Publications
267 results found
Ulmer KJ, Upadhyaya S, Green RA, et al., 2018, A Critique of b-Values Used for Computing Magnitude Scaling Factors, Geotechnical Earthquake Engineering and Soil Dynamics V, Pages: 112-121, ISSN: 0895-0563
© 2018 American Society of Civil Engineers. The objective of this paper is to explore the effects of relative density, effective confining stress, and liquefaction initiation criteria on the slope (or b-value) of the cyclic stress ratio versus number of uniform stress cycles to liquefaction curve in log-log space. The b-value is central to the computation of magnitude scaling factors (MSF) used in evaluating liquefaction potential and can be determined from cyclic laboratory tests such as cyclic triaxial (CTRX), cyclic simple shear (CSS), and cyclic torsional (CTS) tests. This paper provides a summary of b-values calculated from published test data representing multiple types of laboratory tests, sands, sample preparation methods, and liquefaction criteria. Trends between b-values and relative density are shown to be more ambiguous than is often assumed. Effective confining stresses and liquefaction criteria are also shown to have an effect on b-values.
Noorlandt R, Kruiver PP, de Kleine MPE, et al., 2018, Characterisation of ground motion recording stations in the Groningen gas field, Journal of Seismology, Vol: 22, Pages: 605-623, ISSN: 1383-4649
The seismic hazard and risk analysis for the onshore Groningen gas field requires information about local soil properties, in particular shear-wave velocity (V S ). A fieldwork campaign was conducted at 18 surface accelerograph stations of the monitoring network. The subsurface in the region consists of unconsolidated sediments and is heterogeneous in composition and properties. A range of different methods was applied to acquire in situ V S values to a target depth of at least 30 m. The techniques include seismic cone penetration tests (SCPT) with varying source offsets, multichannel analysis of surface waves (MASW) on Rayleigh waves with different processing approaches, microtremor array, cross-hole tomography and suspension P-S logging. The offset SCPT, cross-hole tomography and common midpoint cross-correlation (CMPcc) processing of MASW data all revealed lateral variations on length scales of several to tens of metres in this geological setting. SCPTs resulted in very detailed V S profiles with depth, but represent point measurements in a heterogeneous environment. The MASW results represent V S information on a larger spatial scale and smooth some of the heterogeneity encountered at the sites. The combination of MASW and SCPT proved to be a powerful and cost-effective approach in determining representative V S profiles at the accelerograph station sites. The measured V S profiles correspond well with the modelled profiles and they significantly enhance the ground motion model derivation. The similarity between the theoretical transfer function from the V S profile and the observed amplification from vertical array stations is also excellent.
Dost B, Edwards B, Bommer JJ, 2018, The relationship between M and M<inf>L</inf>: A review and application to induced seismicity in the groningen gas field, the Netherlands, Seismological Research Letters, Vol: 89, Pages: 1062-1074, ISSN: 0895-0695
The use of local magnitude (M L ) in seismic hazard analyses is a topic of recent debate. In regions of weak or moderate seismicity, small earthquakes (characterized by M L ) are commonly used to determine frequency-magnitude distributions (FMDs) for probabilistic seismic hazard calculations. However, empirical and theoretical studies on the relation between moment magnitude (M) and M L for small earthquakes show a systematic difference between the two below a region-dependent magnitude threshold. This difference may introduce bias in the estimation of the frequency of larger events with given M, and consequently seismic hazard. For induced seismicity related to the Groningen gas field, this magnitude threshold is determined to be M ∼ 2, with equality between M and M L at higher magnitudes. A quadratic relation between M and M L is derived for 0:5 < M L < 2, in correspondence to recent theoretical studies. Although the seismic hazard analysis for Groningen is internally consistent when expressed in terms of M L (with the implicit assumption of equivalence between the two scales), a more physical interpretation of the seismicity model requires transformation of the earthquake catalog from local to moment magnitude, especially because the dataset currently used in estimating time-dependent hazard consists mainly of M L < 2:5 events. We show that measured station effects, derived from M calculations, correspond to predicted model calculations used to determine a ground-motion model for the region.
