scholarly journals Statistics of the earthquakes in the central Himalaya and its vicinity in last 56 years, with an emphasis in the 25 April 2015 Gorkha, Nepal earthquake

2021 ◽  
Vol 51 (4) ◽  
pp. 321-343
Author(s):  
Ram Krishna TIWARI ◽  
Harihar PAUDYAL
Keyword(s):  
Fractal Dimension ◽  
Statistical Analysis ◽  
High Stress ◽  
Large Earthquake ◽  
B Value ◽  
Earthquake Activity ◽  
Central Himalaya ◽  
Magnitude Distribution ◽  
Average Value ◽  
Central Nepal

To understand the variation of stress levels in the region 80°E – 89°E and 26°N – 31°N, the statistical analysis of earthquake frequency-magnitude distribution and spatio-temporal variation of fractal correlation dimension of earthquake epicenter distribution are estimated. The analysis is carried out on declusterised catalogue containing 1185 events of 56 years from February 1964 to November 2020. The study area is divided into three regions the western Nepal and vicinity (Region A), central Nepal and vicinity (Region B) and eastern Nepal and vicinity (Region C), respectively. The magnitude of completeness (Mc) varies from 3.6 to 4.0 for the study period. The spatial fractal dimension (Dc) and b-value are calculated as 1.89 ± 0.02 and 0.68 ± 0.03 for the western Nepal, 1.76 ± 0.01 and 0.60 ± 0.05 for the central Nepal, whereas they are estimated as 1.85 ± 0.02 and 0.63 ± 0.03 for the eastern part of the Nepal. The b-values obtained for all three regions are very low comparing to global average value of 1. The time clustering of the events in the respective regions are 0.26 ± 0.003, 0.31 ± 0.004 and 0.26 ± 0.02 as indicated by temporal fractal dimension (Dt). The higher Dc, lower b and Dt values associated with the regions indicate high stress concentration and stronger epicenter clustering in these regions. The strongly increasing trend of fractal dimension and strongly decreasing trend of b-value show the high probabilities of occurring the large earthquake in both central Nepal (82.5°E – 85.5°E and 27.5°N – 30°N) and eastern Nepal (85.5°E – 88.2°E and 26.45°N – 28.6°N) as compared to western Nepal (80°E – 82.5°E and 28°N – 30.5°N). This statistical analysis of spatial and temporal characteristics of the earthquake activity may give significant signs of the future seismic hazard along central Himalaya region.

scholarly journals Box Counting Fractal Dimension and Frequency Size Distributon of Earthquakes in the Central Himalaya Region

2021 ◽  
Vol 26 (2) ◽  
pp. 127-136
Author(s):  
Ram Krishna Tiwari ◽  
Harihar Paudyal
Keyword(s):  
Fractal Dimension ◽  
High Stress ◽  
High Strength ◽  
B Value ◽  
Earthquake Catalog ◽  
Central Himalaya ◽  
Study Region ◽  
B Values ◽  
Box Counting ◽  
Earthquake Distribution

To establish the relations between b-value and fractal dimension (D0) for the earthquake distribution, we study the regional variations of those parameters in the central Himalaya region. The earthquake catalog of 989 events (Mc = 4.0) from 1994.01.31 to 2020.10.28 was analyzed in the study. The study region is divided into two sub-regions (I) Region A: 27.3°N -30.3°N and 80°E -84.8°E (western Nepal and vicinity) and (II) Region B: 26.4°N -28.6°N and 84.8°E -88.4°E (eastern Nepal and vicinity). The b-value observed is within the range between 0.92 to 1.02 for region A and 0.64 to 0.74 for region B showing the homogeneous nature of the variation. The seismic a-value for those regions ranges respectively between 5.385 to 6.007 and 4.565 to 5.218. The low b-values and low seismicity noted for region B may be related with less heterogeneity and high strength in the crust. The high seismicity with average b-values obtained for region A may be related with high heterogeneity and low strength in the crust. The fractal dimension ≥1.74 for region A and ≥ 1.82 for region B indicate that the earthquakes were distributed over two-dimensional embedding space. The observed correlation between D0 and b is negative for western Nepal and positive for eastern Nepal while the correlation between D0 and a/b value is just opposite for the respective regions. The findings identify both regions as high-stress regions. The results coming from the study agree with the results of the preceding works and reveal information about the local disparity of stress and change in tectonic complexity in the central Himalaya region.

