A Survey of Radiation Doses Received by Atomic-bomb Survivors Residing in the U.S.
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A survey has been completed of 300 of an estimated 500–750 survivors of the atomic bombings in Hiroshima and Nagasaki who reside in the U.S. Distributions with respect to age, sex, citizenship status, distance from the hypocenter at the time of bombing, and dose from immediate weapon radiation have been tabulated from the results and are presented for this group of 300 survivors. Also presented are survey results concerning exposures to residual radiation from fallout and neutron-induced radioactivity in the areas adjacent to the hypocenter.Keywords:
Hypocenter
In an earthquake monitoring system, seismic waves are analyzed by experts or computer software to determine a magnitude and to locate the hypocenter of the earthquake. A common method for locating the hypocenter is the optimization of the least square error approach, LSE, where at least three distance values gathered from three or more different monitoring stations are required. This paper presents an approach to locating a hypocenter by employing convex polygon boundaries when computing the location. The boundaries defined by multiple planes avoid computational iterations leaving the polygon where the hypocenter is expected. The LSE approach is then applied for the calculation. Simulation results show that when using this approach the hypocenter can be identified more efficiently.
Hypocenter
Polygon (computer graphics)
Convex polygon
Earthquake location
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To identify the correspondence between the different dynamic responses of the Daguangbao landslide and the different faulting mechanisms of the composite-hypocenter, the whole hypocenter of the Wenchuan earthquake was divided into four sub-hypocenters. On another hand, based on the location of the Dauangbao landslide, the composite-hypocenter was divided into the Initial Sub-hypocenter, the Approaching Sub-hypocenter, the Local Sub-hypocenter, the Receding sub-hypocenter and the Terminal sub-hypocenter. Subsequently, dynamic response of the landslide was modeled by using UDEC software. The results show that progressive damage and critical failure of the mega landslide are triggered by the second sub-hypocenter. Simutaneously, with respect to the second classification basis, its progressive damage is induced by the Approaching Hypocenter and the Local Hypocenter in time sequence. The Local Hypocenter triggers its critical failure. During the long-runout stage, besides the local topography, its self-gravity poses a dominant contribution to the dynamic responses of the landslide. Especially, the inertial seismic force is another key factor that triggers the ejection stage of the landslide. The following seismic forces triggered by the corresponding sub-hypocenter influence the long-runout stage slightly. The horizontal seismic force poses a dominant contribution to the progressive damage and critical failure of the mega landslide.
Hypocenter
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Hypocenter Determination and Estimation 1-D Velocity Models Using Coupled Velocity-Hypocenter Method
Hypocenter relocation is performed to obtain a high-precision hypocenter location (accurate earthquake location). An accurate earthquake location is the key problem in seismology. Further information from an accurate hypocenter location can be used for seismicity analysis, velocity structure study, and earthquake prone mapping as one of the earthquake mitigation efforts. In this research, the method used to relocate the earthquake hypocenter was the Coupled Velocity-Hypocenter. Relocations were conducted in the Central Sulawesi region; we located 40 local earthquake events with a magnitude of ≥ 3.8 ML and a depth of ≤ 25 km. The selected P-wave traveltimes were inverted from 5 seismic stations. The variance of initial velocity models used the 1-D Primary wave velocity model of North Sulawesi, Jeffrey-Bullen and Central Sulawesi. The relocation results show that most of the hypocenters are concentrated precisely in minor faults present in the research area, and the hypocenter distribution of the events indicated as destructive shallow earthquakes occurs at depths of about 5-15 km. The residual distributions resulting from the relocation using the initial velocity model of the Central Sulawesi region indicates an improved quality if compared to Jeffrey-Bullen velocity model and the North Sulawesi velocity model, with RMS error value of 0.08 seconds. This research concluded that the 1-D velocity model in the regional (Central Sulawesi Region) reference was suitable for determining the high-precision hypocenter location.
