In operational applications, hyperelastic adhesive joints are exposed to environmental conditions (moisture and temperature) that affect their mechanical performance. The understanding of how the environment can influence the joint durability through both static and cyclic loading is a key aspect to ensure safety and avoid over-dimensioning. The current work presents an investigation of the effect of environment conditions on the diffusion and mechanical performance of two different hyperelastic adhesive joints (a polyurethane and a silicon-modified polymer). To assess the process of moisture mass diffusion, pure adhesive samples were weighted for 387 days when subjected to outdoor weathering conditions. An FEA-diffusion procedure method was demonstrated by (i) predicting the saturation concentration at steady conditions of 40 °C/15% r.h. (40/15) and 40 °C/60% r.h. (40/60), and (ii) predicting the experienced mass change due to outdoor weathering. The reversibility of the effect of conditioning at 40 °C/60% r.h. on the mechanical properties of the adhesives was assessed via quasi-static and fatigue tensile shear testing. The results support the conclusion that conditioning with the surrogate climate of 40 °C/60% r.h. does not cause irreversible damage, as any potential decrease in shear modulus, tensile shear strength and fatigue life due to 40/60 conditioning can be reversed by re-drying at 40/15.
{"title":"FE-Simulation and Experimental Characterisation of Environmental Effects on the Diffusion and Mechanical Performance of Hyperelastic Adhesive Joints","authors":"P. Fernandes, A. Wulf, C. Nagel, V. C. Beber","doi":"10.3390/eng4030121","DOIUrl":"https://doi.org/10.3390/eng4030121","url":null,"abstract":"In operational applications, hyperelastic adhesive joints are exposed to environmental conditions (moisture and temperature) that affect their mechanical performance. The understanding of how the environment can influence the joint durability through both static and cyclic loading is a key aspect to ensure safety and avoid over-dimensioning. The current work presents an investigation of the effect of environment conditions on the diffusion and mechanical performance of two different hyperelastic adhesive joints (a polyurethane and a silicon-modified polymer). To assess the process of moisture mass diffusion, pure adhesive samples were weighted for 387 days when subjected to outdoor weathering conditions. An FEA-diffusion procedure method was demonstrated by (i) predicting the saturation concentration at steady conditions of 40 °C/15% r.h. (40/15) and 40 °C/60% r.h. (40/60), and (ii) predicting the experienced mass change due to outdoor weathering. The reversibility of the effect of conditioning at 40 °C/60% r.h. on the mechanical properties of the adhesives was assessed via quasi-static and fatigue tensile shear testing. The results support the conclusion that conditioning with the surrogate climate of 40 °C/60% r.h. does not cause irreversible damage, as any potential decrease in shear modulus, tensile shear strength and fatigue life due to 40/60 conditioning can be reversed by re-drying at 40/15.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90931950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hazem H. Hammam, Mostafa A. Hosny, H. Omran, S. Ibrahim
One of the most popular power management regulators is the low drop-out voltage regulator (LDO). LDOs have different specifications such as the power supply rejection (PSR) over different frequencies, stability over different load ranges, inrush current spike flows through the input supply, and power consumption. In this work, we present a low power low inrush current LDO design with different techniques for PSR and stability improvement across different frequencies. The LDO presented in this work is a low-power and small area LDO but achieves a high PSR over a wide range of frequencies. The LDO is designed in 65 nm CMOS technology and achieves a PSR better than 80 dB up to 30 MHz for an output load current of 25 mA using an output load capacitor of 4 µF. The design can be used in capless/capped LDOs with wide load current ranges as high as 200 mA and load capacitor range from 1 nF to 12 µF with inrush current improvement by more than 2×. The presented LDO consumes a zero-load quiescent current of 10 µA and its area of 180 µm × 180 µm.
