The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform

Stefan Mikulla - One of the best experts on this subject based on the ideXlab platform.

  • the multi parameter wireless sensing system mpwise its description and application to earthquake risk mitigation
    Sensors, 2017
    Co-Authors: T. Boxberger, Marco Pilz, Stefano Parolai, Massimiliano Pittore, Kevin Fleming, Stefan Mikulla
    Abstract:

    The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the Recorded Ground Motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-Motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

  • the multi parameter wireless sensing system mpwise its description and application to earthquake risk mitigation
    Sensors, 2017
    Co-Authors: T. Boxberger, Marco Pilz, Stefano Parolai, Massimiliano Pittore, Kevin Fleming, Stefan Mikulla
    Abstract:

    The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the Recorded Ground Motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-Motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

R. Sigbjörnsson - One of the best experts on this subject based on the ideXlab platform.

  • Rotation-invariant mean duration of strong Ground Motion
    Bulletin of Earthquake Engineering, 2014
    Co-Authors: R. Rupakhety, R. Sigbjörnsson
    Abstract:

    Strong-Motion duration is usually computed separately for three components of Recorded Ground-Motion time series. This results in different values of duration for the three components. Furthermore, the computed duration values are dependent on the sensor orientation. Physically, such dependence is not desirable. In this work, computing duration based on resultant Recorded Motion instead of individual components is proposed. Such a measure of duration is shown to be rotation-invariant and hence independent of the sensor axes. Furthermore, it is demonstrated that the duration of resultant Motion represents the mean duration for all possible arbitrary sensor orientations in three-dimensional space. The results indicate that the apparent difference between duration of horizontal and vertical Motion reported in the literature is not universal to all definitions of duration. A set of 462 three-component accelerograms from Europe and the Middle East is used to demonstrate and support the presented findings and arguments.

  • Rotation-invariant measures of earthquake response spectra
    Bulletin of Earthquake Engineering, 2013
    Co-Authors: R. Rupakhety, R. Sigbjörnsson
    Abstract:

    A new procedure for combining the response spectra of two horizontal components of Recorded Ground Motion is presented. The presented formulation accounts for different orientations of accelerometer sensors and derives the maximum and the expected (mean) horizontal response spectra at a site, both of which are invariant to rotation of sensor axes. The maximum response spectrum is derived as the peak resultant response of single degree of freedom oscillators subjected to the as-Recorded Ground acceleration. The expected spectrum is derived by projecting the displacement response (due to as-Recorded Motion) along two orthogonal axes to a principal axes in which the displacement responses are uncorrelated. This property is used to formulate an approximation for the expected response spectrum over all possible sensor orientations. A large set of accelerometric data from Europe and the Middle East is used to demonstrate the applicability of the proposed response spectral measures.

P. Anbazhagan - One of the best experts on this subject based on the ideXlab platform.

  • Regional stochastic Ground-Motion model for low to moderate seismicity area with variable seismotectonic: application to Peninsular India
    Bulletin of Earthquake Engineering, 2019
    Co-Authors: Ketan Bajaj, P. Anbazhagan
    Abstract:

    A new stochastic Ground Motion prediction equation (GMPE) for low and diverse seismicity region, i.e., Peninsular India has been derived for a wide range of magnitude ( $$M_{w}$$ M w 4–8) and distance (10–500 km). Source, path, and site terms have been determined by comparing the Recorded and simulated response spectra using derived values from the literature. Uncertainty has been assessed through simulation by random sampling of the corresponding distribution of all the input parameters. To capture the non-uniform seismicity of Peninsular India, GMPE has been derived using constant stress and variable stress model. The synthetic data has been regressed using linear mixed-effect model algorithm by determining the functional form that is compatible for magnitude and distance scaling. Sensitivity analysis has been used in determining the impact of uncertainty of each input parameter on GMPE standard deviation. Further, new GMPEs have been validated using the Recorded Ground-Motion data.

  • Regional stochastic GMPE with available Recorded data for active region – Application to the Himalayan region
    Soil Dynamics and Earthquake Engineering, 2019
    Co-Authors: Ketan Bajaj, P. Anbazhagan
    Abstract:

    Abstract New Ground Motion prediction equation for the active Himalayan region for a wide range of moment magnitude ( M w 4–9) and distance (10–750 km) is developed. For simulating the synthetic Ground Motions; source, path, and site terms are derived using the Fourier amplitude spectrum of the Recorded Ground Motion data. Uncertainty of input parameters is propagated through simulation by random sampling of the corresponding distribution of input parameters. Synthetic and Recorded data are regressed using random-effect maximum likelihood regression algorithm by determining the compatible functional form. Sensitivity analysis is used in determining the impact of uncertainty of each input parameter on standard deviation of the regression residuals about the median prediction equation. Major contribution to total uncertainty is from Kappa factor in case of within-event terms and from stress drop in case of event-to-event variability. Predicted and Recorded response spectra is matching within ±1 standard deviation for the entire period range.

