Pub Date : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467476
Zhouqiao Zhao, Guoyuan Wu, K. Boriboonsomsin, A. Kailas
There has been growing interest in the electrification of medium- and heavy-duty vehicles (M-HDVs) in real-world, regional distribution applications. Fleet dispatch optimization of battery-electric trucks (BETs) is critical given the limited onboard energy, charging characteristics, and operational considerations. Our paper proposes a bi-level hierarchical method to optimize BET dispatch during pickup and delivery runs. With any route/scheduling change, the average speed, travel time, and energy consumption from one location to another will change accordingly because of the weight of the goods and the real-time traffic condition. So, the "electric vehicle routing problem" was extended to include pickup and delivery, time windows, and partial recharge. The proposed algorithm significantly reduces the operation cost of the BET fleet considering labor, energy consumption, and time window penalties without compromising computational efficiency.
{"title":"Vehicle Dispatching and Scheduling Algorithms for Battery Electric Heavy-Duty Truck Fleets Considering En-route Opportunity Charging","authors":"Zhouqiao Zhao, Guoyuan Wu, K. Boriboonsomsin, A. Kailas","doi":"10.1109/SusTech51236.2021.9467476","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467476","url":null,"abstract":"There has been growing interest in the electrification of medium- and heavy-duty vehicles (M-HDVs) in real-world, regional distribution applications. Fleet dispatch optimization of battery-electric trucks (BETs) is critical given the limited onboard energy, charging characteristics, and operational considerations. Our paper proposes a bi-level hierarchical method to optimize BET dispatch during pickup and delivery runs. With any route/scheduling change, the average speed, travel time, and energy consumption from one location to another will change accordingly because of the weight of the goods and the real-time traffic condition. So, the \"electric vehicle routing problem\" was extended to include pickup and delivery, time windows, and partial recharge. The proposed algorithm significantly reduces the operation cost of the BET fleet considering labor, energy consumption, and time window penalties without compromising computational efficiency.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131034665","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467474
D. Nair, R. T.
The integration of renewable energy into the existing distribution system results in the development of an active, interconnected system. PV generation is one of the widely integrated renewable energy sources. As the level of PV penetration increases the challenges will also increase. This paper presents the impact of PV in distribution systems in terms of voltage profile, power flow and short circuit analysis. This change in the short circuit current level and power flow direction will affect the coordinated operation of the protection system of the electrical network. Test systems representing distribution systems are modelled in the Python platform. Python is an open-source software platform with excellent community support, machine learning and data analysis features. A case study is conducted on an IEEE 33 bus distribution system to analyse the impact of PV penetration on protective devices and protection issues. The results show that when high PV penetration occurs the systems short circuit current level and direction of power flow changes which will affect the operation of the protective devices. Further, when PV penetration increases up to 40 % the short circuit current level may vary up to 7 times the standard value which will affect the performance of the protective device as the device setting is primarily dependent upon the short circuit current value.
{"title":"Investigation on Impact of Solar PV penetration on the Operation of Protective Relays in a Distribution System using Python","authors":"D. Nair, R. T.","doi":"10.1109/SusTech51236.2021.9467474","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467474","url":null,"abstract":"The integration of renewable energy into the existing distribution system results in the development of an active, interconnected system. PV generation is one of the widely integrated renewable energy sources. As the level of PV penetration increases the challenges will also increase. This paper presents the impact of PV in distribution systems in terms of voltage profile, power flow and short circuit analysis. This change in the short circuit current level and power flow direction will affect the coordinated operation of the protection system of the electrical network. Test systems representing distribution systems are modelled in the Python platform. Python is an open-source software platform with excellent community support, machine learning and data analysis features. A case study is conducted on an IEEE 33 bus distribution system to analyse the impact of PV penetration on protective devices and protection issues. The results show that when high PV penetration occurs the systems short circuit current level and direction of power flow changes which will affect the operation of the protective devices. Further, when PV penetration increases up to 40 % the short circuit current level may vary up to 7 times the standard value which will affect the performance of the protective device as the device setting is primarily dependent upon the short circuit current value.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132370026","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467454
J. Ordonez, Camilo Ordonez
Some of the current vaccines have shown the need to have an infrastructure for cold vaccine storage and distribution. This represents a major logistic challenge for developed countries and a major limitation for underdeveloped ones. This paper proposes the use of thermoelectric devices in the insulation of the boxes being considered for distribution of vaccines with storage requirements near 203 K. We present some initial design considerations and propose a method of use in conjunction with a conventional refrigeration to improve the ability of the box insulation active and passive strategies to maintain the desired storage temperatures.
