Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting deci...Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.展开更多
In the framework of the spectral element method, a comparison is carried out on turbulent first-and second-order statistics generated by large eddy simulation (LES), under-resolved (UDNS) and fully resolved direct num...In the framework of the spectral element method, a comparison is carried out on turbulent first-and second-order statistics generated by large eddy simulation (LES), under-resolved (UDNS) and fully resolved direct numerical simulation (DNS). The LES is based on classical models like the dynamic Smagorinsky approach or the approximate deconvolution method. Two test problems are solved: the lid-driven cubical cavity and the differentially heated cavity. With the DNS data as benchmark solutions, it is shown that the numerical results produced by the UDNS calculation are of the same accuracy, even in some cases of better quality, as the LES computations. The conclusion advocates the use of UDNS and calls for improvement of the available algorithms.展开更多
The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision ...The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision positioning recognition method.Many researchers have done a lot of work in these two aspects,and a variety of end-effector structures and advanced position recognition methods are constantly appearing in people’s view.The working principle,structural characteristics,advantages and disadvantages of each end-effector are summarized to help us design better fruit and vegetable picking robot.The authors start from the rigid fruit and vegetable picking robot grasping methods,separation methods,and position recognition methods,firstly introduce three different grasping methods and the characteristics of the two separation methods,then introduce the under-driven picking robot developed on the basis of the traditional rigid picking robot,then explain the single special,multi-feature,and deep learning location position recognition methods currently used,and finally make a summary and outlook on the rigid fruit and vegetable picking robot from the structural development and position recognition methods.展开更多
文摘Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.
文摘In the framework of the spectral element method, a comparison is carried out on turbulent first-and second-order statistics generated by large eddy simulation (LES), under-resolved (UDNS) and fully resolved direct numerical simulation (DNS). The LES is based on classical models like the dynamic Smagorinsky approach or the approximate deconvolution method. Two test problems are solved: the lid-driven cubical cavity and the differentially heated cavity. With the DNS data as benchmark solutions, it is shown that the numerical results produced by the UDNS calculation are of the same accuracy, even in some cases of better quality, as the LES computations. The conclusion advocates the use of UDNS and calls for improvement of the available algorithms.
基金supported by the National Natural Science Foundation of China(Grant No.51775002)the 14th Five-Year Plan of Beijing Education Science(Grant No.CDDB21173).
文摘The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision positioning recognition method.Many researchers have done a lot of work in these two aspects,and a variety of end-effector structures and advanced position recognition methods are constantly appearing in people’s view.The working principle,structural characteristics,advantages and disadvantages of each end-effector are summarized to help us design better fruit and vegetable picking robot.The authors start from the rigid fruit and vegetable picking robot grasping methods,separation methods,and position recognition methods,firstly introduce three different grasping methods and the characteristics of the two separation methods,then introduce the under-driven picking robot developed on the basis of the traditional rigid picking robot,then explain the single special,multi-feature,and deep learning location position recognition methods currently used,and finally make a summary and outlook on the rigid fruit and vegetable picking robot from the structural development and position recognition methods.