{"title":"A Low Power Low Inrush Current LDO with Different Techniques for PSR and Stability Improvement","authors":"Hazem H. Hammam, Mostafa A. Hosny, H. Omran, S. Ibrahim","doi":"10.3390/eng4030120","DOIUrl":"https://doi.org/10.3390/eng4030120","url":null,"abstract":"One of the most popular power management regulators is the low drop-out voltage regulator (LDO). LDOs have different specifications such as the power supply rejection (PSR) over different frequencies, stability over different load ranges, inrush current spike flows through the input supply, and power consumption. In this work, we present a low power low inrush current LDO design with different techniques for PSR and stability improvement across different frequencies. The LDO presented in this work is a low-power and small area LDO but achieves a high PSR over a wide range of frequencies. The LDO is designed in 65 nm CMOS technology and achieves a PSR better than 80 dB up to 30 MHz for an output load current of 25 mA using an output load capacitor of 4 µF. The design can be used in capless/capped LDOs with wide load current ranges as high as 200 mA and load capacitor range from 1 nF to 12 µF with inrush current improvement by more than 2×. The presented LDO consumes a zero-load quiescent current of 10 µA and its area of 180 µm × 180 µm.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75999922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paulo V. R. Gomes, R. N. Bonifácio, Barbara P. G. Silva, J. C. Ferreira, R. D. de Souza, L. Otubo, D. Lazar, A. O. Neto
This study reports a bottom-up approach for the conversion of cyclohexane into graphene nanoflakes, which were then deposited onto fiberglass using a non-thermal generator. The composite was characterized using transmission electron microscopy, which revealed the formation of stacked few-layer graphene with a partially disordered structure and a d-spacing of 0.358 nm between the layers. X-ray diffraction confirmed the observations from the TEM images. SEM images showed the agglomeration of carbonaceous material onto the fiberglass, which experienced some delamination due to the synthesis method. Raman spectroscopy indicated that the obtained graphene exhibited a predominance of defects in its structure. Additionally, atomic force microscopy (AFM) analyses revealed the formation of graphene layers with varying levels of porosity.
{"title":"Graphene Deposited on Glass Fiber Using a Non-Thermal Plasma System","authors":"Paulo V. R. Gomes, R. N. Bonifácio, Barbara P. G. Silva, J. C. Ferreira, R. D. de Souza, L. Otubo, D. Lazar, A. O. Neto","doi":"10.3390/eng4030119","DOIUrl":"https://doi.org/10.3390/eng4030119","url":null,"abstract":"This study reports a bottom-up approach for the conversion of cyclohexane into graphene nanoflakes, which were then deposited onto fiberglass using a non-thermal generator. The composite was characterized using transmission electron microscopy, which revealed the formation of stacked few-layer graphene with a partially disordered structure and a d-spacing of 0.358 nm between the layers. X-ray diffraction confirmed the observations from the TEM images. SEM images showed the agglomeration of carbonaceous material onto the fiberglass, which experienced some delamination due to the synthesis method. Raman spectroscopy indicated that the obtained graphene exhibited a predominance of defects in its structure. Additionally, atomic force microscopy (AFM) analyses revealed the formation of graphene layers with varying levels of porosity.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75851646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1016/j.compchemeng.2023.108388
Mohammed Yaqot, B. Menezes, J. D. Kelly
{"title":"Real-time coordination of multiple shuttle-conveyor-belts for inventory control of multi-quality stockpiles","authors":"Mohammed Yaqot, B. Menezes, J. D. Kelly","doi":"10.1016/j.compchemeng.2023.108388","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2023.108388","url":null,"abstract":"","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"114 1","pages":"108388"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79737156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1016/j.compchemeng.2023.108382
Wentao Tang, P. Carrette, Y. Cai, J. M. Williamson, P. Daoutidis
{"title":"Automatic decomposition of large-scale industrial processes for distributed MPC on the Shell-Yokogawa Platform for Advanced Control and Estimation (PACE)","authors":"Wentao Tang, P. Carrette, Y. Cai, J. M. Williamson, P. Daoutidis","doi":"10.1016/j.compchemeng.2023.108382","DOIUrl":"https://doi.org/10.1016/j.compchemeng.2023.108382","url":null,"abstract":"","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"10 1","pages":"108382"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73190382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose an unsupervised method for eigen tree hierarchies and quantisation group association for segmentation of corrosion in marine vessel hull inspection via camera images. Our unsupervised approach produces image segments that are examined to decide on defect recognition. The method generates a binary decision tree, which, by means of bottom-up pruning, is revised, and dominant leaf nodes predict the areas of interest. Our method is compared with other techniques, and the results indicate that it achieves better performance for true- vs. false-positive area against ideal (ground truth) coverage.
