| 1 | Data-Driven Prediction of Mechanical Properties in Support of Rapid Certification of Additively Manufactured Alloys显示文摘Predicting the mechanical properties of additively manufactured parts is often a tedious process,requiring the integration of multiple stand-alone and expensive simulations.Furthermore,as properties are highly location-dependent due to repeated heating and cooling cycles,the properties prediction models must be run for multiple locations before the part-level performance can be analyzed for certification,compounding the computational expense.This work has proposed a rapid prediction framework that replaces the physics-based mechanistic models with Gaussian process metamodels,a type of machine learning model for statistical inference with limited data.The metamodels can predict the varying properties within an entire part in a fraction of the time while providing uncertainty quantification.The framework was demonstrated with the prediction of the tensile yield strength of Ferrium?PH48S maraging stainless steel fabricated by additive manufacturing.Impressive agreement was found between the metamodels and the mechanistic models,and the computation was dramatically decreased from hours of physics-based simulations to less than a second with metamodels.This method can be extended to predict various materials properties in different alloy systems whose processstructure-property-performance interrelationships are linked by mechanistic models.It is powerful for rapidly identifying the spatial properties of a part with compositional and processing parameter variations,and can support part certification by providing a fast interface between materials models and part-level thermal and performance simulations. | Fuyao Yan Yu-Chin Chan Abhinav Saboo Jiten Shah Gregory BOlson Wei Chen | 2018 | Computer Modeling in Engineering & Sciences2018，，12： | 1 |
| 2 | Intelligent fish tank based on WiFi module显示文摘In the paper,the intelligent fish tank using STC89C52 as the control core embedded HC-SR04 ultrasonic distance measurement module and DS18B20 temperature sensor is introduced.This system can be used to remotely control and collect the data of the temperature and the level of water in the fish tank through WiFi module (ESP8266-01).When the water level is less than the default value,the system will be adjusted by adding water into the tank.At the same time,people could also get the data and control the tank whenever they want.The micro-controller is connected to the Internet through the WiFi module.With the help of MicroPython firmware,python programs are compiled within this WiFi module in order to connect to the WiFi at home,providing data transfer function.Android smart phones could connect to this system through WiFi and send commands.In this way,the fish tank could be controlled remotely to ensure the stability of the water temperature and level in the tank. | Feng Yan Fuyao Wang | 2018 | Journal of Autonomous Intelligence2018，1，1： | 0 |
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