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Accurate component maps are crucial for gas turbine performance simulation. However, generating component maps is challenging due to limited data availability and individual characteristic differences between gas turbines. Thus, a component characteristic adaptation method is proposed here. Initially, the original component analytical formulas (OCAF) are enhanced, and the analytical normalized characteristic parameters (ANCPs) are calculated. Subsequently, the real normalized characteristic parameters (RNCPs) are calculated reversely based on field-measured data. Next, the tuning factors are optimized to obtain optimal improved component analytical formulas (ICAF). Finally, the effectiveness of the proposed method is validated using LM2500+ gas turbine field data and compared with two previous adaptive methods. The results reveal that the proposed method offers high tunability and computational efficiency during the adaptation process, significantly improving the accuracy of the gas turbine performance simulation model. This study paves the way for more reliable gas turbine performance simulations and enhanced fault diagnosis in the field. [ABSTRACT FROM AUTHOR]

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Unmanned aerial vehicle (UAV) and structure from motion (SfM) photogrammetry techniques are widely used for field-based, high-throughput plant phenotyping nowadays, but some of the intermediate processes throughout the workflow remain manual. For example, geographic information system (GIS) software is used to manually assess the 2D/3D field reconstruction quality and cropping region of interests (ROIs) from the whole field. In addition, extracting phenotypic traits from raw UAV images is more competitive than directly from the digital orthomosaic (DOM). Currently, no easy-to-use tools are available to implement previous tasks for commonly used commercial SfM software, such as Pix4D and Agisoft Metashape. Hence, an open source software package called easy intermediate data processor (EasyIDP; MIT license) was developed to decrease the workload in intermediate data processing mentioned above. The functions of the proposed package include (1) an ROI cropping module, assisting in reconstruction quality assessment and cropping ROIs from the whole field, and (2) an ROI reversing module, projecting ROIs to relative raw images. The result showed that both cropping and reversing modules work as expected. Moreover, the effects of ROI height selection and reversed ROI position on raw images to reverse calculation were discussed. This tool shows great potential for decreasing workload in data annotation for machine learning applications.

• Full model of the evaluation method of gear profile deviations considering installation errors. • Results showed that the method could significantly decrease influence of installation errors. • The application range of EMI-Profile method was simulated. Gear elemental deviations, such as profile deviations, are important items for gear accuracy evaluation and generally measured on a Gear Measurement Center or Coordinate Measuring Machine. There are installation errors when the gear installed on the shaft positioned in the center before measurement. Therefore, the evaluation method of gear profile deviations considering installation errors was introduced to measure gear profile deviations without the precise adjustment of installation errors in the study. In this method, installation errors were described as the installation eccentricity error and the installation wobbling error. Then, the installation error model, the coordinate transformation model and the tooth profile deviation evaluation method were established. The gear base circle center was calculated with the tooth profile measurement points. Then, the tooth profile measurement points under the machine coordinate system were transformed into the coordinates in the work-piece coordinate system. After that, the profile deviations were evaluated according to ISO 1328-1:2013. The measurement experiments were carried out on a gear measurement center under different installation errors. The application scope of the method was discussed by simulation. The range of the total profile deviation obtained with this method was 0.51 μm under four groups of the installation conditions, whereas the value obtained with GMC was 3.17 μm. Experimental results showed that this method could significantly decrease the influence of installation errors for measuring gear profile deviations under the rough positioning conditions of product gears. [ABSTRACT FROM AUTHOR]

The research on the influence that groundwater exerts on borehole ground heat exchanger has been made progress. However, the investigation on how to obtain the groundwater velocity is a little. According to the line heat source model with groundwater flow, a new methodology is explored to obtain the value and direction of groundwater velocity while it flows through borehole. Some points are distributed around borehole and they have the same distance to the center line of borehole, and the temperature responses of these points are significant parameters which lay firm foundation for reverse-reasoning. The reverse-reasoning calculation can be conducted by establishing objective function. The comparisons of temperature responses between theoretical results and the simulative recorded data are made. The impact degree of groundwater flow can be displayed and then the velocity is estimated. Differences among points' temperature responses are made full use of to respectively indicate the direction and value ranges of velocity. The relativity between the points' location and the velocity intensity is investigated and then some cases are chosen as the trials to verify the rationality of reverse calculation method. To a large extent, the research work of this paper provides theoretical guidance or computing mode for getting velocity of groundwater. The methodology can be employed for obtaining the velocity in actual engineering projects or other cases. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) and structure from motion (SfM) photogrammetry techniques are widely used for field-based, high-throughput plant phenotyping nowadays, but some of the intermediate processes throughout the workflow remain manual. For example, geographic information system (GIS) software is used to manually assess the 2D/3D field reconstruction quality and cropping region of interests (ROIs) from the whole field. In addition, extracting phenotypic traits from raw UAV images is more competitive than directly from the digital orthomosaic (DOM). Currently, no easy-to-use tools are available to implement previous tasks for commonly used commercial SfM software, such as Pix4D and Agisoft Metashape. Hence, an open source software package called easy intermediate data processor (EasyIDP; MIT license) was developed to decrease the workload in intermediate data processing mentioned above. The functions of the proposed package include (1) an ROI cropping module, assisting in reconstruction quality assessment and cropping ROIs from the whole field, and (2) an ROI reversing module, projecting ROIs to relative raw images. The result showed that both cropping and reversing modules work as expected. Moreover, the effects of ROI height selection and reversed ROI position on raw images to reverse calculation were discussed. This tool shows great potential for decreasing workload in data annotation for machine learning applications. [ABSTRACT FROM AUTHOR]