{"title":"Thermoelectric insulation for cold temperature vaccine storage","authors":"J. Ordonez, Camilo Ordonez","doi":"10.1109/SusTech51236.2021.9467454","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467454","url":null,"abstract":"Some of the current vaccines have shown the need to have an infrastructure for cold vaccine storage and distribution. This represents a major logistic challenge for developed countries and a major limitation for underdeveloped ones. This paper proposes the use of thermoelectric devices in the insulation of the boxes being considered for distribution of vaccines with storage requirements near 203 K. We present some initial design considerations and propose a method of use in conjunction with a conventional refrigeration to improve the ability of the box insulation active and passive strategies to maintain the desired storage temperatures.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134022898","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467433
C. Monjardin, Amiel Marvin Lloyd P. Castro, F. J. Tan
Climate change has been affecting the Earth for more than several decades. With these prevailing effects, the demand to determine the possible impact of this changes in a specific area’s water availability and variability as well as rainfall levels are becoming necessary for planning. To predict the precipitation levels for the next 20 years, downscaling method was employed here. The study aimed to analyze and evaluate the effects of climate change on the water availability and variability in Bauan, Batangas by downscaling rainfall data considering Earth System Models’ Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 scenarios. The study could help in the planning and management of water supply in a certain area that mainly relies on surface water sources. The Statistical Downscaling Model – Decision Centric 4.2.9 and Hydrologic Engineering Center – Hydrological Modeling System (HEC-HMS) were used to attain the objective of this research. After the downscaling process and hydrologic simulation, a set of predicted data were produced, rainfall levels and water inflows in the watershed were generated for each RCP scenario. Results of each RCP scenario were compared to each other to analyze the differences in these what ifs scenarios. Future climate changes in Bauan, Batangas were projected under the RCP 2.6, 4.5, and 8.5 scenarios for a period of 20 years (2021 – 2041). The highest inflow data is 603.8 m3/s from the RCP 4.5 scenario while the highest average inflow was from RCP 8.5 with an inflow value of 541.848 m3/s. Meanwhile, the RCP 2.6 projected the lowest value of inflow and the lowest average among the three, with values of 359.9 m3/s and 406.505 m3/s.
{"title":"Water Availability and Variability Analysis Using Different Earth System Models RCP 2.6, 4.5, and 8.5 Scenarios in Bauan, Batangas Philippines","authors":"C. Monjardin, Amiel Marvin Lloyd P. Castro, F. J. Tan","doi":"10.1109/SusTech51236.2021.9467433","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467433","url":null,"abstract":"Climate change has been affecting the Earth for more than several decades. With these prevailing effects, the demand to determine the possible impact of this changes in a specific area’s water availability and variability as well as rainfall levels are becoming necessary for planning. To predict the precipitation levels for the next 20 years, downscaling method was employed here. The study aimed to analyze and evaluate the effects of climate change on the water availability and variability in Bauan, Batangas by downscaling rainfall data considering Earth System Models’ Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 scenarios. The study could help in the planning and management of water supply in a certain area that mainly relies on surface water sources. The Statistical Downscaling Model – Decision Centric 4.2.9 and Hydrologic Engineering Center – Hydrological Modeling System (HEC-HMS) were used to attain the objective of this research. After the downscaling process and hydrologic simulation, a set of predicted data were produced, rainfall levels and water inflows in the watershed were generated for each RCP scenario. Results of each RCP scenario were compared to each other to analyze the differences in these what ifs scenarios. Future climate changes in Bauan, Batangas were projected under the RCP 2.6, 4.5, and 8.5 scenarios for a period of 20 years (2021 – 2041). The highest inflow data is 603.8 m3/s from the RCP 4.5 scenario while the highest average inflow was from RCP 8.5 with an inflow value of 541.848 m3/s. Meanwhile, the RCP 2.6 projected the lowest value of inflow and the lowest average among the three, with values of 359.9 m3/s and 406.505 m3/s.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124809921","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467467
R. Kamali-Sarvestani
This paper reports the fabrication of flexible logic gates using printed field effect transistors made by Graphene as semiconductor and honey as the gate material. PMOS transistors were made with Graphene and then analyzed to find the voltage characteristics and best operation mode. The PMOS transistors showed a good slew rate. Details of design and fabrication were studied and reported. The PMOS circuits included Inverters, AND logic, and OR logic. The logic gate performance was compatible to the circuit simulation observed by transistor models. These new logic gates have applications in biomedical interfacing and wearable electronics.
