This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of tho...This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of those strategies on the fabricated silicon force-balance MEMS accelerometer. The mathematical model presented is implemented in VHDL- AMS and SIMULINK TM,respectively. The simulation results from the two approaches are compared and show a slight difference. Using VHDL-AMS is flexible,reusable,and more accurate. But there is not a mature solver developed for the language and this approach takes more time, while the simulation model can be easily built and quickly evaluated using SIMULINK.展开更多
A tool was developed to assist the cooling systems designer in designing and installing the microsprinklers and fan cooling system. The tool was developed by integrating a mathematical model into an electronic spark m...A tool was developed to assist the cooling systems designer in designing and installing the microsprinklers and fan cooling system. The tool was developed by integrating a mathematical model into an electronic spark map in order to use the mathematical model practically. The mathematical model was developed using the designs, parameters, variables, and constant values of the microsprinklers and fans cooling system. Subsequently, an electronic spark map （decision tree） was developed, and then the mathematical model was integrated into the electronic spark map. Afterwards, C# （C Sharp） programming language was used to develop a computer system via the electronic spark map, and to make the user interface. The developed computer system assists the designer in making decisions to specify and to calculate the required discharge of cooling system pump, length and diameter of cooling system pipelines, number of cooling fans, and number of microsprinklers. Moreover, this tool calculates the capital investment and the fixed, variable, and total costs of the cooling system. However, the mathematical model of the spark map requires some input data such as： pressure and discharge of microsprinklers, and some other engineering parameters. Data of 4 cooling systems were used to carry out the model validation. The differences between actual and calculated values were determined, and the standard deviations were calculated. The coefficients of variation were between 2.25% and 4.13%.展开更多
文摘This paper presents two approaches for system-level simulation of force-balance accelerometers. The derivation of the system-level model is elaborated and simulation results are obtained from the implementation of those strategies on the fabricated silicon force-balance MEMS accelerometer. The mathematical model presented is implemented in VHDL- AMS and SIMULINK TM,respectively. The simulation results from the two approaches are compared and show a slight difference. Using VHDL-AMS is flexible,reusable,and more accurate. But there is not a mature solver developed for the language and this approach takes more time, while the simulation model can be easily built and quickly evaluated using SIMULINK.
文摘A tool was developed to assist the cooling systems designer in designing and installing the microsprinklers and fan cooling system. The tool was developed by integrating a mathematical model into an electronic spark map in order to use the mathematical model practically. The mathematical model was developed using the designs, parameters, variables, and constant values of the microsprinklers and fans cooling system. Subsequently, an electronic spark map （decision tree） was developed, and then the mathematical model was integrated into the electronic spark map. Afterwards, C# （C Sharp） programming language was used to develop a computer system via the electronic spark map, and to make the user interface. The developed computer system assists the designer in making decisions to specify and to calculate the required discharge of cooling system pump, length and diameter of cooling system pipelines, number of cooling fans, and number of microsprinklers. Moreover, this tool calculates the capital investment and the fixed, variable, and total costs of the cooling system. However, the mathematical model of the spark map requires some input data such as： pressure and discharge of microsprinklers, and some other engineering parameters. Data of 4 cooling systems were used to carry out the model validation. The differences between actual and calculated values were determined, and the standard deviations were calculated. The coefficients of variation were between 2.25% and 4.13%.
