185 research outputs found
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Advances in artificial intelligence (AI) are fueling a new paradigm of
discoveries in natural sciences. Today, AI has started to advance natural
sciences by improving, accelerating, and enabling our understanding of natural
phenomena at a wide range of spatial and temporal scales, giving rise to a new
area of research known as AI for science (AI4Science). Being an emerging
research paradigm, AI4Science is unique in that it is an enormous and highly
interdisciplinary area. Thus, a unified and technical treatment of this field
is needed yet challenging. This work aims to provide a technically thorough
account of a subarea of AI4Science; namely, AI for quantum, atomistic, and
continuum systems. These areas aim at understanding the physical world from the
subatomic (wavefunctions and electron density), atomic (molecules, proteins,
materials, and interactions), to macro (fluids, climate, and subsurface) scales
and form an important subarea of AI4Science. A unique advantage of focusing on
these areas is that they largely share a common set of challenges, thereby
allowing a unified and foundational treatment. A key common challenge is how to
capture physics first principles, especially symmetries, in natural systems by
deep learning methods. We provide an in-depth yet intuitive account of
techniques to achieve equivariance to symmetry transformations. We also discuss
other common technical challenges, including explainability,
out-of-distribution generalization, knowledge transfer with foundation and
large language models, and uncertainty quantification. To facilitate learning
and education, we provide categorized lists of resources that we found to be
useful. We strive to be thorough and unified and hope this initial effort may
trigger more community interests and efforts to further advance AI4Science
From Perturbation to Ejecta: An Exploration of Mixing Regimes in the Blast-Driven Instability using High-speed Experiments and Hydrocode Simulations.
The fluid mixing caused by variable-density instabilities is important in a wide variety of scenarios from ocean mixing and astrophysical phenomena to nuclear fusion techniques and atomic weapons. This thesis explores the mixing resulting from a specific instability known as the Blast-Driven Instability (BDI). A novel experimental platform was designed and built with the intention of studying the BDI for this thesis. Using high speed experimental techniques, the first fully time-resolved observations of the BDI are made. An understanding of the general dynamics caused by the BDI are established. Analytical models used successfully in the literature are also shown to need modifications in order to capture the BDI behavior. These observations are then used to test two common mixing models (RANS and LES) in a digital-twin simulation designed to precisely match the novel facility used in the high-speed experiments. Simulation results are analyzed against the data and reasons for their agreement, or lack thereof, are explored in detail. The RANS and LES simulation are shown to capture the BDI development to the 0th order, at the least. The LES simulations are also shown to be crucially dependent upon the characterization of initial conditions. The experimental data is used in conjunction with the simulation results to explore the BDI's sensitivity to two key governing parameters. How changes in the governing parameters create qualitative and quantitative changes in the BDI's behavior is explored extensively. Incident blast-wave strength is shown to change the hydrodynamic time scale, while changes in density difference cause much more non-linear effects. Finally, various scaling attempts are investigated in an attempt to decipher how the mixing induced by the BDI can be explicitly linked to the governing parameters.Ph.D
Integrated Chemical Processes in Liquid Multiphase Systems
The essential principles of green chemistry are the use of renewable raw materials, highly efficient catalysts and green solvents linked with energy efficiency and process optimization in real-time. Experts from different fields show, how to examine all levels from the molecular elementary steps up to the design and operation of an entire plant for developing novel and efficient production processes
Etude et développement de micro-oscillateurs fluidiques pour le refroidissement de systèmes électroniques embarqués
Dans le domaine aéronautique, les contraintes sur le refroidissement sont multiples. L'efficacité d'un système de refroidissement ne se résume plus au simple taux de chaleur dissipée, mais englobe d'autres facteurs comme la compacité, le poids, la robustesse, le coût de maintenance ainsi que la durabilité. Une conception du système de refroidissement qui intègre ces aspects pourrait diminuer les coûts de fonctionnement, notamment la consommation de kérosène, et donc réduire l'impact environnemental du vol. La multiplication de systèmes embarqués dans l'aéronautique amène des contraintes supplémentaires pour leur refroidissement. Dans ce contexte, les actionneurs fluidiques présentent un fort potentiel. Ces travaux portent plus précisément, sur l'utilisation de jets pulsés produits par des oscillateurs fluidiques pour refroidir une surface chauffée. Plusieurs travaux sur les jets d'impact ont montré qu'il était possible d'améliorer la dissipation thermique en introduisant des pulsations dans l'écoulement. Il manque cependant un consensus dans la littérature autour de l'ensemble des conditions opératoires propices à l'amélioration des performances. D'où la nécessité de mener une étude sur l'écoulement produit par ces dispositifs fluidiques et le refroidissement qui en résulte. En amont de cela, il est nécessaire de se pencher sur l'effet de certains paramètres liés à la géométrie du l'oscillateur sur son mode de fonctionnement, en commençant par la caractérisation de l'écoulement pulsé produit par l'oscillateur. AK cette fin, un prototype d'oscillateur est réalisé en fabrication additive puis caractérisé via une reconstruction spatiale 2D et 3D du champ de vitesse à l'aide d'un seul fil-chaud et d'une sonde de pression placée au niveau des canaux de retours. Cette méthode de mesure nous permet de mettre en évidence des structures cohérentes et suivre leur évolution. En marge de cette étude, un réseau de neurones artificiels profond, ayant des fonctions d'activations sinusoïdales atypiques, est utilisé pour créer une représentation implicite du champ de vitesse.