{"title":"Improving the Sustainability of Circuits by Using Honey Gate in Transistors for Printing Electronics","authors":"R. Kamali-Sarvestani","doi":"10.1109/SusTech51236.2021.9467467","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467467","url":null,"abstract":"This paper reports the fabrication of flexible logic gates using printed field effect transistors made by Graphene as semiconductor and honey as the gate material. PMOS transistors were made with Graphene and then analyzed to find the voltage characteristics and best operation mode. The PMOS transistors showed a good slew rate. Details of design and fabrication were studied and reported. The PMOS circuits included Inverters, AND logic, and OR logic. The logic gate performance was compatible to the circuit simulation observed by transistor models. These new logic gates have applications in biomedical interfacing and wearable electronics.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"8 353 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115760964","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467426
Sahar Hasan, E. Elwakil, Mohmed Hegab
In December 2019, the pandemic of COVID -19 has hit the world without warning by the unprecedented scale and intensity to be declared officially as a pandemic in March 2020. Consequently, it has forced the countries to follow immediate strategies to alleviate this crisis's impacts. The lockdown and social distance were the most applied precautionary procedures. This situation has devastating consequences for both economic and social life. The construction sector is affected by this temporary paralysis, especially the public-private partnerships (PPP) infrastructure projects with a long-term contract and different stakeholders. Some earlier researches have analyzed the consequences and suggested options to alleviate the negative impacts, but potential positive risks are still spotting. Therefore, there is a need to follow proactive behavior to maximize the potentiality of opportunities. This research is exploring the positive risks for PPP infrastructure projects during COVID 19. This objective has been attained by a literature survey for allocated risks for PPP projects, factors affecting successful PPP projects, and the current practices as a response strategy to COVID -19. The research findings will contribute to building a known base of resilience plans for pandemic through two scenarios of negative and positive impacts to support PPP projects with leading practices. The revealed opportunities have been revealed based on exploring the common concepts between four main areas: 1) Positive Impacts of COVID-19, 2) Principles of resilient infrastructure, 3) Critical success factors of PPP projects, and 4) Current practices to respond to COVID-19. It was found that besides the tremendous burden on project stakeholders, users, the private corporate sector, and the public sector for the short and long term, some opportunities could be attained for PPP infrastructure projects. These revealed opportunities have been summarized as follows: 1) The need for implementing the resilience strategy and long term thinking, 2) Available time for maintenance work and updating operating systems for completed projects, 3) Priority to support and invest in innovative smart infrastructure projects that adopt artificial intelligence and smart systems that reduce human resource interferences and control the social distance, and 4) exploring the need to simplify or remedy the procurement processes of PPP. The concluded opportunities will help investors and public partners react positively during the pandemic and reduce the negative impacts and maximize positive impacts. This attitude will help PPP projects to survive in order to complete successfully after the crisis and integrate resilience into infrastructure projects.
