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Progressive transfer learning for advancing machine learning-based reduced-order modeling
To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for...
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VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems
Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties....
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Construction of a reduced-order model based on tensor decomposition and its application to airbag deployment simulations
We present a construction method for reduced-order models (ROMs) to explore alternatives to numerical simulations. The proposed method can...
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Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems
A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures...
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Enhancing high-fidelity nonlinear solver with reduced order model
We propose the use of reduced order modeling (ROM) to reduce the computational cost and improve the convergence rate of nonlinear solvers of full...
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Subsurface temperature estimates from a Regional Ocean Modelling System (ROMS) reanalysis provide accurate coral heat stress indices across the Main Hawaiian Islands
As ocean temperatures continue to rise, coral bleaching events around the globe are becoming stronger and more frequent. High-resolution temperature...
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β-Variational autoencoders and transformers for reduced-order modelling of fluid flows
Variational autoencoder architectures have the potential to develop reduced-order models for chaotic fluid flows. We propose a method for learning...
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Generative adversarial reduced order modelling
In this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to...
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Modeling advanced air mobility aircraft in data-driven reduced order realistic urban winds
The concept of Advanced Air Mobility involves utilizing cutting-edge transportation platforms to transport passengers and cargo efficiently over...
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Physics-informed neural ODE (PINODE): embedding physics into models using collocation points
Building reduced-order models (ROMs) is essential for efficient forecasting and control of complex dynamical systems. Recently, autoencoder-based...
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Task-oriented machine learning surrogates for tip** points of agent-based models
We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for...
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Reduced order modelling and experimental validation of a MEMS gyroscope test-structure exhibiting 1:2 internal resonance
Micro-Electro-Mechanical Systems revolutionized the consumer market for their small dimensions, high performances and low costs. In recent years, the...
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The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study
The indirect contribution of multiple sclerosis (MS) relapses to disability worsening outcomes, and vice-versa, remains unclear. Disease modifying...
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Surrogate models provide new insights on metrics based on blood flow for the assessment of left ventricular function
Recent developments on the grading of cardiac pathologies suggest flow-related metrics for a deeper evaluation of cardiac function. Blood flow...
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On the evidence of helico-spiralling recirculation within coherent cores of eddies using Lagrangian approach
Oceanic eddies exhibit remarkable coherence and longevity compared to other transient features in the surrounding flow. They possess the ability to...
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Urine metabolomics unravel the effects of short-term dietary interventions on oxidative stress and inflammation: a randomized controlled crossover trial
Dietary biomarkers in urine remain elusive when evaluating diet-induced oxidative stress and inflammation. In our previous study, we conducted a...
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Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys
Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which...
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Widespread global disparities between modelled and observed mid-depth ocean currents
The mid-depth ocean circulation is critically linked to actual changes in the long-term global climate system. However, in the past few decades,...
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Effect of ocean outfall discharge volume and dissolved inorganic nitrogen load on urban eutrophication outcomes in the Southern California Bight
Climate change is increasing drought severity worldwide. Ocean discharges of municipal wastewater are a target for potable water recycling. Potable...
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A comparison of the biomechanical properties of three different lumbar internal fixation methods in the treatment of lumbosacral spinal tuberculosis: finite element analysis
There are various internal fixation methods in treating lumbosacral spinal tuberculosis. The study compared the stability and stress distribution in...