Bommer JJ, Dost B, Edwards B, 2018, The relationship between M and ML – a review and application to induced seismicity in the Groningen gas field, the Netherlands, Seismological Research Letters, ISSN: 0895-0695
The use of local magnitude (ML) in seismic hazard analyses is a topic of recent debate. In 2regions of weak-or moderate-seismicity, small earthquakes (characterized by ML) are 3commonly used to determine frequency-magnitude distributions (FMD) for probabilistic4seismic hazard calculations. However, empirical and theoretical studies on the relation 5between moment magnitude (M) and ML for small earthquakes show a systematic difference between the two below a region-dependent magnitude threshold. This difference may introduce bias in the estimation of the frequency of larger events with given M, and consequently seismic hazard. For induced seismicity related to the Groningen gas field, this magnitude threshold is determined to be M~ 2, with equality between Mand ML at higher magnitudes. A quadratic relation between M and ML is derived for 0.5 < ML < 2, in correspondence to recent theoretical studies. While the seismic hazard analysis for Groningen is internally consistent when expressed in terms of ML (with the implicit assumption of equivalence between the two scales), a more physical interpretation of theseismicity model requirestransformation of the earthquake catalogue from local to moment magnitude, especially since the dataset currently used in estimating time-dependent hazard consists mainly of ML< 2.5 events. We show that measured station effects, derived from Mcalculations, correspond to predicted model calculations used to determine a ground-motion model for the region.
Bommer JJ, Dost B, Edwards B, et al., 2018, Developing a model for the prediction of ground motions due to earthquakes in the Groningen gas field, NETHERLANDS JOURNAL OF GEOSCIENCES-GEOLOGIE EN MIJNBOUW, Vol: 96, Pages: S203-S213, ISSN: 0016-7746
Major efforts are being undertaken to quantify seismic hazard and risk due to production-induced earthquakes in the Groningen gas field as thebasis for rational decision-making about mitigation measures. An essential element is a model to estimate surface ground motions expected at anylocation for each earthquake originating within the gas reservoir. Taking advantage of the excellent geological and geophysical characterisationof thefield and a growing database of ground-motion recordings, models have been developed for predicting response spectral accelerations, peak groundvelocity and ground-motion durations for a wide range of magnitudes. The models reflect the unique source and travel path characteristics of theGroningen earthquakes, and account for the inevitable uncertainty in extrapolating from the small observed magnitudes to potential larger events.The predictions of ground-motion amplitudes include the effects of nonlinear site response of the relatively soft near-surface deposits throughoutthe field.
Green RA, Stafford P, Maurer BW, et al., 2018, Liquefaction hazard due to induced seismicity: Overview of the pilot study being performed for the Groningen region of the Netherlands, 11th U.S. National Conference on Earthquake Engineering, Publisher: Earthquake Engineering Research Institute
Bommer JJ, van Elk J, Doornhof D, et al., 2017, Hazard and risk assessments for induced seismicity in Groningen, Netherlands Journal of Geosciences, Vol: 96, Pages: 2259-s269, ISSN: 0016-7746
Earthquakes associated with gas production have been recorded in the northern part of the Netherlands since 1986. The Huizinge earthquake of 16 August 2012, the strongest so far with a magnitude of M L = 3.6, prompted reassessment of the seismicity induced by production from the Groningen gas field. An international research programme was initiated, with the participation of many Dutch and international universities, knowledge institutes and recognised experts.The prime aim of the programme was to assess the hazard and risk resulting from the induced seismicity. Classic probabilistic seismic hazard and risk assessment (PSHA) was implemented using a Monte Carlo method. The scope of the research programme extended from the cause (production of gas from the underground reservoir) to the effects (risk to people and damage to buildings). Data acquisition through field measurements and laboratory experiments was a substantial element of the research programme. The existing geophone and accelerometer monitoring network was extended, a new network of accelerometers in building foundations was installed, geophones were placed at reservoir level in deep wells, GPS stations were installed and a gravity survey was conducted.Results of the probabilistic seismic hazard and risk assessment have been published in production plans submitted to the Minister of Economic Affairs, Winningsplan Groningen 2013 and 2016 and several intermediate updates. The studies and data acquisition further constrained the uncertainties and resulted in a reduction of the initially assessed hazard and risk.
Stafford PJ, Rodriguez-Marek A, Edwards B, et al., 2017, Scenario dependence of linear site-effect factors for short-period response spectral ordinates, Bulletin of the Seismological Society of America, Vol: 107, Pages: 2859-2872, ISSN: 0037-1106
Ground‐motion models for response spectral ordinates commonly partition site‐response effects into linear and nonlinear components. The nonlinear components depend upon the earthquake scenario being considered implicitly through the use of the expected level of excitation at some reference horizon. The linear components are always assumed to be independent of the earthquake scenario. This article presents empirical and numerical evidence as well as a theoretical explanation for why the linear component of site response depends upon the magnitude and distance of the earthquake scenario. Although the impact is most pronounced for small‐magnitude scenarios, the finding has significant implications for a number of applications of more general interest including the development of site‐response terms within ground‐motion models, the estimation of ground‐motion variability components ϕS2SϕS2S and ϕSSϕSS , the construction of partially nonergodic models for site‐specific hazard assessments, and the validity of the convolution approach for computing surface hazard curves from those at a reference horizon, among others. All of these implications are discussed in the present article.