L'oscillateur ainsi caractérisé a alors été utilisé pour refroidir une plaque en verre chauffé. Des tests sont pratiqués sur des jets stationnaires et des jets pulsés de même débit massique moyen. Une amélioration considérable des performances est observée pour des faibles distances d'impact et des hautes fréquences de pulsation. Des simulations numériques sont ensuite réalisées en utilisant des méthodes statistiques en un point (dites RANS) et des modèles hybrides LES/RANS. En vue de concevoir un système de refroidissement compact et capable de cibler des composants de tailles submillimétriques, des versions micrométriques de ces mêmes oscillateurs ont été conçues et fabriquées ainsi qu'une instrumentation électronique à même de les caractériser. Rares sont les études menées sur les microjets d'impact alors qu'aucune étude n'a pu être recensée à ce jour sur les microjets d'impact pulsés ni sur les micro-oscillateurs fluidiques gazeux. Le défi est donc double : de montrer que les micro-oscillateurs à gaz peuvent fonctionner à cette échelle et de les utiliser pour refroidir des composants dissipateurs de chaleur. À cela vient s'ajouter un problème non moins ambitieux, celui d'instrumenter l'oscillateur ainsi que la surface d'impact chauffée. Étant donné que la fréquence d'oscillation à cette échelle-là se mesure en kilohertz et que les fluctuations de température sont relativement faibles, des capteurs thermiques à base de couches de polysilicium fortement dopé ont donc été produits. Bien que leur haute sensibilité thermique ait été déjà démontrée, il est question ici d'améliorer leur temps de réponse. Pour ce faire, les capteurs ont été partiellement désolidarisés du substrat en silicium. Cette amélioration de la dynamique du capteur a été obtenue au prix d'une structure fragilisée qu'il a fallu prendre en compte dans les étapes technologiques suivantes.Thermal management in the aerospace industry is subject to a number of constraints. The suitability of a cooling system does not only depend on the heat flux that it can evacuate, but also includes such aspects as compactness, weight, sturdiness, cost of maintenance and durability. Taking these factors into consideration contributes to reducing fuel consumption, thus reducing the carbon footprint of the airplane. With this in mind, fluidic actuators were developed for electronics cooling applications on-board airplanes. In other words, the aim is to cool heated surfaces using the periodic unsteady flow produced by no-moving-parts fluidic oscillators. Previous studies had shown the possibility of enhancing jet impingement heat transfer by introducing a periodic perturbation in the flow. Nevertheless, the exact experimental conditions that lead to this improvement remain somewhat inconsistent across different studies. For this reason, this study tackles both the flow features of the pulsed impinging jet as well as their effects on heat transfer. In preparation, the oscillator is characterized by assessing its response to changes in design parameters and experimental conditions. This was followed by a two- and three-dimensional reconstructions of the velocity field outside the device using a hot-wire and a pressure transducer mounted onto one of the feedback loops. Using this technique, it was possible to deduce certain flow characteristics as well as detect and track the evolution of large coherent vortices produced by the pulsed jet. The data from these exhaustive measurements was then used to train a deep neural network that uses sinusoidal activation functions. The result is an implicit representation of the flow that could be useful to designers when the oscillator is only part of a larger system.
