Facultad de Ciencias, Ingeniería y Construcción

Parent Organisation

Universidad UTE

Founding Date

October 2024

Country

City

Quito

Now showing 1 - 10 of 17

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Thermodynamics-Informed Neural Networks for the Design of Solar Collectors: An Application on Water Heating in the Highland Areas of the Andes
(MDPI AG, 2024-10-05)
Mauricio Cáceres
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ÁVILA VEGA, CARLOS FABIÁN
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RIVERA TAPIA, EDGAR DAVID
This study addresses the challenge of optimizing flat-plate solar collector design, traditionally reliant on trial-and-error and simplified engineering design methods. We propose using physics-informed neural networks (PINNs) to predict optimal design conditions in a range of data that not only characterized the highlands of Ecuador but also similar geographical locations. The model integrates three interconnected neural networks to predict global collector efficiency by considering atmospheric, geometric, and physical variables, including overall loss coefficient, efficiency factors, outlet fluid temperature, and useful heat gain. The PINNs model surpasses traditional simplified thermodynamic equations employed in engineering design by effectively integrating thermodynamic principles with data-driven insights, offering more accurate modeling of nonlinear phenomena. This approach enhances the precision of solar collector performance predictions, making it particularly valuable for optimizing designs in Ecuador’s highlands and similar regions with unique climatic conditions. The ANN predicted a collector overall loss coefficient of 5.199 W/(m2·K), closely matching the thermodynamic model’s 5.189 W/(m2·K), with similar accuracy in collector useful energy gain (722.85 W) and global collector efficiency (33.68%). Although the PINNs model showed minor discrepancies in certain parameters, it outperformed traditional methods in capturing the complex, nonlinear behavior of the data set, especially in predicting outlet fluid temperature (55.05 °C vs. 67.22 °C).
Scopus© Citations 6
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Beyond Prescriptive Codes: A Validated Linear–Static Methodology for Seismic Design of Soft-Storey RC Structures
(MDPI AG, 2025-12-23)
Daniel Rios
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Marco Altamirano
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ILBAY YUPA, DANIEL JEFFERSON
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TLAPANCO LIMÓN, JUAN FRANCISCO
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RIVERA TAPIA, EDGAR DAVID
Reinforced concrete buildings with masonry-induced soft-storey irregularities exhibit extreme seismic vulnerability, a critical risk often underestimated by conventional code-based design. Standard equivalent static methods typically fail to capture the intense concentration of seismic demand at the flexible ground level, leading to unconservative designs that do not meet performance objectives. This research proposes a corrective linear–static methodology to address this deficiency. A new Equivalent Lateral Force profile (ELFi1) was developed, derived from modal analyses of 235 representative soft-storey archetypes to accurately account for stiffness heterogeneity. This profile was integrated with a realistic response modification coefficient (Ri1 = 5.04), determined to be 37% lower than the normative R-factor (R = 8) prescribed by code. Nonlinear static analyses confirmed that conventional design resulted in “irreparable” damage (mean Global Damage Index = 0.82). In contrast, redesigning the structure using the proposed ELFi1 and Ri1 methodology successfully mitigated damage concentration, upgrading structural performance to a “repairable” state (mean Global Damage Index = 0.52). Finally, Incremental Dynamic Analysis validated the approach; the redesigned structure satisfied FEMA P695 collapse prevention criteria, achieving an Adjusted Collapse Margin Ratio (ACMR) of 2.10. This study confirms the proposed method is a robust and practical design alternative for soft-storey mechanisms within a simplified linear framework.
Scopus© Citations 1
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Island ecosystems unleashed: rain gardens transforming flood management in Galápagos
(Informa UK Limited, 2025-12-31)
J Almeida
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O Proaño
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ÁVILA VEGA, CARLOS FABIÁN
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D Villacres
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RIVERA TAPIA, EDGAR DAVID
