Academic Journal
Q1Computers and Fluids
About Computers and Fluids
About Computers and Fluids
Computers and Fluids is a peer-reviewed scholarly journal published by Elsevier Ltd (United Kingdom). It focuses on Q1. Publication coverage spans 1973-2026.
Key indicators: ISSN 0045-7930; H-index 144.
Understanding This Journal's Metrics
Journal metrics help researchers assess fit, but they must be interpreted in context:
- H-index (144): Exceptionally high — 144 articles have each been cited at least 144 times. This indicates deep, sustained influence in the field.
Publishing in Computers and Fluids
An established venue in its field. The journal welcomes solid, well-executed research. Ensure your manuscript fits the stated scope and follows author guidelines carefully.
- Scope fit: Confirm your research aligns with Q1. Off-scope manuscripts are typically desk-rejected quickly.
- Author guidelines: Follow formatting, reference style, and article-type requirements exactly — non-compliant manuscripts may be returned without review.
- Submission: Submit via the official journal website.
Is This Journal Right for Your Paper?
- Audience match: Will the journal's readers cite and build on your findings?
- Timeline: Higher-tier journals mean longer review and higher rejection risk. Balance prestige against your schedule.
- Indexing: Confirm indexing in Web of Science, Scopus, and PubMed (if biomedical) meets your institutional requirements.
- Open access needs: Check funder mandates and whether the journal offers compliant OA options.
Frequently Asked Questions
What is the ISSN of Computers and Fluids?
0045-7930.
Who publishes Computers and Fluids?
Elsevier Ltd.
What are Computers and Fluids's metrics?
H-index 144.
Where do I submit to Computers and Fluids?
Via the official website.
Is Computers and Fluids peer-reviewed?
Yes — it is a peer-reviewed scholarly journal indexed in major academic databases.
Source-backed journal facts
Topics in published research
Computational Fluid Dynamics and Aerodynamics; Fluid Dynamics and Turbulent Flows; Lattice Boltzmann Simulation Studies; Advanced Numerical Methods in Computational Mathematics; Fluid Dynamics and Vibration Analysis; Gas Dynamics and Kinetic Theory.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Reported open-access list prices
3,700.00 USD; 3,460.00 EUR; 2,960.00 GBP; 458,910.00 JPY
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.
Coupled level-set lattice Boltzmann method on adaptive Cartesian grids
Julian Vorspohl, Yuxing Peng, Matthias Meinke, Dominik Krug et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107297Physics-informed neural networks for inviscid flows over axisymmetric projectiles
Miguel A. Escudero, Benoît G. Marinus, Karthik Depuru-Mohan
2026-12 · DOI: 10.1016/j.compfluid.2026.107302Consideration on the entropically-damped artificial-compressibility method
Jaeyoung Jung, Marco Giometto
2026-12 · DOI: 10.1016/j.compfluid.2026.107301A physics-informed augmentation of the Spalart-Allmaras model for aerodynamic flows informed by delayed detached eddy simulation
Wei Sun, Haijin Yan, Zhouteng Ye, Feng Feng et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107294An adaptive wavelet transform convolutional neural network embedded multigrid method for elliptic partial differential equations in fluid mechanics
Ruilin Chen, Xiongliang Yao, Longquan Sun, Guihui Ma et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107316Development of data-driven Bayesian shape optimisation framework for reverse flow reduction over a rounded ramp
Aan Yudianto, Saleh Rezaeiravesh, Ajay Harish, Mark Quinn et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107303Adjoint-based shape optimization of a ship hull using a Conditional Variational Autoencoder (CVAE) assisted propulsion surrogate model
Moloud Arian Maram, Georgios Bletsos, Thanh Tung Nguyen, Ahmed Hassan et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107284Improved discrete unified gas kinetic scheme for continuum compressible flows with implicit flux reconstruction
Yinghao Ma, Ziyang Xin, Zhaoli Guo
2026-12 · DOI: 10.1016/j.compfluid.2026.107318A GPU framework for computing multiscale triadic interactions in turbulent flows
Gustavo Lopes, Marco Rosenzweig, Pawel Jan Przytarski, Richard Sandberg et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107298A Discontinuous Galerkin method enhanced via compact Smoothness-Increasing-Accuracy-Conserving (SIAC) reconstruction
Lyes Tezkratt, Jean-Baptiste Chapelier, Robert M. Kirby, Eric Lamballais et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107299A cost-effective pseudo-spectral scheme for high-Reynolds-number channel-flow DNS: Accuracy, effective resolution, and computational cost under memory constraints
Yoshinobu Yamamoto, Yoshiyuki Tsuji
2026-12 · DOI: 10.1016/j.compfluid.2026.107304A filtered recursive regularization collision model for the lattice Boltzmann method in high-Reynolds-number flows
Chenghao Li, Jie Chen, Yongliang Feng
2026-12 · DOI: 10.1016/j.compfluid.2026.107317Simulations of particle-laden flows with large dispersed-phase size disparities using scalable parallel adaptive methods
Linfeng Jiang, Enrico Calzavarini, Dominik Krug
2026-12 · DOI: 10.1016/j.compfluid.2026.107305Machine-learning-enhanced discretize-then-project reduced-order modeling of turbulent flows on collocated grids
Nadim Rooholamin, Kabir Bakhshaei, Giovanni Stabile
2026-12 · DOI: 10.1016/j.compfluid.2026.107315A well-balanced local radial basis functions collocation method for single-layer and two-layer shallow water flows with rainfall and infiltration
Nafea Lachhab, Alia Al-Ghosoun, Mohammed Seaid, Mofdi El-Amrani et al.
2026-12 · DOI: 10.1016/j.compfluid.2026.107300Reynolds-number-adaptive symbolic regression for explainable wall-bounded turbulence modelling
Apostolos Palasis, Dimitrios Angelis, Filippos Sofos
2026-11 · DOI: 10.1016/j.compfluid.2026.107283On-the-fly algorithm for Dynamic Mode Decomposition using Incremental Singular Value Decomposition and Total Least Squares
Daiki Matsumoto, Christian F. Janßen, Thomas Indinger
2026-11 · DOI: 10.1016/j.compfluid.2026.107265A semi-implicit structure-preserving nonstaggered central scheme for shallow water-Exner equations with wet/dry interfaces and a Manning friction on triangles
Zige Wei, Jian Dong, Xu Qian, Xingpo Qiu et al.
2026-11 · DOI: 10.1016/j.compfluid.2026.107282Leveraging modal structure similarity for simulation of spatially evolving wakes
Divyanshu Gola, Sutanu Sarkar
2026-11 · DOI: 10.1016/j.compfluid.2026.107272Assessment of gradient-based reconstruction and artificial diffusivity methods in simulating high-speed compressible flows
Ritu Raj Kumar, Shivam Saini, Nagabhushana Rao Vadlamani, Amareshwara Sainadh Chamarthi et al.
2026-11 · DOI: 10.1016/j.compfluid.2026.107275Reviews
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Version History
October 9, 2026 at 10:13 pm
October 2, 2026