Many moderate and strong earthquakes have occurred in Indonesia. However, since ground motion records are unavailable, a concise earthquake peak ground acceleration (PGA) map has never before been constructed. Several efforts have been made to construct PGA maps after the Mw6.4 2006 Yogyakarta earthquake, i.e. earthquake PGA maps by researchers [1–4]. However, due to their use of completely different earthquake sources, methods of analysis and by using exclusion criteria of ground motion prediction equations (GMPE), the maps differed greatly and did not match the actual structural damage found in the field. Estimation of a 2006 Yogyakarta earthquake PGA map became possible after field surveying of the Imm conducted by Wijaya [5]. The estimated PGA map was constructed based on the isoseimic lines, intensity prediction equation (IPE) by Wijaya [5] and peak ground acceleration at YOGI and BJI station control points, as published by Elnashai et al [6]. A set of most recent GMPEs were chosen, as they closely predicted the PGA at two control points. An Extrapolation Method was developed in which the PGA between YOGI and BJI stations would be extrapolated to all data points in the field to yield the 2006 Yogyakarta seismic PGA map. Result of the investigation indicated that the pattern of the new PGA map does not form a circle with radius R, but occurs longitudinally following the direction of the Opak River fault trace and closely follows the pattern of Imm map and damage to buildings in the field. It was found that the maximum upperbound PGA reached ±0.50-0.51g and it did not occur at the epicenter area but instead took place in relatively deep soil deposit approximately ±2 km west of the Opak River fault.
This paper presents the development of synthetic ground motion at specific sites in Yogyakarta town. In the 2019 Indonesian Seismic Code [1] provides an alternative method in the analysis of building structures by applying the dynamic time history analysis. At least 11-pairs of earthquake recordings must be used in the analysis. Synthetic ground motion utilizing the Method of Probability Seismic Hazard Analysis (PSHA) was used in this study. A selected site in Yogyakarta town was chosen as a pilot study considering that there were many fatalities and building damage caused by the 2006 Yogyakarta earthquake. The Uniform Hazard Spectra (UHS) based on the shallow crustal earthquake source is higher than the Megathrust. The risk targeted spectrum demand MCEr has been considered, which on average 12.3% greater than the UHS. The synthetic ground motions (SGM) are accordingly based on the shallow crustal earthquakes. The dominant magnitude and distance are M D = 6.5 and R D = 14.5 km. They show that the contribution of the Opak River fault to the hazard in Yogyakarta town is very dominant because the distance is very close. Based on the obtained M D and R D , spectral matching, and testing significant duration D 595 , the 12-synthetic ground motions were successfully developed.
Spatial planning has an important role in disaster mitigation efforts. The availability of earthquake maps is very useful in spatial planning. The need for spatial planning today is micro spatial planning. Therefore, the 2017 national earthquake map needs to be detailed into a micro zonation map at the district or city scale. The ground acceleration presented in the national earthquake map was the acceleration at bedrock, while in spatial planning it is the necessary acceleration at the surface. Therefore, the purpose of this research was to obtain a map of the earthquake at the surface with a micro-scale. Determination of the acceleration value at the surface was carried out by two models. Model-1, the surface acceleration was obtained by multiplying the results of the PSHA analysis at bedrock by the amplification factor based on SNI-1726. While Model-2, the acceleration value at the surface was directly obtained from the results of PSHA analysis using the average surface shear wave velocity (Vs30) based on data from the USGS. The result of this study showed that from the 2 analytical models used, Model-2 has a higher surface acceleration value than Model-1. Riau Province has 12 districts. in general, the 12 districts were included in the low to moderate risk index class, but there was one district that was close to the high index class, namely Rokan Hulu district.
Indonesia is not only known as an archipelago that is rich innatural resources but also known as a disaster-prone country. Because ofits location in four major Eurasian, Indo-Australian, Pacific, and Philippinetectonic plates, natural disasters such as earthquakes, floods, landslides, volcanic eruptions, droughts, forest fires, and tsunamis often occurthroughout the region. In 2006, a large earthquake shocked the denselypopulated Yogyakarta Province and its surrounding areas. This earthquakecaused huge fatalities and damaged thousands of buildings andinfrastructures. The Pacitan region is geographically close to Yogyakarta, and is located only 120 km from the epicenter of the quake. Therefore, awareness of disaster mitigation is a critical action in reducing disasterrisks. In addition, the Pacitan Regency is a hilly and mountainous regioncovering a total area of 1,389.87 km. Its territory also includes karstregions and lowland areas. A preliminary research utilizing the HAZUSmethod was conducted for assessing the damage probability of residentialhouses at an earthquake-prone area of Pacitan sub-district. The indicativeresults show that the unreinforced masonry (URML) types are the mostdestructive followed by Wood, light frame (W1), reinforced masonry lowrise(RM2L), and reinforced masonry mid-rise (RM2M) when appliedacross three scenarios of earthquake with magnitudes of 6, 6.5, and 7, respectively.
