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Physics
This chapter covers topics studied in a General Physics I class. When analyzing mechanisms, students need a solid foundation in physics. In...
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Physics-Informed Machine Learning for metal additive manufacturing
The advancement of additive manufacturing (AM) technologies has facilitated the design and fabrication of innovative and complicated structures or...
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Analyticity and Physics
My goal is to present to you some aspects of the role that the mathematical concept as subtle and abstract as “analyticity” plays in physics. In...
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Encoding physics to learn reaction–diffusion processes
Modelling complex spatiotemporal dynamical systems, such as reaction–diffusion processes, which can be found in many fundamental dynamical effects in...
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Physics-enhanced deep surrogates for partial differential equations
Many physics and engineering applications demand partial differential equations (PDE) property evaluations that are traditionally computed with...
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Surface Physics
Scientific interest in surface physics began very early with the XVIII century efforts trying to explain surface tension and capillarity. Molecules...
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Incorporating physics into data-driven computer vision
Many computer vision techniques infer properties of our physical world from images. Although images are formed through the physics of light and...
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Hybrid modeling of multibody vehicles with partially known physics: discovering complex behaviors of tires
There are multibody systems whose physics are partially known owing to their complexity and nonlinearity. Therefore, motion equations are not utterly...
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Physics-Informed Particle-Based Reinforcement Learning for Autonomy in Signalized Intersections
In this paper, we develop a framework to enhance the control of autonomous vehicles within signalized intersections by integrating system dynamics...
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Science diplomacy in medical physics – an international perspective
PurposeScience diplomacy in medical physics is a relatively young research field and translational practice that focuses on establishing...
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Physics-Informed Bayesian learning of electrohydrodynamic polymer jet printing dynamics
Calibration of highly dynamic multi-physics manufacturing processes such as electrohydrodynamics-based additive manufacturing (AM) technologies...
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Simulation of realistic granular soils in triaxial test using physics engine
The discrete element method (DEM) is the most widely applied numerical tool to simulate triaxial test, a common geotechnical test to measure the...
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The International Organization for Medical Physics – a driving force for the global development of medical physics
The International Organization for Medical Physics (IOMP) is the world’s largest professional organization in the field of medical physics and has...
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Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling
This work offers a discussion on how computational mechanics and physics-informed machine learning can be integrated into the process of sensing,...
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Physics in a Digital Twin World
This chapter explores the use of physics-based modeling & simulation technologies as part of Digital Twin solutions. It describes how an...
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Virtual Physics Learning for Basic Education
This project shows an interactive virtual laboratory for teaching Physics, in the first year of BGU (Bachillerato General Unificado), adapted to the...
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Semiconductor Physics
Solid-state physics, or the study of carrier movement through a solid, arose due to the discovery of quantum mechanics. Diodes and transistors are...
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Physics enhanced sparse identification of dynamical systems with discontinuous nonlinearities
A method is introduced for the identification of the nonlinear governing equations of dynamical systems in the presence of discontinuous and...
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Structure-preserving formulations for data-driven analysis of coupled multi-physics systems
We develop a novel methodology for data-driven simulation of coupled multi-physics systems. The result of the method is a learned numerical...
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Hybrid physics data-driven model-based fusion framework for machining tool wear prediction
Accurate tool wear prediction is of great significance to improve production efficiency, ensure product quality and reduce machining cost. This paper...
