Search results for: fault propagation fold

Authors: Mehdi Radmehr, Amir Hamed Mashhadzadeh, Mehdi Jafari

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Traditional HVDC systems are tough to DC short circuits as they are current regulated with a large reactance connected in series with cables. Multi-terminal DC wind farm topologies are attracting increasing research attempt. With AC/DC converters on the generator side, this topology can be developed into a multi-terminal DC network for wind power collection, which is especially suitable for large-scale offshore wind farms. For wind farms, the topology uses high-voltage direct-current transmission based on voltage-source converters (VSC-HVDC). Therefore, they do not suffer from over currents due to DC cable faults and there is no over current to react to. In this study, the multi-terminal DC wind farm topology is introduced. Then, possible internal DC faults are analyzed according to type and characteristic. Fault over current expressions are given in detail. Under this characteristic analysis, fault detection and detailed protection methods are proposed. Theoretical analysis and PSCAD/EMTDC simulations are provided.

Keywords: DC short circuits, multi-terminal DC wind farm topologies, HVDC transmission based on VSC, fault analysis

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: Akshay A. Pandya, B. R. Parekh

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This paper presents how earth fault damage in the transformer can be detected by Sweep Frequency Response Analysis (SFRA). The test methods used by the authors for presenting the results are described. The power transformer of rating 10 KVA, 11000 V/440 V, 3-phase, 50 Hz, Dyn11 has been specially developed in-house for carrying out SFRA testing by practically simulated various transformer damages on it. Earth fault has been practically simulated on HV “U” phase winding and LV “W” phase winding separately. The result of these simulated faults are presented and discussed. The motivation of this presented work is to extend the guideline approach; there are ideas to organize database containing collected measurement results. Since the SFRA interpretation is based on experience, such databases are thought to be of great importance when interpreting SFRA response. The evaluation of the SFRA responses against guidelines and experience have to be performed and conclusions regarding usefulness of each simulation has been drawn and at last overall conclusion has also been drawn.

Keywords: earth fault damage, power transformer, practical simulation, SFRA traces, transformer damages

Procedia PDF Downloads 269

Authors: Shyaka Eugene

Abstract:

The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Rohit Shrivastava, Stefan Luding

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A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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Authors: Wahab Ali Shah, Junjia He

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In this work, we performed a large-scale investigation into leader development in a 10 m rod-plane gap under a long front positive impulse. To describe the leader propagation under slow front impulse voltages, we recorded the leader propagation with a high-speed charge coupled device (CCD) camera. It is important to figure out this phenomenon to deepen our understanding of leader discharge. The observation results showed that the leader mechanism is a very complex physical phenomenon; it could be categorized into two types of leader process, namely, continuous and the discontinuous leader streamer-leader propagation. Furthermore, we studied the continuous leader development parameters, including two-dimensional (2-D) leader length, injected charge, and final jump stage, as well as leader velocity for rod–plane configuration. We observed that the discontinuous leader makes an important contribution to the appearance of channel re-illuminations of the positive leader. The comparative study shows better results in terms of standard switch impulse and long front positive impulse. Finally, the results are presented with a view toward improving our understanding of propagation mechanisms related to restrike phenomena, which are rarely reported. To clarify the above doubts under long front cases, we carried out extensive experiments in this study.

Keywords: continuous and discontinuous leader, high-speed photographs, long air gap, positive long front impulse, restrike phenomena

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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During recent years wind turbine technology has undergone rapid developments. Growth in size and the optimization of wind turbines has enabled wind energy to become increasingly competitive with conventional energy sources. As a result today’s wind turbines participate actively in the power production of several countries around the world. These developments raise a number of challenges to be dealt with now and in the future. The penetration of wind energy in the grid raises questions about the compatibility of the wind turbine power production with the grid. In particular, the contribution to grid stability, power quality and behavior during fault situations plays therefore as important a role as the reliability. In the present work, we addressed two fault situations that have shown their influence on the generator and the behavior of the wind over the defects which are briefly discussed based on simulation results.

