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Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenge relies on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5-68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti-6Al-4V sheet under both quasi-static and modest-rate dynamic loading (failure in 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. Additional shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the 'state-of-the-art' in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods.
In recent years, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel dereverberation techniques and automatic speech recognition (ASR) techniques that are robust to reverberation. In this paper, we describe the REVERB challenge, which is an evaluation campaign that was designed to evaluate such speech enhancement (SE) and ASR techniques to reveal the state-of-the-art techniques and obtain new insights regarding potential future research directions. Even though most existing benchmark tasks and challenges for distant speech processing focus on the noise robustness issue and sometimes only on a single- channel scenario, a particular novelty of the REVERB challenge is that it is carefully designed to test robustness against reverberation, based on both real, single- channel, and multichannel recordings. This challenge attracted 27 papers, which represent 25 systems specifically designed for SE purposes and 49 systems specifically designed for ASR purposes. This paper describes the problems dealt within the challenge, provides an overview of the submitted systems, and scrutinizes them to clarify what current processing strategies appear effective in reverberant speech processing.
Background:
Over the past ten years, we carried out several comprehensive studies in the area of entrepreneurship education using business games that simulate the business processes of startups. The studies researched the learning effects of these games on German university students.
Aim:
The studies we present investigated if the simulation game-based educational entrepreneurship programs in Germany reached their goals. These goals included the fostering of participants’ entrepreneurial competencies and desire to create a startup.
Method:
We show traditional summative output-oriented results and more profound results based on our theory-based evaluation approach. A so-called logic model provides a framework for the interpretation of what takes place during the entrepreneurship business simulations. Currently, we have conducted research on more than 50 regular university courses with more than 1000 students. Another part of our studies is the evaluation of entrepreneurship education in the German national business game-based competition, EXIST priME Cup (further called EPC). More than 12,000 students attended more than 500 of these cup seminars. We also show new results from an online survey that was carried out to measure the long-term effects of the startup simulation-based seminars.
Results:
The results of five studies are summarized, and show an overall increase in the participants’ knowledge of business administration and business plan preparation skills (required in start-up context). Apart from other results, significant gender-based differences are identified. The differences relate to entrepreneurial attitudes and motivation. Some test scenarios with cup seminars for women only with extended debriefing seem to reduce this decrease in the motivation of women; further research with larger samples is necessary. A new study on the long-term effects shows a very high acceptance rate and demonstrates the satisfaction of former students. The simulation game-based program resulted in participants starting startups at a rate that is approximately twice as high (around 16%) as the normal rate in Germany.