Analysis of preheating temperature field characteristics in selective laser sintering

Selective laser sintering technology has broad application prospects in the manufacture of small batch parts with complex structure. In the sintering process, the preheating efficiency and temperature of powder layer determine the processing quality. A method of preheating powder by lamp radiation and tropical heat conduction is proposed in this paper. The thermal radiation model is established, and the angle coefficient is introduced to describe the proportion of radiation energy on the surface of powder layer. Based on the geometric characteristics of the powder cylinder, the heat conduction process is simplified to one-dimensional heat conduction along the radial direction, and the heat conduction model is established. The coupled temperature field under two actions is obtained by combining the heat radiation model with the heat conduction model. The uniformity coefficient [Formula: see text]/[Formula: see text] of the temperature field is defined to represent the uniformity of the preheating temperature field of the powder layer. By comparing the uniformity coefficient [Formula: see text], a more uniform temperature field can be obtained when the height coefficient is 1.8 under combined action. The validity of the model is verified by a comparative experiment with processed water atomized iron powder. Constructing uniform temperature field can effectively reduce the deformation of parts and improve the forming quality.

Laser Remelting Process Simulation and Optimization for Additive Manufacturing of Nickel-Based Super Alloys

Nickel-based super alloys are popular for applications in the energy and aerospace industries due to their excellent corrosion and high-temperature resistance. Direct metal deposition (DMD) of nickel alloys has reached technology readiness for several applications, especially for the repair of turbomachinery components. However, issues related to part quality and defect formation during the DMD process still persist. Laser remelting can effectively prevent and repair defects during metal additive manufacturing (AM); however, very few studies have focused on numerical modeling and experimental process parameter optimization in this context. Therefore, the aim of this study is to investigate the effect of determining the remelting process parameters via numerical simulation and experimental analyses in order to optimize an industrial process chain for part repair by DMD. A heat conduction model analyzed 360 different process conditions, and the predicted melt geometry was compared with observations from a fluid flow model and experimental single tracks for selected reference conditions. Subsequently, the remelting process was applied to a demonstrator repair case. The results show that the models can well predict the melt pool shape and that the optimized remelting process increases the bonding quality between base and DMD materials. Therefore, DMD part fabrication and repair processes can benefit from the remelting step developed here.

Mathematical modelling of enterprise financial risk assessment based on risk conduction model

Risk transmission has three elements: risk source, risk flow and risk carrier. The paper quotes the asymmetric model and the joint asymmetric model to analyse the conduction effects of financial risks. At the same time, the article uses the elasticity coefficient to quantitatively calculate the risk transmission effect of the two supply chain financial financing modes. The research results prove that the risk transmission ability of each financial market has individual differences, and the foreign exchange market does not have significant risk transmission ability to other markets during the rising stage. The joint asymmetric model is more effective in predicting corporate financial risks.

Conduction Transformation-Based Coordination Method for Conflict in Product Adaptive Design Driven by Functional Requirements

A conduction transformation-based coordination method for product structure optimization design was proposed for the conflict between satisfying product functional requirements and realizing adaptive modification. Customer functional requirements were analyzed hierarchically, the extension domains that indicated the matching degree between customer requirement and product function were delimited; and then a multi-layer function-behavior-structure (FBS) mapping model was established. Product function-structure correlation analysis was carried out in two dimensions, i.e., “structure-structure”, and “structure-function”; a product structure behavior function (SBF) reverse conduction model was constructed based on FBS decomposition model; thus, to realize reverse conduction from structure layer to function layer. For conflict coordination in structure modification, extension transformation operations were created, the conduction transformation trigger unit was extracted, and the trigger condition was also clarified; thus, the coordination strategy for the contradiction in adaptive design could be generated by conducting active and conduction transformations. Finally, the effectiveness and feasibility of this method were verified with the structure optimization design of a delivery system of cutting machine as an example; and the discussion section emphasized that this proposed method used conduction transformation to address design conflict, instead of generating the optimal change propagation path, and how to obtain innovation inspiration.

Depth detection of spar cap defects in large-scale wind turbine blades based on 3D heat conduction model using step heating infrared thermography

The defects dispersed in spar cap often lead to failure of large-scale wind turbine blades. To predict the residual service life of blade and make repair, it is necessary to detect the depth of spar cap defects. Step-heating thermography (SHT) is a common infrared technique in this domain. However, the existing methods of SHT on defect depth detection are generally based on 1D models, which are unable to accurately detect the depth of spar cap defects because of ignoring material anisotropy and in-plane heat flow. To improve the depth detection accuracy of spar cap defects, a 3D model based on the theory of heat transfer is established by using equivalent source method (ESM), and a defect depth criterion is proposed based on the analytical solution of heat conduction equation. The modeling process are as follows. The heat conduction model of SHT was established by ESM. Then, coordinate transformation, variables separation and Laplace transformation were utilized to solve the 3D heat conduction equation. A defect depth criterion was proposed based on emerging contrast Cr. A GFRP composites plate containing 12 square flat-bottom holes with different sizes and depths was manufactured to represent spar cap with large thermal resistance defects, such as Delamination and crack. Experimental results demonstrate the validity of 3D model. Then the model was applied to on-site SHT test of a 1.5 megawatts (MW) wind turbine blade. The test results prove that the depth detection accuracy of spar cap defects can be significantly improved by using 3D model. In addition, by using a improved principle component analysis (PCA) method containing contrast enhancement factor, artifacts can be reduced and the recognition time of defects can be shortened.

Validation of the simplified heat conduction model of EN ISO 52016-1

The issue of improving the building energy efficiency led to the development of calculation methods for the building energy performance assessment. To overcome the low accessibility to detailed input data, the recently introduced EN ISO 52016-1 hourly method is based on assumptions and simplifications chosen to allow a sufficient accuracy in the outcomes with a low amount of input data. Among these assumptions, a simplified mass distribution in the envelope components is considered. In the present work, the hypothesis of the simplified heat conduction model introduced by the EN ISO 52016-1 technical standard and an improved solution provided by its Italian National Annex were evaluated. In particular, the accuracy in the prediction of the internal surface temperature was assessed in comparison with a detailed finite difference conduction algorithm. The validation was performed for 5 opaque component test cases, covering a wide range of areal heat capacity values, by considering both internal and external thermal constraints (e.g. variation of the air temperature). For the structures and boundary conditions considered, results reveal that the standard algorithm allows to predict the internal surface temperatures with a valuable level of accuracy compared to the finite difference algorithm.

Modeling analysis and optimization of temperature curve of welding furnace

Reflux welding is widely used in SMT (surface patch technology) During this production process, the quality of the product is essential to maintain the temperature and the furnace speed required by the process. The furnace temperature curve in the furnace is an important form of reaction welding process. In order to improve the process efficiency of the return furnace, the heating welding process model is established based on the Fourier heat conduction law,1 D heat conduction model and Newton cooling law and draws the furnace temperature curve model. Then, the upper boundary of the conveyor speed using the boundary analysis and multiple target planning, and further explore the research and optimization direction of subsequent process flow. At the same time, this paper examines and analyzes the modeling process and results, and effectively demonstrates the scientific nature and accuracy of the model. Finally, the paper analyzes the significance of the above model and research in chip processing.