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Related papers: Autonomous Discovery of Tough Structures

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Autonomous vehicles (AVs) promise efficient, clean and cost-effective transportation systems, but their reliance on sensors, wireless communications, and decision-making systems makes them vulnerable to cyberattacks and physical threats.…

Cryptography and Security · Computer Science 2026-04-15 Chieh Tsai , Murad Mehrab Abrar , Salim Hariri

One of the main goals and challenges of materials discovery is to find the best candidates for each interest property or application. Machine learning rises in this context to efficiently optimize this search, exploring the immense…

Materials Science · Physics 2021-08-04 Gabriel R. Schleder , Bruno Focassio , Adalberto Fazzio

Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder…

Machine Learning · Statistics 2018-08-01 Samuel S. Schoenholz

Autonomous driving is getting a lot of attention in the last decade and will be the hot topic at least until the first successful certification of a car with Level 5 autonomy. There are many public datasets in the academic community.…

Computer Vision and Pattern Recognition · Computer Science 2019-01-29 Michal Uricar , David Hurych , Pavel Krizek , Senthil Yogamani

Modern vehicles have electrical architectures whose complexity grows year after year due to feature growth corresponding to customer expectations. The latest of the expectations, automation of the dynamic driving task however, is poised to…

Software Engineering · Computer Science 2020-01-09 Naveen Mohan

The metallurgy and materials communities have long known and exploited fundamental links between chemical and structural ordering in metallic solids and their mechanical properties. The highest reported strength achievable through the…

The increasing importance of carbon capture technologies for deployment in remediating CO2 emissions, and thus the necessity to improve capture materials to allow scalability and efficiency, faces the challenge of materials development,…

Quantum transport is strongly influenced by interference with phase relations that depend sensitively on the scattering medium. Since even small changes in the geometry of the medium can turn constructive interference to destructive, a…

Quantum Physics · Physics 2015-03-10 Stefano Mostarda , Federico Levi , Diego Prada-Gracia , Florian Mintert , Francesco Rao

Although it is not a new concept, 3D integration increasingly receives widespread interest and focus as lithographic scaling becomes more challenging, and as the ability to make miniature vias greatly improves. Like Moores law, 3D…

Hardware Architecture · Computer Science 2025-10-21 Philip Emma , Eren Kurshan

Safety filters provide a practical approach for enforcing safety constraints in autonomous systems. While learning-based tools scale to high-dimensional systems, their performance depends on informative data that includes states likely to…

Robotics · Computer Science 2026-04-16 James Dallas , Thomas Lew , John Talbot , Jonathan DeCastro , Somil Bansal , John Subosits

Constitutive modeling lies at the core of mechanics, allowing us to map strains onto stresses for a material in a given mechanical setting. Historically, researchers relied on phenomenological modeling where simple mathematical…

Computational Engineering, Finance, and Science · Computer Science 2024-08-28 Asghar A. Jadoon , Knut A. Meyer , Jan N. Fuhg

Snap-fits are versatile mechanical designs in industrial products, which enable the repeated assembling and disassembling of two solid parts. This important property is attributed to a fine balance between geometry, friction, and bending…

Soft Condensed Matter · Physics 2020-11-11 Keisuke Yoshida , Hirofumi Wada

Man-made slender structures are known to be sensitive to high levels of vibration, due to their flexibility, which often cause irreversible damage. In nature, trees repeatedly endure large amplitudes of motion, mostly caused by strong…

Fluid Dynamics · Physics 2015-05-28 Benoit Theckes , Emmanuel de Langre , Xavier Boutillon

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical…

The aim of this research is to introduce a novel structural design process that allows architects and engineers to extend their typical design space horizon and thereby promoting the idea of creativity in structural design. The theoretical…

Machine Learning · Computer Science 2018-09-25 Lukas Fuhrimann , Vahid Moosavi , Patrick Ole Ohlbrock , Pierluigi Dacunto

Given that observational and numerical climate data are being produced at ever more prodigious rates, increasingly sophisticated and automated analysis techniques have become essential. Deep learning is quickly becoming a standard approach…

Fluid Dynamics · Physics 2017-09-12 A. Rupe , J. P. Crutchfield , K. Kashinath , Prabhat

Autonomous materials discovery with desired properties is one of the ultimate goals for materials science, and the current studies have been focusing mostly on high-throughput screening based on density functional theory calculations and…

A thin film at a liquid interface responds to uniaxial confinement by wrinkling and then by folding; its shape and energy have been computed exactly before self contact. Here, we address the mechanics of large folds, i.e. folds that absorb…

Soft Condensed Matter · Physics 2014-10-22 Vincent Démery , Benny Davidovitch , Christian D. Santangelo

Dynamic Bayesian networks provide a compact and natural representation for complex dynamic systems. However, in many cases, there is no expert available from whom a model can be elicited. Learning provides an alternative approach for…

Artificial Intelligence · Computer Science 2013-01-30 Xavier Boyen , Nir Friedman , Daphne Koller

An important task in structural design is to quantify the structural performance of an object under the external forces it may experience during its use. The problem proves to be computationally very challenging as the external forces'…

Machine Learning · Statistics 2018-10-26 Yining Wang , Erva Ulu , Aarti Singh , Levent Burak Kara
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