Facultad de Arquitectura y Urbanismo

Parent Organisation

Universidad UTE

Founding Date

October 2024

Country

City

Quito

Now showing 1 - 10 of 268

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An urban river park restoration assessment model using analytical network process (ANP)
(2019)
Shafaghat, A.
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Jing, K.S.
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Keyvanfar, A.
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Jamshidnezhad, A.
;
Lamit, H.
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An extended ambient intelligence implementation for enhanced human-space interaction
(2016)
Liu Cheng, A.
;
Bier, H.H.
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A treatment wetland park assessment model for evaluating urban ecosystem stability using analytical hierarchy process (AHP)
(2019)
Arezou Shafaghat
;
Ooi Jin Ying
;
Ali Keyvanfar
;
Amir Jamshidnezhad
;
M. Salim Ferwati
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QT interval prolongation and its related factors before and after receiving lopinavir-ritonavir in the COVID-19 era: a historical cohort study
(Elsevier BV, 2026-06)
Jangjou, Ali
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Izadpanah, Payman
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Moqhadas, Mostafa
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Faramarzi, Hosein
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Fahimi, Mohammad Hossein
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Delamination, frequency, and bending analysis of GPLRC curved panel with initial crack via machine learning and three-dimensional layerwise theory
(Elsevier BV, 2025-12)
Xinrong Cao
;
Xiaohong Yang
;
Linyuan Fan
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HABIBI, MOSTAFA
;
Ibrahim Albaijan
In the present study, the thermal stability of graphene-reinforced composite laminates (GPL-RC) with diverse functional gradients and width delamination layers is examined. In this regard, various models of laminated GPL-RC are considered with different geometrical and material parameters. Utilizing the physics-informed neural networks (PINN), we calculate the energy release rate (ERR) at the cleavage boundary, aiming to gauge cleavage growth potential. This study also delves effects of various graphene reinforcement distributions and delamination configurations on the vibrational attributes of delaminated GPL-RC sheets, with an emphasis on pre/post heat bending modalities. Solutions are grounded in the third-order shear strain theory (TSDT), integrating von Karman geometric nonlinearity. Using the principle of minimal potential energy, the nonlinear equilibrium equations are tackled using PINN. Theoretical insights obtained are verified via a comparison to other published studies. Notably, parametric experiments indicate that the ERR in the FGX configuration in which most reinforcement material located adjacent to the upper and lower surfaces of the plate, is double that of the FGA, in which most reinforcement material adjacent to the lower surface of the plate. Moreover, while the FGX sheet's fundamental frequency surpasses other graphene configurations at the primary temperature, its natural frequency in the post-buckling modality is notably the least compared to the entire sample set.
Scopus© Citations 7
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Advancements in nano-enhanced steel structures for earthquake resilience: Integrating metallic elements, AI, and sensor technology for engineering disasters mitigation in steel buildings
(2024)
Xiaoping Zou
;
Gongxing Yan
;
Khidhair Jasim Mohammed
;
Meldi Suhatril
;
Mohamed Amine Khadimallah
This study develops Titanium (Ti) and Magnesium (Mg)-based nano-alloys to enhance the earthquake resilience of steel structures using machine learning (SVM) and sensor technology. Embedding Ti and Mg into steel at the nanoscale creates a lightweight, durable, and flexible material capable of withstanding seismic forces. Ti enhances tensile strength and flexibility, while Mg reduces weight, lowering seismic loads on buildings. The performance of these nano-alloys was assessed through shake table tests, cyclic load testing, and dynamic response testing, showing that nano-alloy-enhanced steel structures experienced 60% less displacement and 40% lower acceleration than traditional steel, demonstrating superior energy absorption and stress distribution. Fatigue tests revealed that the nano-alloy could endure 20, 000 loading cycles, outperforming the 8, 000 cycles of conventional steel. Integrated sensor technology, including strain gauges and accelerometers, provided real-time stress and deformation data, confirming the material’s effectiveness in stress distribution and vibration damping. The SVM model optimized alloy composition, achieving 94% prediction accuracy in assessing seismic performance, highlighting the nano-alloys' durability and resilience. This study suggests that Ti and Mg nano-alloys could greatly improve earthquake-resistant construction.
