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  • Articles  (2,875)
  • 2020-2024  (2,875)
  • 2010-2014  (2)
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  • 2020  (2,875)
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  • 1
    Publication Date: 2024-07-05
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2024-07-05
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  • 3
    Publication Date: 2024-07-02
    Language: English
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  • 4
    Publication Date: 2024-07-02
    Language: English
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  • 5
    Publication Date: 2024-07-02
    Description: Understanding fracturing processes and the hydromechanical relation to induced seismicity is a key question for enhanced geothermal systems (EGS). Commonly massive fluid injection, predominately causing hydroshearing, are used in large-scale EGS but also hydraulic fracturing approaches were discussed. To evaluate the applicability of hydraulic fracturing techniques in EGS, six in situ, multistage hydraulic fracturing experiments with three different injection schemes were performed under controlled conditions in crystalline rock at the A¨ spo¨ Hard Rock Laboratory (Sweden). During the experiments the near-field ground motion was continuously recorded by 11 piezoelectric borehole sensors with a sampling rate of 1 MHz. The sensor network covered a volume of 30×30×30 m around a horizontal, 28-m-long injection borehole at a depth of 410 m. To extract and characterize massive, induced, high-frequency acoustic emission (AE) activity from continuous recordings, a semi-automated workflow was developed relying on full waveform based detection, classification and location procedures. The approach extended the AE catalogue from 196 triggered events in previous studies to more than 19 600 located AEs. The enhanced catalogue, for the first time, allows a detailed analysis of induced seismicity during single hydraulic fracturing experiments, including the individual fracturing stages and the comparison between injection schemes. Beside the detailed study of the spatio-temporal patterns, event clusters and the growth of seismic clouds, we estimate relative magnitudes and b-values of AEs for conventional, cyclic progressive and dynamic pulse injection schemes, the latter two being fatigue hydraulic fracturing techniques. While the conventional fracturing leads to AE patterns clustered in planar regions, indicating the generation of a single main fracture plane, the cyclic progressive injection scheme results in a more diffuse, cloud-like AE distribution, indicating the activation of a more complex fracture network. For a given amount of hydraulic energy (pressure multiplied by injected volume) pumped into the system, the cyclic progressive scheme is characterized by a lower rate of seismicity, lower maximum magnitudes and significantly larger b-values, implying an increased number of small events relative to the large ones. To our knowledge, this is the first direct comparison of high resolution seismicity in a mine-scale experiment induced by different hydraulic fracturing schemes.
    Language: English
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  • 6
    Publication Date: 2024-07-02
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  • 7
    Publication Date: 2024-07-01
    Description: Accelerograms are the primary source for characterizing strong ground motion. It is therefore of paramount interest to have high‐quality recordings free from any nonphysical contamination. Frequently, accelerograms are affected by baseline jumps and drifts, either related to the instrument and/or a major earthquake. In this work, I propose a correction method for these undesired baseline drifts based on segmented linear least squares. The algorithm operates on the integrated waveforms and combines all three instrument components to estimate a model that modifies the baseline to be at zero continuously. The procedure consists of two steps: first a suite of models with variable numbers of discontinuities is derived for all three instrument components. During this process, the number of discontinuities is reduced in a parsimonious way, for example, two very close discontinuities are merged into a single one. In the second step, the optimal model is selected on the basis of the Bayesian information criterion. I exemplify the application on synthetic waveforms with known discontinuities and on observed waveforms from a unified strong‐motion database of the Japan Meteorological Agency (JMA) and the National Research Institute for Earth Science and Disaster Prevention (NIED, Japan) networks for the major events of the 2016 Kumamoto earthquakes. After the baseline jump correction, the waveforms are furthermore corrected for displacement according to Wang et al. (2011). The resulting displacements are comparable to the Interferometric Synthetic Aperture Radar‐derived displacement estimates for the Kumamoto earthquake sequence.
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  • 8
    Publication Date: 2024-07-01
    Description: The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation–maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motionmodeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motionmodels using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastías and Montalva (2016) with ∼2400 records from 319 events in the Chilean subduction zone. Our GMMwith the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.
    Language: English
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  • 9
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    Naturalis Biodiversity Center
    In:  Blumea: Biodiversity, Evolution and Biogeography of Plants vol. 65 no. 2, pp. 121-125
    Publication Date: 2024-06-29
    Description: Peliosanthes macrophylla var. assamensis, a new variety from Behali Reserve Forest in Assam, Northeast India, is described with accompanying photos and relevant taxonomic data. It differs from var. macrophylla from Arunachal Pradesh and Sikkim, Northeast India, mainly by the staminal corona internally protruding near the middle (vs internally upright corona without a particular inward protrusion), shorter anthers somewhat divergent distally (vs nearly upright anthers), and longer, papillulate pistils exceeding the anthers (vs glabrous pistils not exceeding the anthers).
    Keywords: Plant Science ; Ecology ; Evolution ; Behavior and Systematics ; Asparagaceae ; Eastern Himalayas ; floral structure ; new variety ; Peliosanthes macrophylla ; taxonomy
    Repository Name: National Museum of Natural History, Netherlands
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  • 10
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    Naturalis Biodiversity Center
    In:  Blumea: Biodiversity, Evolution and Biogeography of Plants vol. 65 no. 1, pp. 83-85
    Publication Date: 2024-06-24
    Description: Maesa brevipedicellata, a new species of Maesa (Primulaceae-Maesoideae) from Papua New Guinea, is described and illustrated based on herbarium specimen observations. The collections of this species resemble M. rufovillosa and were previously determined as that species. Maesa brevipedicellata is unique with its selfsupporting habit, hispid hairs throughout and paniculate inflorescences with very short pedicels. This new species mainly differs from M. rufovillosa by the habit (tree/shrub in M. brevipedicellata vs climber in M. rufovillosa) and the inflorescence structure (panicles in M. brevipedicellata vs simple racemes in M. rufovillosa).
    Keywords: Plant Science ; Ecology ; Evolution ; Behavior and Systematics ; Ericales ; Maesa ; Malesia ; Myrsinaceae ; new species ; Papuasia ; taxonomy
    Repository Name: National Museum of Natural History, Netherlands
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