Examinando por Autor "Alberdi Celaya, Elisabete"

Mostrando 1 - 3 de 3
  • Miniatura
    Ítem
    Development of a transdisciplinary research-based framework for the improvement of thermal comfort of schools through the analysis of shading system
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-01) Oregi Isasi, Xabat; Goti Elordi, Aitor; Pérez Acebo, Heriberto; Álvarez González, Irantzu; Eguía Ribero, María Isabel; Alberdi Celaya, Elisabete
    This article investigates a methodology for the application of the design of sunlighting and shading systems in educational settings, focusing on their impact on thermal comfort. As educational environments increasingly recognize the importance of physical comfort in enhancing learning outcomes, this study starts with an analysis of current shading practices and their effectiveness. A user-friendly methodology for assessing sunlight and shading in schools is developed, utilizing a transdisciplinary research approach, with various stakeholders, including educators, architects, and environmental scientists. Through case studies conducted in Zornotza, Spain, the research warns about the detrimental effects of inadequate shading on student well-being and proposes design solutions for each of the cases. Our findings underscore the necessity for innovative design strategies that integrate both passive and active shading solutions, ultimately contributing to healthier, more sustainable learning environments. These innovative strategies can be better oriented at the early stages of the analysis of the problem if transdisciplinary research is applied, advocating for a holistic approach to educational facility design that prioritizes the comfort and success of students.
  • Miniatura
    Ítem
    Identifying the future skills requirements of the job profiles related to sustainability in the engineering sector
    (Gökmen Arslan, 2023) Goti Elordi, Aitor; Akyazi, Tugçe; Loroño, Agathe; Alberdi Celaya, Elisabete; Oyarbide Zubillaga, Aitor; Ukar Arrien, Olatz
    The field of engineering has undergone significant evolution over the time. With the advent of newindustrial revolutions and the growing importance of sustainability, the skills necessary to excel as anengineer have changed drastically. To be a competent engineer in the future, and to achieve thepsychological wellbeing of a qualified and up-to-date professional, it is necessary to analyze potentialchanges that may occur in the field and adapt one's skills accordingly. Engineers can stay ahead of thecurve and remain relevant in an ever-changing landscape, only by anticipating and preparing forfuture developments as well as foreseeing the future skills needs. In order to address the need ofidentifying the future skill requirements for engineers, in this work, we created a skills database with astrong focus on sustainability. This database not only integrates current skills, but also foresees andestablishes the skills related to sustainability, which will be needed in the future. For this aim, webenefited from the ESCO database for selecting the engineering job profiles related to sustainabilityas well as the current skills needs of the engineers. On the other hand, we conducted a detailed deskresearch in order to analyse and identify the future skills needs for the selected engineering jobprofiles. The aim of our work is to address the lack of a skills database specifically designed for theengineering field in relation to sustainability. The database is intended to provide end -users withinformation on new skill requirements that may arise from future changes, such as industrial andsustainable shifts.
  • Miniatura
    Ítem
    Metallurgical copper recovery prediction using conditional quantile regression based on a copula model
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-07) Hernández, Heber; Díaz Viera, Martín Alberto; Alberdi Celaya, Elisabete; Oyarbide Zubillaga, Aitor; Goti Elordi, Aitor
    This article proposes a novel methodology for estimating metallurgical copper recovery, a critical feature in mining project evaluations. The complexity of modeling this nonadditive variable using geostatistical methods due to low sampling density, strong heterotopic relationships with other measurements, and nonlinearity is highlighted. As an alternative, a copula-based conditional quantile regression method is proposed, which does not rely on linearity or additivity assumptions and can fit any statistical distribution. The proposed methodology was evaluated using geochemical log data and metallurgical testing from a simulated block model of a porphyry copper deposit. A highly heterotopic sample was prepared for copper recovery, sampled at 10% with respect to other variables. A copula-based nonparametric dependence model was constructed from the sample data using a kernel smoothing method, followed by the application of a conditional quantile regression for the estimation of copper recovery with chalcocite content as secondary variable, which turned out to be the most related. The accuracy of the method was evaluated using the remaining 90% of the data not included in the model. The new methodology was compared to cokriging placed under the same conditions, using performance metrics RMSE, MAE, MAPE, and R2. The results show that the proposed methodology reproduces the spatial variability of the secondary variable without the need for a variogram model and improves all evaluation metrics compared to the geostatistical method.