Cristian Fernando Guaman Sanchez

Building Information Modeling-based (BIM) Digital Twins (DT) are increasingly adopted to support sustainable building management; however, the growing body of secondary literature—systematic reviews, surveys, and bibliometric studies—remains methodologically fragmented and lacks a consolidated tertiary synthesis. This fragmentation prevents researchers and practitioners from identifying consistent guidelines, validated frameworks, and comparable software ecosystems across the field. To address this gap, this study conducts a tertiary review of 57 secondary studies published between 2018 and 2025, following Kitchenham and Charters’ evidence-based guidelines and the PICOC framework. Data extraction and comparative analysis were conducted across seven criteria, including methodological approaches, proposed frameworks, enabling technologies, software tools, and reported limitations. The results reveal that bibliometric analyses and systematic literature reviews dominate the field, with few yielding structured frameworks and taxonomies; nearly half of the reviewed studies do not assess specific software platforms. Artificial intelligence and the internet of things are among the most widely studied enabling technologies, primarily associated with energy management, predictive maintenance, and structural monitoring, yet their integration with BIM-based DT platforms is inconsistently documented. The findings expose persistent interoperability constraints, insufficient data governance structures, limited maturity models, and a lack of large-scale empirical validation—gaps that this tertiary synthesis maps and prioritizes to guide future research toward reproducible, scalable, and sustainability-oriented DT implementations in the architecture, engineering, and construction sector.

Numerous studies have demonstrated that the modeling and simulation of wind turbines constitute essential tools for dynamic analysis, the evaluation of control strategies, and the integration of wind power generation into modern electrical power systems. Ackermann [9] establishes the fundamental framework for the analysis of wind energy in power systems, whereas Slootweg et al. [10] propose wind turbine representation models suitable for fundamental-frequency power system simulations. Likewise, Silva [11] investigates the integration of wind farms based on doubly fed induction generators (DFIGs) and their associated control strategies. Furthermore, studies conducted by Kouadria et al. [3], Ovando et al. [5], Tammaruckwattana and Ohyama [6], Rocha [4], and Xie et al. [8] demonstrate the effectiveness of wind turbine emulators and simulation platforms for the experimental validation of control algorithms and energy conversion strategies.

Los riesgos químicos no controlados generalmente concurren en afectaciones importantes a la salud de los trabajadores en los diferentes procesos que estos se encuentran. El presente estudio se realizó en una unidad privada de tratamiento renal, donde se practican terapias de hemodiálisis para tratar a pacientes enfermos con insuficiencia renal. Para asegurar que esta terapia sea adecuada se realizan varios procesos dentro de los cuales se encuentra la desincrustación de máquinas de hemodiálisis, en donde es necesario el uso de químicos como el ácido acético que permite la desinfección de los equipos señalados. Para esto se midieron los niveles de concentración de este ácido con el método de absorción en carbón y cromatografía iónica, para luego compararlos con los Valores Umbrales Límite TLV. Luego del análisis de resultados obtenidos, se concluye que la concentración del ácido acético en el proceso de trasvase en el caso del TLV- STEL excede la concentración permitida. Finalmente se establecen medidas generales, tendientes a controlar los efectos de este resultado para garantizar a las personas involucradas el desarrollo sus actividades en un ambiente seguro.