{"title":"Opportunities for Infrastructure PPP Projects in Time of COVID-19 - as a Resilience Strategy","authors":"Sahar Hasan, E. Elwakil, Mohmed Hegab","doi":"10.1109/SusTech51236.2021.9467426","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467426","url":null,"abstract":"In December 2019, the pandemic of COVID -19 has hit the world without warning by the unprecedented scale and intensity to be declared officially as a pandemic in March 2020. Consequently, it has forced the countries to follow immediate strategies to alleviate this crisis's impacts. The lockdown and social distance were the most applied precautionary procedures. This situation has devastating consequences for both economic and social life. The construction sector is affected by this temporary paralysis, especially the public-private partnerships (PPP) infrastructure projects with a long-term contract and different stakeholders. Some earlier researches have analyzed the consequences and suggested options to alleviate the negative impacts, but potential positive risks are still spotting. Therefore, there is a need to follow proactive behavior to maximize the potentiality of opportunities. This research is exploring the positive risks for PPP infrastructure projects during COVID 19. This objective has been attained by a literature survey for allocated risks for PPP projects, factors affecting successful PPP projects, and the current practices as a response strategy to COVID -19. The research findings will contribute to building a known base of resilience plans for pandemic through two scenarios of negative and positive impacts to support PPP projects with leading practices. The revealed opportunities have been revealed based on exploring the common concepts between four main areas: 1) Positive Impacts of COVID-19, 2) Principles of resilient infrastructure, 3) Critical success factors of PPP projects, and 4) Current practices to respond to COVID-19. It was found that besides the tremendous burden on project stakeholders, users, the private corporate sector, and the public sector for the short and long term, some opportunities could be attained for PPP infrastructure projects. These revealed opportunities have been summarized as follows: 1) The need for implementing the resilience strategy and long term thinking, 2) Available time for maintenance work and updating operating systems for completed projects, 3) Priority to support and invest in innovative smart infrastructure projects that adopt artificial intelligence and smart systems that reduce human resource interferences and control the social distance, and 4) exploring the need to simplify or remedy the procurement processes of PPP. The concluded opportunities will help investors and public partners react positively during the pandemic and reduce the negative impacts and maximize positive impacts. This attitude will help PPP projects to survive in order to complete successfully after the crisis and integrate resilience into infrastructure projects.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130614539","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467475
K. Sood, Rakeshkumar V. Mahto, H. Shah, A. Murrell
The use of micro-autonomous drones are increasingly used for commercial and defense related applications. Importantly they play a critical role in search and rescue operations during a natural or human-made calamity. However, to operate in such a volatile environment, the sensor’s quality, prolonged flight-time, and resilience to the harsh operation conditions are vital characteristics of a micro-autonomous drone. For satisfying these characteristics, an adaptable, resilient and efficient power source is required. Compared to a battery or fuel cell-based power source, the type III-V based photovoltaics (PV) have shown a higher power-to-weight ratio. However, in a fixed configuration PV based micro-autonomous drones’ performance deteriorates due to partial or complete shading conditions. Therefore, instead of fixed topology PV module, we have used a complementary metal oxide semiconductor (CMOS) embedded PV module as a power source for micro-autonomous drone. In this work, we use machine learning techniques to determine the number of shaded PV cells present in CMOS embedded PV panel. We apply several machine learning techniques to enhance the performance of reconfigurable PV based power supply operating under different partial shading conditions. We present a comparative analysis of SVM, Naive Baiyes, Random Forest, Voting Classifier and Decision Trees as the machine learning techniques, verify their accuracy and present the classification results. The outcome of this work will lead to further usage of machine learning techniques in power management of micro-autonomous drone.
