Anibal Alviz-Meza | Universidad Señor de Sipan (original) (raw)

Papers by Anibal Alviz-Meza

Research paper thumbnail of Tracing Andean Origins: A Machine Learning Framework for Lead Isotopes

EarthArXiv (California Digital Library), Mar 19, 2024

This study uses machine learning techniques to facilitate the geolocation of Andean lead isotopes... more This study uses machine learning techniques to facilitate the geolocation of Andean lead isotopes, a novel approach in this geographical context. Two predictive models for latitude and longitude were developed based on the compilation of a database of the lead isotope ratios 206 Pb/ 204 Pb, 207 Pb/ 204 Pb, and 208 Pb/ 204 Pb from multiple Andean provinces. These models were cross-validated using GridsearchCV to assess their performance, identifying Random Forest as the best-performing model. Also, clustering analysis with the K-means model and Euclidean distance was used to correlate artifact isotope compositions with known sources. The limitations and scope of the models were listed for their appropriate usability and interpretability. This work extends basic geochronological studies, integrates a comprehensive database, and applies state-of-theart algorithms to generate predictive models, contributing to a deeper understanding of Andean mineral resources' historical distribution and use.

Research paper thumbnail of Energy-carbon emission nexus in a residential building using BIM under different climate conditions: an application of multi-objective optimization

Frontiers in Energy Research, Nov 26, 2023

This study was carried out to investigate the impact of building insulation, a method of reducing... more This study was carried out to investigate the impact of building insulation, a method of reducing energy consumption, on the amount of energy consumed in a building, as well as its impact on cooling and heating loads and carbon emission. A residential structure was designed in Revit, and DesignBuilder determined the cooling and heating loads, as well as the energy consumption. Under three distinct climate conditions, the impact of the environment on the energy-carbon emission nexus of residential buildings was assessed. The cold mountain climate of Koick, Slovakia; the arid desert climate of Ha'il, Saudi Arabia; and the tropical monsoon climate of Borneo, Indonesia were chosen. During the design stage, the Particle Swarm Optimization (PSO) method was used to minimize the energy consumption cost (ECC) and CO 2 emissions. Over the course of 24 h, the cooling and heating loads decreased by 2.51 kW and 1.9 kW, respectively. When the two modes in Ha'il were combined, the heating load was reduced to 850 kWh and the cooling load was reduced to 650 kWh, according to the results. In Borneo, the heating load was reduced by 200 kWh, while in Koick, it was reduced by 2,000 kWh. The cooling load was reduced by 550 and 50 kWh in Borneo and Koick, respectively. This system appears to perform better in arid and hot climates in terms of both heating and cooling loads. However, energy losses in the arid and hot climate (Ha'il) are greater than in other climates. This could be due to temperature and humidity differences between the inside and outside. According to the findings of the PSO evolutionary algorithm optimization, the building can be constructed to reduce ECC by 19% by taking into account input characteristics such as Wind-to-Wall Ratio (WWR), wall, glazes, and weather conditions. This research provides useful insights into the practical application of optimization methods for reducing CO 2 emissions, paving the way for more sustainable and eco-conscious architectural practices.

Research paper thumbnail of Influence of the Oxygen Content, Pressure and Temperature in the Api N-80 Corrosion for Applications of Ccs-eor Processes

DOAJ (DOAJ: Directory of Open Access Journals), Oct 31, 2022

Enhanced oil recovery in processes involving the presence of carbon dioxide (CO2) is the option w... more Enhanced oil recovery in processes involving the presence of carbon dioxide (CO2) is the option with the greatest potential for carbon capture and storage (CCS-EOR). The content of molecular oxygen in the flue gas current generates problems and risks associated with corrosion that must be evaluated. Similarly, the analysis of the effects of temperature and working pressure, represent two variables of great interest. In this research, the effects of the variables oxygen removal efficiency, temperature, and pressure, in real conditions of an oil field in Colombia, were evaluated by means of a thermodynamic simulation tool. The presence of the following corrosion products Fe2O3, Fe3O4, MnCO3, MnO2, and FeCO3 was determined. It was observed that the presence of FeCO3 and MnCO3 corrosion products occur only for removal efficiencies equal to or greater than 95%. Temperature has a greater influence on the products formed in equilibrium (Fe2O3, Fe3O4, MnCO3) at a constant pressure, whereas pressure has a greater influence on MnO2 and FeCO3 at a constant temperature.

Research paper thumbnail of Energy Consumption and Carbon Dioxide Production Optimization in an Educational Building Using the Supported Vector Machine and Ant Colony System

Sustainability

Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it... more Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it is essential to find ways to reduce the amount of energy used in this sector. The road administration organization in Jakarta, Indonesia, utilized a questionnaire as well as the insights of industry experts to determine the most effective energy optimization parameters. It was decided to select variables such as the wall and ceiling materials, the number and type of windows, and the wall and ceiling insulation thickness. Several different modes were evaluated using the DesignBuilder software. Training the data with a supported vector machine (SVM) revealed the relationship between the inputs and the two critical outputs, namely the amount of energy consumption and CO2 production, and the ant colony algorithm was used for optimization. According to the findings, the ratio of the north and east windows to the wall in one direction is 70 percent, while the ratio of the south window to the ...

