{
  "abstract": "Integrating sustainable biodiesel blends into variable compression ratio (VCR) diesel engines significantly alters combustion dynamics and structural vibrations. The present study introduces a Bayesian optimized 1D convolutional neural network-long-short-term memory (CNN-LSTM) deep learning framework designed for optimizing the multiaxis engine vibrations. The predictive architecture processes a six-parameter input matrix encompassing engine load, compression ratio (CR), and critical thermophysical fuel properties. A precise evaluation demonstrated the superior fidelity of the hybrid network, achieving up to a coefficient of determination (R2) of 0.985 and a root mean square error (RMSE) of 0.288 m/s2, substantially outperforming optimized support vector machine (SVM) and multilayer perceptron (MLP) benchmarks. Multiaxis spatial stability was visually confirmed using Taylor diagrams, while a 3000-iteration bootstrap analysis validated algorithmic robustness within a narrow 95% confidence interval (0.38–0.79 m/s2). Permutation feature importance and SHapley Additive exPlanations (SHAP) analysis clarified the thermodynamic decision-making process, revealing that elevated engine load and CR intensify mechanical ringing, whereas the higher density and viscosity of biodiesel blends act as natural vibration dampeners. High-resolution contour maps generated through systematic response surface mapping provided precise predictive optimization surfaces. Deploying this advanced methodology establishes a highly reliable, cost-effective virtual calibration tool for next-generation biodiesel-fueled engines, eliminating the necessity for exhaustive physical testing.",
  "abstract_shown": true,
  "affiliations": [
    "Cukurova University , , ,"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Ihsan Uluocak",
      "orcid": "0000-0002-0030-7833"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dkwktqfsr1tcm.bib",
  "cited_by": 0,
  "doi": "10.1021/acsomega.6c08418",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13717663/?tool=EBI",
  "id": "dkwktqfsr1tcm",
  "issns": [
    "2470-1343"
  ],
  "landing_url": "https://pubs.acs.org/acsodf/article/11/42/65616/5452989/Predictive-Optimization-of-Vibrations-in-a",
  "language": "eng",
  "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": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "2204|Biodiesel Production and Applications"
    ]
  ],
  "openalex": "W7222598400",
  "pdf_url": "https://pubs.acs.org/doi/pdf/10.1021/acsomega.6c08418",
  "pmcid": "PMC13717663",
  "pmid": "42959595",
  "published": "2026-10-16",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/dkwktqfsr1tcm.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:39Z",
      "native_id": "10.1021/acsomega.6c08418",
      "source": "crossref",
      "url": "https://pubs.acs.org/acsodf/article/11/42/65616/5452989/Predictive-Optimization-of-Vibrations-in-a"
    },
    {
      "first_seen": "2026-10-31T00:20:37Z",
      "native_id": "PMC:PMC13717663",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13717663"
    },
    {
      "first_seen": "2026-11-01T00:20:50Z",
      "native_id": "MED:42959595",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42959595"
    },
    {
      "first_seen": "2026-11-02T12:21:56Z",
      "native_id": "PMC13717663",
      "source": "pmc",
      "url": "https://doi.org/10.1021/acsomega.6c08418"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "issn:2470-1343",
      "subfield": "general"
    }
  ],
  "title": "Predictive Optimization of Vibrations in a Biodiesel-Fueled Variable Compression Ratio Engine Using BO-CNN-LSTM",
  "title_text": "Predictive Optimization of Vibrations in a Biodiesel-Fueled Variable Compression Ratio Engine Using BO-CNN-LSTM",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T12:21:56Z",
  "url": "https://research.draconitic.com/paper/dkwktqfsr1tcm",
  "venue": "ACS Omega",
  "versions": []
}