Rodriguez-Marek A, Kruiver PP, Meijers P, et al., 2017, A regional site-response model for the Groningen gas field, Bulletin of the Seismological Society of America, Vol: 107, Pages: 2067-2077, ISSN: 1943-3573
A key element in the assessment of induced seismic hazard and risk due to induced earthquakes in the Groningen gas field is a model for the prediction of ground motions. Rather than use ground-motion prediction equations (GMPEs) with generic site amplification factors conditioned on proxyparameters such as VS30, a field-wide zonation of frequency-dependent non-linear amplification factors has been developed. Each amplification factor is associated with a measure of site-to-site variability that captures the variation of VSprofiles and hence amplification factors across each zone, as well as the influence of uncertainty in the modulus reduction and damping functions for each soil layer. This model can be used in conjunction with predictions of response spectral accelerations at a reference rock horizon at a depthof about 800 m to calculate fully probabilistic estimates of the hazard in terms of ground shaking at the surface for a large region potentially affected by induced earthquakes.
Bommer JJ, Crowley H, 2017, The purpose and definition of the minimum magnitude limit in PSHA calculations, Seismological Research Letters, Vol: 88, Pages: 1097-1106, ISSN: 0895-0695
A lower limit of magnitude Mmin is routinely defined for integrations of earthquake scenarios in probabilistic seismic‐hazard analysis but there is widespread misunderstanding of the technical bases for determining the value of this parameter. In this article, several misconceptions are identified and discarded prior to providing a clear and unambiguous definition of Mmin that points to the fact that seismic‐hazard assessment is always conditioned by the intended application of the outputs. We argue that Mmin is therefore an engineering parameter that is ultimately related to seismic risk rather than seismic hazard. The confusion surrounding this topic could be largely alleviated by defining lower limits on appropriate intensity measures rather than on magnitudes used as a proxy for shaking levels.
Bommer JJ, Stafford PJ, Edwards B, et al., 2017, Framework for a ground-motion model for induced seismic hazard and risk analysis in the Groningen gas field, the Netherlands, Earthquake Spectra, Vol: 33, Pages: 481-498, ISSN: 8755-2930
The potential for building damage and personal injury due to induced earthquakes in the Groningen gas field is being modeled in order to inform risk management decisions. To facilitate the quantitative estimation of the induced seismic hazard and risk, a ground motion prediction model has been developed for response spectral accelerations and duration due to these earthquakes that originate within the reservoir at 3 km depth. The model is consistent with the motions recorded from small-magnitude events and captures the epistemic uncertainty associated with extrapolation to larger magnitudes. In order to reflect the conditions in the field, the model first predicts accelerations at a rock horizon some 800 m below the surface and then convolves these motions with frequency-dependent nonlinear amplification factors assigned to zones across the study area. The variability of the ground motions is modeled in all of its constituent parts at the rock and surface levels.
Bommer JJ, van Elk J, 2017, Comment on “The maximum possible and maximum expected earthquake magnitude for production-induced earthquakes at the gas field in Groningen, The Netherlands” by Gert Zöller and Matthias Holschneider, Bulletin of the Seismological Society of America, Vol: 107, ISSN: 1943-3573
Zöller and Holschneider (2016) propose estimates of the maximum magnitude of induced earthquakes resulting from gas production in the Groningen field in The Netherlands by applying the approach of Zöller and Holschneider (2014) to the earthquake catalog for the Groningen field. We wish neither to make any comment on the analytical approach that the authors propose, nor to comment on their results in this particular application. We do feel obliged to clarify for readers the context of the study by Zöller and Holschneider (2016) in relation to the March 2016 workshop to which they refer. In particular, the sentence in their Introduction stating that “this short note provides the results of those authors” (p. 2917) could be interpreted as implying that their paper presents the results from the workshop. The paper by Zöller and Holschneider (2016) summarizes one of the many inputs that contributed to the workshop, but not the final outcome of the workshop.