Research paper thumbnail of Novel Ocean Wave Height and Energy Spectrum Forecasting Approaches: An Application of Semi-Analytical and Machine Learning Models

Water

Accurate and reliable wave forecasting is crucial for optimizing the performance of various marin... more Accurate and reliable wave forecasting is crucial for optimizing the performance of various marine operations, such as offshore energy production, shipping, and fishing. Meanwhile, predicting wave height and wave energy is crucial for achieving sustainability as a renewable energy source, as it enables the harnessing of the power of wave energy efficiently based on the water-energy nexus. Advanced wave forecasting models, such as machine learning models and the semi-analytical approach, have been developed to provide more accurate predictions of ocean waves. In this study, the Sverdrup Munk Bretschneider (SMB) semi-analytical approach, Emotional Artificial Neural Network (EANN) approach, and Wavelet Artificial Neural Network (WANN) approach will be used to estimate ocean wave parameters in the Gulf of Mexico and Aleutian Basin. The accuracy and reliability of these approaches will be evaluated, and the spatial and temporal variability of the wave field will be investigated. The avai...

Research paper thumbnail of A Novel Strategy for Converting Conventional Structures into Net-Zero-Energy Buildings without Destruction

Sustainability

The majority of energy consumption is attributed to buildings. Buildings designed with environmen... more The majority of energy consumption is attributed to buildings. Buildings designed with environmentally sustainable features have the potential to reduce energy consumption. The demolition of ecologically detrimental structures incurs expenses and damages the natural environment. The act of constructing models for the purpose of destruction was deemed superfluous. The replication of the structural model was accompanied by a modification of the design, and a variety of tactics were employed. The proposed upgrades for the building include the installation of new windows, incorporation of greenery on the walls and roof, implementation of insulation, and integration of solar panels in a four-story residential building in Najran, Saudi Arabia. Simultaneously installing insulation prior to changing windows will ensure that the energy consumption of the building, green wall, or green roof will remain unaffected. The installation of solar panels on the walls and top roof of a structure has t...

Research paper thumbnail of Techno-Environmental Evaluation and Optimization of a Hybrid System: Application of Numerical Simulation and Gray Wolf Algorithm in Saudi Arabia

Sustainability

Renewable energy systems have the potential to address increasing energy demand, mitigate environ... more Renewable energy systems have the potential to address increasing energy demand, mitigate environmental degradation, and decrease reliance on fossil fuels. Wind and solar power are examples of renewable energy sources that are characterized by their cleanliness, environmental friendliness, and sustainability. The combination of wind and solar energy is motivated by each energy source’s inherent variability. The objective of this study is to assess the technical, economic, and environmental aspects of a hybrid system designed to provide energy. This study utilizes numerical simulation and develops a novel model using the gray wolf optimization (GWO) algorithm to assess the technical, economic, and environmental consequences of adopting a hybrid system. The evaluation focused on determining the optimal configuration of a greenhouse unit in Najran, Saudi Arabia, over a period of 20 years. The results showed that the diesel generator produced 42% of the required energy when combined wit...

Research paper thumbnail of A Novel Strategy for Converting Conventional Structures into Net-Zero-Energy Buildings without Destruction

Sustainability, 2023

features have the potential to reduce energy consumption. The demolition of ecologically detrimen... more features have the potential to reduce energy consumption. The demolition of ecologically detrimental structures incurs expenses and damages the natural environment. The act of constructing models for the purpose of destruction was deemed superfluous. The replication of the structural model was accompanied by a modification of the design, and a variety of tactics were employed. The proposed upgrades for the building include the installation of new windows, incorporation of greenery on the walls and roof, implementation of insulation, and integration of solar panels in a four-story residential building in Najran, Saudi Arabia. Simultaneously installing insulation prior to changing windows will ensure that the energy consumption of the building, green wall, or green roof will remain unaffected. The installation of solar panels on the walls and top roof of a structure has the potential to generate a monthly electricity output up to two times greater than the structure’s consumption. The spas can be heated on a daily basis by substituting the heating system with solar collectors. The implementation of sustainable building practices has resulted in a significant reduction in energy consumption. Specifically, electricity, gas, heating, and cooling consumption decreased by 11%, 85%, 28%, and 83%, respectively.

Research paper thumbnail of Effects of Composition, Structure of Amine, Pressure and Temperature on CO2 Capture Efficiency and Corrosion of Carbon Steels Using Amine-based Solvents: a Review

DOAJ (DOAJ: Directory of Open Access Journals), Nov 1, 2022

The emission of carbon dioxide (CO2) into the atmosphere is a significant environmental problem. ... more The emission of carbon dioxide (CO2) into the atmosphere is a significant environmental problem. Many technologies are proposed and implemented to sequester CO2 before it is released into the atmosphere. For capturing carbon dioxide (CO2) from exhaust gas and syngas streams in all industrial processes and combustion, chemical absorption using amine-based solvents has shown to be the most studied, reliable, and efficient technology. As a result of the dissolution of CO2 gas and its reaction with the amine solvents, the solution becomes corrosive. This undesirable phenomenon creates a corrosion problem in the absorption column, usually carbon steel. This review paper aims to understand the effects of the variables amine composition in the solution, amine structure, pressure, and temperature on the efficiency of CO2 capture and corrosion of carbon steels using chemical absorption technology using amine-based solvents.