The oscillators were then used to cool a heated plate whose temperature was measured using an infrared camera. Both steady and pulsed jets were studied for a large range of frequencies, impact distances and flow rates. Remarkable enhancement was observed for small impact distances and high frequencies. Simulations where then performed using both RANS and hybrid LES/RANS approaches. In the second part of this work, a miniaturized version of the oscillator was produced that can efficiently target small electronic components. Impinging microjets have rarely been studied, while little to no works could be found on pulsed microjets of air or no-moving-parts microfluidic oscillators. The goal of the present study is then twofold, to prove that functional microfluidic oscillators with air as working fluid can be produced and that they can efficiently cool a heated surface. From an experimental standpoint, this requires proper instrumentation capable of acquiring measurements at the spatial and temporal scales of the system. For this end, high-sensitivity thermal sensors were implemented inside the microfluidic device as well as on the heated target surface. The current iteration of these sensing elements involves partially suspending them over the substrate on which they were built in order to reduce their thermal inertia. The carefully suspended structures were shown to withstand the subsequent fabrication steps despite undergoing high temperatures and pressures
Understanding Quantum Technologies 2022
Understanding Quantum Technologies 2022 is a creative-commons ebook that
provides a unique 360 degrees overview of quantum technologies from science and
technology to geopolitical and societal issues. It covers quantum physics
history, quantum physics 101, gate-based quantum computing, quantum computing
engineering (including quantum error corrections and quantum computing
energetics), quantum computing hardware (all qubit types, including quantum
annealing and quantum simulation paradigms, history, science, research,
implementation and vendors), quantum enabling technologies (cryogenics, control
electronics, photonics, components fabs, raw materials), quantum computing
algorithms, software development tools and use cases, unconventional computing
(potential alternatives to quantum and classical computing), quantum
telecommunications and cryptography, quantum sensing, quantum technologies
around the world, quantum technologies societal impact and even quantum fake
sciences. The main audience are computer science engineers, developers and IT
specialists as well as quantum scientists and students who want to acquire a
global view of how quantum technologies work, and particularly quantum
computing. This version is an extensive update to the 2021 edition published in
October 2021.Comment: 1132 pages, 920 figures, Letter forma
Physics-guided machine learning for turbulence closure and reduced-order modeling
A recent advance in scientific machine learning has started to show promising results in fluid mechanics. Despite their early success, the application of data-driven methods to turbulent flow simulation is non-trivial due to underlying highly nonlinear multiscale interactions. Here we present novel physics-guided machine learning (PGML) approaches for turbulence closure model discovery and model order reduction of complex multiscale systems. Our turbulence closure model discovery approach is based on exploiting big data without relying on underlying turbulence physics and learning from physical constraints. Specifically, we propose a frame invariant neural network model that can incorporate physical symmetries as inductive biases and illustrates its stable performance in the coarse-grid simulation without any kind of post-processing of the predicted subgrid-scale closure model. The frame invariant SGS model guarantees desired physical constraints without the need for any regularization terms and ultimately generalizes to different initial conditions and Reynolds numbers. To achieve data-efficient training and improved generalization, we propose a concatenated neural network with an uncertainty quantification mechanism that leverages information from hierarchies of models. The concatenated neural network is based on embedding information from cheap to evaluate low-fidelity approximations into the certain hidden layer of the neural network both during training and deployment. This framework is demonstrated for a range of problems, including turbulent boundary layer reconstruction, and reduced-order modeling of the vortex merging process. Furthermore, we investigate the seamless integration of sparse and noisy observations into non-intrusive reduced-order models, and hybrid models where the dynamical core of the system is modeled using the known governing equations, and the subgrid-scale processes are modeled using a deep learning model. To summarize, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics-informed learning algorithms to generate predictive technologies for turbulent fluid flows
Active nematic turbulence: An experimental study
[eng] One of the most striking phenomena of active fluids, i.e., fluids composed of self-propelled constituents, is the emergence of chaotic spatiotemporal flows. "This regime, reminiscent of inertial turbulence but happening at low Reynolds numbers, has become to be known as active turbulence. It has been observed in a variety of systems, such as bacterial suspensions or epithelial tissues. Despite the visual similarities, active turbulent flows possess fundamental differences from classical turbulent flows. The differences essentially emanate from the fact that active turbulence originates at vanishing Reynolds numbers from the self-organization of the fluid constituents, which move coordinately at distances much larger than their own size. As a result, active chaotic flows are endowed with a characteristic length scale.
