A new predictor for tsunami runup

2020 ◽  
Author(s):  
Martin Wronna ◽  
Utku Kânoğlu ◽  
Maria Ana Baptista
Keyword(s):  
Real Time ◽  
Empirical Formula ◽  
Amplitude Ratio ◽  
Slope Angle ◽  
Early Warning Systems ◽  
Tsunami Early Warning ◽  
Tsunami Runup ◽  
Empirical Estimates ◽  
Tsunami Waveforms ◽  
Definition Of

<p>We present a new Tsunami Runup Predictor (TRP). The TRP includes the length of the beach slope, the length of the accelerating phase of the wave plus the amplitude ratio for leading depression waves.</p><p>We use numerical and analytical tools to compute the runup for a dataset of 210 initial tsunami waveforms. In our tests, the slope angle of the beach varies between 1 and 5 degrees and the distance of the initial wave to the coast varies between 50 and 360 km. The results show a high correlation between the TRP and the dimensionless runup, enabling the definition of an empirical formula to predict the runup.</p><p>We further test the empirical formula using a set of past events with field data. The comparison of the empirical estimates with the runup measurements of post-tsunami surveys gives promising results.</p><p>The TRP allows estimating the tsunami runup in real-time once the offshore waveform is known.</p><p>The capacity to predict the maximum runup along the coast in real-time and include it in routine operations of Tsunami Early Warning Systems will constitute an enormous advance.</p><p><em><span>The authors would like to acknowledge the financial support  FCT through project</span></em><span> <strong>UIDB/50019/2020 – IDL.</strong></span></p>

scholarly journals Near real-time GPS applications for tsunami early warning systems

2010 ◽  
Vol 10 (2) ◽  
pp. 181-189 ◽  
Author(s):  
C. Falck ◽  
M. Ramatschi ◽  
C. Subarya ◽  
M. Bartsch ◽  
A. Merx ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Tide Gauge ◽  
Warning System ◽  
Early Warning Systems ◽  
Time Data ◽  
Essential Information ◽  
Tsunami Early Warning ◽  
Land Mass

Abstract. GPS (Global Positioning System) technology is widely used for positioning applications. Many of them have high requirements with respect to precision, reliability or fast product delivery, but usually not all at the same time as it is the case for early warning applications. The tasks for the GPS-based components within the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) are to support the determination of sea levels (measured onshore and offshore) and to detect co-seismic land mass displacements with the lowest possible latency (design goal: first reliable results after 5 min). The completed system was designed to fulfil these tasks in near real-time, rather than for scientific research requirements. The obtained data products (movements of GPS antennas) are supporting the warning process in different ways. The measurements from GPS instruments on buoys allow the earliest possible detection or confirmation of tsunami waves on the ocean. Onshore GPS measurements are made collocated with tide gauges or seismological stations and give information about co-seismic land mass movements as recorded, e.g., during the great Sumatra-Andaman earthquake of 2004 (Subarya et al., 2006). This information is important to separate tsunami-caused sea height movements from apparent sea height changes at tide gauge locations (sensor station movement) and also as additional information about earthquakes' mechanisms, as this is an essential information to predict a tsunami (Sobolev et al., 2007). This article gives an end-to-end overview of the GITEWS GPS-component system, from the GPS sensors (GPS receiver with GPS antenna and auxiliary systems, either onshore or offshore) to the early warning centre displays. We describe how the GPS sensors have been installed, how they are operated and the methods used to collect, transfer and process the GPS data in near real-time. This includes the sensor system design, the communication system layout with real-time data streaming, the data processing strategy and the final products of the GPS-based early warning system components.

scholarly journals Real-time inversion of tsunamis generated by landslides

2011 ◽  
Vol 11 (9) ◽  
pp. 2511-2520 ◽  
Author(s):  
C. Cecioni ◽  
A. Romano ◽  
G. Bellotti ◽  
M. Risio ◽  
P. de Girolamo
Keyword(s):  
Real Time ◽  
Laboratory Experiments ◽  
Early Warning Systems ◽  
Time Inversion ◽  
Warning Systems ◽  
Optimal Position ◽  
Tsunami Early Warning ◽  
Tsunami Waves ◽  
Inversion Procedure ◽  
Tsunami Early Warning Systems

Abstract. In this paper, we test a method for forecasting in real-time the properties of offshore propagating tsunami waves generated by landslides, with the aim of supporting tsunami early warning systems. The method uses an inversion procedure, that takes input data measurements of water surface elevation at a point close to the tsunamigenic source. The measurements are used to correct the results of pre-computed numerical simulations, reproducing the wave field induced by different landslide scenarios. The accuracy of the method is evaluated using the results of laboratory experiments, aimed at studying tsunamis generated by landslides sliding along the flank of a circular shoreline island. The paper investigates what the optimal position is of where to measure the tsunamis, what the effects are, the accuracy of the results, and of uncertainties on the landslide scenarios. Finally, the method is successfully tested using partial input time series, simulating the behaviour of the system in real-time during the tsunami event when forecasts are updated, as the measurements become available.