This article delineates a sustainable stormwater drainage system designed to prevent floods in Santa Cruz Island, specifically in Puerto Ayora. The proposal prioritizes minimizing human intervention impact on infrastructure, considering the local context. A comprehensive environmental analysis covering topography, climate, hydrology, urban, and landscape aspects informs the design, ensuring adaptability to the island’s future needs. The core features a channel drainage system incorporating gutters, sinks, and filter gardens. Filter gardens retain stormwater, allowing controlled discharge, interconnected from house downspouts to channels. Three strategically proposed drainage systems connect to different discharge points: a lake, an aquifer, and the sea. This diverse approach avoids large excavations, reducing costs and preserving local flora and fauna. The result is a sustainable drainage solution aligned with a nature-based paradigm, effectively reducing runoff flow.
Scopus© Citations 2
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Parametric Research of Granular Flow in Silos: A Micro- Mechanical Approach
(Escuela Politecnica Nacional, 2023-11-14)
RIVERA TAPIA, EDGAR DAVID
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Alvaro Ávila
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ÁVILA VEGA, CARLOS FABIÁN
<jats:p>El estudio del material granular almacenado en silos se lo ha realizado habitualmente con las formulaciones de la mecánica del medio continuo y los elementos finitos. Sin embargo, existen diversas limitaciones al cuantificar la interacción entre partículas y su comportamiento individual. Por lo tanto, se plantea la utilización del método del elemento discreto (DEM) para evitar las limitaciones intrínsecas de modelos continuos en el análisis del flujo de maíz (materia granular) durante los procesos de descarga en silos. El elemento discreto es una eficaz herramienta mecánico-computacional que permite modelar ensambles granulares al considerar sus propiedades físicas y mecánicas tanto al nivel individual como de conglomerado. En esta investigación, los ensambles diseñados son representaciones numéricas de granos de maíz almacenado en silos. Los resultados de las simulaciones se cuantifican en términos de perfiles de velocidad, cadenas de fuerza, esfuerzos en las paredes del silo, y deformaciones del conglomerado granular. Uno de los principales hallazgos de esta investigación es la importancia del ángulo de reposo del maíz en la descarga de silos ya que los esfuerzos, deformaciones y cadenas de fuerza varían dependiendo de este valor (27°).</jats:p>
Scopus© Citations 1
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Triclosan removal from synthetic solution using corn cobs and their magnetic composites: Insights from batch adsorption and fixed-bed column studies
(Elsevier BV, 2025-06-01)
Cristina E. Almeida Naranjo
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Fabián Santana-Romo
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GALLEGOS CASTRO, ELVIA DEL CARMEN
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Cristina Alejandra Villamar Ayala
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Debut, Alexis
Triclosan, a lipophilic contaminant and endocrine disruptor, is widely detected in industrial, pharmaceutical, and domestic wastewaters. Organic residues impregnated with nanoparticles could be efficient adsorbents for such contaminants. This study evaluated the efficiency of corn cobs (CC), iron oxide (IO), and their magnetic composites in removing triclosan (30 mg L−1) using batch and fixed-bed column tests. Adsorbents were characterized by analytical (ASTM standards), instrumental (microscopy, spectroscopy, BET, X-ray diffraction), and computational methods. Batch tests analyzed CC/IO/composite doses (0.001–2.5 g L−1), contact times (2.5–60 min), and CC ratios (1:1, 2:1, 4:1). Results fit kinetic and isothermal models. Fixed-bed columns used CC and 4CC:1IO (most efficient). CC contained ∼94.2 % lignocellulosic material, an irregular surface with 0.4 m² g−1, and functional groups (OH, C[dbnd]O, C-O-H). IOs (∼15 nm) had a surface area of 66.3 m²/g, while composites ranged from 1.4 to 2.2 m² g−1. Optimal doses were 2.0 g L−1 for CC and 3.75–25-fold for IO/composites, removing 84.7–94.1 % triclosan within 40–60 min. Data fit the pseudo-second order model (R² = 0.89–0.99) and isotherms aligned with Langmuir and Sips models (R² = 0.97–0.99). In fixed-bed columns, CC and 4CC:1IO reached saturation at 700 and 1250 min, respectively, fitting the Bohart-Adams model (R² = 0.93–0.98). Computational chemistry elucidated triclosan removal mechanisms related to its lipophilicity, solubility, and reactive lignocellulosic sites. CC and their composites are effective, sustainable, and low-cost alternatives for removing triclosan and other lipophilic emerging contaminants, with potential for broader water treatment applications. This study evaluated the adsorption capacity of the materials for triclosan removal, incorporating kinetic models, breakthrough curves, and computational simulations to understand the removal mechanisms.
Scopus© Citations 12
