Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551014
Pertenecen a esta colección Tesis y Trabajos de grado de los Doctorados correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- A methodology to optimize water networks in buildings using digital technologies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-04) Cortez Lara, Pedro Maximiliano; Barrios Piña, Héctor Alfonso; emimmayorquin, emipsanchez; Mora Polanco, Abrahan Rafael; Rangel Ramírez, José Guadalupe; Bustamante Bello, Martín Rogelio; Escuela de Ingeniería y Ciencias; Campus Puebla; Sánchez Andrade, BenjamínRecent advances in construction Digital Technologies (DT) have renewed interest in Building Information Modeling (BIM). At the same time, concerns about the environmental impact of the building sector continue to grow. Yet, studies that link BIM with Water Efficiency Analysis (WEA) remain limited. Most available work offers only simplified assumptions, partial simulations, or narrow approaches focused on specific modeling tasks. As a result, many buildings still rely on oversized Water Networks (WN). These systems increase carbon and water footprints and pose sanitary risks due to long periods of water stagnation. This research seeks to address these issues by developing a method to improve WN through DT while reducing their environmental impact. The study adopts a mixed approach that integrates BIM, Metaheuristics, and Input–Output (IO) analysis. The first part of the study analyzed the influence of Peak Water Demand (PWD) in WN and introduced a procedure to estimate it using standardized information. The method was evaluated through a residential case study. The results showed that the proposed approach provides consistent PWD estimates and performs better than the methods currently used in practice. The predicted demand was significantly lower, with values that were about 2.6 times smaller than those obtained through traditional procedures. The method also produced results that were close to the measurements collected on site. Even so, its purpose is not to replicate the exact observed values. A perfect match could reduce the safety margin and lead to undersized systems that fail during unusual or high-demand conditions. The second stage evaluated a methodology to integrate WEA within a BIM environment. Autodesk Revit was chosen as the primary platform because it is widely adopted and can connect different digital tools through a single model. The three proposed domains showed consistent improvements in water savings and reductions in electrical power. Their structure and customization increase the modularity of the methodology. This allows the process to adapt to projects of different scales while keeping a clear and practical workflow. These features help designers and professionals identify relevant elements and parameters early in the design phase. This leads to better water use outcomes and improves the performance of the WN throughout the following stages of the project. The third stage focused on creating a BIM-Metaheuristics algorithm to optimize WN. This part of the research stands out because it requires low technological resources while maintaining high precision in the selection of optimal pipe diameters. The method incorporates environmental factors and hydraulic constraints in a single optimization process. The results indicate that the model can reduce pipe sizes by one nominal diameter in most cases. In more demanding scenarios, the reduction can reach two diameters. These adjustments are obtained while decreasing environmental impact, lowering costs, and minimizing computational demands. The approach is flexible and can be applied to a wide range of building contexts. It consistently produces optimal configurations for WN. This contributes to a shift in how environmental performance is evaluated in plumbing design. This stage also explores the blue and carbon footprint assessment-based BIM-Input Output (BIM-IO) using Multifunctional Analysis of Regions Through Input-Output (MARIO) tool. The proposed framework demonstrated simplicity and ease of use for assessing Blue and Green water footprints in buildings using MARIO and BIM. BIM’s applicability across various building environments enables extensive data extraction. This includes detailed information from systems such as structure, architecture, HVAC, and plumbing. The level of detail depends on the Level of Detail (LOD) used in the model. The outcomes from the third stage were analyzed to determine the environmental impact and development of new policies.