Keywords: doubly fed induction generator (DFIG), wind energy, grid fault, electrical engineering

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: real-time system (RTS), time utility function/ utility accrual (TUF/UA) scheduling, backward recovery mechanism, multiprocessor, discrete event simulation (DES)

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Ying-Chu Chen

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Waste to energy (WTE) technology is becoming increasingly important throughout the world. There are 24 WTE plants in operation in Taiwan that might be ranked the top in density (number of MSW incinerators/area) in the world. Many problems exist in WTE plants, such as low-quality construction, leakage of pipelines, irregular feedings, and lack of maintenance. These problems should be identified and analyzed for effective implementation and efficient operation of WTE plants. This research applies a fault tree analysis (FTA) to identify failures and evaluate their effects on the operation of WTE plants from a technical point of view. Five subsystems of a WTE plant were defined, including loading system, incineration system, effluent disposal system, structural components, and control system. This research results proved that FTA is suitable for WTE evaluation and is an effective analysis tool for technical evaluation in the field of WTE technology.

Keywords: delphi method, fault tree approach, municipal solid waste, waste to energy, WTE

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Authors: Latife Merve Oktay, Berrin Tugrul

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Hydroxytyrosol (HT) is a phenolic phytochemical molecule derived from the hydrolysis of oleuropein, which originates during the maturation of the olives. It has recently received particular attention because of its antioxidant, anti-proliferative, pro-apoptotic and anti-inflammatory activities. In this study, we investigated the cytotoxic and apoptotic effects of hydroxytyrosol and its effects on phosphatidylinositol 3-kinase/Akt (PI3K/Akt) and extracellular signal-regulated kinase 1/2 (ERK 1/2) signaling pathways in human ovarian cancer cell lines OVCAR-3 and MDAH-2774. XTT cell proliferation kit, Cell Death Detection Elisa Plus Kit (Roche) and Human Apoptosis Array (R&D Systems) were used to determine the cytotoxic and apoptotic effects of HT in OVCAR-3 and MDAH-2774 cell lines at 24, 48, 72, and 96 h. Effect of HT on PI3K/Akt and ERK 1/2 signaling pathways were investigated by using specific inhibitors of these pathways. IC50 values of HT were found to be 102.3 µM in MDAH-2774 cells at 72 h and 51.5 µM in OVCAR-3 cells at 96 h. Apoptotic effect of HT in MDAH-2774 cells was the highest at 50 µM at 72 h, and kept decreasing at 100 and 150 µM concentrations and was not seen at 200 µM and higher concentrations. Highest apoptotic effect was seen at 100 µM concentration in OVCAR-3 cells at 96 h, however apoptotic effect was decreased over 100 µM concentrations. According to antibody microarray results, HT increased the levels of pro-apoptotic molecules Bad, Bax, active caspase-3, Htra2/Omi by 2.0-, 1.4-, 1.2-, 4.2-fold, respectively and also increased the levels of pro-apoptotic death receptors TRAIL R1/DR4, TRAIL R2/DR5, FAS/TNFRSF6 by 2.1-, 1.7-, 1.6-fold, respectively, however, it decreased the level of Survivin by 1.6-fold which is one of the inhibitor of apoptosis protein (IAP) family in MDAH-2774 cells. In OVCAR-3 cells, HT decreased the levels of anti-apoptotic proteins Bcl-2, pro-caspase 3 by 3.1-, 8.2-fold, respectively and IAP family proteins CIAP-1, CIAP-2, XIAP, Livin, Survivin by 6.5-, 6.0-, 3.2-, 2.2-, 2.7-fold, respectively and increased the level of cytochrome-c by 1.2-fold. We have shown that HT shows its cytotoxic and apoptotic effect through inhibiting ERK 1/2 signaling pathway in both OVCAR-3 and MDAH-2774 cells. Further studies are needed to investigate molecular mechanisms and modulatory effects of hydroxytyrosol.