SCALING LAWS OF SEISMIC EVENTS — A MODEL WITH FRACTAL GEOMETRY

Fractals ◽  
1999 ◽  
Vol 07 (04) ◽  
pp. 341-351
Author(s):  
C. GODANO ◽  
M. L. ALONZO
Keyword(s):  
Fractal Dimension ◽  
Fractal Geometry ◽  
Scaling Laws ◽  
B Value ◽  
Seismic Events ◽  
Magnitude Distribution ◽  
Transitional State ◽  
Contact Points ◽  
Omori Law ◽  
Local Fluctuations

Most models of earthquakes attempt to reproduce the observed scaling laws of seismic events: the Gutenberg-Richter frequency magnitude distribution, but not the Omori law for aftershocks and the multifractal distribution of hypocenters location. Many of these models are based on the idea of Self-Organized Criticality (SOC). These are dynamic systems which organize themselves into a transitional state and can reproduce the Gutenberg-Richter distribution, but generally do not reproduce the space-time distribution. Here, we suggest a model based on a fractal geometry: the two sides of a fault are modeled by means of a fractal surface. As a first step, one of them is slipped of a random amount with periodic boundary conditions, then new contact points between the surfaces are found. The area surrounded by these points is assumed to be proportional to the area of the earthquake. The size distribution of events is in good agreement with the observed Gutenberg-Richter law and the local fluctuations of the b value are explained in terms of variations of the fractal dimension of the surface. Also the multifractal distribution of earthquakes in space is well-reproduced with global properties not depending on the fractal dimension of the surface. However, we are not able to obtain something similar to the Omori law simply because we do not control the time evolution of the model.

scholarly journals Mapping the <i>b</i>-values along the Longmenshan fault zone before and after the 12 May 2008, Wenchuan, China, <i>M<sub>S</sub></i> 8.0 earthquake

2008 ◽  
Vol 8 (6) ◽  
pp. 1375-1385 ◽  
Author(s):  
Y. Z. Zhao ◽  
Z. L. Wu
Keyword(s):  
Fault Zone ◽  
High Stress ◽  
B Value ◽  
Slip Distribution ◽  
Longmenshan Fault Zone ◽  
Magnitude Distribution ◽  
The North ◽  
Significant Difference ◽  
Before And After ◽  
Longmenshan Fault

Abstract. The b-value in the Gutenberg-Richter frequency-magnitude distribution, which is assumed to be related to stress heterogeneity or asperities, was mapped along the Longmenshan fault zone which accommodated the 12 May 2008, Wenchuan, MS 8.0 earthquake. Spatial distributions of b-value before and after the Wenchuan earthquake, respectively, were compared with the slip distribution of the mainshock. It is shown that the mainshock rupture nucleated near to, but not within, the high-stress (low b-value) asperity in the south part of the Longmenshan fault, propagating north-eastward to the relatively low stress (high b-value) region. Due to the significant difference between the rupture process results from different sources, the comparison between slip distribution and pre-seismic b-value distribution leads to only conclusion of the rule-of-thumb. The temporal change of b-value before the mainshock shows a weak trend of decreasing, being hard to be used as an indicator of the approaching of the mainshock. Distribution of b-values for the aftershocks relates the termination of the mainshock rupture to the harder patch along the Longmenshan fault to the north.

scholarly journals SOURCE PARAMETER AND B-VALUE ESTIMATION OF LOCAL EARTHQUAKES IN KUMAUN REGION, CENTRAL HIMALAYA, INDIA.

2016 ◽  
Vol 4 (9) ◽  
pp. 15254-1266 ◽  
Author(s):  
Vivekanand Pathak ◽  
◽  
CharuC. Pant ◽  
Santosh Joshi. ◽  
◽  
...  
Keyword(s):  
B Value ◽  
Source Parameter ◽  
Central Himalaya ◽  
Local Earthquakes ◽  
Value Estimation

scholarly journals Efektifitas penerapan model pembelajaran kooperatif tipe students team achievement division dalam meningkatkan aktivitas dan hasil belajar kognitif siswa

2019 ◽  
Vol 4 (02) ◽  
pp. 75-82
Author(s):  
Rahmat Saleh ◽  
Filawati Filawati
Keyword(s):  
Statistical Analysis ◽  
Cooperative Learning ◽  
Learning Outcomes ◽  
Cognitive Learning ◽  
Learning Models ◽  
Student Activities ◽  
Average Value ◽  
Qualitative Descriptive ◽  
Quantitative Descriptive ◽  
Descriptive Statistical Analysis

