During different growth periods,canopy size and density in orchards are variable,which need application conditions(flow rate and air flow)to be adjusted to match the canopy’s characteristics.In order to improve orcha...During different growth periods,canopy size and density in orchards are variable,which need application conditions(flow rate and air flow)to be adjusted to match the canopy’s characteristics.In order to improve orchard sprayer’s automatic operating performance,an automatic variable-rate orchard sprayer(VARS)fixed with 40 electromagnetic valves and 8 brushless fans was developed based on the canopy’s spatial dimensions.Each solenoid valve and brushless motor can be individually adjusted in real-time through pulse width modulation(PWM)signals emitted by a control system to adjust each nozzle’s spout and fan rotation speed.A high-precision laser scanning sensor(light detecting and ranging,LIDAR)was adopted as the detector to measure the canopy volume using the variable rate algorithm principle.Field experiments were conducted in an apple orchard,and conventional air blast sprayer(CABS)and directed air-jet sprayer(DAJS)were tested as a comparison.Results showed that on average,46%less spraying solution was applied compared to conventional applications,while penetration rate was similar to DAJS.Normalized deposition in the canopy with variable application was higher than that of conventional applications,indicating that electronic sprayers are more efficient than conventional sprayers.It was also observed that VARS could significantly reduce off-target loss.The field experiment showed that the newly developed variable-rate sprayer can greatly reduce pesticide use and protect the environment for the orchard fruit production,and also provide a reference for design and performance optimization for plant protection machinery.展开更多
An automated method to optimize the definition of the progress variables in the flamelet-based dimension reduction is proposed. The performance of these optimized progress variables in coupling the flamelets and flow ...An automated method to optimize the definition of the progress variables in the flamelet-based dimension reduction is proposed. The performance of these optimized progress variables in coupling the flamelets and flow solver is presented. In the proposed method, the progress variables are defined according to the first two principal components （PCs） from the principal component analysis （PCA） or kernel-density-weighted PCA （KEDPCA） of a set of flamelets. These flamelets can then be mapped to these new progress variables instead of the mixture fraction/conventional progress variables. Thus, a new chemistry look-up table is constructed. A priori validation of these optimized progress variables and the new chemistry table is implemented in a CH4/N2/air lift-off flame. The reconstruction of the lift-off flame shows that the optimized progress variables perform better than the conventional ones, especially in the high temperature area. The coefficient determinations （R2 statistics） show that the KEDPCA performs slightly better than the PCA except for some minor species. The main advantage of the KEDPCA is that it is less sensitive to the database. Meanwhile, the criteria for the optimization are proposed and discussed. The constraint that the progress variables should monotonically evolve from fresh gas to burnt gas is analyzed in detail.展开更多
Building processing,structure,and property(PSP)relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science.Recent techn...Building processing,structure,and property(PSP)relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science.Recent technological advancements in data acquisition and storage,microstructure characterization and reconstruction(MCR),machine learning(ML),materials modeling and simulation,data processing,manufacturing,and experimentation have significantly advanced researchers’abilities in building PSP relations and inverse material design.In this article,we examine these advancements from the perspective of design research.In particular,we introduce a data-centric approach whose fundamental aspects fall into three categories:design representation,design evaluation,and design synthesis.Developments in each of these aspects are guided by and benefit from domain knowledge.Hence,for each aspect,we present a wide range of computational methods whose integration realizes data-centric materials discovery and design.展开更多
基金The authors acknowledge that this work was financially supported by Special Fund for Agro-scientific Research in Public Interest(No.201503130)Beijing Science and technology plan projects(No.D171100002317003)National Natural Science Foundation of China(31470099).
文摘During different growth periods,canopy size and density in orchards are variable,which need application conditions(flow rate and air flow)to be adjusted to match the canopy’s characteristics.In order to improve orchard sprayer’s automatic operating performance,an automatic variable-rate orchard sprayer(VARS)fixed with 40 electromagnetic valves and 8 brushless fans was developed based on the canopy’s spatial dimensions.Each solenoid valve and brushless motor can be individually adjusted in real-time through pulse width modulation(PWM)signals emitted by a control system to adjust each nozzle’s spout and fan rotation speed.A high-precision laser scanning sensor(light detecting and ranging,LIDAR)was adopted as the detector to measure the canopy volume using the variable rate algorithm principle.Field experiments were conducted in an apple orchard,and conventional air blast sprayer(CABS)and directed air-jet sprayer(DAJS)were tested as a comparison.Results showed that on average,46%less spraying solution was applied compared to conventional applications,while penetration rate was similar to DAJS.Normalized deposition in the canopy with variable application was higher than that of conventional applications,indicating that electronic sprayers are more efficient than conventional sprayers.It was also observed that VARS could significantly reduce off-target loss.The field experiment showed that the newly developed variable-rate sprayer can greatly reduce pesticide use and protect the environment for the orchard fruit production,and also provide a reference for design and performance optimization for plant protection machinery.
基金Project supported by the National Natural Science Foundation of China(Nos.50936005,51576182,and 11172296)
文摘An automated method to optimize the definition of the progress variables in the flamelet-based dimension reduction is proposed. The performance of these optimized progress variables in coupling the flamelets and flow solver is presented. In the proposed method, the progress variables are defined according to the first two principal components （PCs） from the principal component analysis （PCA） or kernel-density-weighted PCA （KEDPCA） of a set of flamelets. These flamelets can then be mapped to these new progress variables instead of the mixture fraction/conventional progress variables. Thus, a new chemistry look-up table is constructed. A priori validation of these optimized progress variables and the new chemistry table is implemented in a CH4/N2/air lift-off flame. The reconstruction of the lift-off flame shows that the optimized progress variables perform better than the conventional ones, especially in the high temperature area. The coefficient determinations （R2 statistics） show that the KEDPCA performs slightly better than the PCA except for some minor species. The main advantage of the KEDPCA is that it is less sensitive to the database. Meanwhile, the criteria for the optimization are proposed and discussed. The constraint that the progress variables should monotonically evolve from fresh gas to burnt gas is analyzed in detail.
基金support from the National Science Foundation(NSF)Cyberinfrastructure for Sustained Scientific Innovation program(OAC-1835782)the NSF Designing Materials to Revolutionize and Engineer Our Future program(CMMI-1729743)+1 种基金Center for Hierarchical Materials Design(NIST 70NANB19H005)at Northwestern Universitythe Advanced Research Projects Agency-Energy(APAR-E,DE-AR0001209)。
文摘Building processing,structure,and property(PSP)relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science.Recent technological advancements in data acquisition and storage,microstructure characterization and reconstruction(MCR),machine learning(ML),materials modeling and simulation,data processing,manufacturing,and experimentation have significantly advanced researchers’abilities in building PSP relations and inverse material design.In this article,we examine these advancements from the perspective of design research.In particular,we introduce a data-centric approach whose fundamental aspects fall into three categories:design representation,design evaluation,and design synthesis.Developments in each of these aspects are guided by and benefit from domain knowledge.Hence,for each aspect,we present a wide range of computational methods whose integration realizes data-centric materials discovery and design.