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Toward Responsible AI in High-Stakes Domains: A Dataset for Building Static Analysis with LLMs in Structural Engineering
(MDPI AG, 2025-10-24)
ÁVILA VEGA, CARLOS FABIÁN
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ILBAY YUPA, DANIEL JEFFERSON
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Paola Tapia
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RIVERA TAPIA, EDGAR DAVID
Modern engineering increasingly operates within socio-technical networks, such as the interdependence of energy grids, transport systems, and building codes, where decisions must be reliable and transparent. Large language models (LLMs) such as GPT promise efficiency by interpreting domain-specific queries and generating outputs, yet their predictive nature can introduce biases or fabricated values—risks that are unacceptable in structural engineering, where safety and compliance are paramount. This work presents a dataset that embeds generative AI into validated computational workflows through the Model Context Protocol (MCP). MCP enables API-based integration between ChatGPT (GPT-4o) and numerical solvers by converting natural-language prompts into structured solver commands. This creates context-aware exchanges—for example, transforming a query on seismic drift limits into an OpenSees analysis—whose results are benchmarked against manually generated ETABS models. This architecture ensures traceability, reproducibility, and alignment with seismic design standards. The dataset contains prompts, GPT outputs, solver-based analyses, and comparative error metrics for four reinforced concrete frame models designed under Ecuadorian (NEC-15) and U.S. (ASCE 7-22) codes. The end-to-end runtime for these scenarios, including LLM prompting, MCP orchestration, and solver execution, ranged between 6 and 12 s, demonstrating feasibility for design and verification workflows. Beyond providing records, the dataset establishes a reproducible methodology for integrating LLMs into engineering practice, with three goals: enabling independent verification, fostering collaboration across AI and civil engineering, and setting benchmarks for responsible AI use in high-stakes domains.
Scopus© Citations 4
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In Pursuit of Healthier Learning Environments: High‐Altitude Classroom Ventilation
(Wiley, 2024-01)
ÁVILA VEGA, CARLOS FABIÁN
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Paola Tapia
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Ricardo Vallejo
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Alvaro Ávila
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RIVERA TAPIA, EDGAR DAVID
This study addresses the critical issue of indoor air quality (IAQ) and pathogen transmission within enclosed spaces at high altitudes, focusing on university classrooms in Quito, an Andean city in South America. The aim is to establish safety thresholds for room occupancy and permissible durations of exposure, tailored to this unique environmental context. Through an experimental approach conducted at an elevation of 2900 m above sea level, various natural ventilation strategies were evaluated for their efficacy in mitigating pathogen transmission risks. The study employs the Concentration Decay Test Method to characterize air changes per hour (ACH) and utilizes the Bazant mathematical model to predict occupancy levels based on ventilation, dimensions of the room, respiratory activity, infectiousness rates, and other parameters. Findings highlight the significant impact of ventilation strategies on room occupancy. Notably, higher infectiousness rates and large exposure times drastically reduce permissible occupancy levels, underscoring the importance of effective ventilation in maintaining safety. This research contributes valuable insights for informed decision‐making regarding classroom capacity and safety protocols in Andean higher education settings.
Scopus© Citations 1
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Morphological characterization of the hippocampus: a first database in Ecuador
(Frontiers Media SA, 2024-10-18)
Stefano Buitrón Cevallos
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Alex X. Jerves
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Clayreth Vinueza
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Dennis Hernandez
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ÁVILA VEGA, CARLOS FABIÁN