- Sustainability-driven intelligence, design and choice: Strengthening public policy design and implementation in developing countries through decision support systems(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-06-09) Diaz Vazquez, Diego; Gradilla Hernandes, Misael; emimmayorquin; Pacheco Moscoa, Adriana; Aguilar Jiménez, Alejandro; Campus Guadalajara; García González, AlejandroSustainability has emerged as a critical global concern, necessitating coordinated efforts among governments, industries, academia, and civil society to address multifaceted challenges such as climate change, water scarcity, and environmental degradation. While developed nations have made significant strides in sustainability-focused policies, developing countries face unique obstacles, including limited financial and technical resources, governance weaknesses, and fragmented data management. This thesis addresses these challenges by developing and implementing Sustainability-Driven Decision Support Systems (SDSS) tailored to the needs of developing regions, with a focus on optimizing resource allocation, enhancing policy design, and improving environmental management. The research is structured around three main objectives: (1) developing replicable, data-driven prioritization methodologies to optimize public resource allocation for climate change mitigation and adaptation; (2) evaluating the effectiveness of SDSS in integrating complex datasets from multiple stakeholders to generate actionable insights; and (3) creating cost-efficient, machine learning-based DSS using open-source and remote sensing data to support sustainability efforts. These objectives are explored through three case studies in the state of Jalisco, Mexico, each addressing distinct sustainability challenges. This thesis explores the development and application of sustainability-driven decision support systems (SDSS) in developing regions, with a focus on the Metropolitan Area of Guadalajara. Chapter 1 presents the introduction and thesis structure. Chapter 2 presents a systematic review of SDSS implementations in developing countries, identifying prevailing trends, key barriers such as data scarcity and limited stakeholder engagement, and highlighting the potential for improving governance, data integration, and cross-sectoral collaboration. Chapter 3 develops a multicriteria prioritization framework to mitigate water scarcity through a rainwater harvesting program, significantly improving access to water and public health outcomes. Chapter 4 addresses environmental degradation in the Santiago River Basin by applying a GIS-based methodology to integrate heterogeneous datasets and identify critical microbasins for targeted infrastructure and policy interventions. Chapter 5 introduces a remote sensing-based fire risk prediction model that employs machine learning and open-access data to provide accurate and cost-effective risk assessments suitable for resource-limited contexts. Finally, Chapter 6 synthesizes the main findings and underscores the relevance of systemic, adaptive, and participatory approaches to sustainability governance, advocating for the incorporation of advanced technologies to enhance the effectiveness, scalability, and resilience of SDSS in the context of developing countries.
- Designing sustainable agri-food supply chain networks(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-02) Gholiyanjouybari, Fatemeh; Hajiaghaeikeshteli, Mostafa; emipsanchez; Mejia Argueta, Christopher; Bonakdari, Hossein; School of Engineering and Sciences; Campus Monterrey; Smith Cornejo, Neale Ricardo; Rodríguez Calvo, Ericka ZulemaAgri-food products are critical to sustaining human life, as they provide essential nutrients for maintaining bodily functions. Agri-food production must match potential demand to ensure efficient supply to industries and markets. In terms of national and international concerns, this is one of the most important, even a top priority. In recent years, the agri-food industry has prioritized the development of efficient supply chain systems based on current trends and principles, such as sustainability and circular economy. The principles of sustainability can be employed to effectively utilize or reintroduce agri-food waste back into the network. This PhD dissertation deals with designing new agri-food supply chain networks for the first time in the literature. It not only considers the most important products to study, but also focuses on the recent trends and challenging issues like circular economy, water consumption, CO2 emission, and sustainability. We considered Saffron, Coconut, Soybean, and Pistachio, respectively, in four chapters of this thesis. In this work, we formulate some novel mixed-integer linear programming models to design agri-food supply chain networks in different agriculture industries, considering the above new challenges. The multi-objective networks struggle to manage the total net profit while monitoring CO2 emissions and the satisfaction of customers within the network. Given the NP-hard nature of the networks, the solution approach