Research paper thumbnail of Unidimensional and 3D Analyses of a Radial Inflow Turbine for an Organic Rankine Cycle under Design and Off-Design Conditions

Energies, Apr 12, 2023

The organic Rankine cycle (ORC) is an efficient technology for electricity generation from low- a... more The organic Rankine cycle (ORC) is an efficient technology for electricity generation from low- and medium-temperature heat sources. In this type of power cycle, the radial inflow turbine is the option usually selected for electricity generation. As a critical ORC component, turbine performance markedly affects the efficiency of the system. Therefore, the challenge is to model the behavior of the radial inflow turbine operating with organic fluids for heat recovery applications. In this context, various groups of fluids are highlighted in the scientific literature, including R-123, R-245fa, and R-141b, which are the fluids used in this research. Since little research has focused on the turbine efficiency effect on the power cycle design and analysis, this study presents an analysis of a radial inflow turbine based on a mathematical model of a one-dimensional design of the turbine. From this analysis, geometric, thermal, and operating parameters were determined, as well as volute, stator, and rotor losses. For this purpose, an algorithm was implemented in MATLAB to calculate the one-dimensional parameters of the turbine. Using these parameters, a 3D model of the turbine was designed in ANSYS-CFX, with performance curves of each projected turbine under design and off-design conditions. The numerical results suggest that the isentropic efficiency of all the proposed turbines under design conditions can surpass 75%. Additionally, the findings indicate that different design conditions, such as specific speed, pressure ratio, and turbine size, can affect the efficiency of radial inflow turbines in ORC systems.

Research paper thumbnail of Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

Sustainability

The internal components of a smart building interact through a compatible fabric and logic. A sma... more The internal components of a smart building interact through a compatible fabric and logic. A smart building integrates systems, structure, services, management, and their interrelationships to create a dynamic and cost-efficient environment. Smart buildings reduce the amount of cooling and heating load required to cool and heat spaces, thereby lowering operating costs and energy consumption without sacrificing occupant comfort. Smart structures are an Internet of Things (IoT) concern. The Internet of Things is a global network that virtualizes commonplace objects. The Internet of Things infuses non-technical objects with technology. IoT development has led to the creation of new protocols based on architectures for wireless sensor networks. Energy conservation extends the life and improves the performance of these networks, while overcoming the limitations of IoT node batteries. This research seeks to develop a data transmission model for routing IoT data in smart buildings. Utiliz...

Research paper thumbnail of Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Energy Reports

In this paper, the energy loss of the green building is optimized based on the thickness and lay-... more In this paper, the energy loss of the green building is optimized based on the thickness and lay-up of the Nano-insulation. As different thicknesses and lay-up of the Nano-insulation have a direct effect on energy consumption of the green building with 1590 square meters, especially with nanomaterial, the machine learning models are employed to represent a new model of the thermal conductivity of the proposed advanced insulation with the precision above 99%. The machine learning models are employed to classify and model the behavior of the heat transfer in the green building due to the complex behavior of the thermal conductivity in the green building. Therefore, 110 data for modeling 20 types of lay-up with 6 different thicknesses are prepared by the machine learning models including Support Vector Machine (SVM), Gaussian Process Regression (GPR), and decision tree. Based on the data analysis and statistical data, thermal conductivity modeling with a decision tree represents the best performance and fitted model. The multiDisciplinary Optimizing method (MDO) under energy consumption constraint, economical consideration, and environmental effects on insulation properties is performed to enhance the energy efficiency of the green building. The calculated results with the Degree-Day approach reveal that the amount of energy saving for green buildings with Nano insulation is about 40% higher than common insulation in common types of insulations. The proposed insulation characteristics regarding the value of Present Worth Function (PWF) and economic aspects cause energy saving per unit area and decreasing in CO 2 emission between 290 kg/m 3 to 293 kg/m 3 depending on weather conditions, insulation thickness, and lay-up.

Research paper thumbnail of Machine learning applications for photovoltaic system optimization in zero green energy buildings

Energy Reports

In this paper, the energy supply of a zero-energy building with 220 square meters is considered u... more In this paper, the energy supply of a zero-energy building with 220 square meters is considered using optimized nanocomposite solar panels with respect to maximum efficiency. An optimized hybrid machine learning method plays a key role in presenting solar panel modeling with over 0.99% accuracy. Predicting the properties of the nanomaterial solar cell in four different seasons is performed by efficient support vector machines (SVM), and k-nearest neighbors (KNN) machine learning algorithms. In addition, the KNN algorithm is optimized by the Particle Swarm Optimization (PSO) method to improve the capabilities of KNN and reveal the best performance criteria for the photovoltaic modeling characteristics. The parameters of the nanocomposite cells are optimized using the proposed novel Multidisciplinary Optimization Method (MDO) to increase the efficiency of the solar panel by up to 170%. Optimization of solar cell performance with nanocomposite material under energy consumption constraints is carried out to propose the best construction of cells with 3 layers. The presented approach as a solution and indicator for the next generation of commercial and residential buildings can increase the potential values of solar cells to at least 70%.

Research paper thumbnail of Application of a PCA-based fault detection and diagnosis method in a power generation system with a 2 MW natural gas engine

Eureka: Physics and Engineering, Nov 29, 2022

Based on increasing global energy demand, electric power generation from Internal Combustion Engi... more Based on increasing global energy demand, electric power generation from Internal Combustion Engines (ICE) has increased over the years. On this idea, the industries have adopted different methods and procedures to prevent failures in these engines, achieve an extension of the life cycle of the machines, improve their safety, and provide financial savings. For this reason, this work implements a methodology for detecting and identifying failures in a natural gas engine (JGS 612 GS-N. L), based on the integration of Principal Component Analysis (PCA) and alarm streak analysis. A method used to describe a data set in terms of new uncorrelated variables or components. The components are ordered by the amount of original variance they describe, making the technique useful for reducing the dimensionality of a data set.

