A grid mapping algorithm for modeling with geometric transforms

Barnett, Ryan M.; Murphy, Mark; Deutsch, Clayton V.

doi:10.1016/j.cageo.2019.01.017

Cited by 2 publications

(3 citation statements)

References 4 publications

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“…Isometric mapping algorithm is improved based on the multidimensional scaling algorithm. It adopts geodesic distance between nodes instead of Euclidean distance and realizes a nonlinear dimensionality reduction method through double centroid transformation [14]. In the high-dimensional space, suppose X � X 1 , .…”

Section: Multidimensional Scalingmentioning

confidence: 99%

Design of Remote Real-Time Positioning Method for Long-Distance Running under Wireless Network Technology

Xia

2021

Security and Communication Networks

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Aiming at the problems of low precision, long time, and poor effect of current remote real-time motion location methods, a long-distance real-time motion location method based on wireless network technology was proposed. Through the analysis of wireless network technology, the basic structure and positioning technology of wireless sensor networks are studied. In addition, this paper adopts the core matrix Isomap node location algorithm based on partial least squares (PLS). The distance of geodesic between long-distance running nodes is used to characterize the dissimilarity between nodes, and the sample contribution rate of the partial least squares method is used to find and eliminate the phenomenon of short circuits in long-distance running fields. High-dimensional feature interval is mapped by centroid transformation and kernel transformation. The experimental results show that the method can improve the positioning accuracy and shorten the positioning time effectively.

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Section: Multidimensional Scalingmentioning

confidence: 99%

Design of Remote Real-Time Positioning Method for Long-Distance Running under Wireless Network Technology

Xia

2021

Security and Communication Networks

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“…Then, the temperature and node deformations were solved by the thermo-elastic coupling method. The results at each time were inputted into the slave model (i.e., micro TBC) by the volume element intersection mapping algorithm [24]. The master-slave model was based on two assumptions: (a) The TGO hardly affects the temperature field in the TBC, and (b) the grid node deformation mainly depends on the temperature field at the macro scale [25].…”

Section: Slave Modelmentioning

confidence: 99%

“…To transfer the boundary displacement and body temperature data from the master model (i.e., source) to the slave model (i.e., target), we reasonably adopted the volume element intersection mapping algorithm [24]. The first step in the process of the volume element intersection mapping algorithm is to divide the mapping source mesh into an imaginary structured grid, with each grid section called a "bucket."…”

Section: Matching Of Master Model and Slave Modelmentioning

confidence: 99%

Thermal Fatigue Life Prediction of Thermal Barrier Coat on Nozzle Guide Vane via Master–Slave Model

Guan

Fei

et al. 2019

Applied Sciences

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The aim of this paper was to develop a master-slave model with fluid-thermo-structure (FTS) interaction for the thermal fatigue life prediction of a thermal barrier coat (TBC) in a nozzle guide vane (NGV). The master-slave model integrates the phenomenological life model, multilinear kinematic hardening model, fully coupling thermal-elastic element model, and volume element intersection mapping algorithm to improve the prediction precision and efficiency of thermal fatigue life. The simulation results based on the developed model were validated by temperature-sensitive paint (TSP) technology. It was demonstrated that the predicted temperature well catered for the TSP tests with a maximum error of less than 6%, and the maximum thermal life of TBC was 1558 cycles around the trailing edge, which is consistent with the spallation life cycle of the ceramic top coat at 1323 K. With the increase of pre-oxidation time, the life of TBC declined from 1892 cycles to 895 cycles for the leading edge, and 1558 cycles to 536 cycles for the trailing edge. The predicted life of the key points at the leading edge was longer by 17.7-40.1% than the trailing edge. The developed master-slave model was validated to be feasible and accurate in the thermal fatigue life prediction of TBC on NGV. The efforts of this study provide a framework for the thermal fatigue life prediction of NGV with TBC.Appl. Sci. 2019, 9, 4357 2 of 21 substrate: carrying mechanical loads. Through the oxidation of high-temperature gas, the aluminum in the BC is oxidized to produce an alumina layer (also called the TGO). With the increase in the TGO thickness, the material properties between the TC and BC are destroyed. The mixed layer TC/TGO is liable to crack and peel off under the combined effect of thermal stress and deformation in different layers, which eventually leads to the failure of the NGV [6]. Therefore, it is of some urgency to study the mechanical properties of a mixed layer TC/TGO with regard to a thermal shock environment. Robert [7] presented a Thermo-Calc/Dictra-based approach for the life prediction of isothermally oxidized atmospheric plasma sprayed TBCs. The beta-phase depletion of the coating was predicted and compared to the life prediction criteria based on the TGO thickness and aluminum content in the coating. Based on the BC test results, the life of the TBC was predicted by Song [8], according to degradation and thermal fatigue. Many experiments indicated that the failure of the TBC systems under thermomechanical loading was complicated due to the influences of many factors such as thermal mismatch, oxidation, interface roughness, creep, sintering, and so forth [9][10][11].

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A grid mapping algorithm for modeling with geometric transforms

Cited by 2 publications

References 4 publications

Design of Remote Real-Time Positioning Method for Long-Distance Running under Wireless Network Technology

Design of Remote Real-Time Positioning Method for Long-Distance Running under Wireless Network Technology

Thermal Fatigue Life Prediction of Thermal Barrier Coat on Nozzle Guide Vane via Master–Slave Model

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