Dpto. Construcciones Arquitectónicas, Ingeniería del Terreno y Mecánica de los Medios Continuos ...

De residuo voluminoso a recurso constructivo. Reciclaje de colchones para arquitectura circular

Wed, 01 Jan 2025 00:00:00 GMT

RESTBUILT es un proyecto de investigación desarrollado en la Universidad de Valladolid con el apoyo del Ayuntamiento de Valladolid,, centrado en la valorización de colchones fuera de uso como materia prima para la construcción, dentro de un enfoque de economía circular. La investigación plantea una estrategia basada en el aprovechamiento integral del colchón, sin desmontaje previo, lo que permite simplificar el procesado y reducir significativamente los costes de transformación. Tras un análisis inicial del contexto del residuo- mediante trabajo de campo, visitas técnicas se definieron las bases metodológicas del proyecto. El material fue obtenido con la colaboración de FCC Medio Ambiente y el CTR de Alicante, y se empleó en dos líneas experimentales complementarias. La Universidad de Valladolid desarrolló prototipos de paneles térmico-acústicos a partir de triturado grueso, mientras que la Universidad de Burgos investigó el triturado fino en morteros aligerados. Esta doble aproximación permitió evaluar distintas posibilidades de aplicación. Finalmente, se incorporó un análisis de viabilidad industrial y se promovió una estrategia activa de divulgación a través de publicaciones científicas, congresos, exposiciones y colaboraciones académicas.

Construcción circular: nuevos caminos para el reciclaje y la reutilización en arquitectura

Wed, 01 Jan 2025 00:00:00 GMT

Comparative energy assessment of three glazed courtyard roof designs in a cold climate heritage building

Thu, 01 Jan 2026 00:00:00 GMT

The use of translucent roofs over courtyards in historic buildings has become a common strategy in rehabilitation projects. However, many of these interventions are carried out without bioclimatic or energy-efficiency criteria, leading to risks of overheating and thermal discomfort, particularly during summer. This issue is expected to worsen with climate change, compromising the habitability of these spaces. This study compares the thermal and energy performance of three glazed roof configurations: a triangulated dome, a flat roof, and a south-facing sawtooth roof with vertical glazing. The case study is a Renaissance courtyard located in Burgos, Spain (continental Mediterranean climate). Dynamic simulations using EnergyPlus and Ecotect evaluate solar exposure, annual heating and cooling demand, free-running thermal behavior, and daylight availability. Results show that roof geometry has a decisive impact on energy efficiency. The sawtooth solution eliminates cooling demand under passive operation and maintains thermal comfort (20–25 °C) throughout the year while ensuring daylight levels above 4000 lx. These findings support the use of passive geometric strategies to improve climate adaptation in enclosed heritage courtyards. The methodology is replicable in similar cold-climate contexts and offers practical guidance for energy-efficient retrofitting of historic buildings.

Application Of A Tool To Estimate The Level Of Airtightness Of Residential Buildings

Wed, 01 Jan 2025 00:00:00 GMT

Estimating airtightness is challenging due to variability in influencing factors. Existing models face limitations such as a lack of standardization, sensitivity to construction quality, insufficient representative data, and complexity that reduce their practical utility for designers. This work explores the application of a predictive approach from measured data using Generalized Linear Models (GLIM) that is applicable across diverse construction scenarios. The model incorporates 13 main variables and 4 interaction terms, which explain almost 50% of the variability in airtightness (n50). A typical case study has been chosen in order to show the model’s application, making it user-friendly. This example explores the criteria followed for each variable and building characteristics so that the model can be easily extrapolated to other contexts and applied to other cases.

Assessment of VOCs concentrations in Spanish dwellings: Acetone, toluene, xylene, alpha-pinene and limonene