embraces a set of conventional, new, modified, and hybrid metaheuristics to surmount its complexity effectively. The effectiveness of the proposed mathematical models is certified by case studies and general problems evolved from real-world practices. In Saffron's work, we consider marketing practices and develop a stochastic multiobjective programming model to improve sustainability in three main areas. A convex robust optimization approach addresses farm production capacity uncertainty and saffron demand uncertainty. The LP-metric method is used to validate the mathematical model for the saffron business. We adopt a modified Keshtel algorithm to deal with the problem of NP-hardness. Two strategies are used to evaluate the performance of the proposed solution methods: a statistical comparison and a supportive tool that is based on multicriteria decision-making (MCDM). According to the MCDM method, MOKASEO outperformed other algorithms in small, medium, and large-sized problems compared to the other algorithms tested. The secodn supply chain network that we consider to design its colsed-loop network is for the coconut industry. We propose a new mixed-integer linear programming model to design an agri-food supply chain network under sustainable terms. With the goal of resolving a multi-objective closed-loop supply chain, both forward and reverse movements of products are taken into account. During the planning process, the model monitors environmental pollution within the network as well as job opportunities. Given the NP-hardness of the model, we use six multi-objective optimizers and three hybrid algorithms, among which the multi-objective artificial rabbit optimizer is first developed and applied in this study. Therefore, fifteen practical tests are conducted to determine whether the model is compatible with real conditions. The Friedman statistical test and interval plots demonstrate that optimizers are capable of solving problems of all sizes. In both statistical tests and the hybrid Multi-Criteria Decision Making (MCDM) framework, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) outperformed solving practical tests. In the third work, we study circular economy in a closed-loop supply chain. To do this, we consider one of the most famous and valuable agricultural products, soybean. We formulate a novel mixed-integer linear programming model to design a closed-loop agri-food supply chain network under sustainability and circular economy terms. The multi-objective network strives to reduce CO2 emissions while monitoring customer satisfaction and overall net profit. Since the network is NP-hard, a combination of conventional and hybrid metaheuristics is used to overcome its complexity. Four multi-objective optimization algorithms and three hybrid algorithms are utilized to investigate the model's suitability for real-world conditions. A combination of interval plots and hybrid multi-criteria decision-making techniques demonstrates that optimizers can handle any size problem. For large and mediumsized problems, however, MOHHSA is more effective than MOGWO. Finally, in the fourth paper, we develop a new mixed linear mathematical model for the pistachio supply chain network to minimize the total fixed and variable costs of the closed-loop supply chain. This model is addressed with efficient and well-known meta-heuristic algorithms. A hybrid meta-heuristic algorithm is also developed to enhance the intensification and diversification phases. Finally, we compare and evaluate the quality of both meta-heuristic algorithms and hybrid algorithms.
- Design and evaluation of sustainable biorefineries in Mexico: a modeling and experimental approach(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-02-08) Acevedo García, Berenice; Alvarez Guerra, Alejandro Juan; emimmayorquin; Parra Saldivar, Roberto; Manzano Camarillo, Mario Guadalupe Francisco; Santibañez Aguilar, José Ezequiel; Roldán Ahumada, Ma. Claudia; Escuela de ingeniería y ciencias; Campus MonterreyBiorefineries are an alternative to replace crude oil refineries and reduce fossil fuels consumption worldwide. Mexico has a wide variety of renewable biomass resources with great potential for being used in a biorefinery for production of multiple high value products, as alternatives to crude oil-derived products. To make it work, biorefineries require simultaneous implementation of several conditions such as the use of abundant and renewable biomass feedstocks, production of multiple value-added bioproducts, lignin valorization, integral use of biomass, reuse of residues and byproducts, energy efficiency, to name the most important ones. However, sustainable biorefineries in Mexico require further investigation to determine its feasibility and sustainability. In this thesis, the aims were to develop sustainable designs of biorefineries, based on renewable and abundant biomass in the context of Mexico, for replacing the consumption of fossil resources for production of multiple high value products, such as biopharmaceutical products, chemicals, biofuels, energy, and so on. For doing this, sustainability