Production Of Panels Research Articles

Solar photovoltaic panel production in Mexico: A novel machine learning approach

This study examines the potential for widespread solar photovoltaic panel production in Mexico and emphasizes the country's unique qualities that position it as a strong manufacturing candidate in this field. An advanced model based on artificial neural networks has been developed to predict solar photovoltaic panel plant metrics. This model integrates a state-of-the-art non-linear programming framework using Pyomo as well as an innovative optimization and machine learning toolkit library. This approach creates surrogate models for individual photovoltaic plants including production timelines. While this research, conducted through extensive simulations and meticulous computations, unveiled that Latin America has been significantly underrepresented in the production of silicon, wafers, cells, and modules within the global market; it also demonstrates the substantial potential of scaling up photovoltaic panel production in Mexico, leading to significant economic, social, and environmental benefits. By hyperparameter optimization, an outstanding and competitive artificial neural network model has been developed with a coefficient of determination values above 0.99 for all output variables. It has been found that water and energy consumption during PV panel production is remarkable. However, water consumption (33.16 × 10−4 m3/kWh) and the emissions generated (1.12 × 10−6 TonCO2/kWh) during energy production are significantly lower than those of conventional power plants. Notably, the results highlight a positive economic trend, with module production plants generating the highest profits (35.7%) among all production stages, while polycrystalline silicon production plants yield comparatively lower earnings (13.0%). Furthermore, this study underscores a critical factor in the photovoltaic panel production process which is that cell production plants contribute the most to energy consumption (39.7%) due to their intricate multi-stage processes. The blending of Machine Learning and optimization models heralds a new era in resource allocation for a more sustainable renewable energy sector, offering a brighter, greener future.

Evaluation of the Physical-Mechanical Properties of OSB Panels (Oriented Strand Board) With Different Types of Adhesives and Particle Orientations

Objective: The present study aimed to evaluate the quality of OSB (Oriented Strand Board) panels produced with different particle orientations and adhesive formulations. Method: The panels were produced using strand particles of Pinus taeda, with a nominal density of 0.65 g/cm³ in two particle orientations (oriented and random) and three adhesive formulations (100% phenol formaldehyde, 100% tannin and 50% phenol formaldehyde + 50% tannin), distributed in six treatments. The tests were carried out according to the standards established by the EN 300 (2006) standards. Results and conclusion: The results showed that using the mixture of the phenol and tannin adhesive had better results for the swelling, water absorption properties and the static bending. It was not possible to determine the best type of adhesive to be used, as the results showed an equivalence between the two types of adhesives used, as well as the mixture between them. It was observed that the use of mixtures with 50% of each adhesive can be used in the production process of OSB panels, allowing new alternatives of adhesives for the industries. Research implications: This research investigates the possibility of using different types of natural adhesives in the manufacture of wooden panels, contributing to reducing the use of materials that are harmful to the environment and reducing costs in panel production, contributing to more sustainable production.

Why forest economy can become a driving force of the development of BRICS cooperaion

The changing global geopolitical and economic landscape generates growing interest in new strategic alliances among the world’s fastest growing economies. This is certainly true for the BRICS countries, whose importance for the contemporary world cannot be overestimated. As soon as the group begins to turn into a more institutionalized organization, the question of establishing closer and more numerous economic and social ties will arise. The paper analyzes the trends in the development of the forest economy in Brazil, Russia, India, China and South Africa over the past two decades. It assesses each country’s share in the global timber harvesting and its position on the international market for forest products. Accounting for slightly less than 1/3 of the global annual harvest, the BRICS countries have boosted production and export of their forest products in the XXI century. According to our calculations, only India and China’s production and export of sawn timber and wood panels increased tenfold. The paper examines conditions for turning the forest economy into one of the drivers of cooperation between the BRICS countries and the existing financial, political and environmental constraints. Such cooperation will be possible if there is sufficient demand for forestry products in BRICS; it will require measures to radically improve the logistics of trade between the countries, given their great mutual remoteness. The important role of the BRICS countries in the global forest economy can become an important factor in the further development of cooperation within the group, especially after the expansion expected in 2024.