Thu, 01 Jan 2026 00:00:00 GMT

The presence of certain Volatile Organic Compounds (VOCs) indoors represents a potential concern for occupant health, especially in dwellings with limited ventilation. In this context, the study analyzed the presence of five health-related VOCs (Acetone, Toluene, Xylene, α-Pinene, and Limonene) in Spanish dwellings. This research addresses a significant data gap, as Spain did not participate in similar European indoor air quality campaigns (INDEX or IEA-EBC Annex 68 projects). The main objective of the study was to characterize the indoor air quality in these dwellings and compare the findings with comparable data. The concentrations of these pollutants were measured in different rooms of 29 occupied dwellings located in a continental climate in Spain during the winter period, using solid-phase microextraction coupled with gas chromatography with a flame ionization detector (SPME-GC-FID), under typical winter conditions of reduced ventilation. The results revealed the widespread presence of some compounds in most dwellings, while others were only occasionally detected, associated with specific household activities. The main sources identified were cleaning products, cosmetics, and furnishings. Acetone and Limonene showed the highest concentrations, consistent with their frequent household use, while Toluene and Xylene demonstrated lower levels consistent with the decline in their traditional sources (paints, solvents, tobacco); α-Pinene, meanwhile, was detected at very low levels, possibly due to recent changes in household product formulations. These findings emphasise the importance of ventilation, especially during winter, in reducing VOC accumulation and highlight the need to broaden the regulatory focus on indoor air quality beyond carbon dioxide.

Diagnosis and assessment of a historic timber structure in La Casa del Corregidor, using non-destructive techniques

Sun, 01 Jan 2023 00:00:00 GMT

This paper presents the assessment of the timber structure of “La Casa del Corregidor” building, a singular historic building in Cuenca (World Heritage City). The building is scheduled for restoration in the near future. The study made use of both non-destructive (NDT) and semi-destructive (SDT) techniques. A thorough experimental campaign and inspection were conducted on all the old wood elements across the eight floors of the building. More than 1200 elements of Pinus sylvestris L. wood were inspected. The data collected in this campaign allowed a mechanical evaluation of the timber elements. The following NDT and SDT were used: visual inspection, microphotography, moisture meter, stress-wave measurements, and resistance drilling. These techniques made facilitated the identification of the wood species, detection of natural defects and decayed areas, and estimation of the physical and mechanical properties of the timber elements. The experimental results were statistically analysed using a multidisciplinary approach to determine the scope of the intervention on the structure to meet the new use and its structural requirements. The final report produced at the end of the inspection was made of colour plans describing the singularities, natural defects, timber decays and damages of each single member. The results obtained will orient the building's conservation work. These findings support a minimal intervention, since more than 95 % of the structural elements were found to be in good condition.

Las ciudades y la memoria. Mecanismos de experimentación plástica en paisajes patrimoniales

Tue, 01 Jan 2019 00:00:00 GMT

El patrimonio se construye como una memoria colectiva, un palimpsesto de memorias arquitectónicas, pictóricas, poéticas, paisajísticas, plásticas, de la memoria del propio lugar y de las memorias sedimentadas del espectador, pero también de las memorias de los alumnos que investigan y experimentan por sí mismos. En las ciudades invisibles, Italo Calvino construye 55 paisajes urbanos que juegan con la materia, los tiempos y las formas, y que son tomados como arquetipos que se proyectan en una serie de paisajes reales. La metodología operativa del taller hace uso de un recurso literario, el cadavre exquis de los surrealistas franceses, una narración secuenciada convertida en mecanismo plástico, que sustituye los textos por fragmentos del paisaje que componen al final una gran maqueta. Tomando como base esta metodología experimental, se han realizado una serie de talleres a lo largo de estos años, con la participación de profesores y estudiantes de distintos niveles educativos.

Application of Deep Neural Networks for Leakage Airflow Rate Estimation From Three‐Dimensional Thermal Patterns

Thu, 01 Jan 2026 00:00:00 GMT

The employment of deep convolutional neural networks (CNNs) signifies a substantial progression in the domain of image analysis. The application of this method is particularly suitable when the image set represents a spatial structure and predictive analysis can only be performed using Gaussian processes, which are computationally complex. The uncontrolled airflow of air into buildings, known as infiltration, poses a significant challenge in terms of characterisation and quantification. The irregular contours of gaps and cracks through the enclosure create a virtually endless variety of cases, making a generalizable scientific interpretation that can be applied to existing buildings very difficult. This circumstance is always clearly manifested by an irregular, three-dimensional incoming airflow. This study presents an innovative methodology for estimating airflow rates based on three-dimensional thermal patterns captured through infrared thermography. The experimental setup employs a 3D-printed matrix of spheres, facilitating the characterisation of the spatial temperature distribution within the airflow. The resulting thermal images are processed using a CNNs, which integrates the spatial information contained in the thermograms with a scalar input representing the inlet air temperature. The model′s performance was assessed under a range of conditions, including reduced image resolutions, varying experimental configurations (involving different flow apertures) and a comparison between full thermographic inputs and thermal difference-based features. The results indicate that the model can accurately infer airflow rates within the same aperture (medium absolute error [MAE] < 2%). While generalisation to new apertures presents a greater challenge, the experiments demonstrate that a sufficiently diverse training dataset can enhance the model′s predictive capacity for configurations not included in the training phase. These findings underscore the potential of deep learning as a nonintrusive and efficient tool for estimating airflow in systems where conventional measurement techniques are either difficult to apply or impractical.

