Computational Mathematics (CM)
Browse by
Collections in this community
Recent Submissions

Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations
(202310)This work proposes a novel supervised learning approach to identify damage in operating bridge structures. We propose a method to introduce the effect of environmental and operational conditions into the synthetic damage ... 
Mapping flagellated swimmers to surfaceslip driven swimmers.
(2023)Flagellated microswimmers are ubiquitous in natural habitats. Understanding the hydrodynamic behavior of these cells is of paramount interest, owing to their applications in biomedical engineering and disease spreading. ... 
Swimming Efficiently by Wrapping
(2023)Single flagellated bacteria are ubiquitous in nature. They exhibit various swimming modes using their flagella to explore complex surroundings such as soil and porous polymer networks. Some singleflagellated bacteria ... 
MemoryBased Monte Carlo Integration for Solving Partial Differential Equations Using Neural Networks
(2023)Monte Carlo integration is a widely used quadrature rule to solve Partial Differential Equations with neural networks due to its ability to guarantee overfittingfree solutions and highdimensional scalability. However, ... 
Constant probe orientation for fast contactbased inspection of 3D freeform surfaces using (3+2)axis inspection machines
(2023)A new probe optimization method for contact based (3+2)axis inspection machines is proposed. Given an inspection path of a stylus on a freeform surface, an optimal orientation of the stylus is computed such that (i) the ... 
Solving Boundary Value Problems Via the Nyström Method Using Spline Gauss Rules
(2022)We propose to use spline Gauss quadrature rules for solving boundary value problems (BVPs) using the Nyström method. When solving BVPs, one converts the corresponding partial differential equation inside a domain into the ... 
Physicsguided deeplearning inversion method for the interpretation of noisy loggingwhiledrilling resistivity measurements
(202310)Deep learning (DL) inversion is a promising method for realTime interpretation of loggingwhiledrilling (LWD) resistivity measurements for wellnavigation applications. In this context, measurement noise may significantly ... 
A MULTIDIRECTIONAL DEEP NEURAL NETWORK FOR SELFSUPERVISED RECONSTRUCTION OF SEISMIC DATA
(2021)Seismic studies exhibit gaps in the recorded data due to surface obstacles. To fill in the gaps with selfsupervised deep learning, the network learns to predict different events from the recorded parts of data and then ... 
An exponential integration generalized multiscale finite element method for parabolic problems
(20230415)We consider linear and semilinear parabolic problems posed in highcontrast multiscale media in two dimensions. The presence of highcontrast multiscale media adversely affects the accuracy, stability, and overall efficiency ... 
Machine learning discovery of optimal quadrature rules for isogeometric analysis
(20231101)We propose the use of machine learning techniques to find optimal quadrature rules for the construction of stiffness and mass matrices in isogeometric analysis (IGA). We initially consider 1D spline spaces of arbitrary ... 
An ErrorBased Approximation Sensing Circuit for EventTriggered LowPower Wearable Sensors
(20230424)Eventbased sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all stateoftheart ... 
Diagnosis of the health status of mooring systems for floating offshore wind turbines using autoencoders
(20231101)Floating offshore wind turbines (FOWTs) show promise in terms of energy production, availability, and sustainability, but remain unprofitable due to high maintenance costs. This work proposes a deep learning algorithm to ... 
A simple catch: Fluctuations enable hydrodynamic trapping of microrollers by obstacles
(20230310)It is known that obstacles can hydrodynamically trap bacteria and synthetic microswimmers in orbits, where the trapping time heavily depends on the swimmer flow field and noise is needed to escape the trap. Here, we use ... 
Predictive Maintenance of Floating Offshore Wind Turbine Mooring Lines using Deep Neural Networks
(2022)The recent massive deployment of onshore wind farms has caused controversy to arise mainly around the issues of land occupation, noise and visual pollution and impact on wildlife. Fixed offshore turbines, albeit beneficial ... 
Computational modeling of passive transport of functionalized nanoparticles
(20230314)Functionalized nanoparticles (NPs) are complex objects present in a variety of systems ranging from synthetic grafted nanoparticles to viruses. The morphology and number of the decorating groups can vary widely between ... 
Shape matters: Competing mechanisms of particle shape segregation
(2022)It is wellknown that granular mixtures that differ in size or shape segregate when sheared. In the past, two mechanisms have been proposed to describe this effect, and it is unclear if both exist. To settle this question, ... 
Computational Mesoscale Framework for Biological Clustering and Fractal Aggregation
(20230911)Hierarchical clustering due to diffusion and reaction is a widespread occurrence in natural phenomena, displaying fractal behavior with noninteger size scaling. The study of this phenomenon has garnered interest in both ... 
Numerical simulations of thixotropic semisolid aluminium alloys in openrotor and rotorstator mixers
(20230921)This research uses the BautistaManeroPuig (BMP) model to examine flow patterns of semisolid aluminium alloys (Al) in openrotor and statorrotor mixers via numerical solutions. The model captures the distinct ... 
Geometric Hermite interpolation by rational curves of constant width
(20230928)A constructive characterization of the support function for a rationally parameterized curve of constant width is given. In addition, a Hermite interpolation problem for such kind of curves is solved, which yields a method ... 
Nektar++: Development of the Compressible Flow Solver for Large Scale Aeroacoustic Applications
(2023)A recently developed computational framework for jet noise predictions is presented. The framework consists of two main components, focusing on source prediction and noise propagation. To compute the noise sources, ...