In this thesis, working with an experimental active system displaying nematic order, i.e., head-to- tail orientational order, and composed of proteins from the cytoskeleton, we address some still- standing open questions regarding active turbulence. More specifically, since our experimental system is two-dimensional and has nematic order, we study 2D active nematic turbulence.
We begin this thesis by unveiling the pathway followed by the active fluid with an imposed radial alignment to its final characteristic chaotic state. More in particular, we demonstrate that the AN in the aster configuration is intrinsically unstable to buckling. In turn, a characteristic length scale already emerges at the instability's early stages. Interestingly, the instability of the aligned active nematic can be characterized in terms of a growth rate that exhibits a quadratic or quasi-quadratic dependence on the leading wavenumber. Our experimental results are then compared with predictions obtained from linear stability analysis. This enables us to see that the coupling of the active nematic with adjacent fluid layers precludes long wavelength fluctuations, imposing in this way a genuine wavelength selection mechanism.
In the second project, we measure the active liquid crystal's flow field and the associated kinetic energy spectrum. In this way, we verify the existence of scaling regimes, some of which feature exponents previously predicted through theory and simulations , together with new ones. To understand the newly-discovered scaling regimes, we exploit a theory that includes the hydrodynamic coupling of the active nematic with the two contacting passive fluid layers. This theory assesses the range of validity of the identified scaling regimes, and permits to extract information on important rheological parameters of the active fluid
In the final project, still in progress, we address the presence of energy cascades in active nematic turbulence. Preliminary experimental results, supported with simulations, suggest that even though the free energy balance does not entirely vanish at all length scales, we cannot indeed conclude that there is energy transfer between scales. A significant limitation we encounter when computing the free energy balance of the active nematic is that most of the material parameters
still need to be determined. Therefore, further research research devoted to the evaluation of such parameters may shed light on this respect.
On top of the above fundamental studies, we also demonstrate two implementations of polarimetry measurements coupled with fluorescence imaging, with which we can simultaneously measure the director and velocity fields of the active nematic . The first arrangement is based on a liquid crystal slab, whose retardance can be easily commanded with a computer. By measuring the light intensity reaching the detector at different configurations of the liquid crystal retarder, we can unequivocally and continuously know the sample's local orientation. The alternative implementation incorporates a polarization camera, a device composed of subpixels with different polarizations. This arrangement allows us to obtain exceptional birefringence measurements at significantly high frame rates, even with very low-birefringent samples, as the active nematic.[cat] Els fluids actius, com les suspensions de bacteris o els teixits, sĂłn fluids compostos per moltes unitats capaces de propulsar-se contĂnuament. Aquests fluids presenten propietats molt interessants i radicalment oposades a les que s’observen quan una d’aquestes unitats actives es mou individualment. Un exemple Ă©s el que es coneix com a turbulència activa, on els fluids actius es mouen caòticament i que emergeix inclĂşs a nĂşmeros de Reynolds baixos, quan la inèrcia es menyspreable. Aquest fenomen es diu aixĂ perquè visualment recorda a la turbulència inercial clĂ ssica. Tot i aixĂ, hi ha diferències fonamentals entre aquests dos tipus de turbulència, els quals ens interessa discernir.
En aquesta tesi es presenten estudis experimentals, duts a terme amb una suspensió de proteïnes del citoesquelet, i amb els quals abordem algunes qüestions encara obertes sobre la turbulència activa i les seves similituds i diferències amb la turbulència inercial. Més concretament, com el nostre sistema experimental és 2D i presenta simetria nemà tica, nosaltres estudiem la turbulència nemà tica activa.
En primer lloc, revelem el camĂ que segueix el nemĂ tic actiu alineat radialment fins que arriba al seu estat turbulent. MĂ©s concretament, demostrem que la geometria d’à ster Ă©s inestable; en conseqüència, el fluid actiu comença a deformar-se i llavors emergeix una escala de longitud caracterĂstica. DesprĂ©s duem a terme estudis on l’actiu nemĂ tic ja es troba plenament en el seu estat turbulent. En aquest sentit, demostrem l’existència de règims d’escala en l’espectre d’energia cinètica del nemĂ tic actiu i abordem la presència o no presència de cascades d’energia en el context de la turbulència nemĂ tica activa. Finalment, descrivim dues tècniques de polarimetria acoblades a fluorescència amb les quals podem mesurar simultĂ niament la orientaciĂł i el camp de velocitats del nemĂ tic actiu i que ens permeten dur a terme les mesures experimentals presentades en aquesta tesi
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