Keywords: apoptosis, cytotoxicity, hydroxytyrosol, ovarian cancer

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Authors: Raviraja Shetty G., K. G. Poojitha

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An experiment was conducted at College of Horticulture, Mudigere to study the effect of different growth regulators on seed germination and vegetative propagation by cuttings of Celastrus paniculata an endangered medicinal plant. The extracted seeds are subjected to 11 different pre-soaking treatments which include control, GA3 at 300, 350, 400ppm, KNO3 at 1.0%, 1.5%, 2.0%, H2SO4 at 0.5%, 1.0% and HCl 0.5%,1.0% for 100 seeds per treatment. Among the different germination inducing treatments, seeds treated with gibberellins responded well with high seed germination and vigorous seedling growth. The seeds treated with GA3 400 ppm recorded maximum germination and growth parameters like rate of germination, shoot length, root length, plant vigour, fresh and dry weight of which was followed GA3 350 ppm. The commencement of germination and 50 per cent germination was also earlier in the same treatment. The cuttings of C. paniculata took more time for root initiation up to four months and sprouting percent was moderate as compared to other easy to root species. Among different treatments, IBA 2000 ppm was found to be the best, which recorded the maximum shoot and also root parameters. The results of present investigation will be helpful for conservation of this endangered medicinal plant through propagation

Keywords: conservation, germination, growth, germination, propagation

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Authors: L. Almulla

Abstract:

Native plants are better adapted to the local environment providing a more natural effect on landscape projects; their use will both conserve natural resources and produce sustainable greenery. Continuation of evaluation of additional native plants is essential to increase diversity of plant resources for greenery projects. Therefore, in this project an effort was made to study the mass multiplication of further native plants for greenery applications. Standardization of vegetative propagation methods is essential for conservation and sustainable utilization of native plants in restoration projects. Moreover, these simple propagation methods can be readily adapted by the local nursery sector in Kuwait. In the present study, various treatments were used to mass multiply selected plants using vegetative parts to secure maximum rooting and initial growth. Soft or semi-hardwood cuttings of selected native plants were collected from mother plants and subjected to different treatments. Pennisetum divisum can be vegetatively propagated by cuttings/off-shoots. However, Tamarix aucheriana showed maximum number of rooted cuttings and stronger vigor seedlings with the lowest growth hormone concentration. Standardizing the propagation techniques for the native plant species will add to the rehabilitation and landscape revegetation projects in Kuwait.

Keywords: Kuwait desert, landscape, rooting percentage, vegetative propagation

Procedia PDF Downloads 100

Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: Vinod Kumar

Abstract:

Background: Tissue Plasminogen Activator (tPA) showed a level 1 benefit in acute stroke (within 3-6 hrs). Intracarotid sodium nitroprusside (ICSNP) has been studied in this context with a wide treatment window, fast recovery and affordability. This work proposes two mechanisms for acute cases and one mechanism for chronic cases, which are interrelated, for physiological recovery. a)Retrograde Neurotransmission (acute cases): 1)Normal excitatory impulse: at the synaptic level, glutamate activates NMDA receptors, with nitric oxide synthetase (NOS) on the postsynaptic membrane, for further propagation by the calcium-calmodulin complex. Nitric oxide (NO, produced by NOS) travels backward across the chemical synapse and binds the axon-terminal NO receptor/sGC of a presynaptic neuron, regulating anterograde neurotransmission (ANT) via retrograde neurotransmission (RNT). Heme is the ligand-binding site of the NO receptor/sGC. Heme exhibits > 10,000-fold higher affinity for NO than for oxygen (the 10,000-fold effect) and is completed in 20 msec. 2)Pathological conditions: normal synaptic activity, including both ANT and RNT, is absent. A NO donor (SNP) releases NO from NOS in the postsynaptic region. NO travels backward across a chemical synapse to bind to the heme of a NO receptor in the axon terminal of a presynaptic neuron, generating an impulse, as under normal conditions. b)Vasospasm: (acute cases) Perforators show vasospastic activity. NO vasodilates the perforators via the NO-cAMP pathway. c)Long-Term Potentıatıon (LTP): (chronic cases) The NO–cGMP-pathway plays a role in LTP at many synapses throughout the CNS and at the neuromuscular junction. LTP has been reviewed both generally and with respect to brain regions specific for memory/learning. Aims/Study Des’gn: The principles of “generation of impulses from the presynaptic region to the postsynaptic region by very potent RNT (10,000-fold effect)” and “vasodilation of arteriolar perforators” are the basis of the authors’ hypothesis to treat stroke cases. Case-control prospective study. Mater’als And Methods: The experimental population included 82 stroke patients (10 patients were given control treatments without superfusion or with 5% dextrose superfusion, and 72 patients comprised the ICSNP group). The mean time for superfusion was 9.5 days post-stroke. Pre- and post-ICSNP status was monitored by NIHSS, MRI and TCD. Results: After 90 seconds in the ICSNP group, the mean change in the NIHSS score was a decrease of 1.44 points, or 6.55%; after 2 h, there was a decrease of 1.16 points; after 24 h, there was an increase of 0.66 points, 2.25%, compared to the control-group increase of 0.7 points, or 3.53%; at 7 days, there was an 8.61-point decrease, 44.58%, compared to the control-group increase of 2.55 points, or 22.37%; at 2 months in ICSNP, there was a 6.94-points decrease, 62.80%, compared to the control-group decrease of 2.77 points, or 8.78%. TCD was documented and improvements were noted. Conclusions: ICSNP is a swift-acting drug in the treatment of stroke, acting within 90 seconds on day 9.5 post-stroke with a small decrease after 24 hours. The drug recovers from this decrease quickly.