evaluation, modeling, optimizations tools, and an experimental extraction process were performed. The main results are described as follows. First, the sustainable design of a castor oil-based biorefinery located in Michoacan State in Mexico was developed. Azelaic, sebacic, and undecylenic acids, as well as biodiesel, heat, and power were the major marketable products. An optimization assessment allowed to minimize the environmental impact and maximize the economic revenues. Second, the sustainable design of a biorefinery with lignin valorization that uses birch and pine wood as feedstock, located in Michoacan State, was performed. Ethylene and propylene, the two largest chemicals worldwide produced, were the main products. An energy optimization assessment allowed to reduce several environmental impacts related to the consumption of fuels and energy. Third, the extraction and evaluation of value-added compounds from birch leaves was done in order to determine how feasible is the integral valorization of the birch tree in a biorefinery. Finally, the economic and environmental evaluation of the production of neuroprotective orange residue extracts was done. In conclusion, the castor oil plant and lignin from birch and pine wood are promising alternatives as biorefinery feedstocks for bio-based chemical production that can replace important petrochemical products in Mexico. Furthermore, the optimal distribution of castor oil feedstock allows to upgrade the environmental and economic biorefinery’s performances. Moreover, energy optimization improves the lignin biorefinery's environmental performance and the impact can be measured using the LCA. Also, valorization of the birch leaves is a promising option for production of extracts with high content of phenolic compounds and high antioxidant capacity in a biorefinery based on the birch tree. Additionally, orange residue valorization for production of neuroprotective extracts is a promising approach that can be included in a biorefinery based on orange fruit. Finally, this work contributes to the development of sustainable biorefineries in Mexico using renewable an abundant biomass in Mexico, replacing the consumption of fossil resources.
- Building smart and sustainable societies through basic services provision(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-11-22) Turrén Cruz, Thalia; López Zavala, Miguel Ángel; puemcuervo; Peimbert García, Rodrigo Ernesto; García Chong, Néstor Rodolfo; Escobar Neira, Carolina; Ramírez Orozco, Aldo Iván; School of Engineering and Sciences; Campus Eugenio Garza SadaThis research introduces a Smart & Sustainable Societies (S3) Framework, based on what is necessary to achieve the UN agenda by 2030. The proposed model is based on the integration of three smart strategies: (1) water provision that consists of the use of greywater and rainwater; (2) sanitation provision that aims the nutrients recovery from excreta and organic solid waste and (3) resource-oriented agriculture that conceives the use of water from the water provision system to produce food using nutrients recovered from the sanitation system. Globally, the numerous efforts exerted toward providing basic sanitation services to people have not been sufficient to achieve universal coverage. In developing countries worldwide, many policies, strategies, initiatives, and projects on basic sanitation have failed, despite important investments. Of the several reasons explaining the failure, it is remarkable to note that such approaches have focused mainly on improving the technology of the sanitation system without considering the human aspects, such as user preferences. Moreover, there is not currently a comprehensive approach that ensures the provision of a sanitation service that users want or need to satisfy their needs. It is important to highlight that sanitation is fundamental to human development and well-being, and for developing countries, one of the greatest long-term challenges is to treat all the wastewater generated. Therefore, it is important to include the communities’ point of view on the development and decision making of projects and public policies, not just for sanitation but also for common well-being and other basic services provision. As part of the S3 proposal, an approach to identify user preferences was developed and the results suggests that assessing preferences could be an intrinsic part of the design, planning, and implementation process toward leading rural communities to achieve sustainable development goals on universal basic sanitation. The research points out the necessity of understanding how culture, preferences, practices, and socioeconomic conditions directly affect the possibilities for users to gain access to basic sustainable sanitation services. The S3 framework has the potential to increase societies’ well-being, human development, water availability, food safety, poverty alleviation and healthy environments through the provision of safely managed basic services, the recycling of nutrients and water to achieve sustainability at household and community levels.