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Alfi Rahman
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+6281265919198
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TDMRC Building Universitas Syiah Kuala Jl. Hamzah Fansuri No.8, Kopelma Darussalam, Kecamatan Syiah Kuala Kota Banda Aceh Aceh 23111
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International Journal of Disaster Management
ISSN : 2808439X     EISSN : 25274341     DOI : https://doi.org/10.24815/ijdm.v5i1.25189
The International Journal of Disaster Management (IJDM) is addressing the results of applied research to advance the knowledge in minimizing the potential impact of threats or warnings caused by natural or man-made disasters in a way to reduce the exposure of human activities to risks. IJDM is a journal for researchers, practitioners and policy makers from various disciplines to publish the knowledge advancement on the dynamic relationship between human and disaster, local indigenous knowledge as well as the strategies and technology applied in different elements of the disaster management cycle, including in the response, recovery, reconstruction, prevention, mitigation, and preparedness. The journal scope covers a multi-disciplinary approach in the following key topics: Lessons learned on disaster management from past disasters Technology application for disaster response, reconstruction, and mitigation Management of early response, reconstruction, and recovery Disaster education and strategy to increase awareness and preparedness Post-disaster recovery process and strategies Governance in disaster management Early-warning system, technology, and strategies Knowledge Management for Disaster Risk Reduction GIS and Remote Sensing for Disaster Management Community-Based Disaster Management Climate Risk Management Environmental Aspect in Disaster Natural Hazards coupled with Technological Failures Children Protection and Participation in Disaster Management Local and Indigenous Knowledge for Disaster Risk Reduction Numerical Analysis for Disaster Management Supports
Articles 1 Documents
Search results for , issue "Vol 8, No 3 (2025)" : 1 Documents clear
Surrogate-based reduced-order modeling of tsunami inundation Sihombing, Fritz
International Journal of Disaster Management Vol 8, No 3 (2025)
Publisher : TDMRC, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/ijdm.v8i3.46204

Abstract

Tsunami impact assessment must be conducted rapidly and accurately to ensure adequate emergency risk responses and management, allowing the city to recover swiftly. Significant progress has been made in numerical analysis techniques, yielding more precise assessments and predictions of tsunami forces. However, these advancements come with high computational costs, potentially limiting their applicability for uncertainty quantification and probabilistic risk analysis. Reduced-order modeling is a numerical approach that seeks to find a model in a lower-dimensional space while still representing the physical features of the full-order model with acceptable accuracy. Proper orthogonal decomposition is one such reduced-order modeling method, widely used in various engineering fields. This study proposes a framework to estimate tsunami propagation and land inundation using a surrogate-based reduced-order modeling method. A neural network is employed as the surrogate model. Two error measures are used to analyze its performance: the root mean square error and the average relative error of projection. Results indicate that the root mean square error decreases as more bases are used. However, the average relative error of projection in the online phase does not significantly decrease with an increased number of bases, suggesting that a moderate number of basesbetween five and tenis sufficient for the proposed framework.

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