Searched for: author%3A%22Bessa%2C+M.A.%22
(1 - 16 of 16)
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Comitti, Alessandro (author), Vijayakumaran, H. (author), Nejabatmeimandi, Mohammad Hosein (author), Seixas, Luis (author), Cabello, Adrian (author), Misseroni, Diego (author), Penasa, Massimo (author), Paech, Christoph (author), Bessa, M.A. (author)
The building construction industry is the largest anthropogenic source of pollution, with massive energy consumption and substantial CO2 emissions. Lightweight tension structures allow the simultaneous implementation of several sustainable strategies by using recyclable low-carbon structural membranes offering a greener alternative to glass and...
book chapter 2024
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Dekhovich, A. (author), Tax, D.M.J. (author), Sluiter, M.H.F. (author), Bessa, M.A. (author)
Current deep neural networks (DNNs) are overparameterized and use most of their neuronal connections during inference for each task. The human brain, however, developed specialized regions for different tasks and performs inference with a small fraction of its neuronal connections. We propose an iterative pruning strategy introducing a simple...
journal article 2024
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Dekhovich, A. (author), Tax, D.M.J. (author), Sluiter, M.H.F. (author), Bessa, M.A. (author)
The human brain is capable of learning tasks sequentially mostly without forgetting. However, deep neural networks (DNNs) suffer from catastrophic forgetting when learning one task after another. We address this challenge considering a class-incremental learning scenario where the DNN sees test data without knowing the task from which this...
journal article 2023
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Xu, M. (author), Shin, D. (author), Sberna, P.M. (author), van der Kolk, R.J.H. (author), Cupertino, A. (author), Bessa, M.A. (author), Norte, R.A. (author)
For decades, mechanical resonators with high sensitivity have been realized using thin-film materials under high tensile loads. Although there are remarkable strides in achieving low-dissipation mechanical sensors by utilizing high tensile stress, the performance of even the best strategy is limited by the tensile fracture strength of the...
journal article 2023
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Dekhovich, A. (author), Turan, O.T. (author), Jiaxiang, Y. (author), Bessa, M.A. (author)
Data-driven modeling in mechanics is evolving rapidly based on recent machine learning advances, especially on artificial neural networks. As the field matures, new data and models created by different groups become available, opening possibilities for cooperative modeling. However, artificial neural networks suffer from catastrophic...
journal article 2023
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Chandrashekar, A. (author), Belardinelli, P. (author), Bessa, M.A. (author), Staufer, U. (author), Alijani, F. (author)
Dynamic atomic force microscopy (AFM) is a key platform that enables topological and nanomechanical characterization of novel materials. This is achieved by linking the nanoscale forces that exist between the AFM tip and the sample to specific mathematical functions through modeling. However, the main challenge in dynamic AFM is to quantify...
journal article 2022
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Sasikumar, Aravind (author), Ninyerola, Joan (author), Ruiz, Ivan (author), Bessa, M.A. (author), Turon Travesa, Albert (author)
Aeronautical industries are concerned about the cost effective generation of design allowables for composite laminates. Design allowables take into account the variabilities arising from different sources (material, manufacturing, defects etc.,) which are determined using expensive and time consuming experimental campaigns....
conference paper 2022
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Ferreira, Bernardo P. (author), Andrade Pires, F. M. (author), Bessa, M.A. (author)
This article introduces adaptivity in Clustering-based Reduced Order Models (ACROMs). The strategy is demonstrated for a particular CROM called Self-Consistent Clustering Analysis (SCA), extending it into the Adaptive Self-Consistent Clustering Analysis (ASCA) method. This is shown to improve predictions of Representative Volume Elements ...
journal article 2022
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Kuś, G.I. (author), van der Zwaag, S. (author), Bessa, M.A. (author)
Gaussian processes are well-established Bayesian machine learning algorithms with significant merits, despite a strong limitation: lack of scalability. Clever solutions address this issue by inducing sparsity through low-rank approximations, often based on the Nystrom method. Here, we propose a different method to achieve better scalability...
journal article 2021
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Shin, D. (author), Cupertino, A. (author), de Jong, M.H.J. (author), Steeneken, P.G. (author), Bessa, M.A. (author), Norte, R.A. (author)
From ultrasensitive detectors of fundamental forces to quantum networks and sensors, mechanical resonators are enabling next-generation technologies to operate in room-temperature environments. Currently, silicon nitride nanoresonators stand as a leading microchip platform in these advances by allowing for mechanical resonators whose motion...
journal article 2021
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Furtado, C. (author), Tavares, R. P. (author), Gomes Pereira, L.P. (author), Salgado, M. (author), Otero, F. (author), Catalanotti, G. (author), Arteiro, A. (author), Bessa, M.A. (author), Camanho, P. P. (author)
This work represents the first step towards the application of machine learning techniques in the prediction of statistical design allowables of composite laminates. Building on data generated analytically, four machine algorithms (XGBoost, Random Forests, Gaussian Processes and Artificial Neural Networks) are used to predict the notched...
journal article 2021
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Kuppens, P.R. (author), Bessa, M.A. (author), Herder, J.L. (author), Hopkins, J. B. (author)
Stiffness in compliant mechanisms can be dramatically altered and even eliminated entirely by using static balancing. This requires elastic energy to be inserted before operation, which is most often done with an additional device or preloading assembly. Adding such devices contrasts starkly with primary motivations for using compliant...
journal article 2021
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Kuppens, P.R. (author), Bessa, M.A. (author), Herder, J.L. (author), Hopkins, J. B. (author)
We introduce two essential building blocks with binary stiffness for mechanical digital machines. The large scale fully compliant mechanisms have rectilinear and rotational kinematics and use a new V-shaped negative stiffness structure to create two extreme states of stiffness by static balancing. The use of a mechanical bistable switch...
journal article 2021
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Zhang, Weizhao (author), Bostanabad, Ramin (author), Liang, Biao (author), Su, Xuming (author), Zeng, Danielle (author), Bessa, M.A. (author), Wang, Yanchao (author), Chen, Wei (author), Cao, Jian (author)
Carbon fiber reinforced plastics (CFRPs) are attracting growing attention in industry because of their enhanced properties. Preforming of thermoset carbon fiber prepregs is one of the most common production techniques of CFRPs. To simulate preforming, several computational methods have been developed. Most of these methods, however, obtain...
journal article 2019
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Bessa, M.A. (author), Głowacki, Piotr (author), Houlder, Michael (author)
Designing future-proof materials goes beyond a quest for the best. The next generation of materials needs to be adaptive, multipurpose, and tunable. This is not possible by following the traditional experimentally guided trial-and-error process, as this limits the search for untapped regions of the solution space. Here, a computational data...
journal article 2019
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Mozaffar, M. (author), Bostanabad, R. (author), Chen, W. (author), Ehmann, K. (author), Cao, J. (author), Bessa, M.A. (author)
Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of...
journal article 2019
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