Strategic Minerals for Climate Change and the Energy Transition: The Mining Contribution of Colombia

To transition to carbon neutrality by the year 2050, copper, lithium, rare earths, cobalt, nickel, and silver are essential due to their use in the manufacture of electric cars, lithium batteries, wind turbines, solar panels, motors, and electrical wiring. The main goal of this study is to carry out a mining approach of the prospective areas of Colombia with strategic minerals for energy transition and climate change, analyzing the geospatial location, mining rights, mineral extraction, and royalty collection. Open data from SGC, ANM, and SIMCO geoportals were consulted. The prospective areas totaled 311,535.2 km2, equivalent to 27.3% of Colombia, and were located mainly in the Andes Mountains. The total area of mining rights and applications with strategic minerals for the energy transition is 112,802.2 km2 or 9.9% of Colombia, representing 5731 rights and 3939 applications. From 2012 to 2023, 448,330 tons of nickel, 172.9 tons of silver, and 171.6 tons of copper were mined in Colombia, which has contributed USD 513,140,286 as royalties to the state. No royalties have been earned from the extraction of rare earths, lithium, or cobalt. Fulfilling the Paris Agreement is possible with new sustainable mining projects of strategic minerals.

Properties of chemically foamed polypropylene materials for application to automobile interior door panels

Abstract In recent years, alternative approaches have been implemented in the automotive sector to reduce raw material costs and protect the environment. An increase in weight causes both fuel consumption and CO2 emissions to rise. This study aims to reduce exhaust emissions due to weight reduction by using foamed polypropylene in the door panel production of a subcompact crossover SUV car and saving energy by shortening the injection cycle time. The newly produced 2 % ITP 822 chemical foaming agent added door panel was compared with the current door panel performances. As a result of foam morphology structure, impact, and hardness tests, it was decided that ITP 822 is a suitable chemical foaming agent. In addition, a weight reduction of 5.2 % was achieved. Moreover, the injection cycle time has been reduced by approximately 12 %, reducing the total cycle time from 35 s to 31 s.

Forecasting of Solar Power Using GRU–Temporal Fusion Transformer Model and DILATE Loss Function

Solar power is a clean and sustainable energy source that does not emit greenhouse gases or other atmospheric pollutants. The inherent variability in solar energy due to random fluctuations introduces novel attributes to the power generation and load dynamics of the grid. Consequently, there has been growing attention to developing an accurate forecast model using various machine and deep learning techniques. Temporal attention mechanisms enable the model to concentrate on the critical components of the input sequence at each time step, thereby enhancing the accuracy of the prediction. The suggested GRU–temporal fusion transformer (GRU-TFT) model was trained and validated employing the “Daily Power Production of Solar Panels” Kaggle dataset. Furthermore, an innovative loss function termed DILATE is introduced to train the proposed model specifically for multistep and nonstationary time series forecasting. The outcomes have been subjected to a comparative analysis with alternative algorithms, such as neural basis expansion analysis for interpretable time series (N-BEATS), neural hierarchical interpolation for time series (N-HiTS), and extreme gradient boosting (XGBoost), using several evaluation metrics, including the absolute percentage error (MAE), mean square error (MSE), and root mean square error (RMSE). The model presented in this study exhibited significant performance improvements compared with traditional statistical and machine learning techniques. This is evident from the achieved values of MAE, MSE, and RMSE, which were 1.19, 2.08, and 1.44, respectively. In contrast, the machine learning approach utilizing the Holt–Winters method for time series forecasting in additive mode yielded MAE, MSE, and RMSE scores of 4.126, 29.105, and 5.3949, respectively.

