https://hdl.handle.net/10481/17562 2026-04-11T10:27:16Z 2026-04-11T10:27:16Z Nozarela, Guillermo L. Parras-Martos, Francisco Javier Yamamoto, Carolyna Coenen, Wilfried Martínez Bazán, Jesús Carlos Olivares Granados, Gonzalo Ravindra, Vijay M. Gutiérrez-Montes, Cándido Sánchez, Antonio L. https://hdl.handle.net/10481/112701 2026-04-08T12:06:51Z

Patient-specific CFD modeling of CSF flow in Chiari I malformation: denticulate-ligament-induced compartmentalization explains flow patterns Nozarela, Guillermo L.; Parras-Martos, Francisco Javier; Yamamoto, Carolyna; Coenen, Wilfried; Martínez Bazán, Jesús Carlos; Olivares Granados, Gonzalo; Ravindra, Vijay M.; Gutiérrez-Montes, Cándido; Sánchez, Antonio L. Computational fluid dynamics (CFD) has been widely used to study cerebrospinal fluid (CSF) flow in Chiari Malformation Type I (CM-I). However, most approaches rely on limited patient-specific detail, and it remains unclear whether such minimal input is sufficient to yield physiologically realistic flow predictions. In this study, we construct a series of MRI-based models of the craniocervical CSF space in a CM-I patient, complemented with representations of microanatomical features derived from ex vivo measurements and patient MRI data, to assess how CFD predictions are influenced by the choice of boundary conditions in the numerical integrations and the inclusion or omission of nerve roots and denticulate ligaments in the anatomical model. Our results reveal that while increasing patient-specific detail in boundary conditions improves agreement with velocity fields measured via phase-contrast MRI, key flow features—most notably anterior–posterior compartmentalization and bidirectional patterns during flow reversal—only emerge when denticulate ligaments are included in the model. In contrast, inclusion of nerve roots has a more localized effect on the velocity field and a modest impact on pressure drops. Our findings not only clarify how more detailed boundary conditions and improved anatomical fidelity affect velocity and pressure predictions, but also provide a mechanistic explanation for flow patterns commonly observed in CM-I that have remained unexplained, highlighting the critical role of denticulate ligaments. This work was supported by the American Syringomyelia Alliance Project, Inc. through the project Validating an Analytic Model for Cerebrospinal Fluid Flow Across the Foramen Magnum in Children with Chiari I Malformation with Syringomyelia: A Study of Patients Before and After Surgery. The work is part of the coordinated project PID2020-115961RB-C31, PID2020-115961RB-C32, PID2020-115961RA-C33, financed by MCIN/AEI/10.13039/501100011033 and by PID2023-151343NB-C31, PID2023-151343NB-C32, PID2023-151343NB-C33, financed by MICIU/AEI/10.13039/501100011033 and by FEDER, UE.

Bárcenas Luque, A. J. Blyth, M. G. https://hdl.handle.net/10481/111857 2026-03-03T13:20:24Z

The Moffatt–Pukhnachev flow: a new twist on an old problem Bárcenas Luque, A. J.; Blyth, M. G. The flow of a thin viscous film on the outside of a horizontal circular cylinder, whose angular velocity is time-periodic with specified frequency and amplitude, is investigated. The constant angular velocity problem was originally studied by Moffatt (Moffatt 1977 J. Mécanique16, 651–673) and Pukhnachev (Pukhnachev 1977 J. Appl. Mech. Tech. Phys.18, 344–351). Surface tension is neglected. The evolution equation for the film thickness is solved numerically for a range of oscillation amplitudes and frequency. A blow-up map charted in amplitude–frequency space reveals highly intricate fractal-like structures exhibiting self-similarity. For a general initial condition, numerical computations indicate that the film surface reaches a slope singularity at a finite time and tends to overturn. The high-frequency and low-frequency limits are examined asymptotically using a multiple-scales approach. At high frequency, the analysis suggests that an appropriate choice of initial profile can substantially delay the overturning time, and even yield a time-periodic solution. In the low-frequency limit, it is possible to construct a quasi-periodic solution that does not overturn if the oscillation amplitude lies below a threshold value. Above this value, the solution tends inexorably toward blow-up. It is shown how solutions exhibiting either a single-shock or a double-shock may be constructed in common with the steadily rotating cylinder problem.

Cruz, Carlos Bravo Pareja, Rafael Rescalvo Fernández, Francisco José Fuentes-García, Yaiza Lafuente Bolívar, Francisco Javier https://hdl.handle.net/10481/111509 2026-02-25T11:50:11Z