Kruiver PP, van Dedem E, Romijn R, et al., 2017, An integrated shear-wave velocity model for the Groningen gas field, The Netherlands, Bulletin of Earthquake Engineering, Vol: 15, Pages: 3555-3580, ISSN: 1570-761X
A regional shear-wave velocity (VS) model has been developed for the Groningen gas field in the Netherlands as the basis for seismic microzonation of an area of more than 1000 km2. The VS model, extending to a depth of almost 1 km, is an essential input to the modelling of hazard and risk due to induced earthquakes in the region. The detailed VS profiles are constructed from a novel combination of three data sets covering different, partially overlapping depth ranges. The uppermost 50 m of the VS profiles are obtained from a high-resolution geological model with representative VS values assigned to the sediments. Field measurements of VS were used to derive representative VS values for the different types of sediments. The profiles from 50 to 120 m are obtained from inversion of surface waves recorded (as noise) during deep seismic reflection profiling of the gas reservoir. The deepest part of the profiles is obtained from sonic logging and VP–VS relationships based on measurements in deep boreholes. Criteria were established for the splicing of the three portions to generate continuous models over the entire depth range for use in site response calculations, for which an elastic half-space is assumed to exist below a clear stratigraphic boundary and impedance contrast encountered at about 800 m depth. In order to facilitate fully probabilistic site response analyses, a scheme for the randomisation of the VS profiles is implemented.
Bommer JJ, Stafford PJ, 2016, Seismic hazard and earthquake actions, Seismic Design of Buildings to Eurocode 8, Second Edition, Pages: 7-40, ISBN: 9781498751605
Earthquake-resistant design can be considered as the art of balancing the seismic capacity of structures with the expected seismic demand to which they may be subjected. In this sense, earthquake-resistant design is the mitigation of seismic risk, which may be defined as the possibility of losses (human, social or economic) due to the effects of future earthquakes. Seismic risk is often considered as the convolution of seismic hazard, exposure and vulnerability. Exposure refers to the people, buildings, infrastructure, commercial and industrial facilities located in an area where earthquake effects may be felt; exposure is usually determined by planners and investors, although in some cases avoidance of major geo-hazards may lead to relocation of new infrastructure. Vulnerability is the susceptibility of structures to earthquake effects and is generally defined by the expected degree of damage that would result under different levels of seismic demand; this is the component of the risk equation that can be controlled by engineering design. Seismic hazards are the potentially damaging effects of earthquakes at a particular location, which may include surface rupture, tsunami runup, liquefaction and landslides, although the most important cause of damage on a global scale is earthquake-induced ground shaking (Bird and Bommer, 2004). The focus in this chapter is exclusively on this particular hazard and the definition of seismic actions in terms of strong ground motions. In the context of probabilistic seismic hazard analysis (PSHA), seismic hazard actually refers to the probability of exceeding a specific level of ground shaking within a given window of time.
Bommer JJ, Dost B, Edwards B, et al., 2015, Developing an Application-Specific Ground-Motion Model for Induced Seismicity, Bulletin of the Seismological Society of America, Vol: 106, Pages: 158-173, ISSN: 1943-3573
A key element of quantifying both the hazard and risk due to inducedearthquakes is a suite of appropriate ground-motion prediction equations (GMPEs) thatencompass the possible shaking levels due to such events. Induced earthquakes arelikely to be of smaller magnitude and shallower focal depth than the tectonic earthquakesfor which most GMPEs are derived. Furthermore, whereas GMPEs formoderate-to-large magnitude earthquakes are usually derived to be transportable todifferent locations and applications, taking advantage of the limited regional dependenceobserved for such events, the characteristics of induced earthquakes warrant thedevelopment of application-specific models. A preliminary ground-motion model forinduced seismicity in the Groningen gas field in The Netherlands is presented as anillustration of a possible approach to the development of these equations. The GMPE iscalibrated to local recordings of small-magnitude events and captures the epistemicuncertainty in the extrapolation to larger magnitude considered in the assessment ofthe resulting hazard and risk.
