Local singularity and S–A methods for analyzing ore-producing anomalies in the Jianbiannongchang area of Heilongjiang,China

The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and diverse geological background for mineralization.In this study,isometric logarithmic ratio(ILR)transformations of Au,Cu,Pb,Zn,and Sb contents were performed in the1:50,000 soil geochemical data of the Jianbiannongchang area.Robust principal component analysis(RPCA)was conducted based on ILR transformation.The local singularity and spectrum-area(S-A)methods were used to extract information on mineralogic anomalies.The results showed that:(1)the transformed data eliminated the influence of the original data closure effect,and the PC1and PC2 information obtained by applying RPCA reflected ore-producing element anomalies dominated by Au and Cu.(2)The local singularity method can enhance the information of the local strong and weak slow anomalies.After performing local singularity analysis on PC1 and PC2,the obtained local anomalies reflected the local singularity spatial anomaly patterns related to Cu and Au mineralization in this area,which is an effective method for trapping ore-producing anomalies.(3)Furthermore,the composite anomaly decomposition of PC1 and PC2 was performed using the S-A method,and the screened anomalous and background fields reflect the ore-producing anomalies related to Cu and Au mineralization.This information is in agreement with known Cu and Au mineralization.(4)The geochemical anomalies with mineralization potential were obtained outside the known mineralization sites by integrating the information of oreproducing anomalies extracted by the local singularity and S-A methods,providing the theoretical basis and exploration direction for future exploration in the study area.

A novel hybrid method for aerodynamic noise prediction of high-lift devices

Aerodynamic noise of High-Lift Devices(HLDs)is one of the main sources of airframe noise,and has immediate impacts on the airworthiness certification,environmental protection and security of commercial aircraft.In this study,a novel hybrid method is proposed for the aerodynamic noise prediction of HLD.A negative Spalart-Allmaras(S-A)turbulence model based Improved Delayed Detached Eddy Simulation(IDDES)method coupling with AFT-2017b transition model is developed,in order to elaborately simulate the complex flow field around the HLD and thus obtain the information of acoustic sources.A Farassat-Kirchhoff hybrid method is developed to filter the spurious noise sources caused by the vortex motions in solving the Ffowcs Williams-Hawkings(FW-H)equation with permeable integral surfaces,and accurately predict the far-field noise radiation of the HLD.The results of the 30P30N HLD indicate that,the computational Sound Pressure Levels(SPLs)obtained by the Farassat-Kirchhoff hybrid method conform well with the experimental ones in the spectrum for the given observation point,and are more accurate than those obtained by the Farassat 1A method.Based on the hybrid method,the acoustic directivity of the HLD of a commercial aircraft is obtained,and the variation of the SPLs in the spectrum with the deflection angle of the slat is analyzed.