Introduction: The hippocampal volume is a well-known biomarker to detect and diagnose neurological, psychiatric, and psychological diseases. However, other morphological descriptors are not analyzed. Furthermore, not available databases, or studies, were found with information related to the hippocampal morphology from Latin-American patients living in the Andean highlands. Methods: The hippocampus is manually segmented by two medical imaging specialists on normal brain magnetic resonance images. Then, its morphological qualitative and quantitative descriptors (volume, sphericity, roundness, diameter, volume-surface ratio, and aspect ratio) are computed via 3D digital level-set-based mathematical representation. Furthermore, other morphological descriptors and their possible correlation with the hippocampal volume is analyzed. Results: We introduce a first database with the hippocampus’ morphological characterization of 63 patients from Quito, Ecuador, male and female, aged between 18 and 95 years old. Discussion: This study provides new research opportunities to neurologists, psychologists, and psychiatrists, to further understand the hippocampal morphology of Andean and Latin American patients.
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Pineapple-crown papers with partial NaOH substitution: Performance, costs, and life-cycle footprints
(Elsevier BV, 2026-02)
Ginger Capa
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Cinthia González
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GALLEGOS CASTRO, ELVIA DEL CARMEN
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Patricia Alba
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Edwin Vera
Non-wood agro-residues can reduce the environmental and cost burdens of papermaking, yet process alkalinity often drives impacts. Pineapple crowns were valorized as fiber feedstock and evaluated partial substitution of NaOH with NaHCO3 during processing, using NaOH–NaHCO3 ratios of 1:0, 3:1, and 1:1 (P100:0, P75:25, P50:50). Physical (grammage, thickness, porosity, burst, pH, water uptake) and instrumental characterizations, including Fourier-transform infrared spectroscopy (FTIR), thermogravimetric and derivative thermogravimetric analysis (TGA/DTGA), and scanning electron microscopy (SEM), were coupled with cradle-to-gate life-cycle (CF: carbon footprint; WF: water footprint) and unit-cost analyses. P75:25 achieved the highest grammage (71.86 ± 0.49 g/m2) and balanced network consolidation, while P100:0 maximized burst (19.53 ± 0.91 psi); P50:50 increased porosity and moisture uptake. TGA/DTGA indicated effective polysaccharide/lignin breakdown for P100:0 and P75:25, with elevated high-temperature residue in P50:50, aligning with SEM-resolved fiber compaction. Environmental results decreased monotonically with sodium-bicarbonate substitution: total CF = 0.25, 0.22 (−12 %), and 0.19 kg CO2-eq for P100:0, P75:25, and P50:50. WF per sheet was 6.56, 3.72, and 3.28 L for P100:0, P75:25, and P50:50, respectively. Despite lab-scale costs (≈4.0 USD/sheet), sensitivity indicates reagent price and electricity as main levers. Overall, P75:25 offers the best performance-to-impact trade-off preserving mechanical integrity while lowering CF and WF vs P100:0 supporting pineapple-crown papers as credible candidates for lightweight packaging and printing.
Scopus© Citations 2
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The Influence of Abaca Fiber Treated with Sodium Hydroxide on the Deformation Coefficients Cc, Cs, and Cv of Organic Soils
(MDPI AG, 2024-10-15)
Carlos Contreras
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Jorge Albuja-Sánchez
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Oswaldo Proaño
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ÁVILA VEGA, CARLOS FABIÁN
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Andreína Damián Chalán
This study shows the influence of the inclusion of abaca fiber (Musa Textilis) on the coefficients of consolidation, expansion, and compression for normally consolidated clayey silt organic soil specimens using reconstituted samples. For this purpose, abaca fiber was added according to the dry mass of the soil, in lengths (5, 10, and 15 mm) and concentrations (0.5, 1.0, and 1.5%) subjected to a curing process with sodium hydroxide (NaOH). The virgin and fiber-added soil samples were reconstituted as slurry, and one-dimensional consolidation tests were performed in accordance with ASTM D2435. The results showed a reduction in void ratio (compared to the soil without fiber) and an increase in the coefficient of consolidation (Cv) as a function of fiber concentration and length, with values corresponding to 1.5% and 15 mm increasing from 75.16 to 144.51 cm2/s. Although no significant values were obtained for the compression and expansion coefficients, it was assumed that the soil maintained its compressibility. The statistical analysis employed hierarchical linear models to assess the significance of the effects of incorporating fibers of varying lengths and percentages on the coefficients, comparing them with the control samples. Concurrently, mixed linear models were utilized to evaluate the influence of the methods for obtaining the Cv, revealing that Taylor’s method yielded more conservative values, whereas the Casagrande method produced higher values.
Scopus© Citations 3

Facultad de Ciencias, Ingeniería y Construcción

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