{"title":"Automatic Identification of Corrosion in Marine Vessels Using Decision-Tree Imaging Hierarchies","authors":"G. Chliveros, S. Kontomaris, Apostolos Letsios","doi":"10.3390/eng4030118","DOIUrl":"https://doi.org/10.3390/eng4030118","url":null,"abstract":"We propose an unsupervised method for eigen tree hierarchies and quantisation group association for segmentation of corrosion in marine vessel hull inspection via camera images. Our unsupervised approach produces image segments that are examined to decide on defect recognition. The method generates a binary decision tree, which, by means of bottom-up pruning, is revised, and dominant leaf nodes predict the areas of interest. Our method is compared with other techniques, and the results indicate that it achieves better performance for true- vs. false-positive area against ideal (ground truth) coverage.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86216839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karima Touati, Baraa Al Sahmarany, Malo Le Guern, Y. El Mendili, F. Streiff, S. Goodhew
Mastering construction times is of paramount importance in making vernacular earth construction techniques attractive to modern clients. The work presented here is a contribution towards the optimization of the construction time of cob buildings. Therefore, this paper follows the evolution of a cob’s mechanical properties during its drying process in the case of a double-walling CobBauge system. Laboratory tests and in situ measurements were performed, and further results were described. Volumetric water content sensors were immersed in the walls of a CobBauge prototype building during its construction. The evolution of the cob layer’s compressive strength and Clegg Impact Value (CIV) as a function of its water content has been experimentally studied and discussed. These studies showed that compressive strength and CIV are correlated with water content, and both properties decrease exponentially with time. In this study, a new tool to evaluate cob’s mechanical performances in situ has been proposed, Clegg Impact Soil Tester. This was linked to compressive strength, and a linear relationship between these two properties was found. Finally, appropriate values of compressive strength and CIV to satisfy before formwork stripping and re-lifting were proposed. For this study’s conditions, these values are reached after approximately 27 days.
{"title":"Insight into the Optimization of Implementation Time in Cob Construction: Field Test and Compressive Strength Versus Drying Kinetics","authors":"Karima Touati, Baraa Al Sahmarany, Malo Le Guern, Y. El Mendili, F. Streiff, S. Goodhew","doi":"10.3390/eng4030117","DOIUrl":"https://doi.org/10.3390/eng4030117","url":null,"abstract":"Mastering construction times is of paramount importance in making vernacular earth construction techniques attractive to modern clients. The work presented here is a contribution towards the optimization of the construction time of cob buildings. Therefore, this paper follows the evolution of a cob’s mechanical properties during its drying process in the case of a double-walling CobBauge system. Laboratory tests and in situ measurements were performed, and further results were described. Volumetric water content sensors were immersed in the walls of a CobBauge prototype building during its construction. The evolution of the cob layer’s compressive strength and Clegg Impact Value (CIV) as a function of its water content has been experimentally studied and discussed. These studies showed that compressive strength and CIV are correlated with water content, and both properties decrease exponentially with time. In this study, a new tool to evaluate cob’s mechanical performances in situ has been proposed, Clegg Impact Soil Tester. This was linked to compressive strength, and a linear relationship between these two properties was found. Finally, appropriate values of compressive strength and CIV to satisfy before formwork stripping and re-lifting were proposed. For this study’s conditions, these values are reached after approximately 27 days.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73450604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dmitrii G. Shadrin, A. Menshchikov, Artem V. Nikitin, G. Ovchinnikov, Vera Volohina, S. Nesteruk, M. Pukalchik, M. Fedorov, A. Somov
Leaf area and biomass are important morphological parameters for in situ plant monitoring since a leaf is vital for perceiving and capturing the environmental light as well as represents the overall plant development. The traditional approach for leaf area and biomass measurements is destructive requiring manual labor and may cause damages for the plants. In this work, we report on the AI-based approach for assessing and predicting the leaf area and plant biomass. The proposed approach is able to estimate and predict the overall plants biomass at the early stage of growth in a non-destructive way. For this reason we equip an industrial greenhouse for cucumbers growing with the commercial off-the-shelf environmental sensors and video cameras. The data from sensors are used to monitor the environmental conditions in the greenhouse while the top-down images are used for training Fully Convolutional Neural Networks (FCNN). The FCNN performs the segmentation task for leaf area calculation resulting in 82% accuracy. Application of trained FCNNs to the sequences of camera images allowed the reconstruction of per-plant leaf area and their growth-dynamics. Then we established the dependency between the average leaf area and biomass using the direct measurements of the biomass. This in turn allowed for reconstruction and prediction of the dynamics of biomass growth in the greenhouse using the image data with 10% average relative error for the 12 days prediction horizon. The actual deployment showed the high potential of the proposed data-driven approaches for plant growth dynamics assessment and prediction. Moreover, it closes the gap towards constructing fully closed autonomous greenhouses for harvests and plants biological safety.