The low activity and cognitive learning outcomes of Grade VIIIB MTs Aisyiyah students require innovation in learning by using cooperative learning models. This study aims to determine the increase in activities and learning outcomes in biology through the application of cooperative learning models of students team achievement division class VIIIB MTs Aisyiyah Sungguminasa Kab. Gowa. This type of research is Classroom Action Research which consists of two cycles. The subjects of the study were students of class VIIIB MTs Aisyiyah Sungguminasa Kab. Gowa. The research instrument was an observation sheet and a test. Data analysis techniques with qualitative descriptive statistical analysis for student activities and analyzed with quantitative descriptive statistical analysis for learning outcomes. The results showed that there was an increase in students' cognitive learning activities and outcomes namely from cycle 1 and cycle 2 with an average value of 46.71% and 85.5%. Thus, the conclusion of this research is the use of cooperative learning models of students team achievement division type can increase the activities and learning outcomes of students of class VIIIB MTs Aisyiyah Sungguminasa Kab. Gowa.

scholarly journals Pengaruh Model Pembelajaran Problem Based Learning pada Materi Hukum-Hukum Dasar Kimia terhadap Hasil Belajar Siswa Kelas X MAN 2 Model Palu

2018 ◽  
Vol 7 (3) ◽  
pp. 102
Author(s):  
Tri Sulistiyawati Lamalat ◽  
Supriadi Supriadi ◽  
Siti Nuryanti
Keyword(s):  
Statistical Analysis ◽  
Learning Outcomes ◽  
Problem Based Learning ◽  
Sampling Technique ◽  
Learning Model ◽  
Mean Value ◽  
Control Group ◽  
Control Group Design ◽  
Average Value ◽  
Quasi Experimental

Research on the effect of the problem-based learning model in the basic laws of chemistry on student’s learning outcomes in class X MAN 2 Model Palu has been done. This study aimed to determine the effect of the application of the problem-based learning model in the basic laws of chemistry on student’s learning outcomes in class X MAN 2 Model Palu. The type of research was a quasi-experimental study non-randomized design with pretest-posttest control group design. The sample was conducted with a purposive sampling technique. The study sample was students in class X MIA 6 as an experimental group (n = 22) and students in class X MIA 3 as a control group (n = 22). The data testing of students' learning outcomes used a non-parametric statistical analysis, the analysis of Mann-Whitney U-Test. The research results indicated that the mean value of the experiment class was high compared to the control class, 22.61 >18.39. The statistical analysis obtained that sig. 2-tailed (0,032) ˂ 0.05 and Zcalculation (-2.149) ˂ Ztable (-1.96). The average value of the experiment class was 82.95 while the average value of the control class was 73.64. So it can be concluded that there is the effect of applying the problem-based learning model in the basic laws of chemistry on student’s learning outcomes. 

scholarly journals Characterizing microseismicity at the Rotokawa and Ngatamariki geothermal fields

2021 ◽  
Author(s):  
◽  
Chet Hopp
Keyword(s):  
Matched Filter ◽  
Fluid Pressure ◽  
B Value ◽  
Injection Well ◽  
Taupo Volcanic Zone ◽  
Reservoir Properties ◽  
Injection Wells ◽  
Small Magnitude ◽  
Magnitude Distribution ◽  
Geothermal Fields

<p>In this thesis, we construct a four-year (2012–2015) catalog of microearthquakes for the Ngatamariki and Rotokawa geothermal fields in the Taupō Volcanic Zone of New Zealand, and use these data to improve the knowledge of reservoir behavior. These microearthquakes occur frequently, often every few seconds, and therefore provide a tool that we use to assess reservoir properties with dense spatial and temporal resolution as well as to illuminate the underlying processes of seismogenesis. Using a matched-filter detection technique we detect and precisely relocate nearly 9000 events, from which we calculate 982 focal mechanisms.  At Ngatamariki, these results constitute the first detailed analysis of seismicity at a newly-developed resource. It has been commonly assumed that induced shear on fractures increases reservoir permeability by offsetting asperities on either fracture wall, thereby propping the fracture open. During stimulation treatments of two boreholes (NM08 and NM09), borehole permeability experiences logarithmic growth. At NM08, this growth occurs for eight days in the absence of seismicity, while at NM09 only nine microearthquakes are observed during the one-month treatment. This suggests that hydro-shear, the process of inducing seismicity through increased pore pressure at critically-stressed fractures, is not the dominant mechanism of permeability increase at many geothermal wells. Instead, aseismic processes, likely thermal and overpressure induced fracture opening, dominate well stimulation in high-temperature geothermal settings.  At Rotokawa, the earthquake frequency-magnitude distribution (b-value) is positively correlated with both proximity to major injection wells and depth. In an inferred pressure compartment near injection well RK23, b is ~1.18, but is <1.0 elsewhere, suggesting a connection between increased pore-fluid pressure and small-magnitude events. In addition, throughout the reservoir b increases from a value of ~1.0 at injection depth to almost 1.5 two kilometers below the reservoir, consistent with observations at volcanic areas elsewhere, but opposing the conventional wisdom that b-value is inversely proportional to differential stress.  Finally, the 982 focal mechanism observations that we invert for stress show a normal faulting regime throughout both reservoirs. At Rotokawa, a lowering stress ratio, v, after reintroduction of injection well RK23 (v drops from 0.9 to 0.2 over six months) indicates that anisotropic reservoir cooling affects the reservoir stress state through a process of preferential stress reduction.</p>

