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Experimental multi-parameter optimization can enhance the interfacing of cold atoms with waveguides and cavities. Recent implementations of machine learning (ML) algorithms demonstrate the optimization of complex cold atom ex perimental…

Atomic Physics · Physics 2025-07-16 Paul Anderson , Sreesh Venuturumilli , Michal Bajcsy

This manuscript proposes an optimization framework to find the tailor-made functionally graded material (FGM) profiles for thermoelastic applications. This optimization framework consists of (1) a random profile generation scheme, (2) deep…

Computational Engineering, Finance, and Science · Computer Science 2024-08-27 Piyush Agrawal , Ihina Mahajan , Shivam Choubey , Manish Agrawal

Leveraging the latent heat of phase change materials (PCMs) can reduce the peak temperatures and transient variations in temperature in electronic devices. But as the power levels increase, the thermal conduction pathway from the heat…

Computational Engineering, Finance, and Science · Computer Science 2025-02-04 Meghavin Bhatasana , Amy Marconnet

Effective properties of materials with random heterogeneous structures are typically determined by homogenising the mechanical quantity of interest in a window of observation. The entire problem setting encompasses the solution of a local…

Numerical Analysis · Mathematics 2021-10-22 Felipe Rocha , Simone Deparis , Pablo Antolin , Annalisa Buffa

The generation of cold atom clouds is a complex process which involves the optimization of noisy data in high dimensional parameter spaces. Optimization can be challenging both in and especially outside of the lab due to lack of time,…

The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computational melting point estimation techniques are limited in…

Purpose - This paper continues the development of a comprehensive methodology for fully resolved numerical simulations of fusion deposition modeling. Design/methodology/approach - A front-tracking/finite volume method introduced in Part I…

Fluid Dynamics · Physics 2018-02-27 Huanxiong Xia , Jiacai Lu , Gretar Tryggvason

Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a…

Other Condensed Matter · Physics 2021-11-01 A. M. Samarakoon , D. Alan Tennant , Feng Ye , Qiang Zhang , S. A. Grigera

The addition of metals to any gas can significantly alter its evolution by increasing the rate of radiative cooling. In star-forming environments, enhanced cooling can potentially lead to fragmentation and the formation of low-mass stars,…

Astrophysics · Physics 2009-11-13 Britton D. Smith , Steinn Sigurdsson , Tom Abel

Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations and may be resolved by the methods of Langevin dynamics with…

Machine Learning · Statistics 2021-05-24 Oleksandr Borysenko , Maksym Byshkin

We introduce two models of industrial drying - a simplified one-equation model, and a detailed three-equation model. The purpose of the simplified model is rigorous validation of numerical methods for PDE-constrained optimal control. The…

Optimization and Control · Mathematics 2024-04-26 Lennon Ó Náraigh

Resistance spot welding is the dominant joining process for the body-in-white in the automotive industry, where the weld nugget diameter is the key quality metric. Its measurement requires destructive testing, limiting the potential for…

Machine Learning · Computer Science 2026-01-27 Jan A. Zak , Christian Weißenfels

We study a class of entangling gates for trapped atomic ions and demonstrate the use of numeric optimization techniques to create a wide range of fast, error-robust gate constructions. Our approach introduces a framework for numeric…

In this paper, we develop a convolutional neural network model to predict the mechanical properties of a two-dimensional checkerboard composite quantitatively. The checkerboard composite possesses two phases, one phase is soft and ductile…

Machine Learning · Computer Science 2020-02-03 Diab W. Abueidda , Mohammad Almasri , Rami Ammourah , Umberto Ravaioli , Iwona M. Jasiuk , Nahil A. Sobh

In the last ten years, the average annual growth rate of nonwoven production was 4%. In 2020 and 2021, nonwoven production has increased even further due to the huge demand for nonwoven products needed for protective clothing such as FFP2…

Machine Learning · Computer Science 2024-05-20 Viny Saajan Victor , Andre Schmeißer , Heike Leitte , Simone Gramsch

Additive manufacturing of a single crystalline metallic column is studied using molecular dynamics simulations. In the model, a melt pool is incrementally added and cooled to a target temperature under isobaric conditions to build a…

Materials Science · Physics 2021-01-18 Gurmeet Singh , Anthony M. Waas , Veera Sundararaghavan

Explicitly accounting for uncertainties is paramount to the safety of engineering structures. Optimization which is often carried out at the early stage of the structural design offers an ideal framework for this task. When the…

Methodology · Statistics 2022-12-14 M. Moustapha , A. Galimshina , G. Habert , B. Sudret

The processes occurring in climatic change evolution and their variations play a major role in environmental engineering. Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Gene…

Neural and Evolutionary Computing · Computer Science 2013-04-19 Siddharth Shroff , Vipul Dabhi

The quality of plastic parts produced through injection molding depends on many factors. Especially during the filling stage, defects such as weld lines, burrs, or insufficient filling can occur. Numerical methods need to be employed to…

Computational Engineering, Finance, and Science · Computer Science 2019-03-22 Violeta Karyofylli , Loic Wendling , Michel Make , Norbert Hosters , Marek Behr

There is an abundance of prior research on the optimization of production systems, but there is a research gap when it comes to optimizing which components should be included in a design, and how they should be connected. To overcome this…

Neural and Evolutionary Computing · Computer Science 2024-02-05 N. Paape , J. A. W. M. van Eekelen , M. A. Reniers