  • Pseudo-Spectral Damping Reduction Factors for the Himalayan Region Considering Recorded Ground-Motion Data.
    PloS one, 2016
    Co-Authors: P. Anbazhagan, Anjali Uday, Sayed S. R. Moustafa, Nassir Al-arifi
    Abstract:

    Ground-Motion prediction equations that are used to predict acceleration values are generally developed for a 5% viscous damping ratio. Special structures and structures that use damping devices may have damping ratios other than the conventionally used ratio of 5%. Hence, for such structures, the intensity measures predicted by conventional Ground-Motion prediction equations need to be converted to a particular level of damping using a damping reduction factor (DRF). DRF is the ratio of the spectral ordinate at 5% damping to the ordinate at a defined level of damping. In this study, the DRF has been defined using the spectral ordinate of pseudo-spectral acceleration and the effect of factors such as the duration of Ground Motion, magnitude, hypocenter distance, site classification, damping, and period are studied. In this study, an attempt has also been made to develop an empirical model for the DRF that is specifically applicable to the Himalayan region in terms of these predictor variables. A Recorded earthquake with 410 horizontal Motions was used, with data characterized by magnitudes ranging from 4 to 7.8 and hypocentral distances up to 520 km. The damping was varied from 0.5–30% and the period range considered was 0.02 to 10 s. The proposed model was compared and found to coincide well with models in the existing literature. The proposed model can be used to compute the DRF at any specific period, for any given value of predictor variables.

  • An empirical model for the prediction of significant duration in India
    2014
    Co-Authors: P. Anbazhagan, P R Ashwini, Kiran Kamath
    Abstract:

    The duration of the strong earthquakeGround Motion is one of the mainparameters in seismic design, as it creates cyclic loading on the structural system, which inturn can cause damage to the structure. Therefore, it becomes necessary to estimate theduration of strong Motion as a part of seismi c hazard assessment. This study proposes asimple empirical model derived from Recorded Ground Motion data of the Himalayanregion of North India. Out of various duration parameters defined in the literature, the significant duration is chosen in this study. It is the measure of the damage potential of anearthquake occurring in a region, defined as thetime interval between which the specifiedvalue of Arias Intensity is reached.The m odel has been developed using 914 accelerograms Recorded from 1986 to 2013 and by regressionanalysis. The result obtained from theproposed model has been compared with the observed data a and it is found that the model d it is found that the modelcan predict the earthquake Ground Motion duration precisely.

T. Boxberger - One of the best experts on this subject based on the ideXlab platform.

  • the multi parameter wireless sensing system mpwise its description and application to earthquake risk mitigation
    Sensors, 2017
    Co-Authors: T. Boxberger, Marco Pilz, Stefano Parolai, Massimiliano Pittore, Kevin Fleming, Stefan Mikulla
    Abstract:

    The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the Recorded Ground Motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-Motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

  • the multi parameter wireless sensing system mpwise its description and application to earthquake risk mitigation
    Sensors, 2017
    Co-Authors: T. Boxberger, Marco Pilz, Stefano Parolai, Massimiliano Pittore, Kevin Fleming, Stefan Mikulla
    Abstract:

    The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the Recorded Ground Motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-Motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

R. Rupakhety - One of the best experts on this subject based on the ideXlab platform.

  • Rotation-invariant mean duration of strong Ground Motion
    Bulletin of Earthquake Engineering, 2014
    Co-Authors: R. Rupakhety, R. Sigbjörnsson
    Abstract:

    Strong-Motion duration is usually computed separately for three components of Recorded Ground-Motion time series. This results in different values of duration for the three components. Furthermore, the computed duration values are dependent on the sensor orientation. Physically, such dependence is not desirable. In this work, computing duration based on resultant Recorded Motion instead of individual components is proposed. Such a measure of duration is shown to be rotation-invariant and hence independent of the sensor axes. Furthermore, it is demonstrated that the duration of resultant Motion represents the mean duration for all possible arbitrary sensor orientations in three-dimensional space. The results indicate that the apparent difference between duration of horizontal and vertical Motion reported in the literature is not universal to all definitions of duration. A set of 462 three-component accelerograms from Europe and the Middle East is used to demonstrate and support the presented findings and arguments.

  • Rotation-invariant measures of earthquake response spectra
    Bulletin of Earthquake Engineering, 2013
    Co-Authors: R. Rupakhety, R. Sigbjörnsson
    Abstract:

    A new procedure for combining the response spectra of two horizontal components of Recorded Ground Motion is presented. The presented formulation accounts for different orientations of accelerometer sensors and derives the maximum and the expected (mean) horizontal response spectra at a site, both of which are invariant to rotation of sensor axes. The maximum response spectrum is derived as the peak resultant response of single degree of freedom oscillators subjected to the as-Recorded Ground acceleration. The expected spectrum is derived by projecting the displacement response (due to as-Recorded Motion) along two orthogonal axes to a principal axes in which the displacement responses are uncorrelated. This property is used to formulate an approximation for the expected response spectrum over all possible sensor orientations. A large set of accelerometric data from Europe and the Middle East is used to demonstrate the applicability of the proposed response spectral measures.