As Internet becomes largely used in the AEC (architecture, engineering andconstruction) industry, the main focus is in the area of information and project management. In thedynamic engineering consulting, less has bee...As Internet becomes largely used in the AEC (architecture, engineering andconstruction) industry, the main focus is in the area of information and project management. In thedynamic engineering consulting, less has been done so far. This research tries to find thepossibility and potential of the Internet application in design and consulting for the AEC industryby proposing a working model in specific area, steel construction. Several issues have beendiscussed: defining and formatting the typical procedure and character of the steel constructionconsulting, behavior approach based on activities among partners, and the model organization.展开更多
Among various types of behaviors,locomotion is the foundation for exploration,navigation,foraging,and approaching.Proper locomotion enables animals to move from one place to another via a sequence of actions and is es...Among various types of behaviors,locomotion is the foundation for exploration,navigation,foraging,and approaching.Proper locomotion enables animals to move from one place to another via a sequence of actions and is essential for their survival.展开更多
The energy industry,now in an era of digitization driven by computational design,is gradually moving towards automating the entire process from computational prediction to device assembly,aiming to minimize the relian...The energy industry,now in an era of digitization driven by computational design,is gradually moving towards automating the entire process from computational prediction to device assembly,aiming to minimize the reliance on time-consuming,manual trial-and-error validation.In this study,guided by computational density functional theory(DFT)predictions,a humanoid robotic arm,based on artificial intelligence(AI),was creatively utilized to assemble clean energy devices,solid oxide fuel cells(SOFCs).The material La_(0.35)Bi_(0.15)Sr_(0.5)FeO_(3-δ)(LBSF)was DFT-predicted to have high oxygen reduction reactions(ORRs)ability,suitable for the cathode in SOFCs compared to the conventional La_(0.5)Sr_(0.5)FeO_(3-δ)(LSF).The material was made into ink then passed to the assembly platform with AI-driven robotics.AI-driven robotics was employed with an imitation learning method to effectively learn skills directly from human demonstrations,thereby alleviating researchers from labor-intensive tasks.We demonstrate our approach for autonomous SOFCs fabrication.For easy platform usage in the future,Large Language Models(LLMs)were incorporated to understand human commands.Visual information was captured by an RGBD camera to identify and locate the cathode painting spot.An imitation learning framework was then applied to learn the painting path from human operations and can be generalized to different conditions.The auto-fabricated single cells with the DFT-predicted LBSF cathode were tested and achieved a power density of 966mW∕cm^(2)at 700℃,more than double the performance of LSF.By integrating computational design with an AI-driven assembly platform,this study marks an initial step towards an AI-driven material lab,exponentially accelerating material design in the near future.The platform can also help disabled researchers achieve their ideas through the behavior cloning approach.展开更多
文摘As Internet becomes largely used in the AEC (architecture, engineering andconstruction) industry, the main focus is in the area of information and project management. In thedynamic engineering consulting, less has been done so far. This research tries to find thepossibility and potential of the Internet application in design and consulting for the AEC industryby proposing a working model in specific area, steel construction. Several issues have beendiscussed: defining and formatting the typical procedure and character of the steel constructionconsulting, behavior approach based on activities among partners, and the model organization.
文摘Among various types of behaviors,locomotion is the foundation for exploration,navigation,foraging,and approaching.Proper locomotion enables animals to move from one place to another via a sequence of actions and is essential for their survival.
文摘The energy industry,now in an era of digitization driven by computational design,is gradually moving towards automating the entire process from computational prediction to device assembly,aiming to minimize the reliance on time-consuming,manual trial-and-error validation.In this study,guided by computational density functional theory(DFT)predictions,a humanoid robotic arm,based on artificial intelligence(AI),was creatively utilized to assemble clean energy devices,solid oxide fuel cells(SOFCs).The material La_(0.35)Bi_(0.15)Sr_(0.5)FeO_(3-δ)(LBSF)was DFT-predicted to have high oxygen reduction reactions(ORRs)ability,suitable for the cathode in SOFCs compared to the conventional La_(0.5)Sr_(0.5)FeO_(3-δ)(LSF).The material was made into ink then passed to the assembly platform with AI-driven robotics.AI-driven robotics was employed with an imitation learning method to effectively learn skills directly from human demonstrations,thereby alleviating researchers from labor-intensive tasks.We demonstrate our approach for autonomous SOFCs fabrication.For easy platform usage in the future,Large Language Models(LLMs)were incorporated to understand human commands.Visual information was captured by an RGBD camera to identify and locate the cathode painting spot.An imitation learning framework was then applied to learn the painting path from human operations and can be generalized to different conditions.The auto-fabricated single cells with the DFT-predicted LBSF cathode were tested and achieved a power density of 966mW∕cm^(2)at 700℃,more than double the performance of LSF.By integrating computational design with an AI-driven assembly platform,this study marks an initial step towards an AI-driven material lab,exponentially accelerating material design in the near future.The platform can also help disabled researchers achieve their ideas through the behavior cloning approach.