A reduced stochastic data-driven approach to modelling and generating vertical ground reaction forces during running

Wed, 01 Jan 2025 00:00:00 GMT

This work presents a time-domain approach for characterizing the Ground Reaction Forces (GRFs) exerted by a pedestrian during running. It is focused on the vertical component, but the methodology is adaptable to other components or activities. The approach is developed from a statistical perspective. It relies on experimentally measured force-time series obtained from a healthy male pedestrian at eight step frequencies ranging from 130 to 200 steps/min. These data are subsequently used to build a stochastic data-driven model. The model is composed of multivariate normal distributions which represent the step patterns of each foot independently, capturing potential disparities between them. Additional univariate normal distributions represent the step scaling and the aerial phase, the latter with both feet off the ground. A dimensionality reduction procedure is also implemented to retain the essential geometric features of the steps using a sufficient set of random variables. This approach accounts for the intrinsic variability of running gait by assuming normality in the variables, validated through state-of-the-art statistical tests (Henze-Zirkler and Shapiro-Wilk) and the Box-Cox transformation. It enables the generation of virtual GRFs using pseudo-random numbers from the normal distributions. Results demonstrate strong agreement between virtual and experimental data. The virtual time signals reproduce the stochastic behavior, and their frequency content is also captured with deviations below 4.5%, most of them below 2%. This confirms that the method effectively models the inherent stochastic nature of running human gait.

A nonlinear model for the elastoplastic analysis of 2D frames accounting for damage

Sat, 01 Jan 2011 00:00:00 GMT

A simple and efficient procedure for non-linear analysis of frames is presen- ted, under the hypothesis that the non-linear effects, if appear, are concen- trated in the beam-ends.We consider a damage model based on Continuum Damage Mechanics, but affecting the cross-section as a whole. The elasto- plastic behaviour is included formulating the tangent elastoplastic stiffness matrix in such a way that the yield function, in terms of internal forces (axial, shear and bending moment), is affected by the damage in each plas- tic cross-section. After the verification of the model, an example of applica- tion is solved for different assumptions on the yield function (depending on the internal forces considered) with the damage being taken into account or disregarded. The differences on the collapse load, for each case, are shown and some conclusions obtained, among them that the method can evaluate in a more accurate way the load that causes the collapse of frames under increasing loading, considering a fully plastic non-linear analysis.

Generating vertical ground reaction forces using a stochastic data-driven model for pedestrian walking

Wed, 01 Jan 2025 00:00:00 GMT

A novel time-domain approach to the characterization of the forces induced by a pedestrian is proposed. It focuses on the vertical component while walking, but thanks to how it is conceived, the algorithm can be easily adapted to other activities or any other force component. The work has been developed from the statistical point of view, so a stochastic data-driven model is finally obtained after the algorithm is applied to a set of experimentally measured steps. The model is composed of two mean vectors and their corresponding covariance matrices to represent the steps, as well as some more means and standard deviations to account for the step scaling and double support phase, under the assumption that the random variables follow normal distributions. Velocity and step length are also provided, so the model and the latter data enable the realistic generation of virtual gaits. Some application examples at different walking paces are shown, in which comparisons between the original steps and a set of virtual ones are performed to show the similarities between both. For reproducibility purposes, the data and the developed algorithm have been made available.

