Academic Journal
Q1Engineering with Computers
About Engineering with Computers
Engineering with Computers is a scholarly journal published by Springer London. SCImago 2025 lists it in Q1, with an SJR of 0.976 and H-index of 99.
Coverage: 1985-2026. Research categories: Computer Science Applications (Q1); Engineering (miscellaneous) (Q1); Modeling and Simulation (Q1); Software (Q1).
Verified field sources
- Journal Impact Factor: 4.1 — Official source; checked 2026-10-03. Journal metric year and editorial leadership as listed on the Springer Nature journal homepage.
- Impact Factor year: 2025 — Official source; checked 2026-10-03. Journal metric year and editorial leadership as listed on the Springer Nature journal homepage.
- Editor(s): Prof. Yongjie (Jessica) Zhang PhD (Editor-in-Chief) — Official source; checked 2026-10-03. Journal metric year and editorial leadership as listed on the Springer Nature journal homepage.
Source-backed journal facts
Topics in published research
Numerical methods in engineering; Computational Geometry and Mesh Generation; Composite Structure Analysis and Optimization; Advanced Numerical Analysis Techniques; Advanced Multi-Objective Optimization Algorithms; Manufacturing Process and Optimization.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Reported open-access list prices
2,190.00 USD; 3,090.00 EUR
APC list prices reported by OpenAlex, which obtains this information from DOAJ. Confirm current charges, taxes, waivers and eligibility with the publisher; this is not a fee quotation.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
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Yaser Shahbazi, Mahsa Abdkarimi
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Hooman Fatoorehchi, Philip L. Fosbøl
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Xiao Xiao, Fehmi Cirak
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Jeremy A. McCulloch, Scott L. Delp, Ellen Kuhl
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2026-10 · DOI: 10.1007/s00366-026-02400-7A novel sparse-grid-integrated moment method for estimating augmented failure probability global sensitivity
Zhuangbo Chen, Zhenzhou Lu
2026-10 · DOI: 10.1007/s00366-026-02403-4A high-order wavelet-based collocation method for coupled nonlinear singular differential systems with enhanced accuracy and convergence analysis
Ankita Yadav, Narendra Kumar, Amit K. Verma
2026-10 · DOI: 10.1007/s00366-026-02402-5A novel surrogate model for optimizing lattice for desired force-displacement response
Akshay Kumar, Saketh Sridhara, Krishnan Suresh
2026-10 · DOI: 10.1007/s00366-026-02407-0Size-dependent bending, buckling, and vibration behavior of a nanobeam with periodically distributed holes via a PINN-based method
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2026-10 · DOI: 10.1007/s00366-026-02405-2A survey of AI methods for geometry preparation and mesh generation in engineering simulation
Steven Owen, Nathan Brown, Nikos Chrisochoides, Rao Garimella et al.
2026-10 · DOI: 10.1007/s00366-026-02379-1An efficient isogeometric finite element method for unsteady incompressible viscous flows
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Vikrant Pratap, Bharat B. Tripathi
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Ryan T. Black, Steve A. Maas, Wensi Wu, Jalaj Maheshwari et al.
2026-10 · DOI: 10.1007/s00366-026-02371-9QUEENS: an open-source Python framework for solver-independent analyses of large-scale computational models – from parameter studies and identification, sensitivity analysis, surrogates, optimization, (Bayesian) forward and backward uncertainty quantification to digital twinning
Jonas Biehler, Jonas Nitzler, Sebastian Brandstaeter, Maximilian Dinkel et al.
2026-10 · DOI: 10.1007/s00366-026-02337-xMulti-fidelity shape optimization of hydrogen burners
Raphael Strickling, Faizan Habib Vance, Arne Scholtissek
2026-10 · DOI: 10.1007/s00366-026-02395-1Learning 1D stress resultant plasticity from 2D continuum plasticity: a physics-informed neural network model reduction approach
Emin Kocbay
2026-10 · DOI: 10.1007/s00366-026-02385-3MIFE-ONet: a multiscale information fusion feature equalization operator network for supercritical airfoil surface flow field prediction
Anqiang Tan, Jinhong Wu, Rongxi Zhang, Xufeng Huang et al.
2026-10 · DOI: 10.1007/s00366-026-02376-4A multi-grid, single-mesh online learning framework for efficient large-scale topology optimization
Kangjie Li, Wenjing Ye
2026-10 · DOI: 10.1007/s00366-026-02383-5Reviews
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October 2, 2026 at 8:26 pm
October 2, 2026