Keywords: brain infarcts, intracarotid sodium nitroprusside, perforators, vasodilatıons, retrograde transmission, the 10, 000-fold effect

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Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

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Authors: V. K. Tewari, M. Hussain, H. K. D. Gupta

Abstract:

Background: Nitric Oxide Donars (NODs) (intrathecal sodium nitroprusside (ITSNP) and oral tadalafil 20mg post ITSNP) has been studied in this context in cerebral palsy patients for fast recovery. This work proposes two mechanisms for acute cases and one mechanism for chronic cases, which are interrelated, for physiological recovery. a) Retrograde Neurotransmission (acute cases): 1) Normal excitatory impulse: at the synaptic level, glutamate activates NMDA receptors, with nitric oxide synthetase (NOS) on the postsynaptic membrane, for further propagation by the calcium-calmodulin complex. Nitric oxide (NO, produced by NOS) travels backward across the chemical synapse and binds the axon-terminal NO receptor/sGC of a presynaptic neuron, regulating anterograde neurotransmission (ANT) via retrograde neurotransmission (RNT). Heme is the ligand-binding site of the NO receptor/sGC. Heme exhibits > 10,000-fold higher affinity for NO than for oxygen (the 10,000-fold effect) and is completed in 20 msec. 2) Pathological conditions: normal synaptic activity, including both ANT and RNT, is absent. A NO donor (SNP) releases NO from NOS in the postsynaptic region. NO travels backward across a chemical synapse to bind to the heme of a NO receptor in the axon terminal of a presynaptic neuron, generating an impulse, as under normal conditions. b) Vasopasm: (acute cases) Perforators show vasospastic activity. NO vasodilates the perforators via the NO-cAMP pathway. c) Long-Term Potentiation (LTP): (chronic cases) The NO–cGMP-pathway plays a role in LTP at many synapses throughout the CNS and at the neuromuscular junction. LTP has been reviewed both generally and with respect to brain regions specific for memory/learning. Aims/Study Design: The principles of “generation of impulses from the presynaptic region to the postsynaptic region by very potent RNT (10,000-fold effect)” and “vasodilation of arteriolar perforators” are the basis of the authors’ hypothesis to treat cerebral palsy cases. Case-control prospective study. Materials and Methods: The experimental population included 82 cerebral palsy patients (10 patients were given control treatments without NOD or with 5% dextrose superfusion, and 72 patients comprised the NOD group). The mean time for superfusion was 5 months post-cerebral palsy. Pre- and post-NOD status was monitored by Gross Motor Function Classification System for Cerebral Palsy (GMFCS), MRI, and TCD studies. Results: After 7 days in the NOD group, the mean change in the GMFCS score was an increase of 1.2 points mean; after 3 months, there was an increase of 3.4 points mean, compared to the control-group increase of 0.1 points at 3 months. MRI and TCD documented the improvements. Conclusions: NOD (ITSNP boosts up the recovery and oral tadalafil maintains the recovery to a well-desired level) acts swiftly in the treatment of CP, acting within 7 days on 5 months post-cerebral palsy either of the three mechanisms.

