{
  "abstract": "Post-event building assessment requires linking observed physical damage to its consequences for safety, habitability, functionality, and recovery. Yet post-disaster evidence is often heterogeneous, incomplete, and distributed across images and reconnaissance reports, while recovery models typically require structured engineering inputs. This study develops a multimodal engineering Graph Retrieval-Augmented Generation (GraphRAG) framework that connects post-wind-event damage evidence to physical consequences, building-condition states, recovery actions, and downtime. Image- and text-based evidence is transformed into a provenance-preserving, component-level representation distinguishing confirmed damage, explicit negative evidence, unresolved conditions, and temporary measures. Graph-aligned retrieval combines comparable building scenarios with explicit engineering relationships, while compatibility, contradiction, evidence-precedence, and abstention mechanisms constrain inference under partial observability. Recovery actions are derived from supported damage-consequence relationships, and downtime uncertainty is propagated through an action-dependency network using Monte Carlo simulation. The framework is demonstrated for tornado-affected low-rise residential buildings using reconnaissance and image-based evidence. Comparisons with BaselineRAG and Structured Baseline RAG show improved agreement for key building-condition and recovery outcomes, together with traceable engineering reasoning and preserved evidence provenance. Ablation analyses demonstrate the contributions of engineering context, evidence safeguards, and graph-path traversal. The results support transparent, recovery-oriented assessment from incomplete multimodal post-event evidence.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.28216",
  "author_total": 3,
  "authors": [
    {
      "name": "Seyedeh Fatemeh Mirfakhar"
    },
    {
      "name": "Reda Snaiki"
    },
    {
      "name": "Rocio Lilen Segura"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/449e9pf3bzbq4.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.28216",
  "fulltext_url": null,
  "id": "449e9pf3bzbq4",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.28216",
  "language": null,
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.SE"
    ],
    [
      "arxiv",
      "physics.app-ph"
    ],
    [
      "openalex",
      "2205|Construction Engineering and Safety"
    ]
  ],
  "openalex": "W7223142921",
  "pdf_url": "https://arxiv.org/pdf/2610.28216",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-20",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/449e9pf3bzbq4.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:34:04Z",
      "native_id": "2610.28216",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.28216"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.app-ph",
      "subfield": "applied-instrumentation"
    }
  ],
  "title": "A Multimodal Engineering GraphRAG Framework for Post-Wind-Event Building Assessment and Recovery Inference",
  "title_text": "A Multimodal Engineering GraphRAG Framework for Post-Wind-Event Building Assessment and Recovery Inference",
  "type": "preprint",
  "updated_at": "2026-10-30T12:34:04Z",
  "url": "https://research.draconitic.com/paper/449e9pf3bzbq4",
  "venue": "arXiv",
  "versions": []
}