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In a companion article, we discussed the radiometric sensitivity and resolution of a new passive optical sensing technique, Space-Time Projection Optical Tomography (SPOT), to detect and track sub-cm and larger space debris for Space…

Optics · Physics 2022-11-28 Hasan Bahcivan , David J. Brady

The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micron particles can spread rapidly from their source to residential areas, increasing the risk of respiratory…

Machine Learning · Computer Science 2021-01-18 Hsing-Chung Chen , Karisma Trinanda Putra , Jerry Chun-WeiLin

A common feature of wall-bounded turbulent particle-laden flows is enhanced particle concentrations in a thin layer near the wall due to a phenomenon known as turbophoresis. Even at relatively low bulk volume fractions, particle-particle…

Fluid Dynamics · Physics 2019-08-09 Perry L. Johnson

Explicit quantification of uncertainty in engineering simulations is being increasingly used to inform robust and reliable design practices. In the aerospace industry, computationally-feasible analyses for design optimization purposes often…

Fluid Dynamics · Physics 2019-11-13 Jayant Mukhopadhaya , Brian T. Whitehead , John F. Quindlen , Juan J. Alonso

This paper presents a novel efficient method for spatial monitoring of the distribution of correlated field signals, such as temperature, humidity, etc. using unmanned aerial vehicles (UAVs). The spatial signal is compressed to its…

Signal Processing · Electrical Eng. & Systems 2024-11-27 Maryam Zahra , Homa Tajiani , Hadi Alasti

Real-time safety systems are crucial components of intelligent vehicles. This paper introduces a prediction-based collision risk assessment approach on highways. Given a point mass vehicle dynamics system, a stochastic forward reachable set…

Systems and Control · Electrical Eng. & Systems 2022-05-04 Xinwei Wang , Zirui Li , Javier Alonso-Mora , Meng Wang

Reliable 4D aircraft trajectory prediction, whether in a real-time setting or for analysis of counterfactuals, is important to the efficiency of the aviation system. Toward this end, we first propose a highly generalizable efficient…

Machine Learning · Computer Science 2019-01-01 Yulin Liu , Mark Hansen

In this paper we focus on the problem of assigning uncertainties to single-point predictions generated by a deterministic model that outputs a continuous variable. This problem applies to any state-of-the-art physics or engineering models…

Machine Learning · Statistics 2020-03-12 Enrico Camporeale , Algo Carè

In order to predict the long-term effects of irradiation on the material properties of tungsten, a continuum approach to simulating the interactions of dislocation loops, which arise from radiation damage, is proposed. Continuum models of…

Materials Science · Physics 2026-04-20 Joseph Duque Lopez , Sergei Dudarev , James Kermode , Thomas Hudson

Deterministic simulations of the rate equations governing cluster dynamics in materials are limited by the number of equations to integrate. Stochastic simulations are limited by the high frequency of certain events. We propose a coupling…

Materials Science · Physics 2017-10-11 Pierre Terrier , Manuel Athènes , Thomas Jourdan , Gilles Adjanor , Gabriel Stoltz

The core of every orbit determination process is the comparison between the measured observables and their predicted values, computed using the adopted mathematical models, and the minimization, in a least square sense, of their…

Instrumentation and Methods for Astrophysics · Physics 2019-08-22 Marco Zannoni , Paolo Tortora

Atomic scale simulations are a key element of modern science in that they allow to understand, and even predict, complex physical or chemical phenomena on the basis of the fundamental laws of nature. Among the different existing atomic…

Materials Science · Physics 2021-07-20 Alexandre Boulle , Alain Chartier , Aurélien Debelle , Xin Jin , Jean-Paul Crocombette

Traffic congestion due to uncertainties, such as accidents, is a significant issue in urban areas, as the ripple effect of accidents causes longer delays, increased emissions, and safety concerns. To address this issue, we propose a robust…

Machine Learning · Computer Science 2025-07-31 Kranthi Kumar Talluri , Galia Weidl , Vaishnavi Kasuluru

In this paper, a sampling-based Stochastic Model Predictive Control algorithm is proposed for discrete-time linear systems subject to both parametric uncertainties and additive disturbances. One of the main drivers for the development of…

We propose two algorithms to provide a full preliminary orbit of an Earth-orbiting object with a number of observations lower than the classical methods, such as those by Laplace and Gauss. The first one is the Virtual debris algorithm,…

Space Physics · Physics 2015-05-14 D. Farnocchia , G. Tommei , A. Milani , A. Rossi

We present a new particle-based (discrete element) numerical method for the simulation of granular dynamics, with application to motions of particles on small solar system body and planetary surfaces. The method employs the parallel N-body…

Earth and Planetary Astrophysics · Physics 2013-06-12 Derek C. Richardson , Kevin J. Walsh , Naomi Murdoch , Patrick Michel

Uncontrolled spacecraft will disintegrate and generate a large amount of debris in the reentry process, and ablative debris may cause potential risks to the safety of human life and property on the ground. Therefore, predicting the landing…

Machine Learning · Computer Science 2023-09-08 Hu Gao , Zhihui Li , Depeng Dang , Jingfan Yang , Ning Wang

Uncertainty-aware robot motion prediction is crucial for downstream traversability estimation and safe autonomous navigation in unstructured, off-road environments, where terrain is heterogeneous and perceptual uncertainty is high. Most…

Satellite conjunctions involving "near misses" of space objects are becoming increasingly likely. One approach to risk analysis for them involves the computation of the collision probability, but this has been regarded as having some…

Applications · Statistics 2022-03-11 Soumaya Elkantassi , Anthony Davison

For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to…

Machine Learning · Computer Science 2023-01-27 M. Giselle Fernández-Godino , Donald D. Lucas , Qingkai Kong