Keywords: cerebral palsy, intrathecal sodium nitroprusside, oral tadalafil, perforators, vasodilations, retrograde transmission, the 10, 000-fold effect, long-term potantiation

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Authors: Samar Akef, Ahdab M. K. El-Morshedy, Mohamed M. Samy, Ahmed M. Emam

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This paper presents a safe and realistic design for the proposed high voltage direct current grounding grid for the converter station at Badr City in Egypt. The outcomes show that the estimated results for touch and step voltages are below the safe limits for humans in monopolar operation and fault conditions. The cross-section area of earthing conductor is computed using IEC TS 62344. The results show that touch voltage in monopolar and fault conditions are 46.6 V and 167.68 V, respectively. The optimum number of required earthing rods is obtained by an analytical method. The step voltages are 12.9 and 43 V in monopolar operation and fault conditions. In addition, this paper presents an experimental case study to verify the simulation work executed using CYMGrd software (finite element method based). The percentage error between the measured and simulated surface potential is below 15.9%.

Keywords: grounding, monopolar, fault conditions, step potential, touch potential, CYMGrd, finite element method, experimental case study

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Authors: Daniele Losanno, H. A. Hadad, Giorgio Serino

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This paper presents a numerical investigation on the seismic performance of a benchmark bridge with different optimal isolation systems under near fault ground motion. Usually, very large displacements make seismic isolation an unfeasible solution due to boundary conditions, especially in case of existing bridges or high risk seismic regions. Hence, near-fault ground motions are most likely to affect either structures with long natural period range like isolated structures or structures sensitive to velocity content such as viscously damped structures. The work is aimed at analyzing the seismic performance of a three-span continuous bridge designed with different isolation systems having different levels of damping. The case study was analyzed in different configurations including: (a) simply supported, (b) isolated with lead rubber bearings (LRBs), (c) isolated with rubber isolators and 10% classical damping (HDLRBs), and (d) isolated with rubber isolators and 70% supplemental damping ratio. Case (d) represents an alternative control strategy that combines the effect of seismic isolation with additional supplemental damping trying to take advantages from both solutions. The bridge is modeled in SAP2000 and solved by time history direct-integration analyses under a set of six recorded near-fault ground motions. In addition to this, a set of analysis under Italian code provided seismic action is also conducted, in order to evaluate the effectiveness of the suggested optimal control strategies under far field seismic action. Results of the analysis demonstrated that an isolated bridge equipped with HDLRBs and a total equivalent damping ratio of 70% represents a very effective design solution for both mitigation of displacement demand at the isolation level and base shear reduction in the piers also in case of near fault ground motion.

Keywords: isolated bridges, near-fault motion, seismic response, supplemental damping, optimal design

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In this paper, a robust fault-tolerant predictive control (FTPC) strategy is proposed for systems with linear parameter varying (LPV) models and input constraints subject to sensor faults. Generally, virtual observers are used for improving the observation precision and reduce the impacts of sensor faults and uncertainties in the system. However, this type of observer lacks certain system measurements which substantially reduce its accuracy. To deal with this issue, a real observer is then designed based on the virtual observer, and consequently a real observer-based robust predictive control is designed for polytopic LPV systems. Moreover, the proposed observer can entirely assure that all system states and sensor faults are estimated. As a result, and based on both observers, a robust fault-tolerant predictive control is then established via the Lyapunov method where sufficient conditions are proposed, for stability analysis and control purposes, in linear matrix inequalities (LMIs) form. Finally, simulation results are given to show the effectiveness of the proposed approach.

