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The absorptivity of a material is a major uncertainty in numerical simulations of laser welding and additive manufacturing, and its value is often calibrated through trial-and-error exercises. This adversely affects the capability of…

Three-dimensional metallic microstructures find applications as stents in medicine, as ultrabroadband antennas in communications, in micromechanical parts or as structures of more fundamental interest in photonics like metamaterials. Direct…

Applied Physics · Physics 2021-09-02 Thomas Palmer , Erik H. Waller , Heiko Andrä , Konrad Steiner , Georg von Freymann

Ray tracing algorithms that compute pulse profiles from rotating neutron stars are essential tools for constraining neutron-star properties with data from missions such as NICER. However, the high computational cost of these simulations…

High Energy Astrophysical Phenomena · Physics 2025-06-16 Preston G. Waldrop , Dimitrios Psaltis , Tong Zhao

Reverse engineering can be used to derive a 3D model of an existing physical part when such a model is not readily available. For parts that will be fabricated with subtractive and formative manufacturing processes, existing reverse…

Computational Engineering, Finance, and Science · Computer Science 2026-03-24 Jannatul Bushra , Md Habibor Rahman , Mohammed Shafae , Hannah D. Budinoff

This work integrates in-situ neutron diffraction and crystal plasticity finite element modeling to study the kinematic stability of retained austenite in high carbon bearing steels. The presence of a kinematically metastable retained…

Materials Science · Physics 2018-01-18 Rohit Voothaluru , Vikram Bedekar , Qingge Xie , Alexandru D Stoica , R Scott Hyde , Ke An

As the need for miniaturized structural and functional materials has increased,the need for precise materials characterizaton has also expanded. Nanoindentation is a popular method that can be used to measure material mechanical behavior…

Accurate prediction of mechanical properties of steel during hot rolling processes, such as Thin Slab Direct Rolling (TSDR), remains challenging due to complex interactions among chemical compositions, processing parameters, and resultant…

State-of-the-art methods for quantifying wear in cylinder liners of large internal combustion engines require disassembly and cutting of the liner. This is followed by laboratory-based high-resolution microscopic surface depth measurement…

This short paper presents the potential of using machine learning to predict materials behaviour in the context of hydrogen interaction with steel. Effort has been made to understand the quality, and amount of data needed to get improved…

Materials Science · Physics 2021-10-22 M. Amir Siddiq

Metal Sintering is a necessary step for Metal Injection Molded parts and binder jet such as HP's metal 3D printer. The metal sintering process introduces large deformation varying from 25 to 50% depending on the green part porosity. In this…

Machine Learning · Computer Science 2024-07-25 Rachel , Chen , Juheon Lee , Chuang Gan , Zijiang Yang , Mohammad Amin Nabian , Jun Zeng

We investigated the accelerated prediction of the thermal conductivity of materials through end- to-end structure-based approaches employing machine learning methods. Due to the non-availability of high-quality thermal conductivity data, we…

Materials Science · Physics 2023-11-07 Yagyank Srivastava , Ankit Jain

Learning-based model predictive control has emerged as a powerful approach for handling complex dynamics in mechatronic systems, enabling data-driven performance improvements while respecting safety constraints. However, when computational…

Systems and Control · Electrical Eng. & Systems 2025-12-19 Mark Benazet , Francesco Ricca , Dario Bralla , Melanie N. Zeilinger , Andrea Carron

The ability to control wettability is important for a wide range of technological applications in which precise microfluidic handling is required. It is known that predesigned roughness at a micro- or nano- scale enhances the wetting…

Soft Condensed Matter · Physics 2013-04-09 Michail E. Kavousanakis , Carlos E. Colosqui , Athanasios G. Papathanasiou

Recent advances in 3D deep learning have shown that it is possible to train highly effective deep models for 3D shape generation, directly from 2D images. This is particularly interesting since the availability of 3D models is still limited…

Computer Vision and Pattern Recognition · Computer Science 2019-11-05 Shichen Liu , Shunsuke Saito , Weikai Chen , Hao Li

This Letter introduces an approach for precisely designing surface friction properties using a conditional generative machine learning model, specifically a diffusion denoising probabilistic model (DDPM). We created a dataset of synthetic…

Computational Physics · Physics 2024-01-11 Even Marius Nordhagen , Henrik Andersen Sveinsson , Anders Malthe-Sørenssen

Popular industrial robotic problems such as spray painting and welding require (i) conditioning on free-shape 3D objects and (ii) planning of multiple trajectories to solve the task. Yet, existing solutions make strong assumptions on the…

Robotics · Computer Science 2023-12-07 Gabriele Tiboni , Raffaello Camoriano , Tatiana Tommasi

This work examines the reproducibility and benchmarking of state-of-the-art real-time object detection models. As object detection models are often used in real-world contexts, such as robotics, where inference time is paramount, simply…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Pierre-Luc Asselin , Vincent Coulombe , William Guimont-Martin , William Larrivée-Hardy

Continuous casting is a widely adopted process in the steel industry, where maintaining high steel quality is paramount. Efficient prediction of grade intermixing during ladle changeover operations is critical for maintaining steel quality…

Injection molded part quality can be improved by precise process adjustment, which could rely on in-situ measurements of part quality. Geometrical and appearance quality (visually and sensory) requirements are increasing. However, direct…

Systems and Control · Computer Science 2018-06-24 Pierre Nagorny , Maurice Pillet , Eric Pairel , Ronan Le Goff , Loureaux Jérôme , Wali Marlène , Patrice Kiener

The implementation of thermally sprayed components in steel manufacturing presents challenges for production and plant maintenance. While enhancing performance through specialized surface properties, these components may encounter…

Machine Learning · Computer Science 2025-05-19 Wolfgang Rannetbauer , Simon Hubmer , Carina Hambrock , Ronny Ramlau