losing at least half of their base pairings. Conversely, MALAT1 in HeLa cells is predicted to largely maintain its structure, undergoing 18 novel structural rearrangements. Moreover, 50 validated miRNA-binding sites are affected by putative secondary structural changes in both cancer types, such as miR-217 in K562 cells and miR-20a in HeLa cells. Structural changes unique to K562 cells and HeLa cells provide new mechanistic leads into how the structure of MALAT1 may mediate cancer in a cell-type specific manner.

Structural Changes in Thalamic Nuclei Across Prodromal and Clinical Alzheimer’s Disease

2021 ◽  
pp. 1-11
Author(s):  
Adam S. Bernstein ◽  
Steven Z. Rapcsak ◽  
Michael Hornberger ◽  
Manojkumar Saranathan ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Structural Changes ◽  
Thalamic Nuclei ◽  
Medial Temporal Lobes ◽  
Cognitive Changes ◽  
Temporal Lobes ◽  
Medial Geniculate ◽  
Healthy Control

Background: Increasing evidence suggests that thalamic nuclei may atrophy in Alzheimer’s disease (AD). We hypothesized that there will be significant atrophy of limbic thalamic nuclei associated with declining memory and cognition across the AD continuum. Objective: The objective of this work was to characterize volume differences in thalamic nuclei in subjects with early and late mild cognitive impairment (MCI) as well as AD when compared to healthy control (HC) subjects using a novel MRI-based thalamic segmentation technique (THOMAS). Methods: MPRAGE data from the ADNI database were used in this study (n = 540). Healthy control (n = 125), early MCI (n = 212), late MCI (n = 114), and AD subjects (n = 89) were selected, and their MRI data were parcellated to determine the volumes of 11 thalamic nuclei for each subject. Volumes across the different clinical subgroups were compared using ANCOVA. Results: There were significant differences in thalamic nuclei volumes between HC, late MCI, and AD subjects. The anteroventral, mediodorsal, pulvinar, medial geniculate, and centromedian nuclei were significantly smaller in subjects with late MCI and AD when compared to HC subjects. Furthermore, the mediodorsal, pulvinar, and medial geniculate nuclei were significantly smaller in early MCI when compared to HC subjects. Conclusion: This work highlights nucleus specific atrophy within the thalamus in subjects with early and late MCI and AD. This is consistent with the hypothesis that memory and cognitive changes in AD are mediated by damage to a large-scale integrated neural network that extends beyond the medial temporal lobes.

scholarly journals Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abhishek Uday Patil ◽  
Sejal Ghate ◽  
Deepa Madathil ◽  
Ovid J. L. Tzeng ◽  
Hsu-Wen Huang ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygen Level Dependent ◽  
Detection Algorithm ◽  
Brain Regions ◽  
Creative Cognition ◽  
Network Flexibility ◽  
Community Detection Algorithm ◽  
Window Approach

AbstractCreative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.

Investigation of Sensor Placement in Lamb Wave-Based SHM Method

2012 ◽  
Vol 518 ◽  
pp. 174-183 ◽  
Author(s):  
Pawel Malinowski ◽  
Tomasz Wandowski ◽  
Wiesław M. Ostachowicz
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Guided Waves ◽  
Sensor Placement ◽  
Detection Algorithm ◽  
Piezoelectric Sensors ◽  
Optimal Placement ◽  
Laser Vibrometer ◽  
Contact Method ◽  
Monitoring Method

In this paper the investigation of a structural health monitoring method for thin-walled parts of structures is presented. The concept is based on the guided elastic wave propagation phenomena. This type of waves can be used in order to obtain information about structure condition and possibly damaged areas. Guided elastic waves can travel in the medium with relatively low attenuation, therefore they enable monitoring of extensive parts of structures. In this way it is possible to detect small defects in their early stage of growth. It is essential because undetected damage can endanger integrity of a structure. In reported investigation piezoelectric transducer was used to excite guided waves in chosen specimens. Dispersion of guided waves results in changes of velocity with the wave frequency, therefore a narrowband signal was used. Measurement of the wave field was realized using laser scanning vibrometer that registered the velocity responses at points belonging to a defined mesh. An artificial discontinuity was introduced to the specimen. The goals of the investigation was to detect it and find optimal sensor placement for this task. Determination of the optimal placement of sensors is a very challenging mission. In conducted investigation laser vibrometer was used to facilitate the task. The chosen mesh of measuring points was the basis for the investigation. The purpose was to consider various configuration of piezoelectric sensors. Instead of using vast amount of piezoelectric sensors the earlier mentioned laser vibrometer was used to gather the necessary data from wave propagation. The signals gather by this non-contact method for the considered network were input to the damage detection algorithm. Damage detection algorithm was based on a procedure that seeks in the signals the damage-reflected waves. Knowing the wave velocity in considered material the damage position can be estimated.

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