Latest Articles for Computational Modeling

This article explains how scientists study key ions in water using computational methods.

New methods improve simulations of active matter by reducing density fluctuations.

An automated approach enhances efficiency and accuracy in simulating porous materials.

Introducing a framework for studying complex biological interactions using optimal transport theory.

Study reveals factors affecting single-layer GCN's performance on various data models.

Examining how spiral waves influence brain activity and cognitive functions.

New methods improve understanding of poroelastic materials in biological tissues.

New methods improve modeling of solar sound waves while saving computational resources.

A new method improves surrogate modeling accuracy using physical principles.

New methods enhance analysis of aqueous sulfuric acid using machine learning techniques.

The new Discrete Direct Deconvolution Model enhances turbulence simulation accuracy.

A new approach transforms how we model fluid and solid interactions.

This study develops new methods for analyzing interactions in mean field games.

Improving atmospheric predictions through innovative modeling techniques.

An integrated approach to study phase transitions with uncertainties and injection boundaries.

Research sheds light on aluminum's properties in extreme conditions.

A new method improves simulations of two-phase flows with mass and heat transfer.

Exploring the interaction of fractional Laplacians under Neumann conditions and their implications.

This article discusses efficient methods for estimating parameters in agent-based models.

Exploring the effects of self-interacting dark matter on galaxy structures.

Discover how new methods improve efficiency in complex scientific problems.

Exploring the connection between neural networks and cellular automata through many-valued logic.

Examining how computational methods improve understanding of nickel-based superalloys.

Study investigates the impact of AlphaFold 2 on protein structure determination through Molecular Replacement.

New nuclear network improves supernova explosion simulations with greater accuracy.

A new approach using graph neural networks for efficient multiscale material simulations.

A new wall-model improves turbulent flow predictions with reduced computational costs.

New models enhance hydrogel simulations for bioprinting applications.

Using machine learning to model and predict spins in magnetic materials.

A look at how blood flow models aid in heart disease treatment.

Investigating how neuromodulation enhances recurrent neural network performance.

Insights into the behavior of turbulent fluid dynamics and their implications.

New datasets and machine learning techniques enhance understanding of high-entropy materials.

New model improves gas flow simulations in complex conditions.

Machine learning improves predictions of band gaps, enhancing material electronic property insights.

A new approach improves atomic interaction descriptors with geodesic distance.

New methods improve efficiency in simulating complex materials.

A new approach enhances turbulent flow simulations using machine learning techniques.

A new method enhances predictions for heat transfer in materials using mixed modeling techniques.

This study focuses on achieving reliable majority consensus in microbial populations.