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An advanced inverse modeling framework for efficient and flexible adjoint-based history matching of geothermal fields

Tian, X. (author), Volkov, Oleg (author), Voskov, D.V. (author)

In this study, we present an efficient and flexible adjoint-based framework for history matching and forecasting geothermal energy extraction at a large scale. In this framework, we applied the Principal Component Analysis to reduce the parameter space for representing the complex geological model. The adjoint method is implemented for...

journal article 2024

document

Automatic detection of bulldozer-induced changes on a sandy beach from video using YOLO algorithm

Barbero García, I. (author), Kuschnerus, M. (author), Vos, S.E. (author), Lindenbergh, R.C. (author)

Sandy beaches are subject to changes due to multiple factors, that are both natural (e.g. storms) and anthropogenic. Great efforts are being made to monitor these ecosystems and understand their dynamics in order to assure their conservation. The identification of anthropogenic changes and its differentiation from natural ones is an important...

journal article 2023

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From an ellipsoid-based to an anthropomorphic articulated total body model for multibody applications

Pascoletti, G. (author), Huysmans, T. (author), Molenbroek, J.F.M. (author), Zanetti, E. M. (author)

Human computer models represent a useful tool for investigating the human body response to external static/dynamic loads or for human-centred design. Articulated Total Body (ATB) models are the simplest human multibody models, where body segments are represented by ellipsoids joined at skeletal articulations. Over the years, regression models...

journal article 2023

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Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks

Guendel, Ronny (author), Ullmann, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)

Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a...

conference paper 2023

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Machine learning assisted early anomaly detection of LEDs with spectral power distribution modeling

Liu, Minne (author), Ibrahim, Mesfin S. (author), Wen, Minzhen (author), Li, Sheng (author), Wang, An (author), Zhang, Kouchi (author), Fan, J. (author)

Spectral power distribution (SPD) is the radiation power intensity at different wavelengths, containing the most basic photometric and colorimetric performance of the illuminant, which is able to predict the lifetime of LEDs. This paper proposes an SPD model assisted by machine learning algorithms to detect the early failure of white LEDs. The...

conference paper 2023

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Damage Mode Identification of CFRP-Strengthened Beam Based on Acoustic Emission Technique

Pan, Tanbo (author), Zheng, Yonglai (author), Zhou, Y. (author), Wu, Zhuorui (author), Zhou, Yujue (author)

Externally bonded (EB) carbon fiber reinforced polymer (CFRP) is widely used in structural strengthening and retrofitting. Premature debonding of the FRP severely limits the efficiency of CFRP utilization. The application of CRRP anchorage system offers a solution to the debonding problem. However, the understanding of damage mode identification...

conference paper 2023

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Inter-Annual and Seasonal Variability of Flows: Delivering Climate-Smart Environmental Flow Reference Values

Salinas Rodriquez, Sergio (author), van de Giesen, N.C. (author), McClain, M.E. (author)

Environmental flow (eflow) reference values play a key role in environmental water science and practice. In Mexico, eflow assessments are set by a norm in which the frequency of occurrence is the managing factor to integrate inter-annual and seasonal flow variability components into environmental water reserves. However, the frequency parameters...

journal article 2022

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Hydro-Geochemical Applications and Multivariate Analysis to Assess the Water–Rock Interaction in Arid Environments

Mohamed, Ahmed (author), Asmoay, Ahmed (author), Alshehri, Fahad (author), Abdelrady, Ahmed (author), Othman, Abdullah (author)

Thirty groundwater samples were taken from Assiut’s northern outskirts. The physicochemical properties of these samples were investigated. For the evaluation of water–rock interaction, the saturation index (SI), chloro-alkaline indices (CAI1 and CAI2), Gibbs ratios for cations and anions (GC and GA), principal component analysis (PCA), and...

journal article 2022

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Cluster-based identification algorithm for in-line recycled concrete aggregates characterization using Laser-Induced Breakdown Spectroscopy (LIBS)

Chang, C. (author), Di Maio, F. (author), Rem, P.C. (author), Gebremariam, A.T. (author), Mehari, Fanuel (author), Xia, Han (author)

To upcycle End-of-Life (EoL) concrete from demolished buildings, it is essential to efficiently identify the different materials that may contaminate it. The precise identification and classification of materials and contaminants are vital processes for in-line quality inspection of recycled concrete aggregates transported on a conveyor belt....

journal article 2022

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Evaluation of a Morphable Anthropomorphic Articulated Total Body Model

Pascoletti, Giulia (author), Huysmans, T. (author), Conti, Paolo (author), Zanetti, Elisabetta M. (author)

In this work a new approach for the creation of Articulated Total Body (ATB) models for person-specific multi-body simulations is presented, with the main aim of overcoming limitations related to classical multi-ellipsoids ATB models, based on regression equations having only the weight and the height of the subject as input. The new...

conference paper 2022

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Identifying and Characterizing Conveyor Belt Longitudinal Rip by 3D Point Cloud Processing

Xu, Shichang (author), Cheng, Gang (author), Pang, Y. (author), Jin, Zujin (author), Kang, Bin (author)

Real-time and accurate longitudinal rip detection of a conveyor belt is crucial for the safety and efficiency of an industrial haulage system. However, the existing longitudinal detection methods possess drawbacks, often resulting in false alarms caused by tiny scratches on the belt surface. A method of identifying the longitudinal rip through...

journal article 2021

document

How to compare knee kinetics at different walking speeds?