Keywords: linear parameter varying systems, fault-tolerant predictive control, observer-based control, sensor faults, input constraints, linear matrix inequalities

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Authors: Arash Ghahraman, Gyula Bene

Abstract:

The object of this study is to investigate the effect of viscosity on the propagation of free-surface waves in an incompressible viscous fluid layer of arbitrary depth. While we provide a more detailed study of properties of linear surface waves, the description of fully nonlinear waves in terms of KdV-like (Korteweg-de Vries) equations is discussed. In the linear case, we find that in shallow enough fluids, no surface waves can propagate. Even in any thicker fluid layers, propagation of very short and very long waves is forbidden. When wave propagation is possible, only a single propagating mode exists for any given horizontal wave number. The numerical results show that there can be two types of non-propagating modes. One type is always present, and there exist still infinitely many of such modes at the same parameters. In contrast, there can be zero, one or two modes belonging to the other type. Another significant feature is that KdV-like equations. They describe propagating nonlinear viscous surface waves. Since viscosity gives rise to a new wavenumber that cannot be small at the same time as the original one, these equations may not exist. Nonetheless, we propose a reasonable nonlinear description in terms of 1+1 variate functions that make possible successive approximations.

Keywords: free surface wave, water waves, KdV equation, viscosity

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Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristicssuch as frequency content, amplitude, and duration of seismic waves. The most common method for investigating site response is one-dimensional seismic site response analysis. The infinite horizontal length of the model and the homogeneous characteristic of the soil are crucial assumptions of this method. One boundary condition that can be used in the sides is tying the sides horizontally for vertical 1D wave propagation. However, 1D analysis cannot account for the 2D nature of wave propagation in the condition where the soil profile is not fully horizontal or has heterogeneity within layers. Therefore, 2D seismic site response analysis can be used to take all of these limitations into account for a better understanding of local site conditions. Different types of boundary conditions can be appliedin 2D site response models, such as tied boundary condition, massive columns, and free-field boundary condition. The tied boundary condition has been used in 1D analysis, which is useful for 1D wave propagation. Employing two massive columns at the sides is another approach for capturing the 2D nature of wave propagation. Free-field boundary condition can simulate the free-field motion that would exist far from the domain of interest. The goal for free-field boundary condition is to minimize the unwanted reflection from sides. This research focuses on the comparison between these methods with examples and discusses the details and limitations of each of these boundary conditions.

Keywords: boundary condition, free-field, massive columns, opensees, site response analysis, wave propagation

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Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Tasawer Abbas

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Nanoherbicides utilize nanotechnology to enhance the delivery of biological or chemical herbicides using combinations of nanomaterials. The aim of this research was to examine the efficacy of chitosan nanoparticles containing MCPA herbicide as a potential eco-friendly alternative for weed control in wheat crops. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and ultraviolet absorbance were used to analyze the developed nanoparticles. The SEM analysis indicated that the average size of the particles was 35 nm, forming clusters with a porous structure. Both nanoparticles of fluroxyper + MCPA exhibited maximal absorption peaks at a wavelength of 320 nm. The compound fluroxyper +MCPA has a strong peak at a 2θ value of 30.55°, which correlates to the 78 plane of the anatase phase. The weeds, including Chenopodium album, Lathyrus aphaca, Angalis arvensis, and Melilotus indica, were sprayed with the nanoparticles while they were in the third or fourth leaf stage. There were seven distinct dosages used: doses (D0 (Check weeds), D1 (Recommended dose of traditional herbicide, D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). The chitosan-based nanoparticles of MCPA at the prescribed dosage of conventional herbicide resulted in complete death and visual damage, with a 100% fatality rate. The dosage that was 5-fold lower exhibited the lowest levels of plant height (3.95 cm), chlorophyll content (5.63%), dry biomass (0.10 g), and fresh biomass (0.33 g) in the broad-leaved weed of wheat. The herbicide nanoparticles, when used at a dosage 10-fold lower than that of conventional herbicides, had a comparable impact on the prescribed dosage. Nano-herbicides have the potential to improve the efficiency of standard herbicides by increasing stability and lowering toxicity.