Export Growth and Quality Determination of Wood Forest Products: Evidence from China

The rapid-developed scale of China’s trade in wood forest products has undergone a considerable uptick. Concomitant with the evolution of high-quality development paradigms, product quality within trade frameworks has gained escalating scrutiny. Based on the statistical analysis of the export characteristics of China’s wood forest products, this study leverages BACI data spanning from 1998 to 2017. Utilizing regression-based inverse methods, the study quantifies the quality attributes of these export products, dissects fluctuations in quality, and places particular emphasis on the markets within “Belt and Road Initiative” economies to elucidate dynamic trends and spatial distribution characteristics of export quality in this geoeconomic domain. Based on this, the fixed effect model, random effect model, and system GMM are used to empirically examine the influencing factors of China’s wood forest product export quality. This study found that wood-based panel products have the highest quality, followed by paper products and wood furniture among the three major categories of wood forest products. Besides, the overall quality levels of the three products exported to countries participating in the Belt and Road initiative haven’t significantly changed, while notable changes are evident across divergent export destination markets. In addition, an empirical study on the influencing factors of the export product quality of wood forest products is conducted, which indicates that total factor productivity, R&D investment, capital intensity, labor costs, and foreign direct investment are influencing factors. Finally, based on the research conclusions, suggestions are provided on how to improve the export quality of wood forest products.

Performance evaluation of three grid-connected monocrystalline silicon solar photovoltaic systems in Nepal

This study evaluates three grid-connected solar photovoltaic (PV) systems using four criteria: final yield, performance ratio, capacity utilization factor, and system efficiency. The PV systems were installed on the rooftop of the Nepal Telecom office at Sundhara, Pokhara, and Biratnagar. The generation data was collected through the web interface of the data logger installed at the sites. Long-term comparison (four years) of the plant at Sundhara and the same system comparison of plants at Pokhara and Biratnagar were performed. Long-term analysis of the plant at Sundhara found that the final yield decreased from 2.91 kWh/kWp in 2019 to 2.21 kWh/kWp in 2022. Similarly, the performance ratio decreased from 91.0% in 2019 to 67.3% in 2022, capacity utilization factor decreased from 12.1% in 2019 to 9.2% in 2022, and system efficiency decreased from 16.8% in 2019 to 12.5% in 2022. The same system installed at Pokhara and Biratnagar had slightly varied performance owing to the variation in meteorological parameters. The average air temperature at Biratnagar (26.7°C) was higher than at Pokhara (13.1°C) while the amount of solar radiation at Biratnagar was just higher by 4%. This led to the reduction of final yield by 9% at Biratnagar than at Pokhara as higher temperatures at Biratnagar caused more reduction in the power output from the solar panels. Finally, this study provides insights to researchers, PV installers, and panel manufacturers on the actual performance of grid-connected solar PV in Nepal.

The Impact of Dust Deposition on PV Panels’ Efficiency and Mitigation Solutions: Review Article

Conversion efficiency, power production, and cost of PV panels’ energy are remarkably impacted by external factors including temperature, wind, humidity, dust aggregation, and induction characteristics of the PV system such as tilt angle, altitude, and orientation. One of the prominent elements affecting PV panel performance and capability is dust. Nonetheless, dust features including size, shape, type, etc. are geologically known. Several mitigation methods have been studied for the reduction of dust concentration on the exterior face of the PV modules. The outcomes have demonstrated that dust concentration and pollutants remarkably affect the PV panel energy production. This paper reviews the recently developed research on the outcomes of the dust effect on PV panels in different locations and meets the needs of future research on this subject. Moreover, different cleaning methods that could be advantageous for future researchers in opting for the most applicable technique for dust removal are reviewed.

Potential for using tropical solid wood waste from the Amazon for the production of edge glued panels

The objective of this study was to evaluate the potential use of solid wood waste of the following species Cedrela odorata, Enterolobium schomburgkii, Erisma uncinatum, and Qualea paraensis for the manufacture of edge glued panels. The quality of the finger joint and edge bonding with PVA and EPI adhesives, respectively, with spreading rates of 180 g.m-2, was evaluated through static bending, parallel tensile, and shear tests, using ASTM D 5572, EN 13353, and EN 13354 standards. A total of 1,460 test specimens exposed to dry, high temperature, triple cycle, and wet pre-treatments were tested for glue line resistance. The results of all tests for all pre-treatments of finger joints and edge bonding demonstrated the potential of wood waste for the manufacture of edge glued panels for interior use in dry environments. There was a tendency for resistance values to be balanced in splices and joints combined with mixtures of species, possibly due to the densities of the wood pieces. Wet pre-treatment delivered excellent lower 5th percentile results, highlighting the potential of Amazonian tropical solid wood waste for the production of edge glued panels.