Faster Than Real Time tsunami simulations – challenges and solutions towards High Performance Exascale Computing

2020 ◽  
Author(s):  
Jorge Macias ◽  
Manuel J. Castro ◽  
Marc de la Asunción ◽  
José Manuel González-Vida ◽  
Carlos Sánchez-Linares ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Simulation Models ◽  
Early Warning Systems ◽  
Tsunami Generation ◽  
Tsunami Propagation ◽  
Tsunami Early Warning ◽  
Horizon 2020 ◽  
Landslide Tsunami ◽  
Tsunami Early Warning Systems

<p>Tsunami simulation in the framework of Tsunami Early Warning Systems (TEWS) is a quite recent achievement, but still limited regarding the size of the problem and restricted to tsunami wave propagation. Faster Than Real Time (FTRT) tsunami simulations require greatly improved and highly efficient computational methods to achieve extremely fast and effective calculations. HPC facilities have the role to bring this efficiency to a maximum possible and drastically reducing computational times. Putting these two ingredients together is the aim of Pilot Demonstrator 2 (PD2) in ChEESE project. This PD will comprise both earthquake and landslide sources. Earthquake tsunami generation is to an extent simpler than landslide tsunami generation, as landslide generated tsunamis depend on the landslide dynamics which necessitate coupling dynamic landslide simulation models to the tsunami propagation. In both cases, FTRT simulations in several contexts and configurations will be the final aim of this pilot.</p><p>Among the objectives of our work in ChEESE project are achieving unprecedented FTRT tsunami computations with existing models and investigate the scalability limits of such models; increasing the size of the problems by increasing spatial resolution and/or producing longer simulations while still computing FTRT, dealing with problems and resolutions never done before; developing a TEWS including inundation for a particular target coastal zone, or numerous scenarios allowing PTHA (PD7) and PTF (PD8), an aim unattainable at present or including more physics in shallow water models for taking into account dispersive effects.</p><p>Up to now, the two European tsunami flagship codes selected by ChESEE project (Tsunami-HySEA and Landslide-HySEA) have been audit and efficiency further improved. The improved code versions have been tested in three European 0-Tier HPC facilities: BSC (Spain), CINECA (Italy) and Piz Daint (Switzerland) using up to 32 NVIDIA Graphic Cards (P100 and V100) for scaling purposes. Computing times have been drastically reduced and a PTF study composed by around 10,000 scenarios (4 nested grids, 12 M cells, 8 hours simulations) have been computed in 6 days of wall-clock computations in the 64 GPUs available for us at the BSC.</p><p><strong> </strong><strong>Acknowledgements</strong>. This research has been partially supported by the Spanish Government Research project <strong>MEGAFLOW</strong> (RTI2018-096064-B-C21), Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech and ChEESE project (EU Horizon 2020, grant agreement Nº 823844), https://cheese-coe.eu/</p>

Detection of tsunami induced ionospheric perturbation with ship-based GNSS measurements: 2010 Maule tsunami case study

2020 ◽  
Author(s):  
Michela Ravanelli ◽  
James Foster
Keyword(s):  
Real Time ◽  
Hawaiian Islands ◽  
Cost Effective ◽  
Early Warning Systems ◽  
Electron Content ◽  
Ionospheric Disturbances ◽  
Total Electron ◽  
Tsunami Early Warning ◽  
Phase Measurements ◽  
Gnss Receivers

