Ting Fan Dai

Bio: Ting Fan Dai is an academic researcher. The author has contributed to research in topics: Jet (fluid) & Mechanics. The author has an hindex of 1, co-authored 1 publications receiving 248 citations.

3-D analytic signal in the interpretation of total magnetic field data at low magnetic latitudes

Abstract: The interpretation of magnetic field data at low magnetic latitudes is difficult because the vector nature of the magnetic field increases the complexity of anomalies from magnetic rocks. The most obvious approach to this problem is to reduce the data to the magnetic pole (RTP), where the presumably vertical magnetisation vector will simplify observed anomalies. However, RTP requires special treatment of north-south features in data observed in low magnetic latitudes due to high amplitude corrections of such features. Furthermore, RTP requires the assumption of induced magnetisation with the result that anomalies from remanently and anisotropically magnetised bodies can be severely disturbed. The amplitude of the 3-D analytic signal of the total magnetic field produces maxima over magnetic contacts regardless of the direction of magnetisation. The absence of magnetisation direction in the shape of analytic signal anomalies is a particularly attractive characteristic for the interpretation of magnetic field data near the magnetic equator. Although the amplitude of the analytic signal is dependent on magneti­sation strength and the direction of geological strike with respect to the magnetisation vector, this dependency is easier to deal with in the interpretation of analytic signal amplitude than in the original total field data or pole-reduced magnetic field. It is also straightforward to determine the depth to sources from the distance between inflection points of analytic signal anomalies.

Effect of Air Jet Vortex Generators on the Shock Wave Boundary Layer Interaction of Transonic Wing

Abstract: The interaction between shock waves and turbulent boundary layers (SBLI) is a common phenomenon in transonic and supersonic aircraft wings. In this study, we simulated the SBLI of a classical NACA0012 wing at an angle of attack (AOA) of 1.4° and Mach number (Ma) of 0.78 using the open-source software OpenFOAM. Our results show that an air-jet vortex generator can effectively reduce the length of the separation zone and improve the lift coefficient of the airfoil. The vortex structure generated by the jet vortex generator significantly reduces the separation caused by SBLI. We conducted simulations with jet angles of 30°, 45°, and 60° and found that the larger the jet angle, the stronger the vortex and the greater the improvement in the lift coefficient. When the jet angle was 60°, the vortex structure generated by the jet vortex generator transformed the normal shock wave into a λ shock wave, resulting in a maximum increase in the lift coefficient of 2.35%. The simulations focused on exploring the effect of the jet angle and determined that that optimal jet parameters that effectively reduce SBLI damage and improve the lift coefficient of the airfoil.

Artificial Neural Networks for Mineral-Potential Mapping: A Case Study from Aravalli Province, Western India

Abstract: This paper describes a GIS-based application of a radial basis functional link net (RBFLN) to map the potential of SEDEX-type base metal deposits in a study area in the Aravalli metallogenic province (western India). Available public domain geodata of the study area were processed to generate evidential maps, which subsequently were encoded and combined to derive a set of input feature vectors. A subset of feature vectors with known targets (i.e., either known mineralized or known barren locations) was extracted and divided into (a) a training data set and (b) a validation data set. A series of RBFLNs were trained to determine the network architecture and estimate parameters that mapped the maximum number of validation vectors correctly to their respective targets. The trained RBFLN that gave the best performance for the validation data set was used for processing all feature vectors. The output for each feature vector is a predictive value between 1 and 0, indicating the extent to which a feature vector belongs to either the mineralized or the barren class. These values were mapped to generate a predictive classification map, which was reclassified into a favorability map showing zones with high, moderate and low favorability for SEDEX-type base metal deposits in the study area. The method demarcates successfully high favorability zones, which occupy 6% of the study area and contain 94% of the known base metal deposits.

A combined analytic signal and Euler method (AN-EUL) for automatic interpretation of magnetic data

Abstract: We present a new automatic method of interpretation of magnetic data, called AN-EUL (pronounced “an oil”). The derivation is based on a combination of the analytic signal and the Euler deconvolution methods. With AN-EUL, both the location and the approximate geometry of a magnetic source can be deduced. The method is tested using theoretical simulations with different magnetic models placed at different depths with respect to the observation height. In all cases, the method estimated the locations and the approximate geometries of the sources. The method is tested further using ground magnetic data acquired above a shallow geological dike whose source parameters are known from drill logs, and also from airborne magnetic data measured over a known ferrometallic object. In both these cases, the method correctly estimated the locations and the nature of these sources.

Geophysics for the Mineral Exploration Geoscientist

Abstract: Providing a balance between principles and practice, this state-of-the-art overview of geophysical methods takes readers from the basic physical phenomena, through the acquisition and processing of data, to the creation of geological models of the subsurface and data interpretation to find hidden mineral deposits. Detailed descriptions of all the commonly used geophysical methods are given, including gravity, magnetic, radiometric, electrical, electromagnetic and seismic methods. Each technique is described in a consistent way and without complex mathematics. Emphasising extraction of maximum geological information from geophysical data, the book also explains petrophysics, data modelling and common interpretation pitfalls. Packed with full-colour figures, also available online, the text is supported by selected examples from around the world, including all the major deposit types. Designed for advanced undergraduate and graduate courses in minerals geoscience, this is also a valuable reference for professionals in the mining industry wishing to make greater use of geophysical methods. In 2015, Dentith and Mudge won the ASEG Lindsay Ingall Memorial Award for their combined effort in promoting geophysics to the wider community with the publication of this title.

Understanding 3D analytic signal amplitude

Abstract: The concept of the analytic signal goes back at least to Ville (1948). The analytic signal a ( x ) of function f ( x ) is a complex quantity defined as where H [ f ( x ) ] represents the Hilbert transform of f ( x ) . Nabighian (1972, 1974) applies the analytic signal concept to potential-field data in two dimensions. For a potential field ϕ ( x ) measured along the x -axis at a constant observation height z and generated by a 2D source aligned parallel to the y -axis, the horizontal derivative ϕ x and the vertical derivative ϕ z are a Hilbert transform pair.

iSPITM— the improved source parameter imaging method

Abstract: Interpretation of an anomalous magnetic response involves determining the parameters that characterize the source of the anomaly. The depth to the top of the structure is a parameter that is commonly sought, and the Source Parameter ImagingTM (SPITM) method is one way of determining this depth estimate. One advantage of the SPI method is that the depths can be displayed on an image. Typically there can be one image for an assumed contact (fault) model and another image for an assumed dipping thin sheet (dike) model. The depth estimate obtained will depend on the model assumed. An improvement to the source parameter imaging method extends the method to horizontal cylinders and at the same time allows the most appropriate model to be determined automatically. This model can be displayed on an image and the correct depth estimate for each anomaly can also be determined. The depth estimates can therefore be summarized on one map independent of an assumed model. The images generated from synthetic and field data show that the improved SPI method makes the task of interpreting magnetic data significantly easier.