Structural performance and analytical modelling of hybrid pine-poplar glulam beams through efficient use of resources Cruz, Carlos; Bravo Pareja, Rafael; Rescalvo Fernández, Francisco José; Fuentes-García, Yaiza; Lafuente Bolívar, Francisco Javier This paper presents an experimental and analytical study on the structural performance and resource efficiency of hybrid glulam beams manufactured from pine (Pinus nigra) and poplar (Populus × euramericana, clone MC). In hybrid glulam beams, the modulus of elasticity is inherently non-uniform, varying both longitudinally and transversely because individual boards exhibit spatial stiffness variability along their length and across the cross-section. The main objective is to quantify the mechanical benefits of pine-poplar hybridization and to develop a predictive formulation for the beam modulus of elasticity accounting for these longitudinal and transverse stiffness distributions. Single-species and hybrid glulam beams were manufactured from pine and poplar boards and characterized by non-destructive testing and four-point bending tests according to UNE-EN 408. A new analytical formulation was developed to predict the beam modulus of elasticity from the spatial distribution of board elastic moduli, explicitly considering the strategic placement of the highest-stiffness boards in the outer lamellas, where bending stresses are maximum. The results show that this selection and placement increases the modulus of elasticity of hybrid glulam beams by 21 %, reaching values comparable to single-species pine beams, while also increasing flexural strength by 18 % and reducing beam density by 22 %. These findings are relevant for both researchers and the structural timber industry, enabling efficient, lightweight, and competitive hybrid glulam solutions for structural applications. This work was supported by the SMARTTIMBER project “Productos estructurales inteligentes de madera multiespecie para construcción industrializada baja en carbono”, PID2020.114386RB.I00; the LIGHTTIMBER project “Cajones estructurales de madera técnica aligerada para una construcción de baja huella ecológica”, TED2021–130039B-I00; and the GLUCAR project “Pine-poplar-carbon fibre mixed glulam beams of high performance with laminated optimized by using artificial intelligence”, PID2023–148379OA-I00.

Haji Seyed Asadollah, Seyed Babak Sharafati, Ahmad Haghbin, Masoud Motta, Davide Hosseinian Moghadam Noghani, Mohamadreza https://hdl.handle.net/10481/110969 2026-02-13T10:46:08Z

An intelligent approach for estimating aeration efficiency in stepped cascades: optimized support vector regression models and mutual information theory Haji Seyed Asadollah, Seyed Babak; Sharafati, Ahmad; Haghbin, Masoud; Motta, Davide; Hosseinian Moghadam Noghani, Mohamadreza Soft computing (SC) methods have increasingly been used to solve complex hydraulic engineering problems, especially those characterized by high uncertainty. SC approaches have previously proved to be an accurate tool for predicting the aeration efficiency coefficient (E20) in hydraulic structures such as weirs and flumes. In this study, the performance of the standalone support vector regression (SVR) algorithm and three of its hybrid versions, support vector regression–firefly algorithm (SVR-FA), support vector regression–grasshopper optimization algorithm (SVR-GOA), and support vector regression–artificial bee colony (SVR-ABC), is assessed forthe prediction of E20in stepped cascades.Mutualinformationtheoryis usedto constructinput variable combinations for prediction, including the parameters unit discharge (q), the total number of steps (N), step height (h), chute overall length (L), and chute inclination (a). Entropy indicators, such as maximum likelihood, Jeffrey, Laplace, Schurmann–Grassberger, and minimax, are computed to quantify the epistemic uncertainty associated with the models. Four indices—correlation coefficient (R), Nash– Sutcliffe efficiency (NSE), root mean square error (RMSE), and mean absolute error (MAE)—are employed for evaluating the models’ prediction performance. The models’ outputs reveal that the SVR-FA model (with R ¼ 0:947; NSE ¼ 0:888; RMSE ¼ 0:048 and MAE ¼ 0:027 in testing phase) has the best performance among all the models considered. The input variable combination,including q,N, h, andL, providesthe best predictions withthe SVR, SVR-FA, and SVR-GOA models. Fromthe uncertainty analysis, the SVR-FA model shows the closest entropy values to the observed ones (3.630 vs. 3.628 for the ‘‘classic’’ entropy method and 3.647 vs. 3.643 on average for the Bayesian entropy method). This study proves that SC algorithms can be highly accurate in simulating aeration efficiency in stepped cascades and provide a valid alternative to the traditional empirical equation.

Haghbin, Masoud Sharafati, Ahmad Haji Seyed Asadollah, Seyed Babak Motta, Davide https://hdl.handle.net/10481/110968 2026-02-13T10:24:26Z

Developing a generic relation for predicting sediment pick-up rate using symbolic soft computing techniques Haghbin, Masoud; Sharafati, Ahmad; Haji Seyed Asadollah, Seyed Babak; Motta, Davide Sediment pick-up rate has been investigated using experimental and numerical approaches. However, the use of soft computing methods for its prediction has received less attention so far. In this study, genetic programming (GP), grammatical evolution (GE), and gradient boosting machine (GBM) algorithms are employed to develop a relation in dimensionless form for predicting sediment pick-up rate in open channel flow based on two experimental datasets. Dimensionless Froude number, particle diameter, and depth-averaged turbulent kinetic energy are input variables for prediction. Prediction performance is evaluated with performance indices (root mean square error, mean absolute error, and coefficient of correlation), visual comparisons (scatter, dot, and Bland–Altman plots), and uncertainty indicators (Tsallis and Renyi entropies). Three mathematical expressions for sediment pick-up rate prediction are obtained, with GE producing the most accurate results.