An econometric analysis of the sawmill by-product market to explore bioeconomy options in Austria

Bioeconomy strategies promote higher shares of biomass products in material and energy sectors. Deploying by-products from sawmills is therefore of major interest. This study aims at analyzing market characteristics and implications of bioeconomy strategies by combining three methods: First, an econometric supply and demand model for sawmill by-products (SBP) was estimated based on data from 2001 to 2020. Second, the model was used to analyze a reference and a bioeconomy scenario. Third, a use case was analyzed dealing with the integration of wood gasification and BioSNG (Synthetic Natural Gas) production into Austrian flows of SBP. The results indicate that SBP supply reacts unit-elastic to sawnwood exports, while both supply and demand respond inelastic to SBP prices. Demand is positively inelastic related to SBP as input in panel and pellet production. In a bioeconomy scenario, long-term supply would exceed demand, resulting in additional SBP to be used for gasification. A 100 MW BioSNG plant converting these SBP could provide 528 MWh BioSNG per year. This is a 11 % share of the Austrian target value of 5 TWh green gas.

A Timber–Concrete–Composite Edge Connection for Two-Way Spanning Cross-Laminated Timber Slabs—Experimental Investigations and Analytical Approach

This paper introduces a method to create a moment-resisting edge connection between two cross-laminated timber (CLT) panels. With this connection, two-way spanning cross-laminated timber slabs can be realised, where the span exceeds the manufacturing and transport-related width of the individual CLT panels. Until now, mostly on-site gluing solutions have been suggested for such connections. In this study, a solution using a timber–concrete–composite (TCC) system is proposed. For this, self-tapping screws are inserted along the edge face of the CLT component, enabling the formation of a lap splice between two adjacent CLT elements. This lap splice is reinforced by additional rebars and filled with concrete. This means that only familiar, easy-to-handle materials are used on-site, and there is no need for adhesives, which can be difficult to apply. To evaluate the load-bearing capacity of the connection, it was subjected to a pure bending load in four-point bending tests, where load-bearing capacities of up to 70% of the characteristic load-bearing capacity of the solid CLT elements were achieved. An analytical approach for a simplified engineering calculation model is introduced to determine the load acting upon the screws. Based on the experimental results, it is shown that the analytical approach is able to adequately represent the load-bearing capacity of the connection. The analytically determined forces on the screws may then be used to carry out further verifications on this connection method.

Efficient laboratory perovskite solar cell recycling with a one-step chemical treatment and recovery of ITO-coated glass substrates

The proliferation of organic–inorganic perovskite solar cells (PSCs) has garnered considerable attention due to their potential for low-cost, large-scale photovoltaic panel production. However, the inclusion of lead in PSCs poses significant sustainability challenges, necessitating effective end-of-life treatment strategies to mitigate environmental pollution and comply with electronic waste disposal regulations. In this study, we present a novel recycling system for decomposing and reclaiming the constituent materials of a typical PSC. Utilizing a one-step solution process extraction approach, we successfully preserved the chemical composition of each layer, enabling their potential reuse. This recycling method not only addresses the separation of the toxic lead component but also emphasizes the recovery of other valuable PSC layers. Notably, the commonly used hole transport layer in perovskite solar cells is Spiro-OMeTAD, which was successfully extracted with chlorobenzene, with its purity subsequently confirmed. Moreover, the removal of individual layers facilitated the retrieval of indium-doped tin oxide (ITO) conductive glass, a critical substrate in PSC fabrication. Comparative analysis of the physical and electrical properties of recycled and reference ITO substrates revealed minimal discrepancies, indicating the feasibility of reusing recycled substrates without compromising device performance. The proposed recycling technique offers a practical approach to mitigate pollution risks, minimize waste generation during the recycling process of perovskite-based solar cells, and reduce end-of-life recycling costs.