Scopus© Citations 2
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The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management
(Elsevier BV, 2023-12)
Hesam Kamyab
;
Tayebeh Khademi
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Shreeshivadasan Chelliapan
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Morteza SaberiKamarposhti
;
Shahabaldin Rezania
Scopus© Citations 287
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Unveiling shear performance and structural integrity of studs in steel-concrete composite structures
(Elsevier BV, 2024-03)
Xiang Yang
;
Jiang Daibo
;
Meldi Suhatril
;
Ibrahim Albaijan
;
Hamad Almujibah
Advancements in modern bridge engineering have led to the development of thinner and lighter steel-concrete composite structures. Ultrahigh-performance concrete (UHPC) has emerged as a cutting-edge solution to enhance performance and expedite construction. This research investigates the failure modes and load-slip relationships of short studs shear connectors in steel-thin UHPC composite structures (STUCs) through push-out testing. Experimental results demonstrate that fracture of the stud shank and local concrete crushing are the primary failure modes observed in all specimens. Increasing the stud diameter enhances shear strength, while dense arrangements of short studs and reduced stud height decrease the shear capacity of individual studs. The D19 and D22 studs exhibit significantly higher elasticity moduli (237.7 GPa and 221.4 GPa, respectively) compared to the UHPC layer (45.67 GPa) and the steel girder made of Q235B (216.2 GPa), indicating greater stiffness. The ultimate tensile strength is highest for the D19 stud (487.16 MPa), followed closely by the D22 stud (453.29 MPa) and the steel girder (425.03 MPa), while the UHPC layer shows a considerably lower ultimate strength of 129.01 MPa. All metal components (D19 and D22 studs and steel girder) have a uniform poisson ratio of 0.3, suggesting similar deformation characteristics under stress, in contrast to the UHPC layer's lower ratio of 0.216. Comparisons with existing construction specifications indicate conservative predictions of shear capacity for short studs in thin UHPC layers.
Scopus© Citations 2
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Adsorptive Removal of Simazine Using UiO-66@Al2O3/Activated Carbon Nanocomposites
(Springer Science and Business Media LLC, 2026-06-13)
HESAM, KAMYAB
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Khademi, Tayebeh
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Chelliapan, Shreeshivadasan
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Yuzir, Ali
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Shanmugapriya, D.
Scopus© Citations 2
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A study on improving energy flexibility in building engineering through generalized prediction models: Enhancing local bearing capacity of concrete for engineering structures
(Elsevier BV, 2024-03)
HuaDong Li
;
Jie Zeng
;
Ahmad Almadhor
;
Anis Riahi
;
Hamad Almujibah
Load-bearing in structural engineering involves a structure's ability to support and distribute weight effectively. This research investigates innovative methods to enhance load-bearing capabilities while optimizing energy flexibility within structural systems. Accurately predicting the local bearing capacity of concrete is not only vital for ensuring structural stability in building engineering, especially in anchorage zones, but also for promoting environmental sustainability through optimized material use. Existing prediction models, primarily designed for ordinary-strength concrete, often overlook the nuanced influence of concrete strength and ducts. This oversight can lead to substantial inaccuracies when these models are applied to high-strength and ultra-high-strength concrete. To holistically address these challenges, this study introduces generalized prediction models that factor in crucial elements such as concrete strength, local area aspect ratio, and ducts. The results show that the Mean of the GB50010-2010 model, CECS104:99 model, and ACI318-19 model ranged from 0.845 to 0.937, which might overestimate the experimental data with high variation, while the AASHTO model might underestimate the local bearing capacity of concrete, with a mean value of 1.045. The SD, MAPE, RMSE, IAE, R2, and α20 index were approximately within the range of 0.12–0.19, 0.14–0.24, 227–373, 2.4–3.4%, 0.7–0.9, 0.6–0.9 for the existing models, and 0.11–0.13, 0.09–0.1, 176–178 1.95–1.96%, 0.93–0.94, 0.90–0.91 for FA model and ANN models. This indicated that the proposed FA model and ANN model outperformed all the existing normative models used for concrete local bearing capacity.
Scopus© Citations 7

Facultad de Arquitectura y Urbanismo

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