Bourne SJ, Oates SJ, Bommer JJ, et al., 2015, Monte Carlo Method for Probabilistic Hazard Assessment of Induced Seismicity due to Conventional Natural Gas Production, Bulletin of the Seismological Society of America, Vol: 105, Pages: 1721-1738, ISSN: 0037-1106
A Monte Carlo approach to probabilistic seismic‐hazard analysis is developed for a case of induced seismicity associated with a compacting gas reservoir. The geomechanical foundation for the method is the work of Kostrov (1974) and McGarr (1976) linking total strain to summed seismic moment in an earthquake catalog. Our Monte Carlo method simulates future seismic hazard consistent with historical seismic and compaction datasets by sampling probability distributions for total seismic moment, event locations and magnitudes, and resulting ground motions. Ground motions are aggregated over an ensemble of simulated catalogs to give a probabilistic representation of the ground‐motion hazard. This approach is particularly well suited to the specific nature of the time‐dependent induced seismicity considered.We demonstrate the method by applying it to seismicity induced by reservoir compaction following gas production from the Groningen gas field. A new ground‐motion prediction equation (GMPE) tailored to the Groningen field has been derived by calibrating an existing GMPE with local strong‐motion data. For 2013–2023, we find a 2% chance of exceeding a peak ground acceleration of 0.57g and a 2% chance of exceeding a peak ground velocity of 22 cm/s above the area of maximum compaction. Disaggregation shows that earthquakes of Mw 4–5, at the shortest hypocentral distances of 3 km, and ground motions two standard deviations above the median make the largest contributions to this hazard. Uncertainty in the hazard is primarily due to uncertainty about the future fraction of induced strains that will be seismogenic and how ground motion and its variability will scale to larger magnitudes.
Bommer JJ, Coppersmith KJ, Coppersmith RT, et al., 2015, A SSHAC Level 3 Probabilistic Seismic Hazard Analysis for a New-Build Nuclear Site in South Africa, EARTHQUAKE SPECTRA, Vol: 31, Pages: 661-698, ISSN: 8755-2930
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- Citations: 66
Bommer JJ, Crowley H, Pinho R, 2015, A risk-mitigation approach to the management of induced seismicity, Journal of Seismology, Vol: 19, Pages: 623-646, ISSN: 1383-4649
Earthquakes may be induced by a wide range of anthropogenic activities such as mining, fluid injection and extraction, and hydraulic fracturing. In recent years, the increased occurrence of induced seismicity and the impact of some of these earthquakes on the built environment have heightened both public concern and regulatory scrutiny, motivating the need for a framework for the management of induced seismicity. Efforts to develop systems to enable control of seismicity have not yet resulted in solutions that can be applied with confidence in most cases. The more rational approach proposed herein is based on applying the same risk quantification and mitigation measures that are applied to the hazard from natural seismicity. This framework allows informed decision-making regarding the conduct of anthropogenic activities that may cause earthquakes. The consequent risk, if related to non-structural damage (when re-location is not an option), can be addressed by appropriate financial compensation. If the risk poses a threat to life and limb, then it may be reduced through the application of strengthening measures in the built environment—the cost of which can be balanced against the economic benefits of the activity in question—rather than attempting to ensure that some threshold on earthquake magnitude or ground-shaking amplitude is not exceeded. However, because of the specific characteristics of induced earthquakes—which may occur in regions with little or no natural seismicity—the procedures used in standard earthquake engineering need adaptation and modification for application to induced seismicity.
Atkinson GM, Bommer JJ, Abrahamson NA, 2014, Alternative Approaches to Modeling Epistemic Uncertainty in Ground Motions in Probabilistic Seismic-Hazard Analysis, SEISMOLOGICAL RESEARCH LETTERS, Vol: 85, Pages: 1141-1144, ISSN: 0895-0695
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- Citations: 81
Rodriguez-Marek A, Rathje EM, Bommer JJ, et al., 2014, Application of single-station sigma and site-response characterization in a probabilistic seismic-hazard analysis for a new nuclear site, Bulletin of the Seismological Society of America, Vol: 104, Pages: 1601-1619, ISSN: 0037-1106
Aleatory variability in ground‐motion prediction, represented by the standard deviation (sigma) of a ground‐motion prediction equation, exerts a very strong influence on the results of probabilistic seismic‐hazard analysis (PSHA). This is especially so at the low annual exceedance frequencies considered for nuclear facilities; in these cases, even small reductions in sigma can have a marked effect on the hazard estimates. Proper separation and quantification of aleatory variability and epistemic uncertainty can lead to defensible reductions in sigma. One such approach is the single‐station sigma concept, which removes that part of sigma corresponding to repeatable site‐specific effects. However, the site‐to‐site component must then be constrained by site‐specific measurements or else modeled as epistemic uncertainty and incorporated into the modeling of site effects. The practical application of the single‐station sigma concept, including the characterization of the dynamic properties of the site and the incorporation of site‐response effects into the hazard calculations, is illustrated for a PSHA conducted at a rock site under consideration for the potential construction of a nuclear power plant.