<p>The VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm has been successfully applied to TIDs (Travelling ionospheric disturbances) detection in several real-time scenarios [1, 2]. VARION, thus, estimates sTEC (slant total electron content) variations starting from the single time differences of geometry-free combinations of GNSS carrier-phase measurements. This feature makes VARION suitable to also leverage GNSS observations coming from moving receivers such as ship-based GNSS receivers: the receiver motion does not affect the sTEC estimation process.</p><p>The aim of this work is to use the observations coming from two GNSS receivers installed on a ship moving near Kauai Island in the Hawaiian archipelago to detect the TIDs connected to the 2010 Maule earthquake and tsunami [3]. Indeed, this earthquake triggered a tsunami that affected all the Pacific region and that reached the Hawaiian islands after about 15 hours. All our analysis was carried out in post-processing, but simulated a real-time scenario: only the data available in real time were used.</p><p>In order to get a reference, the ship-based sTEC variations were compared with the ones coming from GNSS permanent stations situated in the Hawaiian Islands. In particular, if we considered the same satellite, the same TID is detected by both ship and ground receivers. As expected, the ship-based  sTEC variations are a little bit noisier since they are coming from a kinematic platform.</p><p>Hence, the results, although preliminary, are very encouraging: the same TIDs is detected both from the sea (ships) and land (permanent receivers).  Therefore, the VARION algorithm is also able to leverage observations coming from ship-based GNSS receivers to detect TIDs in real-time.</p><p>In conclusion, we firmly believe that the application of VARION to observation coming from ship-based GNSS receivers could really represent a real-time and cost-effective tool to enhance tsunami early warning systems, without requiring the installation of complex infrastructures in open sea.</p><p>References</p><p>[1] Giorgio Savastano, Attila Komjathy, Olga Verkhoglyadova, Augusto Mazzoni, Mattia Crespi, Yong Wei, and Anthony J Mannucci, “Real-time detection of tsunami ionospheric disturbances with a stand-alone gnss receiver: A preliminary feasibility demonstration, ”Scientific reports, vol. 7, pp. 46607, 2017.</p><p>[2] Giorgio Savastano, Attila Komjathy, Esayas Shume, Panagiotis Vergados, Michela Ravanelli, Olga Verkhoglyadova, Xing Meng, and Mattia Crespi, “Advantages of geostationary satellites for ionospheric anomaly studies: Ionospheric plasma depletion following a rocket launch,”Remote Sensing, vol. 11, no. 14, pp. 1734, 2019</p><p>[3] https://earthquake.usgs.gov/earthquakes/eventpage/official20100227063411530_30/executive</p>

A Real Time Control Architecture for Continuously Managing Patients in a Care Unit

1995 ◽  
Vol 34 (05) ◽  
pp. 475-488
Author(s):  
B. Seroussi ◽  
J. F. Boisvieux ◽  
V. Morice
Keyword(s):  
Real Time ◽  
Linear Time ◽  
Treatment Plan ◽  
Control Architecture ◽  
Real Time Control ◽  
Time Representation ◽  
Time Control ◽  
Continuous Support ◽  
Definition Of ◽  
Computerized System

Abstract:The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.

Design and development of a backstepping controller autopilot for fixed-wing UAVs

2021 ◽  
pp. 1-27
Author(s):  
D. Sartori ◽  
F. Quagliotti ◽  
M.J. Rutherford ◽  
K.P. Valavanis
Keyword(s):  
Real Time ◽  
Control Law ◽  
Parametric Uncertainties ◽  
Hardware In The Loop ◽  
Aircraft Control ◽  
Backstepping Approach ◽  
Small Uav ◽  
Backstepping Controller ◽  
Definition Of ◽  
Performance Results

Abstract Backstepping represents a promising control law for fixed-wing Unmanned Aerial Vehicles (UAVs). Its non-linearity and its adaptation capabilities guarantee adequate control performance over the whole flight envelope, even when the aircraft model is affected by parametric uncertainties. In the literature, several works apply backstepping controllers to various aspects of fixed-wing UAV flight. Unfortunately, many of them have not been implemented in a real-time controller, and only few attempt simultaneous longitudinal and lateral–directional aircraft control. In this paper, an existing backstepping approach able to control longitudinal and lateral–directional motions is adapted for the definition of a control strategy suitable for small UAV autopilots. Rapidly changing inner-loop variables are controlled with non-adaptive backstepping, while slower outer loop navigation variables are Proportional–Integral–Derivative (PID) controlled. The controller is evaluated through numerical simulations for two very diverse fixed-wing aircraft performing complex manoeuvres. The controller behaviour with model parametric uncertainties or in presence of noise is also tested. The performance results of a real-time implementation on a microcontroller are evaluated through hardware-in-the-loop simulation.

scholarly journals Electronic Orientation Aid for Visually Impaired using Graphics Processing Unit (GPU)

2020 ◽  
Vol 32 ◽  
pp. 03054
Author(s):  
Akshata Parab ◽  
Rashmi Nagare ◽  
Omkar Kolambekar ◽  
Parag Patil
Keyword(s):  
Real Time ◽  
Visually Impaired ◽  
Graphics Processing Unit ◽  
Human Perception ◽  
Processing Unit ◽  
Surrounding Environment ◽  
Visually Impaired People ◽  
Impaired People ◽  
Definition Of ◽  
Graphics Processing

