Stabilization of solitons of the multidimensional nonlinear Schrodinger equation: Matter-wave breathers

We demonstrate that stabilization of solitons of the multidimensional Schrodinger equation with a cubic nonlinearity may be achieved by a suitable periodic control of the nonlinear term. The effect of this control is to stabilize the unstable solitary waves which belong to the frontier between expanding and collapsing solutions and to provide an oscillating solitonic structure, some sort of breather-type solution. We obtain precise conditions on the control parameters to achieve the stabilization and compare our results with accurate numerical simulations of the nonlinear Schrodinger equation. Because of the application of these ideas to matter waves these solutions are some sort of matter breathers

Airflow and Thermal Behavior within Peaches Packaging Box Using Computational Fluid Dynamics - A Preliminary Study

Post-harvest cold storage of peaches is an essential element to maintain the quality of the fruits without any loss. This work aims to present a CFD model, to predict airflow patterns and temperature profiles in ventilated packaging systems, during the forced-air cooling of Peaches stored in a cold chamber. Transient CFD simulations are performed for the chamber containing four ventilated boxes and the evaluation of the results show that the temperature removal near the vent holes and the hand holes is relatively high when compared to other regions of the packaging box. This preliminary study reveals the airflow behavior develop an uneven temperature distribution within the box. To overcome the flaws, future work is focused on modifying the vent hole design to improve the airflow phenomenon to maintain the temperature homogeneity throughout the box. Keywords: Peach, Computational fluid dynamics, Airflow, Heat transfer, Packagin

Testing of a resistive sensor with fabric medium for monitoring frost formation in refrigeration systems

Refrigeration is one of the key elements for food preservation. With global temperatures increasing due to global warming, the efficiency in refrigerated storage systems must be improved. One of the problems that is yet to be solved in these systems is the efficient and accurate removal of the frost formed on the heat exchanger surface. In previous works, a low-cost resistive sensor has been developed to detect frost formation for accurate removal. This paper shows the results of an experimental study carried out to increase the accuracy, by placing different configurations of a fabric medium in between the sensor electrodes.This study is within the activities of project “Pack2Life – High performance packaging”, project IDT in consortium No.33792, call No.03/SI/2017, Ref. POCI-01-0247-FEDER-033792, promoted by COMPETE 2020 and co-funded by FEDER within Portugal 2020. This work has been supported by the project Centro-01-0145-FEDER000017 - EMaDeS - Energy, Materials and Sustainable Development, co-funded by the Portugal 2020 Program (PT 2020), within the Regional Operational Program of the Center (CENTRO 2020) and the European Union through the European Regional Development Fund (ERDF). The authors thank the opportunity and financial support to carry on this project to Fundação para a Ciência e Tecnologia (FCT) and R&D Unit "Centre for Mechanical and Aerospace Science and Technologies" (C-MAST), under project UIDB/00151/2020.info:eu-repo/semantics/publishedVersio

Active and Intelligent Packaging with Phase Change Materials to Promote the Shelf Life Extension of Food Products

Active packaging aims to extend the shelf life of fruits and vegetables using active agents such as Oxygen, Carbon-di-oxide, ethylene scavengers and moisture absorber. Intelligent packaging provides information about the fruits quality inside the package to the customer and this packaging technology detects the internal changes of fruits and vegetables using sensors and indicators. Further to improve the post-harvest storage PCM such as Rubitherm can be used depending on the package box dimension to remove the field heat from the products and maintain its temperature with low variation during transport and display. Gel packs having less weight with PET and PS can also be an alternate method in the packaging. The application of these technologies may lead to a revolution in post-harvest storage, transportation, and further retail sale. This paper reviews the theoretical principles of food packaging and recent developments in packaging technologies using PCMs. Keywords: Active packaging, Intelligent packaging, Phase change materials, Shelf life extension, Fruit

Experimental study of a hybrid solar photovoltaic, thermoelectric and thermal module