Akkar S, Sandıkkaya MA, Bommer JJ, 2014, Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East, Bulletin of Earthquake Engineering, Vol: 12, Pages: 359-387, ISSN: 1570-761X
This article presents the latest generation of ground-motion models for the prediction of elastic response (pseudo-) spectral accelerations, as well as peak ground acceleration and velocity, derived using pan-European databases. The models present a number of novelties with respect to previous generations of models (Ambraseys et al. in Earthq Eng Struct Dyn 25:371–400, 1996, Bull Earthq Eng 3:1–53, 2005; Bommer et al. in Bull Earthq Eng 1:171–203, 2003; Akkar and Bommer in Seismol Res Lett 81:195–206, 2010), namely: inclusion of a nonlinear site amplification function that is a function of V S30 and reference peak ground acceleration on rock; extension of the magnitude range of applicability of the model down to M w 4; extension of the distance range of applicability out to 200 km; extension to shorter and longer periods (down to 0.01 s and up to 4 s); and consistent models for both point-source (epicentral, R epi, and hypocentral distance, R hyp) and finite-fault (distance to the surface projection of the rupture, R JB) distance metrics. In addition, data from more than 1.5 times as many earthquakes, compared to previous pan-European models, have been used, leading to regressions based on approximately twice as many records in total. The metadata of these records have been carefully compiled and reappraised in recent European projects. These improvements lead to more robust ground-motion prediction equations than have previously been published for shallow (focal depths less than 30 km) crustal earthquakes in Europe and the Middle East. We conclude with suggestions for the application of the equations to seismic hazard assessments in Europe and the Middle East within a logic-tree framework to capture epistemic uncertainty.
Akkar S, Sandykkaya MA, Bommer JJ, 2014, Erratum to: Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East, Bulletin of Earthquake Engineering, Vol: 12, Pages: 389-390, ISSN: 1570-761X
Douglas J, Akkar S, Ameri G, et al., 2014, Comparisons among the five ground-motion models developed using RESORCE for the prediction of response spectral accelerations due to earthquakes in Europe and the Middle East, BULLETIN OF EARTHQUAKE ENGINEERING, Vol: 12, Pages: 341-358, ISSN: 1570-761X
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- Citations: 60
Bommer JJ, Strasser FO, Pagani M, et al., 2013, Quality Assurance for Logic-Tree Implementation in Probabilistic Seismic-Hazard Analysis for Nuclear Applications: A Practical Example, SEISMOLOGICAL RESEARCH LETTERS, Vol: 84, Pages: 938-945, ISSN: 0895-0695
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- Citations: 19
Midzi V, Bommer JJ, Strasser FO, et al., 2013, An intensity database for earthquakes in South Africa from 1912 to 2011, JOURNAL OF SEISMOLOGY, Vol: 17, Pages: 1183-1205, ISSN: 1383-4649
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- Citations: 24
Bommer JJ, 2012, Challenges of Building Logic Trees for Probabilistic Seismic Hazard Analysis, EARTHQUAKE SPECTRA, Vol: 28, Pages: 1723-1735, ISSN: 8755-2930
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- Citations: 66
Coppersmith KJ, Bommer JJ, 2012, Use of the SSHAC methodology within regulated environments: Cost-effective application for seismic characterization at multiple sites, NUCLEAR ENGINEERING AND DESIGN, Vol: 245, Pages: 233-240, ISSN: 0029-5493
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- Citations: 7
Bommer JJ, Akkar S, Drouet S, 2012, Extending ground-motion prediction equations for spectral accelerations to higher response frequencies, BULLETIN OF EARTHQUAKE ENGINEERING, Vol: 10, Pages: 379-399, ISSN: 1570-761X
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- Citations: 10
Arango MC, Strasser FO, Bommer JJ, et al., 2012, An Evaluation of the Applicability of Current Ground-Motion Models to the South and Central American Subduction Zones, BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA, Vol: 102, Pages: 143-168, ISSN: 0037-1106
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- Citations: 20
Bommer JJ, Akkar S, 2012, Consistent Source-to-Site Distance Metrics in Ground-Motion Prediction Equations and Seismic Source Models for PSHA, EARTHQUAKE SPECTRA, Vol: 28, Pages: 1-15, ISSN: 8755-2930
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- Citations: 55
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