A Retrospective Analysis of b-Value Changes Preceding Strong Earthquakes

2021 ◽  
Author(s):  
Nicolas D. DeSalvio ◽  
Maxwell L. Rudolph
Keyword(s):  
B Value ◽  
Earthquake Precursors ◽  
Earthquake Catalog ◽  
Traffic Light ◽  
Magnitude Distribution ◽  
Parameter Combination ◽  
Definition Of ◽  
Value Changes ◽  
Frequency Magnitude Distribution ◽  
Optimal Set

Abstract Earthquake precursors have long been sought as a means to predict earthquakes with very limited success. Recently, it has been suggested that a decrease in the Gutenberg–Richter b-value after a magnitude 6 earthquake is predictive of an imminent mainshock of larger magnitude, and a three-level traffic-light system has been proposed. However, this method is dependent on parameters that must be chosen by an expert. We systematically explore the parameter space to find an optimal set of parameters based on the Matthews correlation coefficient. For each parameter combination, we analyze the temporal changes in the frequency–magnitude distribution for every M ≥ 6 earthquake sequence in the U.S. Geological Survey Comprehensive Earthquake Catalog for western North America. We then consider smaller events, those with a foreshock magnitude as small as 5, and repeat the analysis to assess its performance for events that modify stresses over smaller spatial regions. We analyze 25 M ≥ 6 events and 88 M 5–6 events. We find that no perfect parameter combination exists. Although the method generates correct retrodictions for some M 5 events, the predictions are dependent on the retrospectively selected parameters. About 80%–95% of magnitude 5–6 events have too little data to generate a result. Predictions are time dependent and have large uncertainties. Without a precise definition of precursory b-value changes, this and similar prediction schemes are incompatible with the IASPEI criteria for evaluating earthquake precursors. If limitations on measuring precursory changes in seismicity and relating them to the state of stress in the crust can be overcome, real-time forecasting of mainshocks could reduce the loss of lives.

The Influence of Verbal-Linguistic Intelligence on Students Learning Outcomes in English at SMA Negeri 1 Sidrap

2021 ◽  
Vol 1 (2) ◽  
pp. 141-148
Author(s):  
Rini Handayani ◽  
Geminastiti Sakkir ◽  
Rosmini Kasman
Keyword(s):  
Statistical Analysis ◽  
Learning Outcomes ◽  
Quantitative Research ◽  
Design Research ◽  
Positive Influence ◽  
Average Value ◽  
Regression Test ◽  
Simple Regression ◽  
Descriptive Statistical Analysis ◽  
Learning English

This study aims to determine verbal linguistic intelligence, to determine the results learning English especially on students' speaking, and to find out the influence of verbal linguistic intelligence on learning outcomes in English students of class X IPA 1 of SMAN 1 Sidrap. This research is quantitative research; this type of research is a pre-experimental design research. The population in this study was all students of class X SMAN 1 Sidrap, amounting to 182 people, while the study sample was the entire population, namely students of class X IPA 1 SMAN 1 Sidrap, amounting to 32 people. The instruments used in this study were interviews, questionnaires, treatment and recording tools. The data analysis technique used is descriptive statistical analysis and simple regression test through the application of SPSS. Based on the results of descriptive statistical analysis, verbal linguistic intelligence obtained an average value of 84.94, the lowest value obtained 0, and the highest value 107 and are at a percentage of 56.25% are in the average category. The results of learning English in this case speaking students obtained an average value of 96, the lowest value of 0, and the highest value of 96 and are in the good category with a percentage of 65.625%. The simple regression test results obtained sig <α (0,000 <0.05). This means that Ho is rejected and Ha is accepted, which means there is a positive influence between verbal linguistic intelligence on learning outcomes of students of class X Science 1 of SMAN 1 Sidrap.

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