{
  "abstract": "Solar-driven biomass pyrolysis combines renewable feedstock with solar heat, but variable irradiation challenges reactor performance. This study evaluates whether a silicon carbide (SiC) foam-enhanced packed-bed reactor can maintain favorable performance across an empirical distribution of solar input and identifies the foam porosity and carrier-gas nominal residence time best suited to that variability. An 85-case computational fluid dynamics dataset was used to train machine-learning surrogate models linking solar input, foam porosity, and nominal residence time to effective conversion rate (ECR) and volatile energy fraction (VEF). Multi-objective optimization identified six candidate designs, which were evaluated using Monte Carlo samples drawn from five years of Zurich irradiance data and bagging-based surrogate predictions. Results show that pronounced performance sensitivity was concentrated in the lowest 20% of the empirical solar-input distribution. Under conservative estimates, all six candidates had a joint probability above 50% of achieving ECR > 70% and VEF > 80%. The combination of foam porosity 0.90 and nominal residence time 60 s achieved the highest joint probability (61%). These findings demonstrate that a fixed SiC foam reactor can maintain favorable performance under variable solar input and provide practical guidance for uncertainty-aware reactor design.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Yang Liu"
    },
    {
      "name": "Ruming Pan"
    },
    {
      "name": "Renaud Ansart"
    },
    {
      "name": "Gerald Debenest"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/frpxcceqvtm2s.bib",
  "cited_by": 0,
  "doi": "10.1016/j.egyai.2026.100947",
  "fulltext_url": null,
  "id": "frpxcceqvtm2s",
  "issns": [
    "2666-5468"
  ],
  "landing_url": "https://hal.science/hal-05837032v1",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.phys"
    ],
    [
      "hal",
      "1.phys.meca"
    ],
    [
      "hal",
      "2.phys.meca.mefl"
    ],
    [
      "openalex",
      "2204|Thermochemical Biomass Conversion Processes"
    ]
  ],
  "openalex": "W7223098652",
  "pdf_url": "https://hal.science/hal-05837032/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-23",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/frpxcceqvtm2s.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:01Z",
      "native_id": "hal-05837032",
      "source": "hal",
      "url": "https://hal.science/hal-05837032v1"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "hal:2.phys.meca.mefl",
      "subfield": "fluid-dynamics"
    }
  ],
  "title": "Silicon carbide foam packed-bed reactor for solar-driven biomass pyrolysis: Robust design under variable solar input",
  "title_text": "Silicon carbide foam packed-bed reactor for solar-driven biomass pyrolysis: Robust design under variable solar input",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:01Z",
  "url": "https://research.draconitic.com/paper/frpxcceqvtm2s",
  "venue": "Energy and AI",
  "versions": []
}