{"title":"Power Management of Autonomous Drones using Machine Learning","authors":"K. Sood, Rakeshkumar V. Mahto, H. Shah, A. Murrell","doi":"10.1109/SusTech51236.2021.9467475","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467475","url":null,"abstract":"The use of micro-autonomous drones are increasingly used for commercial and defense related applications. Importantly they play a critical role in search and rescue operations during a natural or human-made calamity. However, to operate in such a volatile environment, the sensor’s quality, prolonged flight-time, and resilience to the harsh operation conditions are vital characteristics of a micro-autonomous drone. For satisfying these characteristics, an adaptable, resilient and efficient power source is required. Compared to a battery or fuel cell-based power source, the type III-V based photovoltaics (PV) have shown a higher power-to-weight ratio. However, in a fixed configuration PV based micro-autonomous drones’ performance deteriorates due to partial or complete shading conditions. Therefore, instead of fixed topology PV module, we have used a complementary metal oxide semiconductor (CMOS) embedded PV module as a power source for micro-autonomous drone. In this work, we use machine learning techniques to determine the number of shaded PV cells present in CMOS embedded PV panel. We apply several machine learning techniques to enhance the performance of reconfigurable PV based power supply operating under different partial shading conditions. We present a comparative analysis of SVM, Naive Baiyes, Random Forest, Voting Classifier and Decision Trees as the machine learning techniques, verify their accuracy and present the classification results. The outcome of this work will lead to further usage of machine learning techniques in power management of micro-autonomous drone.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122560866","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467413
Haoyu Niu, Tiebiao Zhao, Jiamin Wei, Dong Wang, Y. Chen
The accurate estimation and mapping of evapotranspiration (ET) are essential for crop water management. As one of the traditional ET estimation methods, crop coefficient (Kc) has been commonly used. Many studies indicated a linear regression relationship between the Kc curve and the vegetation index curve. The linear regression model is usually developed between the Kc and the normalized difference vegetation index (NDVI) derived from satellite imagery. The satellite images can provide temporally and spatially distributed measurements. However, multispectral satellite imagery’s spatial resolution is in the range of meters, which is often not enough for crops with clumped canopy structures, such as trees and vines. Little ET estimation has been studied based on the single-tree level. Thus, the purpose of this study was to develop a reliable tree-level ET estimation method using UAV high-resolution multispectral images. Compared with satellite imagery, the spatial resolution of UAV images can be as high as centimeter-level. A field study was conducted to investigate pomegranate trees at the USDA-ARS (US Department of Agriculture, Agricultural Research Service) San Joaquin Valley Agricultural Sciences Center in Parlier, California, USA. The NDVI map was derived from UAV imagery. The Kc values were calculated based on the actual ET from a weighing lysimeter and reference ET from the weather station. The authors then established a linear regression model between the NDVI and Kc to estimate the actual daily ET. Results showed that the linear regression model could estimate tree-level ET with an R2 and mean absolute error (MAE) of 0.9143 and 0.39 mm/day, respectively.
{"title":"Reliable Tree-level Evapotranspiration Estimation of Pomegranate Trees Using Lysimeter and UAV Multispectral Imagery","authors":"Haoyu Niu, Tiebiao Zhao, Jiamin Wei, Dong Wang, Y. Chen","doi":"10.1109/SusTech51236.2021.9467413","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467413","url":null,"abstract":"The accurate estimation and mapping of evapotranspiration (ET) are essential for crop water management. As one of the traditional ET estimation methods, crop coefficient (Kc) has been commonly used. Many studies indicated a linear regression relationship between the Kc curve and the vegetation index curve. The linear regression model is usually developed between the Kc and the normalized difference vegetation index (NDVI) derived from satellite imagery. The satellite images can provide temporally and spatially distributed measurements. However, multispectral satellite imagery’s spatial resolution is in the range of meters, which is often not enough for crops with clumped canopy structures, such as trees and vines. Little ET estimation has been studied based on the single-tree level. Thus, the purpose of this study was to develop a reliable tree-level ET estimation method using UAV high-resolution multispectral images. Compared with satellite imagery, the spatial resolution of UAV images can be as high as centimeter-level. A field study was conducted to investigate pomegranate trees at the USDA-ARS (US Department of Agriculture, Agricultural Research Service) San Joaquin Valley Agricultural Sciences Center in Parlier, California, USA. The NDVI map was derived from UAV imagery. The Kc values were calculated based on the actual ET from a weighing lysimeter and reference ET from the weather station. The authors then established a linear regression model between the NDVI and Kc to estimate the actual daily ET. Results showed that the linear regression model could estimate tree-level ET with an R2 and mean absolute error (MAE) of 0.9143 and 0.39 mm/day, respectively.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"508 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129030335","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 : 2021-04-22DOI: 10.1109/sustech51236.2021.9467460
M. Pouri
In recent years, there has been a rapid growth in the use of digital sharing platforms by individuals as well as companies in various sectors. These platforms - such as Uber, Airbnb, Couchsurfing, BlaBlaCar, and many others - are predominantly associated with the sharing economy phenomenon. Due to affordability, efficiency, convenience and accessibility of their services, sharing platforms have appeared to be an attractive way of accessing resources for consumers. From a sustainability perspective, it is however important to investigate how the growth of digitally enabled sharing can affect the prevailing consumption patterns as well as socio-economic structures. The present work aims to address the category of potential sustainability impacts of shared consumption and sharing practices on the environment and society that should be considered in designing digital sharing systems in order to see how they can promote or hinder sustainability.