Keywords: mortality, visual injury, chlorophyl contents, chitosan-based nanoparticles

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Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

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In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

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Authors: Hyun-Woo Cho

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Automatic process monitoring schemes are designed to give early warnings for unusual process events or abnormalities as soon as possible. For this end, various techniques have been developed and utilized in various industrial processes. It includes multivariate statistical methods, representation skills in reduced spaces, kernel-based nonlinear techniques, etc. This work presents a nonlinear empirical monitoring scheme for batch type production processes with incomplete process measurement data. While normal operation data are easy to get, unusual fault data occurs infrequently and thus are difficult to collect. In this work, noise filtering steps are added in order to enhance monitoring performance by eliminating irrelevant information of the data. The performance of the monitoring scheme was demonstrated using batch process data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: batch process, monitoring, measurement, kernel method

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Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

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Most reinforced concrete structures are designed only under heavy loads have large transverse reinforcement spacing values, and therefore suffer severe failure after intense ground movements. The main goal of this paper is to compare the shear- and axial failure of concrete bending frames available in Tehran using incremental dynamic analysis under near- and far-field records. For this purpose, IDA analyses of 5, 10, and 15-story concrete structures were done under seven far-fault records and five near-faults records. The results show that in two-dimensional models of short-rise, mid-rise and high-rise reinforced concrete frames located on Type-3 soil, increasing the distance of the transverse reinforcement can increase the maximum inter-story drift ratio values up to 37%. According to the existing results on 5, 10, and 15-story reinforced concrete models located on Type-3 soil, records with characteristics such as fling-step and directivity create maximum drift values between floors more than far-fault earthquakes. The results indicated that in the case of seismic excitation modes under earthquake encompassing directivity or fling-step, the probability values of failure and failure possibility increasing rate values are much smaller than the corresponding values of far-fault earthquakes. However, in near-fault frame records, the probability of exceedance occurs at lower seismic intensities compared to far-fault records.

Keywords: IDA, failure curve, directivity, maximum floor drift, fling step, evaluating probable bending of frames, near-field and far-field earthquake records

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: Puja Sharma, S. R. Dhiman, Bhararti Kashyap, Y. C. Gupta, Shabnam Pangtu

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The experiments were carried out for mass multiplication and domestication of an endangered native tree spp, an orchid and an ornamental shrub having high medicinal value. Floriculture industry is novelty driven, hence the potential of these native ornamentals was assessed for their utilization as a novelty in the industry. For the mass propagation of endangered tree Oroxylum indicum, seed propagation and vegetative propagation techniques were successfully utilized. Highest seed germination was recorded in a medium containing cocopeat and perlite (1:1 v/v). Semi hard wood cuttings treated with IBA 2000 ppm planted in cocopeat+ sand+ perlite medium and maintained at 80% RH has resulted in about 90% rooting. The low growing tree was successfully domestication and has potential to be utilized in landscape industry. In the present study, cutting propagation and division of clump were used as methods for multiplication of Aerides multiflora, a native orchid spp. Soft wood cuttings treated with IBA 500 ppm planted in cocopeat medium was found to be the most suitable vegetative method resulting in 90 % rooting. It was domesticated as pot plant and for making hanging baskets. Propagation through seeds and cuttings was carried out for Pyracantha crenulata, a native ornamental shrub which is a cardiovascular medicine. For vegetative propagation, treatment of basal end of semi- hardwood cuttings of Pyracantha with IBA 3000 ppm (quick dip) and planting in cocopeat under mist chamber maintained at a relative humidity of 70-80% resulted in about 90% rooting out of all applied treatments in the study. For seed propagation, treatment of seeds in boiling water for 20 minutes and planting in cocopeat resulted in 82.55 % germination. The shrub was domesticated for its use as pot plant, protective hedge and for making bonsai.

Keywords: native, endangered, multiplication, domestication, oroxylum, aerides, pyracantha

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Authors: Mohammad Arabi

Abstract:

The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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