Forecasting meteorological impacts on the environmental sustainability of a large-scale solar plant via artificial intelligence-based life cycle assessment

Although large-scale solar (LSS) is a promising renewable energy technology, it causes adverse impacts on the ecosystem, human health, and resource depletion throughout its upstream (i.e., raw material extraction to solar panel production) and downstream (i.e., plant demolition and waste management) processes. The LSS operational performance also fluctuates due to meteorological conditions, leading to uncertainty in electricity generation and raising concerns about its overall environmental performance. Hitherto, there has been no evidence-backed study that evaluates the ecological sustainability of LSS with the consideration of meteorological uncertainties. In this study, a novel integrated Life Cycle Assessment (LCA) and Artificial Neural Network (ANN) framework is developed to forecast the meteorological impacts on LSS's electricity generation and its life cycle environmental sustainability. For LCA, 18 impact categories and three damage categories are characterised and assessed by ReCiPe 2016 via SimaPro v. 9.1. For ANN, a feedforward neural network is applied via Neural Designer 5.9.3. Taking an LSS plant in Malaysia as a case study, the photovoltaic panel production stage contributes the highest environmental impact in LSS (30 % of human health, 30 % of ecosystem quality, and 34 % of resource scarcity). Aluminium recycling reduces by 10 % for human health, 10 % for ecosystem quality, and 9 % for resource scarcity. The emissions avoided by the forecasted LSS-generated electricity offset the environmental burden for human health, ecosystem quality, and resource scarcity 12–68 times, 13–73 times, and 18–98 times, respectively. The developed ANN-LCA framework can provide LSS stakeholders with data-backed insights to effectively design an environmentally conscious LSS facility, considering meteorological influences.

Over 18% Efficiency Ternary Organic Solar Cells with 300nm Thick Active Layer Enabled by an Oligomeric Acceptor.

The development of high-efficiency thickness-insensitive organic solar cells (OSCs) is crucially important for the mass production of solar panels. However, increasing the active layer thickness usually induces a substantial loss in efficiency. Herein, a ternary strategy in which an oligomer DY-TF is incorporated into PM6:L8-BO system as a guest component is adopted to break this dilemma. The S···F intramolecular noncovalent interactions in the backbone endow DY-TF with a high planarity. Upon the addition of DY-TF, the crystallinity of the blend is effectively improved, leading to increased charge carrier mobility, which is highly desirable in the fabrication of thick-film devices. As a result, thin-film PM6:L8-BO:DY-TF-based device (110nm) shows a power conversion efficiency (PCE) of 19.13%. Impressively, when the active layer thickness increases to 300nm, an efficiency of 18.23% (certified as 17.8%) is achieved, representing the highest efficiency reported for 300 nm thick OSCs thus far. Additionally, blade-coated thick device (300nm) delivers a promising PCE of 17.38%. This work brings new insights into the construction of efficient OSCs with high thickness tolerance, showing great potential for roll-to-roll printing of large-area solar cells.

IoT Monitoring for PV System Optimization in Hospital Environment Application

Purpose: The objective of this study is to implement IoT monitoring to remotely monitor PV system output and efficiency to ensure the continuous supply to ventilators and monitors in the ICU Room of RSI Siti Khadijah Palembang.
 Methodology/approach: The approach implemented in this study is by installing IoT Monitoring as an automatic transfer switch to ensure the continuous supply for the load.
 Results/findings: The IoT monitoring shows the real-time production of PV panels, battery capacity, and inverter output. Hence, the operator can monitor the PV system output and decide whether to keep using sources from PV panels or switch to grid utilities during cloudy/rainy days.
 Limitations: The IoT monitoring system has supervised the system's reliability, but it is necessary to improve the output and efficiency of the PV system by adding artificial intelligence algorithms and installing active cooling to prevent overheating.
 Contribution: This study shows the effectiveness of implementing IoT monitoring for the On-Grid PV system installed on the rooftop of RSI Siti Khadijah Palembang.