{"title":"Implications for Designing Sustainable Digital Sharing Systems","authors":"M. Pouri","doi":"10.1109/sustech51236.2021.9467460","DOIUrl":"https://doi.org/10.1109/sustech51236.2021.9467460","url":null,"abstract":"In recent years, there has been a rapid growth in the use of digital sharing platforms by individuals as well as companies in various sectors. These platforms - such as Uber, Airbnb, Couchsurfing, BlaBlaCar, and many others - are predominantly associated with the sharing economy phenomenon. Due to affordability, efficiency, convenience and accessibility of their services, sharing platforms have appeared to be an attractive way of accessing resources for consumers. From a sustainability perspective, it is however important to investigate how the growth of digitally enabled sharing can affect the prevailing consumption patterns as well as socio-economic structures. The present work aims to address the category of potential sustainability impacts of shared consumption and sharing practices on the environment and society that should be considered in designing digital sharing systems in order to see how they can promote or hinder sustainability.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"1 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124334236","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 : 2021-04-22DOI: 10.1109/SusTech51236.2021.9467471
Maniell Workman, D. Z. Chen, S. Musa
Photovoltaic semiconductors are diodes which produce a current when exposed to light. The ideality factor is a parameter which tells how closely a semiconductor behaves to an ideal diode. In an ideal diode, the only mechanism for hole electron recombination is direct bimolecular recombination. Because there are multiple mechanisms of recombination, there are no real devices with a perfect ideality factor. The types of recombination occurring within a device can be inferred by its ideality factor. In this work, we examine the ideality factor of perovskite solar cells to identify possible recombination mechanisms in the device. Analyzing fabricated perovskite solar cells using their ideality factor can indicate which type of recombination is dominant in the device. The interaction between the perovskite crystal and transport layers is of high interest as differentials in energy band can hinder overall power conversion efficiency and act as a site for nonradiative recombination loss. We show that measuring the ideality factor of high performing cells and correlating the recombination mechanisms inferred can positively drive the electrochemistry of fabricating these devices. Thereby driving researchers to maximize or minimize types of recombination for optimization.
{"title":"Ideality Factor Based Computational Analysis of Perovskite Solar Cells","authors":"Maniell Workman, D. Z. Chen, S. Musa","doi":"10.1109/SusTech51236.2021.9467471","DOIUrl":"https://doi.org/10.1109/SusTech51236.2021.9467471","url":null,"abstract":"Photovoltaic semiconductors are diodes which produce a current when exposed to light. The ideality factor is a parameter which tells how closely a semiconductor behaves to an ideal diode. In an ideal diode, the only mechanism for hole electron recombination is direct bimolecular recombination. Because there are multiple mechanisms of recombination, there are no real devices with a perfect ideality factor. The types of recombination occurring within a device can be inferred by its ideality factor. In this work, we examine the ideality factor of perovskite solar cells to identify possible recombination mechanisms in the device. Analyzing fabricated perovskite solar cells using their ideality factor can indicate which type of recombination is dominant in the device. The interaction between the perovskite crystal and transport layers is of high interest as differentials in energy band can hinder overall power conversion efficiency and act as a site for nonradiative recombination loss. We show that measuring the ideality factor of high performing cells and correlating the recombination mechanisms inferred can positively drive the electrochemistry of fabricating these devices. Thereby driving researchers to maximize or minimize types of recombination for optimization.","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122826693","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：