Searched for: subject%3A%22Bayesian%255C+inference%22
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Molhoek, Jord (author)
Many real-world problems fall in the category of sequential decision-making under uncertainty; Markov Decision Processes (MDPs) are a common method for modeling such problems. To solve an MDP, one could start from scratch or one could already have an idea of what good policies look like. Furthermore, there could be uncertainty in this idea. In...
master thesis 2024
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Dash, T.K. (author), Driessen, J.N. (author), Krasnov, O.A. (author), Yarovoy, Alexander (author)
The challenge of reconstructing the Doppler spectrum of a precipitation-like event observed by a fast-scanning weather radar is addressed. A novel method is proposed where the echo sequence in time is assumed to be a complex Gaussian process with a known covariance structure. It is a two-step approach where the first step is the estimation of...
conference paper 2024
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Moriaux, Olivier (author), Zamponi, R. (author), Schram, Christophe (author)
The empirical calibration of remote microphone probes (RMP), used to acquire wall-pressure fluctuations, can introduce spurious resonance into the sensor transfer function due to the difference in the pressure field inside the calibrator geometry over multiple calibration steps. Such spurious resonance subsequently propagates into the...
journal article 2024
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Dziarnowska, Weronika (author)
Researchers have been interested in studying the connection between emotion and memory for decades but much remains unknown due to the elusive nature of the human brain. Furthering our understanding of the phenomenon is crucial for improving the treatment of neurological disorders associated with emotion dysregulation, as well as for enhancing...
master thesis 2023
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Moreno León, C. (author)
Radar-tracking of low-observable targets such as drones suffers from low detection performance. In these type of applications, it is desirable to avoid data thresholding in order to preserve the weak target signal in the raw sensor data. This thesis considers the Multiple Object Tracking (MOT) problem in the context of radar Track-before-Detect ...
doctoral thesis 2023
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Peker, Uri (author)
Probabilistic numerics methods are a novel approach to quantifying the approximation errors in numerical computations as probabilistic uncertainties. A recent method that was developed is the Bayesian Finite Element Method, which aims to determine the discretization errors along a coarse mesh probabilistically. This work analyzes the use of...
master thesis 2023
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Shi, Dongdong (author)
Wind energy becomes more and more popular since it is environmentally friendly. Wind farm control is one of the most popular topics and it works on steering the wind farm to extract energy from wind as much as possible. Generally, the model capturing wake effects between turbines in the wind farm plays a role in wind farm control. The existing...
master thesis 2023
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Moriaux, Olivier (author)
Unsteady surface pressures shed light on the turbulent structures of boundary layer flow, which dictate for a large part the aerodynamic and aeroacoustic performance of aerodynamic bodies submersed in a flow. Remote microphone probes (RMP), e.g., pinhole probes, provide advantages compared to flush-mounted probes because of their reduced sensing...
master thesis 2023
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Wu, Jiansong (author), Cai, Jitao (author), Liu, Z. (author), Yuan, S. (author), Bai, Yiping (author), Zhou, Rui (author)
As an effective way to facilitate the increasing demand for reliable infrastructure, energy supply and sustainable urban development, underground utility tunnels have been developed rapidly in recent years. Due to the widespread distribution of utility tunnels, the safe operation of natural gas pipelines accommodated in utility tunnels has...
journal article 2023
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Zhang, Xinqi (author), Shi, Jihao (author), Huang, Xinyan (author), Xiao, Fu (author), Yang, M. (author), Huang, Jiawei (author), Yin, Xiaokang (author), Sohail Usmani, Asif (author), Chen, Guoming (author)
Deep learning has been widely applied to automated leakage detection and location of natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial dependency of sensors, which limits leakage detection performance. Graph deep learning is a promising alternative to prevailing approaches as it can model spatial...
journal article 2023
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Zeng, Cheng (author), Huang, Jinsong (author), Wang, H. (author), Xie, Jiawei (author), Zhang, Yuting (author)
Reliable estimation of rail useful lifetime can provide valuable information for predictive maintenance in railway systems. However, in most cases, lifetime data is incomplete because not all pieces of rail experience failure by the end of the study horizon, a problem known as censoring. Ignoring or otherwise mistreating the censored cases...
journal article 2023
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Igea, Felipe (author), Cicirello, A. (author)
Multi-modal distributions of some physics-based model parameters are often encountered in engineering due to different situations such as a change in some environmental conditions, and the presence of some types of damage and non-linearity. In statistical model updating, for locally identifiable parameters, it can be anticipated that multi...
journal article 2023
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Qin, Ziqiu (author)
In anti-cancer therapy, ntiangiogenic treatments are applied and take effect on the vascularization of tissue. To evaluate the efficacy of treatments, we adopt two methods to solve the physiological pharmacokinetic model’s parameter estimation problem, providing discrete, partial, and noisy observations of stochastic differential equations. One...
master thesis 2022
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Martinez Colan, Andres (author)
Bayesian system identification has been extensively adopted in Structural Health Monitoring as a way to probabilistically infer unobservable parameters of the physical model of a structure using measurement data. Combining the Bayesian approach with distributed optic fibre sensors can potentially improve the accuracy and reduce the uncertainty...
master thesis 2022
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Lathourakis, Christos (author)
An issue of utmost significance constitutes the maintenance of engineering systems exposed to corrosive environments, e.g. coastal and marine environments, highly acidic environments, etc. The most beneficial sequence of maintenance decisions, i.e. the one that corresponds to the minimum maintenance cost, can be sought as the solution to an...
master thesis 2022
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Bouwmeester, J. (author), Menicucci, A. (author), Gill, E.K.A. (author)
The objective of this paper is to investigate which approach would lead to more reliable CubeSats: full subsystem redundancy or improved testing. Based on data from surveys, the reliability of satellites and subsystems is estimated using a Kaplan–Meier estimator. Subsequently, a variety of reliability models is defined and their maximum...
journal article 2022
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van Zwieten, G.J. (author), van Brummelen, E. Harald (author), Hanssen, R.F. (author)
Earthquakes cause lasting changes in static equilibrium, resulting in global deformation fields that can be observed. Consequently, deformation measurements such as those provided by satellite based InSAR monitoring can be used to infer an earthquake's faulting mechanism. This inverse problem requires a numerical forward model that is both...
journal article 2022
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Lye, Adolphus (author), Cicirello, A. (author), Patelli, Edoardo (author)
Bayesian inference is a popular approach towards parameter identification in engineering problems. Such technique would involve iterative sampling methods which are often robust. However, these sampling methods often require significant computational resources and also the tuning of a large number of parameters. This motivates the development...
journal article 2022
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Zou, J. (author), Cicirello, A. (author), Iliopoulos, Alexandros (author), Lourens, E. (author)
Fatigue assessment in offshore wind turbine support structures requires the monitoring of strains below the mudline, where the highest bending moments occur. However, direct measurement of these strains is generally impractical. This paper presents the validation of a virtual sensing technique based on the Gaussian process latent force model...
conference paper 2022
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Kekkonen, H.N. (author)
We consider the statistical non-linear inverse problem of recovering the absorption term f > 0 in the heat equation {∂tu-12Δu+fu=0onO×(0,T)u=gon∂ O×(0,T)u(·,0)=u0onO, where O ϵ ℝd is a bounded domain, T < ∞ is a fixed time, and g, u 0 are given sufficiently smooth functions describing boundary and initial values respectively. The data...
journal article 2022
Searched for: subject%3A%22Bayesian%255C+inference%22
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