{"title":"Assessment of Leaf Area and Biomass through AI-Enabled Deployment","authors":"Dmitrii G. Shadrin, A. Menshchikov, Artem V. Nikitin, G. Ovchinnikov, Vera Volohina, S. Nesteruk, M. Pukalchik, M. Fedorov, A. Somov","doi":"10.3390/eng4030116","DOIUrl":"https://doi.org/10.3390/eng4030116","url":null,"abstract":"Leaf area and biomass are important morphological parameters for in situ plant monitoring since a leaf is vital for perceiving and capturing the environmental light as well as represents the overall plant development. The traditional approach for leaf area and biomass measurements is destructive requiring manual labor and may cause damages for the plants. In this work, we report on the AI-based approach for assessing and predicting the leaf area and plant biomass. The proposed approach is able to estimate and predict the overall plants biomass at the early stage of growth in a non-destructive way. For this reason we equip an industrial greenhouse for cucumbers growing with the commercial off-the-shelf environmental sensors and video cameras. The data from sensors are used to monitor the environmental conditions in the greenhouse while the top-down images are used for training Fully Convolutional Neural Networks (FCNN). The FCNN performs the segmentation task for leaf area calculation resulting in 82% accuracy. Application of trained FCNNs to the sequences of camera images allowed the reconstruction of per-plant leaf area and their growth-dynamics. Then we established the dependency between the average leaf area and biomass using the direct measurements of the biomass. This in turn allowed for reconstruction and prediction of the dynamics of biomass growth in the greenhouse using the image data with 10% average relative error for the 12 days prediction horizon. The actual deployment showed the high potential of the proposed data-driven approaches for plant growth dynamics assessment and prediction. Moreover, it closes the gap towards constructing fully closed autonomous greenhouses for harvests and plants biological safety.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84821993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jessica McKenna, Sophia Harris, Kris Heinrich, Taylor Stewart, K. Gharehbaghi
Green building materials have nontoxic properties and are made from recycled materials. This means they are, in most cases, created from renewable resources in comparison to non-renewable resources. This research aims to further improve the justification of green buildings and their materials. This is undertaken to determine the validity of such construction techniques. This research utilizes both qualitative and quantitative methods through five Australian case studies. The case studies, which are based on new and redeveloped structures, are selected via different geological locations and are evaluated via logical argumentation along with correlation research. Further, the research will address the problem by identifying a variety of green building materials that can be used to substitute non-green building materials. With careful comparisons among the five buildings, the green signs and implementation advantages and disadvantages will be evaluated. The result of this comparison will assist in improving the current education around the topic of green building and benefit the overall response to positive change within the construction industry. Although green building initiatives are not difficult to apply, they can be cost efficient. To maximize their cost efficiency, these initiatives need to be fully adopted. This includes the adaptation of specific building orientation, design, and sealing off penetrations to greatly improve passive heating and cooling. Further, the use of rainwater tanks also assists with energy efficiency by reducing the amount of mains water used. The utilization of natural lighting along with an advanced solar power system would further reduce the overall energy usage.
{"title":"The Evaluation of Green Building’s Feasibility: Comparative Analysis across Different Geological Conditions","authors":"Jessica McKenna, Sophia Harris, Kris Heinrich, Taylor Stewart, K. Gharehbaghi","doi":"10.3390/eng4030115","DOIUrl":"https://doi.org/10.3390/eng4030115","url":null,"abstract":"Green building materials have nontoxic properties and are made from recycled materials. This means they are, in most cases, created from renewable resources in comparison to non-renewable resources. This research aims to further improve the justification of green buildings and their materials. This is undertaken to determine the validity of such construction techniques. This research utilizes both qualitative and quantitative methods through five Australian case studies. The case studies, which are based on new and redeveloped structures, are selected via different geological locations and are evaluated via logical argumentation along with correlation research. Further, the research will address the problem by identifying a variety of green building materials that can be used to substitute non-green building materials. With careful comparisons among the five buildings, the green signs and implementation advantages and disadvantages will be evaluated. The result of this comparison will assist in improving the current education around the topic of green building and benefit the overall response to positive change within the construction industry. Although green building initiatives are not difficult to apply, they can be cost efficient. To maximize their cost efficiency, these initiatives need to be fully adopted. This includes the adaptation of specific building orientation, design, and sealing off penetrations to greatly improve passive heating and cooling. Further, the use of rainwater tanks also assists with energy efficiency by reducing the amount of mains water used. The utilization of natural lighting along with an advanced solar power system would further reduce the overall energy usage.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76368014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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