ELIMINATION OF THE DEFECTIVE LAYER AND STRESS CONCENTRATORS DURING MICROMACHINING OF HOLES IN THIN SHEET BLANKS OF METAL CELLULAR PANELS

Thin-sheet blanks made of aluminum (in particular, AMg2-N), titanium (VT-15, VT-19) or stainless (12X17) alloys are widely used in the production of honeycomb panels in the aviation and space industries. Foil (thickness 0.025-0.055 mm) is used for the production of fillers for cellular sandwich panels; it is pre-perforated with holes of 0.05-0.18 mm and laid out in a corrugated box with adhesive strips. The possibility of making holes by the laser jet method is considered, as it precedes the occurrence of mechanical damage and thermal defects of the surface adjacent to the treatment zone. It is shown that the Water Jet Guided Laser (WJGL) is an effective and efficient method of obtaining profile holes in the fillers of cellular panels and in the panels themselves, which is characterized by high productivity and allows obtaining holes without thermal and mechanical defects. The method can be used both for foil fillers and for metal panels made of stainless steel up to 1.5 mm thick.

Control of technological parameters in the process of ribbed panel forging: use of measuring equipment and mathematical modeling methods

The article discusses the control of technological parameters for the process of isothermal forging of cross-ribbed panels. To ensure defect-free manufacturing of panels, strict adherence to the temperature and rate conditions is required. However, due to errors and external disturbances, the measuring equipment does not often provide reliable information. In addition, the temperature of the metal in the deformation zone can only be estimated indirectly. Therefore, by analogy with the Kalman filter, it is proposed to combine data from sensors and the results calculated using the finite element method. For this purpose, the accuracy and speed of calculation of the finite element model were studied in four popular specialized software products: DeForm, QForm, Forge NxT, Simufact Forming. Comparison of the results of the analysis made it possible to confirm the high degree of reliability of modeling and the potential possibility of controlling technological parameters for the production of defect-free panels by the suggested way. It is shown that the finite element method in the two-dimensional formulation of the problem provides an acceptable calculation speed for monitoring the progress of operations in real time. The obtained results are relevant for metallurgical enterprises for which there are increased requirements for compliance with the range of permissible changes in technological parameters during production processes.

Direct Tensile Capacity of Steel-Tube Connections in a Precast Concrete Double-Wall System

This study introduces a new precast concrete (PC) double-wall system designed to simplify the complex fabrication process of existing PC double-wall systems and eliminate laitance and other defects that can occur during the manufacture of concrete panels. An experiment and finite element analysis were conducted on 11 specimens to determine the tensile resistance performance of rectangular steel tubes that maintain spacing to avoid damage to the PC panels during transportation or on-site installation. Specimens varied in terms of the end details of the rectangular steel tubes, such as the presence of welded steel plates or embedded concrete and total length in terms of whether longer or shorter specimens were used. As a result, the specimens showed a 20–30% increase in maximum tensile strength compared to the control specimen according to the end details, except for the case where side steel plates were cut and bent inward. The control specimen filled with concrete was the most suitable for connections when constructing PC double-wall systems. It has significant tensile resistance according to the experiment and finite element analysis and does not require additional construction steps or costs.

Development of highly porous alkaline cements from industrial waste for thermal insulation of building envelops

Alkali activated cements (AAC) are becoming an increasingly promising alternative to traditional Portland cement. There are still some significant barriers which have yet to be addressed, by all the agents involved in the construction industry. However, it appears that some AAC applications can be introduced in current applications at a faster rate than, for instance, structural concrete. One of these applications are materials with thermal performance, based on the capacity of some types of AAC to expand during initial reactions. The present paper aims to assess the viability of producing porous AAC for application in thermally effective façade panels. A wide range of industrial by-products were activated with sodium hydroxide and sodium silicate. Two additional by-products were incorporated to increase the thermal damping of the pastes, with the intention of taking advantage of the large pore volume. Flexural and compressive strength and density was measured, and selected pastes were then submitted to microstructural characterisation (SEM/EDX), environmental behaviour (heavy metal leaching), porosity (SEM) and thermal performance (thermal coefficient). The results showed maximum compressive strengths of 2.5 MPa, while the majority of the pastes tested showed conductivity values below the threshold of 0.2 W/m.°C, which is the requirement for obtaining a classification of ‘thermal’. Therefore, the production of panels for thermal insulation based on alkali activated industrial by-products is competitive with traditional materials based on current commercial solutions, and, given the non-structural nature of this application, can be very close to reach industrial production.