Mechanical Properties Characterization of Welded Automotive Steels

Among the various welding technologies, resistance spot welding (RSW) and laser beam welding (LBW) play a significant role as joining methods for the automobile industry. The application of RSW and LBW for the automotive body alters the microstructure in the welded areas. It is necessary to identify the mechanical properties of the welded material to be able to make a reliable statement about the material behavior and the strength of welded components. This study develops a method by which to determine the mechanical properties for the weldment of RSW and LBW for two dual phase (DP) steels, DP600 and DP1000, which are commonly used for the automotive bodies. The mechanical properties of the resistance spot weldment were obtained by performing tensile tests on the notched tensile specimen to cause an elongation of the notched and welded area in order to investigate its properties. In order to determine the mechanical properties of the laser beam weldment, indentation tests were performed on the welded material to calculate its force-penetration depth-curve. Inverse numerical simulation was used to simulate the indentation tests to determine and verify the parameters of a nonlinear isotropic material model for the weldment of LBW. Furthermore, using this method, the parameters for the material model of RSW were verified. The material parameters and microstructure of the weldment of RSW and LBW are compared and discussed. The results show that the novel method introduced in this work is a valid approach to determine the mechanical properties of welded high-strength steel structures. In addition, it can be seen that LBW and RSW lead to a reduction in ductility and an increase in the amount of yield and tensile strength of both DP600 and DP1000

Hedging Break-Even Biodiesel Production Costs Using Soybean Oil Futures

The effectiveness of hedging volatile input prices for biodiesel producers is examined over one- to eight-week time horizons. Results reveal that hedging break-even soybean costs with soybean oil futures offers significant reductions in input price risk. The degree of risk reduction is dependent upon type of hedge, naïve or risk-minimizing, and upon time horizon. In contrast, cross-hedging break-even poultry fat costs with soybean oil futures failed to reduce input price risk.biodiesel, hedging, poultry fat, soybean oil, Agribusiness, Demand and Price Analysis, Environmental Economics and Policy,

The Hawking-Penrose singularity theorem for C1,1C^{1,1}-Lorentzian metrics

We show that the Hawking--Penrose singularity theorem, and the generalisation of this theorem due to Galloway and Senovilla, continue to hold for Lorentzian metrics that are of $C^{1, 1}$-regularity. We formulate appropriate weak versions of the strong energy condition and genericity condition for $C^{1,1}$-metrics, and of $C^0$-trapped submanifolds. By regularisation, we show that, under these weak conditions, causal geodesics necessarily become non-maximising. This requires a detailed analysis of the matrix Riccati equation for the approximating metrics, which may be of independent interest.Comment: Minor amendments in v4: Removed non-equivalent condition from Def. 2.2 and adapted Lemma 3.5 and the proof of Lemma 3.

How general conditions affect regional innovation systems: The case of the two Germanys

We compare two leading regional innovation systems (RIS) in East Germany with two RIS in West Germany of about the same size and internal settlement structure. Our analyses show that differences in the performance between the regions cannot easily be related to the structural properties of the respective innovation networks because divergent general economic conditions in the two parts of the country as well as the integration of regions into their neighboring spatial environment play a rather dominant role. Overall, our analysis clearly shows that an analysis of RIS should account for the general economic conditions as well as for the position of a region in its spatial environment. Focusing just on the respective region is not enough

Insider trading among central bankers: A treatise on temptation and policy choice

Corruption among central banks induces distorted policies by, first, increasing the inflation bias and, second, potentially inducing a pro-cyclical adjustment of employment. In response to a negative supply shock a corrupt central banker is tempted to decrease money supply. In this case, he pretends an ultraconservative attitude while in reality he is driven by self interest. If societies with extreme tastes (relating only to inflation or employment) are not governed by central bankers with similar preferences, corruption might be tolerated as an instrument of bringing factual policies more in line with its public desire. This finding provides a warning signal against the choice of non-representative central bankers

Quantifying Mechanical Properties of Automotive Steels with Deep Learning Based Computer Vision Algorithms

This paper demonstrates that the instrumented indentation test (IIT), together with a trained artificial neural network (ANN), has the capability to characterize the mechanical properties of the local parts of a welded steel structure such as a weld nugget or heat affected zone. Aside from force-indentation depth curves generated from the IIT, the profile of the indented surface deformed after the indentation test also has a strong correlation with the materials’ plastic behavior. The profile of the indented surface was used as the training dataset to design an ANN to determine the material parameters of the welded zones. The deformation of the indented surface in three dimensions shown in images were analyzed with the computer vision algorithms and the obtained data were employed to train the ANN for the characterization of the mechanical properties. Moreover, this method was applied to the images taken with a simple light microscope from the surface of a specimen. Therefore, it is possible to quantify the mechanical properties of the automotive steels with the four independent methods: (1) force-indentation depth curve; (2) profile of the indented surface; (3) analyzing of the 3D-measurement image; and (4) evaluation of the images taken by a simple light microscope. The results show that there is a very good agreement between the material parameters obtained from the trained ANN and the experimental uniaxial tensile test. The results present that the mechanical properties of an unknown steel can be determined by only analyzing the images taken from its surface after pushing a simple indenter into its surface

Facial expressions and personality: A kinematical investigation during an emotion induction experiment

Background/Aims: In order to elucidate the relationship between personality traits and expression of positive emotions in healthy volunteers, standardized personality inventories and kinematical analysis of facial expressions can be helpful and were applied in the present study. Methods: Markers fixed at distinct points of the face emitting ultrasonic signals at high frequency gave a direct measure of facial movements with high spatial-temporal resolution. Forty-six healthy participants (mean age: 40.7 years; 20 males, 26 females) watching a witty movie ('Mr. Bean') were investigated. Results: Speed of `laughing' was associated with higher scores on Zuckerman's Sensation Seeking Scale and NEO-FFI (Openness to Experience). Conclusion: Kinematical analysis of facial expressions seems to reflect sensation seeking and related personality styles. Higher speed of facial movements in sensation seekers suggests lowered serotonergic function. Copyright (c) 2006 S. Karger AG, Basel