Research paper thumbnail of Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Energy Reports, 2023

In this paper, the energy loss of the green building is optimized based on the thickness and lay-... more In this paper, the energy loss of the green building is optimized based on the thickness and lay-up of the Nano-insulation. As different thicknesses and lay-up of the Nano-insulation have a direct effect on energy consumption of the green building with 1590 square meters, especially with nanomaterial, the machine learning models are employed to represent a new model of the thermal conductivity of the proposed advanced insulation with the precision above 99%. The machine learning models are employed to classify and model the behavior of the heat transfer in the green building due to the complex behavior of the thermal conductivity in the green building. Therefore, 110 data for modeling 20 types of lay-up with 6 different thicknesses are prepared by the machine learning models including Support Vector Machine (SVM), Gaussian Process Regression (GPR), and decision tree. Based on the data analysis and statistical data, thermal conductivity modeling with a decision tree represents the best performance and fitted model. The multiDisciplinary Optimizing method (MDO) under energy consumption constraint, economical consideration, and environmental effects on insulation properties is performed to enhance the energy efficiency of the green building. The calculated results with the Degree-Day approach reveal that the amount of energy saving for green buildings with Nano insulation is about 40% higher than common insulation in common types of insulations. The proposed insulation characteristics regarding the value of Present Worth Function (PWF) and economic aspects cause energy saving per unit area and decreasing in CO 2 emission between 290 kg/m 3 to 293 kg/m 3 depending on weather conditions, insulation thickness, and lay-up.

Research paper thumbnail of Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

Sustainability, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Unidimensional and 3D Analyses of a Radial Inflow Turbine for an Organic Rankine Cycle under Design and Off-Design Conditions

Energies, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of An Application of Machine Learning to Estimate and Evaluate the Energy Consumption in an Office Room

Sustainability

There are no exact criteria for the architecture of openings and windows in office buildings in o... more There are no exact criteria for the architecture of openings and windows in office buildings in order to optimize energy consumption. Due to the physical limitations of this renewable energy source and the lack of conscious control over its capabilities, the amount of light entering offices and the role of daylight as a source of energy are determined by how they are constructed. In this study, the standard room dimensions, which are suitable for three to five employees, are compared to computer simulations. DesignBuilder and EnergyPlus are utilized to simulate the office’s lighting and energy consumption. This study presents a new method for estimating conventional energy consumption based on gene expression programming (GEP). A gravitational search algorithm (GSA) is implemented in order to optimize the model results. Using input and output data collected from a simulation of conventional energy use, the physical law underlying the problem and the relationship between inputs and o...

Research paper thumbnail of Comparison of Wavelet Artificial Neural Network, Wavelet Support Vector Machine, and Adaptive Neuro-Fuzzy Inference System Methods in Estimating Total Solar Radiation in Iraq

Energies

Estimating the amount of solar radiation is very important in evaluating the amount of energy tha... more Estimating the amount of solar radiation is very important in evaluating the amount of energy that can be received from the sun for the construction of solar power plants. Using machine learning tools to estimate solar energy can be a helpful method. With a high number of sunny days, Iraq has a high potential for using solar energy. This study used the Wavelet Artificial Neural Network (WANN), Wavelet Support Vector Machine (WSVM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to estimate solar energy at Wasit and Dhi Qar stations in Iraq. RMSE, EMA, R2, and IA criteria were used to evaluate the performance of the techniques and compare the results with the actual measured value. The results showed that the WANN and WSVM methods had similar results in solar energy modeling. However, the results of the WANN technique were slightly better than the WSVM technique. In Wasit and Dhi Qar stations, the value of R2 for the WANN and WSVM methods was 0.89 and 0.86, respectively...

Research paper thumbnail of Bibliometric Analysis of Fourth Industrial Revolution Applied to Material Sciences Based on Web of Science and Scopus Databases from 2017 to 2021

ChemEngineering

Material science is a broad discipline focused on subjects such as metals, ceramics, polymers, el... more Material science is a broad discipline focused on subjects such as metals, ceramics, polymers, electronics, and composite materials. Each of these fields covers areas associated with designing, synthesizing, and manufacturing, materials. These are tasks in which the use of technology may constitute paramount importance, reducing cost and time to develop new materials and substituting try-and-error standard procedures. This study aimed to analyze, quantify and map the scientific production of research on the fourth industrial revolution linked to material science studies in Scopus and Web of Science databases from 2017 to 2021. For this bibliometric analysis, the Biblioshiny software from RStudio was employed to categorize and evaluate the contribution of authors, countries, institutions, and journals. VOSviewer was used to visualize their collaboration networks. As a result, we found that artificial intelligence represents a hotspot technology used in material science, which has bec...

Research paper thumbnail of Tracing Andean Origins: A Machine Learning Framework for Lead Isotopes

EarthArXiv (California Digital Library), Mar 19, 2024

This study uses machine learning techniques to facilitate the geolocation of Andean lead isotopes... more This study uses machine learning techniques to facilitate the geolocation of Andean lead isotopes, a novel approach in this geographical context. Two predictive models for latitude and longitude were developed based on the compilation of a database of the lead isotope ratios 206 Pb/ 204 Pb, 207 Pb/ 204 Pb, and 208 Pb/ 204 Pb from multiple Andean provinces. These models were cross-validated using GridsearchCV to assess their performance, identifying Random Forest as the best-performing model. Also, clustering analysis with the K-means model and Euclidean distance was used to correlate artifact isotope compositions with known sources. The limitations and scope of the models were listed for their appropriate usability and interpretability. This work extends basic geochronological studies, integrates a comprehensive database, and applies state-of-theart algorithms to generate predictive models, contributing to a deeper understanding of Andean mineral resources' historical distribution and use.