One of the most causes of damage to structures during an earthquake is liquefaction. Liquefaction happened in loose sand, which saturated under earthquake shaking. Earthquake shaking will cause cyclic loading to the ground's surface, which potential for the occurrence of liquefaction. The liquefaction phenomenon is a soil behavior under cyclic loads that occurs in just a few moments. Due to the short cyclic load, the soil mass suddenly changes from a solid limit to a liquid limit or has a paramount consistency, such as liquid. Liquefaction events during an earthquake can be characterized by the presence of ground movement in the horizontal direction, seepage water out from fracture of the ground, movement of sloping or descending buildings, displacement of ground advance, and landslides. This study took a case study in Glagah Beach at Kulonprogo Regency. That is beach areas, a landform alongside body water, which consists of loose particles such as sand where Yogyakarta International Airport (YIA) is located. The analysis was carried out to determine the potential of liquefaction based N-SPT data using the Seed, Martin & Lysmer (1975). Based on these data, The Cyclic Stress Ratio (CSR) value is calculated, which is the ratio between the average shear stress caused by the earthquake with the significant vertical stress in each layer and the value of the Cyclic Resistance Ratio (CRR), which is the amount of soil resistance to liquefaction. The analysis in the Kulonprogo Regency area is an area that is considered to require liquefaction. Analysis of liquefaction potential based on N-SPT data with the Seed, Martin & Lysmer (1975) method on a 6.3 magnitude earthquake. The result indicates that the liquefaction potential occurs up to a depth of 8.5 meters.
The concept of seismic intensity measures has long beendiscussed and has been collected by researchers among whom are by [1-6]. However, the effect of earthquake duration on the structural response hasnot received attention from the researcher so it has not been seen in the listof the existing seismic intensity measures. In the spectral response, forexample, it has been accommodated peak value and earthquake frequencycontent but has not accommodated the duration of the earthquake. Theeffect of earthquake duration on a response, damage or collapse capacity ofthe structure has been done by the researchers [7-10]. The spectrallyequivalent approach/control has been used by [9,10]., while the collapsecapacity approach is cursed by [8]. The use of the classification of theearthquake frequency content as independent variables has been suggestedby [7]. In this study, the classification of earthquake frequency (lowfrequency), earthquake duration as the independent variable and peakacceleration control have been used. Single degree of Freedom (SDOF)structures excited by 15-earthquakes with effective durations varyingbetween te = 6.34 to 30.18 s have been used. The results showed that notall seismic intensity measure used had a strong relationship with effectiveduration. The earthquake effective duration has a positive relationship withthe damage index but the relationship is relatively weak
Among the devastated earthquakes that have occurred in theYogyakarta Special Province (YSP) were earthquakes that occur in 1867,1943 and 2006 [1,2]. Macro site coefficient is already available in [3]however, more detailed site coefficient or presented on a micro scale is notyet available. The disaster mitigation program is needed and one of whichis the availability of the microseismic site coefficient maps for short periodFa and long period Fv particularly for building design. The probabilisticseismic hazard analysis (PSHA) has been carried out. The subduction andthe shallow crustal earthquakes within 500km radius from the city ofYogyakarta have been used. In contrast to [4], PSHA was carried out byusing 10% probability of the earthquake being exceeded within 50 years. Result of this study indicates that YSP is dominated by hard SD andmedium soil categories. The medium soil is mainly located at along theOpak and Progo river valleys and along the southern coast of Bantul andKulonprogo districts. The short period site coefficient Fa is stronglyinfluenced by the Opak fault as an earthquake source, while the sitecoefficient for long period Fv is more influenced by the Megathrustearthquake source. For PGA < 1.0g, the seismic coefficient Fa for shortperiod increases with increasing Vs30, meanwhile for long period ofseismic coefficient Fv decreases with increasing Vs30.
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