An iterative neural network approach applied to human-induced force reconstruction using a non-linear electrodynamic shaker

Mon, 01 Jan 2024 00:00:00 GMT

Human-induced force analysis plays an important role across a wide range of disciplines, including biomechanics, sport engineering, health monitoring or structural engineering. Specifically, this paper focuses on the replication of ground reaction forces (GRF) generated by humans during movement. They can provide critical information about human-mechanics and be used to optimize athletic performance, prevent and rehabilitate injuries and assess structural vibrations in engineering applications. It is presented an experimental approach that uses an electrodynamic shaker (APS 400) to replicate GRFs generated by humans during movement, with a high degree of accuracy. Successful force reconstruction implies a high fidelity in signal reproduction with the electrodynamic shaker, which leads to an inverse problem, where a reference signal must be replicated with a nonlinear and non-invertible system. The solution presented in this paper relies on the development of an iterative neural network and an inversion-free approach, which aims to generate the most effective drive signal that minimizes the error between the experimental force signal exerted by the shaker and the reference. After the optimization process, the weights of the neural network are updated to make the shaker behave as desired, achieving excellent results in both time and frequency domains.

Structural stability in elastoplastic 2D frames

Thu, 01 Jan 2015 00:00:00 GMT

The evaluation of the maximum level of load that any 2D framed structure can undergo, before plastic collapse or buckling, is addressed in this paper. The analytical approach, based on a beam element with elastic behaviour except on its ends, uses an incremental approach to determine when changes appear due to plastic behaviour. When the combination of axial force and bending moment in any cross-section reaches the plastic function, that section is considered to yield suddenly and relative displacements can appear because of the yielding. The model includes the traditional plastic hinge, which only considers relative rotation due to the effect of the bending moment. The sequential loading and yielding reduces the stiffness and stability of the frame, which is computed and compared with the classic plastic methods of analysis.

Influence of DuctileDamage Evolution on the Collapse Load of Frames

Fri, 01 Jan 2010 00:00:00 GMT

In this note we analyze the influence of four damage models on the collapse load of a structure. The models considered here have been developed using the hypothesis based on the concept of effective stress and the principle of strain equivalence and they were proposed by Lemaitre and Chaboche (1990, Mechanics of Solid Materials), Wang (1992, “Unified CDM Model and Local Criterion for Ductile Fracture—I. Unified CDM Model for Ductile Fracture,” Eng. Fract. Mech., 42, pp. 177–183), Chandrakanth and Pandey (1995, “An Isotropic Damage Model for Ductile Material,” Eng. Fract. Mech., 50, pp. 457–465), and Bonora (1997, “A Nonlinear CDM Model for Ductile Failure,” Eng. Fract. Mech., 58, pp. 11–28). The differences between them consist mainly in the form of the dissipative potential from which the kinetic law of damage is derived and also in the assumptions made about some parameters of the material.

Damage coupled to yield function for the elastoplastic analysis of framed structures

Tue, 01 Jan 2008 00:00:00 GMT

A method for coupling the variable damage to the yield function of a 2D beam element is presented. The damage is represented by a scalar interna! variable which expresses the loss of strength of the material during ductile or fatigue processes and it is concentrated at the ends ofthe element. Yield surfaces, considering the interaction of bending moment, axial force, shear force and damage of material are also given. And the yield function obtained can be used to determine the elastoplastic stiffness matrix ofbeam element used for the structural analysis.

Thermal behaviour optimization in thick bricks wall of architectural heritage

Thu, 01 Jan 2026 00:00:00 GMT

The thermal envelope of a building plays a key role in its energy efficiency; therefore, accurately characterizing its behaviour is essential to reliably estimate energy consumption. In historic buildings, errors in these estimations can compromise the rehabilitation process and lead to ineffective interventions. Understanding the thermal behaviour of traditional construction systems allows for the establishment of realistic and non-invasive in situ assessment methods, which are crucial for appropriate energy retrofitting. This study evaluates the applicability of the Heat Flow Meter (HFM) method in thick brick masonry walls of historic buildings, by installing heat flux sensors on both sides of the wall. The analysis was carried out on a landmark 20th-century building over a 45-day winter monitoring period, assessing the thermal performance of the wall to validate the method’s effectiveness in heritage contexts, while identifying the advantages and limitations of the efficiency of its heating system. The results were compared with the theoretical model based on Fourier’s law, revealing notable discrepancies: daily periods were observed during which the wall simultaneously received heat from both the interior and exterior environments, contradicting the assumption of unidirectional heat transfer. This phenomenon highlights the potential of massive walls to act as dynamic thermal regulators. The study demonstrates the value of harnessing these ambient thermal gains as a passive strategy to improve energy efficiency without compromising indoor comfort established in regulations, and reinforces the relevance of traditional construction solutions in the sustainable conservation of built heritage.