Research paper thumbnail of Energy-carbon emission nexus in a residential building using BIM under different climate conditions: an application of multi-objective optimization

Frontiers in Energy Research, Nov 26, 2023

This study was carried out to investigate the impact of building insulation, a method of reducing... more This study was carried out to investigate the impact of building insulation, a method of reducing energy consumption, on the amount of energy consumed in a building, as well as its impact on cooling and heating loads and carbon emission. A residential structure was designed in Revit, and DesignBuilder determined the cooling and heating loads, as well as the energy consumption. Under three distinct climate conditions, the impact of the environment on the energy-carbon emission nexus of residential buildings was assessed. The cold mountain climate of Koick, Slovakia; the arid desert climate of Ha'il, Saudi Arabia; and the tropical monsoon climate of Borneo, Indonesia were chosen. During the design stage, the Particle Swarm Optimization (PSO) method was used to minimize the energy consumption cost (ECC) and CO 2 emissions. Over the course of 24 h, the cooling and heating loads decreased by 2.51 kW and 1.9 kW, respectively. When the two modes in Ha'il were combined, the heating load was reduced to 850 kWh and the cooling load was reduced to 650 kWh, according to the results. In Borneo, the heating load was reduced by 200 kWh, while in Koick, it was reduced by 2,000 kWh. The cooling load was reduced by 550 and 50 kWh in Borneo and Koick, respectively. This system appears to perform better in arid and hot climates in terms of both heating and cooling loads. However, energy losses in the arid and hot climate (Ha'il) are greater than in other climates. This could be due to temperature and humidity differences between the inside and outside. According to the findings of the PSO evolutionary algorithm optimization, the building can be constructed to reduce ECC by 19% by taking into account input characteristics such as Wind-to-Wall Ratio (WWR), wall, glazes, and weather conditions. This research provides useful insights into the practical application of optimization methods for reducing CO 2 emissions, paving the way for more sustainable and eco-conscious architectural practices.

Research paper thumbnail of Influence of the Oxygen Content, Pressure and Temperature in the Api N-80 Corrosion for Applications of Ccs-eor Processes

DOAJ (DOAJ: Directory of Open Access Journals), Oct 31, 2022

Enhanced oil recovery in processes involving the presence of carbon dioxide (CO2) is the option w... more Enhanced oil recovery in processes involving the presence of carbon dioxide (CO2) is the option with the greatest potential for carbon capture and storage (CCS-EOR). The content of molecular oxygen in the flue gas current generates problems and risks associated with corrosion that must be evaluated. Similarly, the analysis of the effects of temperature and working pressure, represent two variables of great interest. In this research, the effects of the variables oxygen removal efficiency, temperature, and pressure, in real conditions of an oil field in Colombia, were evaluated by means of a thermodynamic simulation tool. The presence of the following corrosion products Fe2O3, Fe3O4, MnCO3, MnO2, and FeCO3 was determined. It was observed that the presence of FeCO3 and MnCO3 corrosion products occur only for removal efficiencies equal to or greater than 95%. Temperature has a greater influence on the products formed in equilibrium (Fe2O3, Fe3O4, MnCO3) at a constant pressure, whereas pressure has a greater influence on MnO2 and FeCO3 at a constant temperature.

Research paper thumbnail of Energy Consumption and Carbon Dioxide Production Optimization in an Educational Building Using the Supported Vector Machine and Ant Colony System

Sustainability

Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it... more Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it is essential to find ways to reduce the amount of energy used in this sector. The road administration organization in Jakarta, Indonesia, utilized a questionnaire as well as the insights of industry experts to determine the most effective energy optimization parameters. It was decided to select variables such as the wall and ceiling materials, the number and type of windows, and the wall and ceiling insulation thickness. Several different modes were evaluated using the DesignBuilder software. Training the data with a supported vector machine (SVM) revealed the relationship between the inputs and the two critical outputs, namely the amount of energy consumption and CO2 production, and the ant colony algorithm was used for optimization. According to the findings, the ratio of the north and east windows to the wall in one direction is 70 percent, while the ratio of the south window to the ...

Research paper thumbnail of Novel Ocean Wave Height and Energy Spectrum Forecasting Approaches: An Application of Semi-Analytical and Machine Learning Models

Water

Accurate and reliable wave forecasting is crucial for optimizing the performance of various marin... more Accurate and reliable wave forecasting is crucial for optimizing the performance of various marine operations, such as offshore energy production, shipping, and fishing. Meanwhile, predicting wave height and wave energy is crucial for achieving sustainability as a renewable energy source, as it enables the harnessing of the power of wave energy efficiently based on the water-energy nexus. Advanced wave forecasting models, such as machine learning models and the semi-analytical approach, have been developed to provide more accurate predictions of ocean waves. In this study, the Sverdrup Munk Bretschneider (SMB) semi-analytical approach, Emotional Artificial Neural Network (EANN) approach, and Wavelet Artificial Neural Network (WANN) approach will be used to estimate ocean wave parameters in the Gulf of Mexico and Aleutian Basin. The accuracy and reliability of these approaches will be evaluated, and the spatial and temporal variability of the wave field will be investigated. The avai...