Meinders, Evy (author), Booij, Marjolein J. (author), van den Noort, Josien C. (author), Harlaar, J. (author)

Background: Walking speed is a confounding factor in biomechanical analyses of gait, but still many studies compare gait biomechanics at comfortable walking speed (CWS) that is likely to differ between groups or conditions. To identify gait deviation unrelated to walking speed, methods are needed to correct biomechanical data over the gait...

journal article 2021

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The variation in 3D face shapes of dutch children for mask design

Goto, L. (author), Lee, Wonsup (author), Huysmans, T. (author), Molenbroek, J.F.M. (author), Goossens, R.H.M. (author)

The use of 3D anthropometric data of children’s heads and faces has great potential in the development of protective gear and medical products that need to provide a close fit in order to function well. Given the lack of detailed data of this kind, the aim of this study is to map the size and shape variation of Dutch children’s heads and...

journal article 2021

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Data-Driven Incipient Fault Detection via Canonical Variate Dissimilarity and Mixed Kernel Principal Component Analysis

Wu, P. (author), Ferrari, Riccardo M.G. (author), Liu, Y. (author), van Wingerden, J.W. (author)

Incipient fault detection plays a crucial role in preventing the occurrence of serious faults or failures in industrial processes. In most industrial processes, linear, and nonlinear relationships coexist. To improve fault detection performance, both linear and nonlinear features should be considered simultaneously. In this article, a novel...

journal article 2021

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What motivates stakeholders to engage in collaborative innovation in the infrastructure megaprojects?

Chen, Xiaoyan (author), He, Qinghua (author), Zhang, Xinyue (author), Cao, Tingting (author), Liu, Y. (author)

Collaborative innovation has become an innovation paradigm to improve innovation performance and firms’ economic output. However, there is relatively little research investigating stakeholders’ drivers for engaging in collaborative innovation and the relative importance of drivers in infrastructure megaprojects. This research aims to address...

journal article 2021

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On the use of machine learning models for prediction of compressive strength of concrete: Influence of dimensionality reduction on the model performance

Wan, Z. (author), Xu, Y. (author), Šavija, B. (author)

Compressive strength is the most significant metric to evaluate the mechanical properties of concrete. Machine learning (ML) methods have shown promising results for predicting compres-sive strength of concrete. However, at present, no in-depth studies have been devoted to the influence of dimensionality reduction on the performance of...

journal article 2021

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EquiSim: An Open-Source Articulatable Statistical Model of the Equine Distal Limb

Van Houtte, Jeroen (author), Vandenberghe, Filip (author), Zheng, Guoyan (author), Huysmans, T. (author), Sijbers, Jan (author)

Most digital models of the equine distal limb that are available in the community are static and/or subject specific; hence, they have limited applications in veterinary research. In this paper, we present an articulatable model of the entire equine distal limb based on statistical shape modeling. The model describes the inter-subject...

journal article 2021

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Multivariate and location-specific correlates of fuel consumption: A test track study

Melman, T. (author), Abbink, D.A. (author), Mouton, Xavier (author), Tapus, Adriana (author), de Winter, J.C.F. (author)

Current predictors of fuel consumption are typically based on computer simulations or data collections in real traffic, where the route and vehicle type are not under the researcher's control. Here, we predicted fuel consumption using test track data, an approach that allowed for location-specific predictions. Ninety-one drivers drove a total...

journal article 2021

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A dynamic OD prediction approach for urban networks based on automatic number plate recognition data

Liu, Jing (author), Zheng, Fangfang (author), van Zuylen, H.J. (author), Li, Jie (author)

OD flows provide important information for traffic management and planning. The prediction of dynamic OD matrices gives the possibility to apply anticipatory traffic management measures. In this paper, we propose an OD prediction approach based on the data obtained by Automated Number Plate Recognition (ANPR) cameras. The principal component...

journal article 2020

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Accelerating a geometrical approximated PCA algorithm using AVX2 and CUDA

Machidon, Alina L. (author), Machidon, Octavian M. (author), Ciobanu, C.B. (author), Ogrutan, Petre L. (author)

Remote sensing data has known an explosive growth in the past decade. This has led to the need for efficient dimensionality reduction techniques, mathematical procedures that transform the high-dimensional data into a meaningful, reduced representation. Projection Pursuit (PP) based algorithms were shown to be efficient solutions for...

journal article 2020