Nowadays, solar energy, which can be photovoltaic and thermal, is a clean and reliable source of energy for the production of electric and thermal power. However, new ways for improving photovoltaic efficiency are fundamental for an extensive application of this technology. Most of the energy absorbed by the PV panel converts itself into heat, which usually is lost and does not have any energetic value. The performance of a combined photovoltaic (PV), thermoelectric generator (TEG) and water heating panel is tested in practice. The thermoelectric set is applied on the back of the PV panel so that the two devices have approximately the same temperature. On the other face of the thermoelectric set, there is the water heating panel, which consists of an aluminium heat exchanger specially designed for this hybrid module. The exposed surface of the hybrid panel has an area of about 2.72 dm2. Experimental tests were conducted in direct solar exposure during July. The experimental results indicate that the maximum global module efficiency was 91.3% for an irradiance of 1089 W/m2. The power peak production was 29.7 W, at 2 p.m., with an irradiance value of 1230 W/m2.info:eu-repo/semantics/publishedVersio

Experimental Study of Thermal Performance of Different Fruit Packaging Box Designs

Packaging was recently identified as an essential element in addressing the key challenge of sustainable food supply and is gaining interest among researchers. It is a central element in food quality preservation due to its role in heat and mass exchange with the external atmosphere, contributing to the preservation of food quality during storage and extending food shelf life. This work proposes three new packaging configurations with the same size but different geometry and ventilation hole sizes and geometry, that change the conditions in which the heat and mass exchange occurs, during either the cooling period of fruits, inside the cooling chamber, or during the period when the packaging is exposed to ambient conditions, outside the cooling chamber. For this purpose, packages with fruit models that replicate the properties of real fruit were subjected to a cooling process inside a cooling chamber for 8 h. Subsequently, during the heating phase, the packages were exposed to ambient conditions for 10 h. Thermal conditions were also monitored, both inside and outside the chamber. Additionally, for comparative purposes, the thermal behavior of commercial packaging was also evaluated for the same operating conditions in the cooling and heating phases. The results show that the new packages do not substantially promote the preservation of fruits in the cooling phase, but in the heating phase, they ensure an extension of the period with proper thermal conditions of up to 50% in relation to the conventional packaging. This result is particularly important since the heating phase, in which fruits are outside the storage chamber, is the period with the greatest impact on the fruits’ useful life.This study was conducted within the activities of project “Pack2Life—High performance packaging”, project IDT in consortium n. 33792, call n. 03/SI/2017, Ref. POCI-01-0247-FEDER- 033792, promoted by COMPETE 2020 and co-funded by FEDER within Portugal 2020. The authors are grateful for the opportunity and financial support to continue this project to Fundação para a Ciência e a Tecnologia (FCT) and R&D Unit “Centre for Mechanical and Aerospace Science and Technologies” (C-MAST), under project UIDB/00151/2020.info:eu-repo/semantics/publishedVersio

Conveyor Belt Operation Case Study

Publisher Copyright: © 2023 by the authors.Conveyor belts (CBs) are widely used for the continuous transport of bulk materials. CBs must be extremely reliable due to the cost associated with their failure in continuous production systems. Thus, it is highly relevant in terms of maintenance and planning to find solutions to reduce the existing stoppages from these assets. In this sense, it is essential to monitor and collect real-time data from this piece of equipment. This work presents a case study, where a model that combines the Lean Philosophy, Total Productive Maintenance (TPM), and the enabling technologies of Industry 4.0 is applied to a CB. The proposed model monitors the CB and provides data on its operation, which, using the calculation of indicators, allows a more accurate and thorough view and evaluation, contributing to improving and supporting decision making by those responsible for maintenance. The data collected by the sensor help those responsible for maintenance and production, in the readjustment of more accurate and optimized planning, programming, and execution, supporting decision making in these areas. During the field test of a two-hour monitoring period (10 a.m. to 12 p.m.), the model identified six stoppages, resulting in approximately 88.6% of operational time for the conveyor. The field test showed that this model can result in more accurate maintenance decision making than conventional approaches. This research also contributes to the advancement of electronics and industrial automation sectors by empowering companies to transform maintenance methodologies. The potential of this approach and its implications for enhanced productivity and overall performance are therefore highlighted.publishersversionpublishe