Research paper thumbnail of A Novel Strategy for Converting Conventional Structures into Net-Zero-Energy Buildings without Destruction

Sustainability

The majority of energy consumption is attributed to buildings. Buildings designed with environmen... more The majority of energy consumption is attributed to buildings. Buildings designed with environmentally sustainable features have the potential to reduce energy consumption. The demolition of ecologically detrimental structures incurs expenses and damages the natural environment. The act of constructing models for the purpose of destruction was deemed superfluous. The replication of the structural model was accompanied by a modification of the design, and a variety of tactics were employed. The proposed upgrades for the building include the installation of new windows, incorporation of greenery on the walls and roof, implementation of insulation, and integration of solar panels in a four-story residential building in Najran, Saudi Arabia. Simultaneously installing insulation prior to changing windows will ensure that the energy consumption of the building, green wall, or green roof will remain unaffected. The installation of solar panels on the walls and top roof of a structure has t...

Research paper thumbnail of Techno-Environmental Evaluation and Optimization of a Hybrid System: Application of Numerical Simulation and Gray Wolf Algorithm in Saudi Arabia

Sustainability

Renewable energy systems have the potential to address increasing energy demand, mitigate environ... more Renewable energy systems have the potential to address increasing energy demand, mitigate environmental degradation, and decrease reliance on fossil fuels. Wind and solar power are examples of renewable energy sources that are characterized by their cleanliness, environmental friendliness, and sustainability. The combination of wind and solar energy is motivated by each energy source’s inherent variability. The objective of this study is to assess the technical, economic, and environmental aspects of a hybrid system designed to provide energy. This study utilizes numerical simulation and develops a novel model using the gray wolf optimization (GWO) algorithm to assess the technical, economic, and environmental consequences of adopting a hybrid system. The evaluation focused on determining the optimal configuration of a greenhouse unit in Najran, Saudi Arabia, over a period of 20 years. The results showed that the diesel generator produced 42% of the required energy when combined wit...

Research paper thumbnail of A Novel Strategy for Converting Conventional Structures into Net-Zero-Energy Buildings without Destruction

Sustainability, 2023

features have the potential to reduce energy consumption. The demolition of ecologically detrimen... more features have the potential to reduce energy consumption. The demolition of ecologically detrimental structures incurs expenses and damages the natural environment. The act of constructing models for the purpose of destruction was deemed superfluous. The replication of the structural model was accompanied by a modification of the design, and a variety of tactics were employed. The proposed upgrades for the building include the installation of new windows, incorporation of greenery on the walls and roof, implementation of insulation, and integration of solar panels in a four-story residential building in Najran, Saudi Arabia. Simultaneously installing insulation prior to changing windows will ensure that the energy consumption of the building, green wall, or green roof will remain unaffected. The installation of solar panels on the walls and top roof of a structure has the potential to generate a monthly electricity output up to two times greater than the structure’s consumption. The spas can be heated on a daily basis by substituting the heating system with solar collectors. The implementation of sustainable building practices has resulted in a significant reduction in energy consumption. Specifically, electricity, gas, heating, and cooling consumption decreased by 11%, 85%, 28%, and 83%, respectively.

Research paper thumbnail of Effects of Composition, Structure of Amine, Pressure and Temperature on CO2 Capture Efficiency and Corrosion of Carbon Steels Using Amine-based Solvents: a Review

DOAJ (DOAJ: Directory of Open Access Journals), Nov 1, 2022

The emission of carbon dioxide (CO2) into the atmosphere is a significant environmental problem. ... more The emission of carbon dioxide (CO2) into the atmosphere is a significant environmental problem. Many technologies are proposed and implemented to sequester CO2 before it is released into the atmosphere. For capturing carbon dioxide (CO2) from exhaust gas and syngas streams in all industrial processes and combustion, chemical absorption using amine-based solvents has shown to be the most studied, reliable, and efficient technology. As a result of the dissolution of CO2 gas and its reaction with the amine solvents, the solution becomes corrosive. This undesirable phenomenon creates a corrosion problem in the absorption column, usually carbon steel. This review paper aims to understand the effects of the variables amine composition in the solution, amine structure, pressure, and temperature on the efficiency of CO2 capture and corrosion of carbon steels using chemical absorption technology using amine-based solvents.

Research paper thumbnail of Unidimensional and 3D Analyses of a Radial Inflow Turbine for an Organic Rankine Cycle under Design and Off-Design Conditions

Energies, Apr 12, 2023

The organic Rankine cycle (ORC) is an efficient technology for electricity generation from low- a... more The organic Rankine cycle (ORC) is an efficient technology for electricity generation from low- and medium-temperature heat sources. In this type of power cycle, the radial inflow turbine is the option usually selected for electricity generation. As a critical ORC component, turbine performance markedly affects the efficiency of the system. Therefore, the challenge is to model the behavior of the radial inflow turbine operating with organic fluids for heat recovery applications. In this context, various groups of fluids are highlighted in the scientific literature, including R-123, R-245fa, and R-141b, which are the fluids used in this research. Since little research has focused on the turbine efficiency effect on the power cycle design and analysis, this study presents an analysis of a radial inflow turbine based on a mathematical model of a one-dimensional design of the turbine. From this analysis, geometric, thermal, and operating parameters were determined, as well as volute, stator, and rotor losses. For this purpose, an algorithm was implemented in MATLAB to calculate the one-dimensional parameters of the turbine. Using these parameters, a 3D model of the turbine was designed in ANSYS-CFX, with performance curves of each projected turbine under design and off-design conditions. The numerical results suggest that the isentropic efficiency of all the proposed turbines under design conditions can surpass 75%. Additionally, the findings indicate that different design conditions, such as specific speed, pressure ratio, and turbine size, can affect the efficiency of radial inflow turbines in ORC systems.

