435032 research outputs found
Sort by
Effect of Post-Weld Heat Treatment on the Impact Toughness and Microstructure of 2.25Cr-1Mo-0.25 V High-Strength Steel Submerged Arc Welding Weld Metals
No full textIn the overall integrity assessment of welded structural components in hydrogenation reactors, the welded metal was often considered a weak zone due to its uneven microstructure and poor impact toughness. Improving the impact toughness of this zone had become one of the core research topics for improving the service reliability and lifespan of welded structural components. In this study, three weld metals with a as-welded state and two different post-weld heat treatments (PWHT.MIN: 705 °C × 8 h, PWHT.MAX: 705 °C × 32 h) were selected. The impact toughness of the weld metals were examined by the Charpy V-notch impact test, while scanning electron microscope (SEM) and electron backscatter diffraction (EBSD) were utilized to evaluate the microstructures of the weld metals. The results indicated that the impact energy of weld metal in the as-welded weld metal is less than 10 J, while as-PWHT weld metal significantly improves the impact toughness (PWHT.MIN: 90 J, PWHT.MAX: 180 J), which is related to the differences in microstructural types and grain orientation spread (GOS). After PWHT, the microstructure transforms from granular bainite to ferrite; PWHT facilitates the full diffusion of alloying elements, promotes grain nucleation and growth, and optimizes GOS, thereby improving the crack resistance and impact toughness of weld metal.</p
Integrated machine-learning modelling for mechanical property prediction – A case study on laser-welded TC4 titanium alloy
No full textLaser welding of TC4 titanium alloy is extensively employed in high-end manufacturing sectors such as aerospace, owing to high specific strength and low density. However, the complex interactions among multiple welding process parameters present a significant challenge for a coordinated control, thus hindering further improvements in joint performance. This study employs machine learning to predict the tensile strength and elongation of laser welded joints of TC4 titanium alloy, aiming to optimize the welding process and improve joint performance. We develop predictive models correlating laser welding parameters with mechanical properties using a multilayer perceptron (MLP), support vector regression (SVR), and four ensemble algorithms—XGBoost, CatBoost, LightGBM, and random forest (RF). XGBoost model achieves the highest accuracy in predicting tensile strength, (R2 = 0.90 training; 0.84 test). For elongation prediction, the CatBoost model is better than other models, (R2 = 0.90 training; 0.85 test). SHAP analysis demonstrates that heat input has the most significant influence on the tensile strength prediction model, whereas tensile strength is the most critical input variable in the elongation prediction. Incorporating tensile strength as an input variable in the elongation prediction model substantially improves generalization, raising test-set R2 from 0.38 to 0.85 (a 123.68% relative improvement), and simultaneously reducing hyperparameter-tuning complexity. Error-propagation analysis reveals that tensile strength prediction errors have only a minor effect on elongation prediction, supporting a phased collaborative modeling strategy between these targets. The findings provide a practical pathway for intelligent optimization of TC4 laser welding processes and precise control of joint performance, thereby advancing lightweight manufacturing of high-end equipments.</p
Tuning Immersion and Performance with Adaptive Generative Music in VR
No full textMusic in virtual environments often enhances atmosphere and pacing, not performance. AI/procedural audio enable real-time adaptive soundtracks, but their behavioral effects in HMD-VR are unclear. We built a VR archery system with Unity, Google MusicFXDJ, Ubiq-Genie generating music from gameplay events. In a within-subjects study (N=22), participants shot with a matched fixed soundtrack or an adaptive one that raised tension in four phases as arrows ran out. Adaptive music increased presence and emotional impact and produced an inverted-U on precision: moderate tension improved accuracy and aiming time; high tension impaired both. AI music can act as feedback for VR training/rehab/entertainment
French B Movies: Suburban Spaces, Universalism, and the Challenge of Hollywood. By David A. Pettersen
No full textFee structure and equity fund manager’s optimal locking in profits strategy
No full textWe study the effects of fee structures on fund managers’ strategies for locking in profits. Utilizing the optimal stopping time method, we identify two critical portfolio value thresholds that signal when a manager will choose to lock in profits. Fee components such as management fees, self-investment ratios, and high-water marks significantly influence these decisions. Specifically, higher management fees are associated with increased risk aversion, leading to a narrower continuation region, indicating a preference for lower risk. Conversely, performance fees encourage greater risk-taking. We use the S&P 500 Index and NASDAQ Composite index as representatives of managers’ portfolios and apply our model to illustrate how managers adjust their profit-locking strategies in response to their desired rewards
Totalitarianism
No full textTotalitarianism as a category originates in the European Interwar period. The first models to win favour in political science and political theory were ‘statist’; by the end of the Cold War, these had been overtaken by theories proposing an ‘ideological’ conception organised around the New Man and the new society. Both, however, may be understood to be sub-types of ‘classical’ totalitarianism, which may be extended legitimately in the contemporary period to accommodate the rise of new, politically-dangerous forms of religious extremism (primarily, ‘Islamism’), though which are, necessarily, rather incompatible with theorisations of ‘neoliberal’, ‘biopolitical’, or ‘digital’ totalitarianism
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