Modeling Flow Pattern and Evolution of Meandering Channels with a Nonlinear Model

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We study the drainage of a viscous liquid film coating the outside of a solid horizontal cylinder, where gravity acts vertically. We focus on the limit of large Ohnesorge numbers Oh, where inertia is negligible compared to viscous effects. We first study t ...

Realand imaginary -time quantum state evolutions are crucial in physics and chemistry for exploring quantum dynamics, preparing ground states, and computing thermodynamic observables. On near -term devices, variational quantum time evolution is a promising ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

When two objects slide against each other, wear and friction occur at their interface. The accumulation of wear forms what is commonly referred to as a ``third-body''. Understanding third-body evolution has significant applications in industry, where contr ...

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

The optical domain presents potential avenues for enhancing both computing and communication due to its inherent properties of bandwidth, parallelism, and energy efficiency. This research focuses on harnessing 3-Dimensional (3D) diffractive optics for nove ...

In high elevation Alpine areas, characterised by high snow accumulation and radiation-driven melt processes, the formation of peculiar ablation features called sun cups can be observed. Sun cups likely influence the energy and mass balance of the wet snowp ...

We present a simple, vertically-explicit 2D model of river bank erosion that also takes the effect of sediment stabilization by plant roots into account. The model is solved in quasi-analytical form for an exemplary non-stationary hydrograph temporal signa ...

Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...

The prediction of trajectories of buoyancy-driven objects immersed in a viscous fluid is a key problem in fluid dynamics. Simple-shaped objects, such as disks, present a great variety of trajectories, ranging from zig-zag to tumbling and chaotic motions. Y ...

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

Purpose: The purpose of this study was to describe, validate, and compare the contrast sensitivity functions (CSFs) acquired with the novel quick CSF (qCSF) method from patients with early and intermediate age-related macular degeneration (eAMD and iAMD) a ...

This thesis presents advancements in the understanding of the plasma conditions leading to the excitation and saturation of the Edge Harmonic Oscillations (EHOs) observed during QH-mode operation in tokamak plasmas. Such operations represent a safer altern ...

Photoplethysmography (PPG) is a widely emerging method to assess vascular health in humans. The origins of the signal of reflective PPG on peripheral arteries have not been thoroughly investigated. We aimed to identify and quantify the optical and biomecha ...

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

Riverbeds represent the habitat of numerous aquatic species. Exchanges between the groundwater, the hyporheic zone and the surface flow are also essential for river ecosystems. Fine sediment transported by rivers deposits inside or on top of the bed and mo ...

This article presents the outcomes of a large project towards the investigation of the lateral performance of full-scale industrialized light-frame wooden diaphragms. 10 full-scale diaphragms of 3.6 m by 2.4 m were tested under in-plane lateral loading (mo ...

The organic Rankine cycle (ORC) system is among the technologies applied to exploit waste heat in vehicles. Since common organic fluids have lower latent heat than water, higher mass flow rates are required to convert the same waste heat, considerably incr ...

Modeling Flow Pattern and Evolution of Meandering Channels with a Nonlinear Model

Chattez avec Graph Search

Stability of a liquid layer draining around a horizontal cylinder: Interplay of capillary and gravity forces

Variational quantum time evolution without the quantum geometric tensor

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Adaptive projected variational quantum dynamics

Modeling friction and wear using an adaptive discrete-continuum coupling

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

3D diffractive optics for linear interconnects and nonlinear processing

Influence of sun cups on surface albedo of wet Alpine snowpack

Mechanistic 2D flow-erosion modelling of vegetated river banks

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Permeability sets the linear path instability of buoyancy-driven disks

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Evaluating contrast sensitivity in early and intermediate age-related Macular Degeneration with the Quick Contrast Sensitivity Function

Exploration of the parameter space for the excitation and saturation of Edge Harmonic Oscillations

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

The inductive bias of deep learning: Connecting weights and functions

Clogging of riverbed substrates by fine sediment

Testing and nonlinear modelling of industrialized light-frame wooden diaphragms including optimized nailing and nonstructural sheathing

Small-scale turbopumps for waste heat recovery applications based on an organic Rankine cycle: a study from pre-design to experimental validation