Research paper thumbnail of Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

Sustainability

The internal components of a smart building interact through a compatible fabric and logic. A sma... more The internal components of a smart building interact through a compatible fabric and logic. A smart building integrates systems, structure, services, management, and their interrelationships to create a dynamic and cost-efficient environment. Smart buildings reduce the amount of cooling and heating load required to cool and heat spaces, thereby lowering operating costs and energy consumption without sacrificing occupant comfort. Smart structures are an Internet of Things (IoT) concern. The Internet of Things is a global network that virtualizes commonplace objects. The Internet of Things infuses non-technical objects with technology. IoT development has led to the creation of new protocols based on architectures for wireless sensor networks. Energy conservation extends the life and improves the performance of these networks, while overcoming the limitations of IoT node batteries. This research seeks to develop a data transmission model for routing IoT data in smart buildings. Utiliz...

Research paper thumbnail of Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Energy Reports

In this paper, the energy loss of the green building is optimized based on the thickness and lay-... more In this paper, the energy loss of the green building is optimized based on the thickness and lay-up of the Nano-insulation. As different thicknesses and lay-up of the Nano-insulation have a direct effect on energy consumption of the green building with 1590 square meters, especially with nanomaterial, the machine learning models are employed to represent a new model of the thermal conductivity of the proposed advanced insulation with the precision above 99%. The machine learning models are employed to classify and model the behavior of the heat transfer in the green building due to the complex behavior of the thermal conductivity in the green building. Therefore, 110 data for modeling 20 types of lay-up with 6 different thicknesses are prepared by the machine learning models including Support Vector Machine (SVM), Gaussian Process Regression (GPR), and decision tree. Based on the data analysis and statistical data, thermal conductivity modeling with a decision tree represents the best performance and fitted model. The multiDisciplinary Optimizing method (MDO) under energy consumption constraint, economical consideration, and environmental effects on insulation properties is performed to enhance the energy efficiency of the green building. The calculated results with the Degree-Day approach reveal that the amount of energy saving for green buildings with Nano insulation is about 40% higher than common insulation in common types of insulations. The proposed insulation characteristics regarding the value of Present Worth Function (PWF) and economic aspects cause energy saving per unit area and decreasing in CO 2 emission between 290 kg/m 3 to 293 kg/m 3 depending on weather conditions, insulation thickness, and lay-up.

Research paper thumbnail of Machine learning applications for photovoltaic system optimization in zero green energy buildings

Energy Reports

In this paper, the energy supply of a zero-energy building with 220 square meters is considered u... more In this paper, the energy supply of a zero-energy building with 220 square meters is considered using optimized nanocomposite solar panels with respect to maximum efficiency. An optimized hybrid machine learning method plays a key role in presenting solar panel modeling with over 0.99% accuracy. Predicting the properties of the nanomaterial solar cell in four different seasons is performed by efficient support vector machines (SVM), and k-nearest neighbors (KNN) machine learning algorithms. In addition, the KNN algorithm is optimized by the Particle Swarm Optimization (PSO) method to improve the capabilities of KNN and reveal the best performance criteria for the photovoltaic modeling characteristics. The parameters of the nanocomposite cells are optimized using the proposed novel Multidisciplinary Optimization Method (MDO) to increase the efficiency of the solar panel by up to 170%. Optimization of solar cell performance with nanocomposite material under energy consumption constraints is carried out to propose the best construction of cells with 3 layers. The presented approach as a solution and indicator for the next generation of commercial and residential buildings can increase the potential values of solar cells to at least 70%.

Research paper thumbnail of Application of a PCA-based fault detection and diagnosis method in a power generation system with a 2 MW natural gas engine

Eureka: Physics and Engineering, Nov 29, 2022

Based on increasing global energy demand, electric power generation from Internal Combustion Engi... more Based on increasing global energy demand, electric power generation from Internal Combustion Engines (ICE) has increased over the years. On this idea, the industries have adopted different methods and procedures to prevent failures in these engines, achieve an extension of the life cycle of the machines, improve their safety, and provide financial savings. For this reason, this work implements a methodology for detecting and identifying failures in a natural gas engine (JGS 612 GS-N. L), based on the integration of Principal Component Analysis (PCA) and alarm streak analysis. A method used to describe a data set in terms of new uncorrelated variables or components. The components are ordered by the amount of original variance they describe, making the technique useful for reducing the dimensionality of a data set.

Research paper thumbnail of Thermal conductivity improvement in a green building with Nano insulations using machine learning methods

Energy Reports, 2023

In this paper, the energy loss of the green building is optimized based on the thickness and lay-... more In this paper, the energy loss of the green building is optimized based on the thickness and lay-up of the Nano-insulation. As different thicknesses and lay-up of the Nano-insulation have a direct effect on energy consumption of the green building with 1590 square meters, especially with nanomaterial, the machine learning models are employed to represent a new model of the thermal conductivity of the proposed advanced insulation with the precision above 99%. The machine learning models are employed to classify and model the behavior of the heat transfer in the green building due to the complex behavior of the thermal conductivity in the green building. Therefore, 110 data for modeling 20 types of lay-up with 6 different thicknesses are prepared by the machine learning models including Support Vector Machine (SVM), Gaussian Process Regression (GPR), and decision tree. Based on the data analysis and statistical data, thermal conductivity modeling with a decision tree represents the best performance and fitted model. The multiDisciplinary Optimizing method (MDO) under energy consumption constraint, economical consideration, and environmental effects on insulation properties is performed to enhance the energy efficiency of the green building. The calculated results with the Degree-Day approach reveal that the amount of energy saving for green buildings with Nano insulation is about 40% higher than common insulation in common types of insulations. The proposed insulation characteristics regarding the value of Present Worth Function (PWF) and economic aspects cause energy saving per unit area and decreasing in CO 2 emission between 290 kg/m 3 to 293 kg/m 3 depending on weather conditions, insulation thickness, and lay-up.