Vision is one of the very essential human senses and it plays a major role in human perception about surrounding environment. But for people with visual impairment their definition of vision is different. Visually impaired people are often unaware of dangers in front of them, even in familiar environment. This study proposes a real time guiding system for visually impaired people for solving their navigation problem and to travel without any difficulty. This system will help the visually impaired people by detecting the objects and giving necessary information about that object. This information may include what the object is, its location, its precision, distance from the visually impaired etc. All these information will be conveyed to the person through audio commands so that they can navigate freely anywhere anytime with no or minimal assistance. Object detection is done using You Only Look Once (YOLO) algorithm. As the process of capturing the video/images and sending it to the main module has to be carried at greater speed, Graphics Processing Unit (GPU) is used. This will help in enhancing the overall speed of the system and will help the visually Impaired to get the maximum necessary instructions as quickly as possible. The process starts from capturing the real time video, sending it for analysis and processing and get the calculated results. The results obtained from analysis are conveyed to user by means of hearing aid. As a result by this system the blind or the visually impaired people can visualize the surrounding environment and travel freely from source to destination on their own.

Rapid earthquake source characterization in the context of tsunami early warning

2021 ◽  
Author(s):  
Alberto Armigliato ◽  
Martina Zanetti ◽  
Stefano Tinti ◽  
Filippo Zaniboni ◽  
Glauco Gallotti ◽  
...  
Keyword(s):  
Focal Mechanism ◽  
Early Warning ◽  
Fault Plane ◽  
Early Warning Systems ◽  
Slip Distribution ◽  
Generation Process ◽  
Tsunami Early Warning ◽  
Earthquake Focal Mechanism ◽  
Run Up ◽  
Seismic Networks

<p>It is well known that for earthquake-generated tsunamis impacting near-field coastlines the focal mechanism, the position of the fault with respect to the coastline and the on fault slip distribution are key factors in determining the efficiency of the generation process and the distribution of the maximum run-up and inundation along the nearby coasts. The time needed to obtain the aforementioned information from the analysis of seismic records is usually too long compared to the time required to issue a timely tsunami warning/alert to the nearest coastlines. In the context of tsunami early warning systems, a big challenge is hence to be able to define 1) the relative position of the hypocenter and of the fault and 2) the earthquake focal mechanism, based only on the preliminary earthquake localization and magnitude estimation, which are made available by seismic networks soon after the earthquake occurs.</p><p>In this study, the intrinsic unpredictability of the position of the hypocenter on the fault plane is studied through a probabilistic approach based on the analysis of two finite fault model datasets (SRCMOD and USGS) and by limiting the analysis to moderate-to-large shallow earthquakes (Mw  6 and depth  50 km). After a proper homogenization procedure needed to define a common geometry for all samples in the two datasets, the hypocentral positions are fitted with different probability density functions (PDFs) separately in the along-dip and along-strike directions.</p><p>Regarding the focal mechanism determination, different approaches have been tested: the most successful is restricted to subduction-type earthquakes. It defines average values and uncertainties for strike, dip and rake angles based on a combination of a proper zonation of the main tsunamigenic subduction areas worldwide and of subduction zone geometries available from publicdatabases.</p><p>The general workflow that we propose can be schematically outlined as follows. Once an earthquake occurs and the magnitude and hypocentral solutions are made available by seismic networks, it is possible to assign the focal mechanism by selecting the characteristic values for strike, dip and rake of the zone where the hypocenter falls into. Fault length and width, as well as the slip distribution on the fault plane, are computed through regression laws against magnitude proposed by previous studies. The resulting rectangular fault plane can be discretized into a matrix of subfaults: the position of the center of each subfault can be considered as a “realization” of the hypocenter position, which can then be assigned a probability. In this way, we can define a number of earthquake fault scenarios, each of which is assigned a probability, and we can run tsunami numerical simulations for each scenario to quantify the classical observables, such as water elevation time series in selected offshore/coastal tide-gauges, flow depth, run-up, inundation distance. The final results can be provided as probabilistic distributions of the different observables.</p><p>The general approach, which is still in a proof-of-concept stage, is applied to the 16 September 2015 Illapel (Chile) tsunamigenic earthquake (Mw = 8.2). The comparison with the available tsunami observations is discussed with special attention devoted to the early-warning perspective.</p>

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