Hypocenter
Relocation
Earthquake location
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Parameters of hypocenters and times of 4760 seismic events taken from KNET catalog compiled by the Research Station of the Russian Academy of Sciences for the period since May 2003 till the end of 2020 have been determined by different programs: Hypocenter, HYP, Hypoellipse, HYPO71, Dbloc2. The smallest divergence of epicenters' coordinates is observed for the earthquakes, which have happened within the area of 41°–44.5°N and 73°–77.5°E entirely covering the territory of Bishkek geodynamic test site. Such an analysis can be used to assess the quality of seismic wave arrival times determination. The best agreement is observed between the programs Hypocenter and HYP: for more than 95% of events the epicenter displacement is less than 10 km and the change of time at origin is less than 0.5 sec. This indicates the preservation of the uniformity of the KNET seismological catalog when switching from using Hypocenter to HYP as the main locator program.
Hypocenter
Epicenter
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Abstract Accurate earthquake locations are important for understanding earthquake processes. Recent advances in earthquake relocation methods have resulted in relative centroid locations with smaller uncertainties using cross‐correlation‐based methods. However, relative hypocenter locations, which are traditionally determined using the onset times of event waveforms, generally possess larger uncertainties than that of the centroids. Here, we develop a new cross‐correlation‐based relative hypocenter relocation method based on the network correlation coefficient method, whereby we incorporate an additional step to search for a suitable window to cross‐correlate the event waveform onsets. We then perform a joint inversion on the obtained relative hypocenter and centroid locations to directly compare their relative locations under a unified coordinate. We apply this method to three regions where repeating earthquakes have been detected, and reveal both the repetitive rupture of similar centroids by these repeating events and newly illuminated hypocenter hotspots that serve as the onset region of earthquakes that grow into different but selective magnitudes. Our joint analysis of hypocenter and centroid locations enables quick estimations of rupture propagation directions without the need to perform slip inversion analyses. We estimate the location uncertainties via bootstrapping, with the 95% confidence intervals yielding sub‐100 m horizontal uncertainties in both the centroid and hypocenter locations with the best station coverage and event availability. These results point to limited but existing correspondence between the hypocenter and centroid locations and the earthquake magnitudes, as well as complexity in the hypocenter distributions, even within repeating earthquake sequences whose rupture areas largely overlap.
Hypocenter
Centroid
Earthquake location
Relocation
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In this study, we determined the accurate hypocenter location of November 15, 2019, the Molucca Sea earthquake aftershocks using the Modified Joint Hypocenter Determination (MJHD) method. This method calculated the hypocenter and seismic station correction simultaneously using the seismic wave travel time inversion. The P and S wave arrival time at each station from the BMKG database was used in this study. After relocated, most of the aftershocks hypocenter categorized as shallow and medium depth earthquakes with the range of focal depth between 25-150 km.
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Research has been done about the relocation of earthquake hypocenter position, seismic wave local velocity and correction of seismic wave recording station at the Abang-Culik Fault area according to coordinate 115,25°-115,75° BT and 8,00°-8,60° LS. Data which was used on this research was the earthquake data that occur in the 2015-2020 period. The research was conducted using the coupled velocity-hypocenter method. From the relocation result, the position of the earthquake hypocenter shifted, which initially spread to become more concentrated in the fault plane area. The local velocity decreasing a lot in the 3rd layer which was influenced by the presence of the Mount Agung magma pocket in that area. The correction of Station shown that only 1 station has a negative value of delay time, namely IGBI station while the other 13 stations show a positive value of delay time.
Hypocenter
Relocation
Position (finance)
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Abstract Prediction analysis provides an efficient means of estimating errors in local earthquake hypocenter determinations using a dense array of seismometers. The standard errors of the hypocentral coordinates and the origin time due to random errors in the data and model parameters may be calculated rigorously for a least-squares hypocenter inversion procedure using arbitrary earth models. Contour maps of the estimated standard errors in the hypocenter parameters are plotted for two array configurations and for several earth models and event depths. These maps are useful in predicting the relative accuracy and difficulty of hypocenter location as a function of position in the array, and in selecting events with small relative error to be used in velocity-structure refinement in the vicinity of the array. In particular, the method may be used to provide a means of optimizing array geometry to provide maximum hypocenter control in specific target regions. Tests were made using hypothetical data with prescribed error distributions showing good agreement with the error analysis.
Hypocenter
Seismometer
Position (finance)
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Hypocenter
Statistic
Representation
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