Medium materials for improving frost detection on a resistive sensor

Reducing food waste demands improvements in refrigeration systems. Furthermore, the rise of temperatures worldwide demands more capable and efficient refrigeration equipment. One of the problems that affects refrigeration equipment is the accumulation of frost in the heat exchanger that reduces efficiency, and in extreme cases, blocks the air flow. Usually, defrosting is timed for the worst-case scenario, which results in many unnecessary defrosting operations that compromise the efficiency, and temperature stability in the refrigerated environment. This paper presents a low-cost resistive sensor’s reliability case studies, using several materials and configurations.This study is within the activities of project “Pack2Life – High performance packaging”, project IDT in consortium n.o 33792, call n.o 03/SI/2017, Ref. POCI-01-0247-FEDER-033792, promoted by COMPETE 2020 and co-funded by FEDER within Portugal 2020. This work has was supported by the project Centro-01-0145-FEDER000017 - EMaDeS - Energy, Materials and Sustainable Development, co-funded by the Portugal 2020 Program (PT 2020), within the Regional Operational Program of the Center (CENTRO 2020) and the EU through the European Regional Development Fund (ERDF). The authors thank the opportunity and financial support to carry on this project to Fundação para a Ciência e Tecnologia (FCT) and R&D Unit “Centre for Mechanical and Aerospace Science and Technologies” (C-MAST), under project UIDB/00151/2020. The authors also thank Cláudia Monteiro for her assistance in the production of the ceramic samples.info:eu-repo/semantics/publishedVersio

Automated Weed Detection Systems: A Review

A weed plant can be described as a plant that is unwanted at a specific location at a given time. Farmers have fought against the weed populations for as long as land has been used for food production. In conventional agriculture this weed control contributes a considerable amount to the overall cost of the produce. Automatic weed detection is one of the viable solutions for efficient reduction or exclusion of chemicals in crop production. Research studies have been focusing and combining modern approaches and proposed techniques which automatically analyze and evaluate segmented weed images. This study discusses and compares the weed control methods and gives special attention in describing the current research in automating the weed detection and control. Keywords: Detection, Weed, Agriculture 4.0, Computational vision, Robotic

Methods for Detecting and Classifying Weeds, Diseases and Fruits Using AI to Improve the Sustainability of Agricultural Crops: A Review

The rapid growth of the world’s population has put significant pressure on agriculture to meet the increasing demand for food. In this context, agriculture faces multiple challenges, one of which is weed management. While herbicides have traditionally been used to control weed growth, their excessive and random use can lead to environmental pollution and herbicide resistance. To address these challenges, in the agricultural industry, deep learning models have become a possible tool for decision-making by using massive amounts of information collected from smart farm sensors. However, agriculture’s varied environments pose a challenge to testing and adopting new technology effectively. This study reviews recent advances in deep learning models and methods for detecting and classifying weeds to improve the sustainability of agricultural crops. The study compares performance metrics such as recall, accuracy, F1-Score, and precision, and highlights the adoption of novel techniques, such as attention mechanisms, single-stage detection models, and new lightweight models, which can enhance the model’s performance. The use of deep learning methods in weed detection and classification has shown great potential in improving crop yields and reducing adverse environmental impacts of agriculture. The reduction in herbicide use can prevent pollution of water, food, land, and the ecosystem and avoid the resistance of weeds to chemicals. This can help mitigate and adapt to climate change by minimizing agriculture’s environmental impact and improving the sustainability of the agricultural sector. In addition to discussing recent advances, this study also highlights the challenges faced in adopting new technology in agriculture and proposes novel techniques to enhance the performance of deep learning models. The study provides valuable insights into the latest advances and challenges in process systems engineering and technology for agricultural activities