Research paper thumbnail of Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

Sustainability, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Unidimensional and 3D Analyses of a Radial Inflow Turbine for an Organic Rankine Cycle under Design and Off-Design Conditions

Energies, 2023

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of An Application of Machine Learning to Estimate and Evaluate the Energy Consumption in an Office Room

Sustainability

There are no exact criteria for the architecture of openings and windows in office buildings in o... more There are no exact criteria for the architecture of openings and windows in office buildings in order to optimize energy consumption. Due to the physical limitations of this renewable energy source and the lack of conscious control over its capabilities, the amount of light entering offices and the role of daylight as a source of energy are determined by how they are constructed. In this study, the standard room dimensions, which are suitable for three to five employees, are compared to computer simulations. DesignBuilder and EnergyPlus are utilized to simulate the office’s lighting and energy consumption. This study presents a new method for estimating conventional energy consumption based on gene expression programming (GEP). A gravitational search algorithm (GSA) is implemented in order to optimize the model results. Using input and output data collected from a simulation of conventional energy use, the physical law underlying the problem and the relationship between inputs and o...

Research paper thumbnail of Comparison of Wavelet Artificial Neural Network, Wavelet Support Vector Machine, and Adaptive Neuro-Fuzzy Inference System Methods in Estimating Total Solar Radiation in Iraq

Energies

Estimating the amount of solar radiation is very important in evaluating the amount of energy tha... more Estimating the amount of solar radiation is very important in evaluating the amount of energy that can be received from the sun for the construction of solar power plants. Using machine learning tools to estimate solar energy can be a helpful method. With a high number of sunny days, Iraq has a high potential for using solar energy. This study used the Wavelet Artificial Neural Network (WANN), Wavelet Support Vector Machine (WSVM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to estimate solar energy at Wasit and Dhi Qar stations in Iraq. RMSE, EMA, R2, and IA criteria were used to evaluate the performance of the techniques and compare the results with the actual measured value. The results showed that the WANN and WSVM methods had similar results in solar energy modeling. However, the results of the WANN technique were slightly better than the WSVM technique. In Wasit and Dhi Qar stations, the value of R2 for the WANN and WSVM methods was 0.89 and 0.86, respectively...

Research paper thumbnail of Bibliometric Analysis of Fourth Industrial Revolution Applied to Material Sciences Based on Web of Science and Scopus Databases from 2017 to 2021

ChemEngineering

Material science is a broad discipline focused on subjects such as metals, ceramics, polymers, el... more Material science is a broad discipline focused on subjects such as metals, ceramics, polymers, electronics, and composite materials. Each of these fields covers areas associated with designing, synthesizing, and manufacturing, materials. These are tasks in which the use of technology may constitute paramount importance, reducing cost and time to develop new materials and substituting try-and-error standard procedures. This study aimed to analyze, quantify and map the scientific production of research on the fourth industrial revolution linked to material science studies in Scopus and Web of Science databases from 2017 to 2021. For this bibliometric analysis, the Biblioshiny software from RStudio was employed to categorize and evaluate the contribution of authors, countries, institutions, and journals. VOSviewer was used to visualize their collaboration networks. As a result, we found that artificial intelligence represents a hotspot technology used in material science, which has bec...

Research paper thumbnail of Future of the Chemical Engineering Program from the Universidad Nacional de Colombia Regarding its International Prospecting

ResearchGate, 2022

This research initiative reflects a quantitative point of view of the current panorama of the Che... more This research initiative reflects a quantitative point of view of the current panorama of the Chemical Engineering program of the Universidad Nacional de Colombia regarding international references that question the future of this Alma Mater. As a starting point, the historical milestones of the school's creation are presented, as well as the evolution of its structure, study plans, and incorporation of new programs. However, missionary aspects such as teaching, research, and internationalization are addressed as the central axis of this academic exercise. In general terms, the chemical engineering program requires several initiatives to increase the teaching staff, its scientific production, and its global impact. Also, I recommend promoting the incoming mobility of international students to the institution, increasing the cooperative work with local and external institutions, and adapting the focus of the courses offered to introduce the creation of new ventures and fields of action associated with chemical engineering program.

Research paper thumbnail of Proyecto Aplicado en Machine Learning and Data Science

NoteBook from GoogleColab, 2022

Establecer los departamentos y el nivel educativo con las tasas maximas y minimas de deserción en... more Establecer los departamentos y el nivel educativo con las tasas maximas y minimas de deserción en Colombia, junto con las demás variables de interes, empleando visualizaciones para entendimiento. Estudiar la correlación de las variables en el nivel educativo con un mayor indice de deserción en Colombia emplenado estadistica inferencial para su validación. Obtener un modelo y su valor de presición para la variable deserción en el nivel educativo seleccionado empleando una función predictiva para el periodo comprendido entre 2018 y 2020.