Fracture mechanisms and failure criteria of adhesive joints and toughened epoxy adhesives

PhDAdhesive bonded applications are used widely in industry because of significant advantages such as uniform stress distribution, and the ability to join different materials. However most epoxy structural adhesives are brittle at room temperature and it is required to improve their toughness. The objective of this work was to understand the fracture of adhesive joints, failure criteria and rubber toughening mechanisms via a series of experiments and FEA modelling. Double lap joints (DLJ) bonded by commercial AV119 adhesive were studied. It was found that local strain and failure path were controlled by adhesive thickness. In order to model adhesive joints accurately and efficiently, systematic fracture tests were implemented to determine the fracture criteria. Mode-I, mode-II and mixed mode fracture energy release rates were obtained by Fixed Arm Peel, 4-point End Notched Flexure (ENF) and Mixed Mode Bending (MMB) tests. Numerical analysis was applied to determine the parameters of the Drucker-Prager material model and Cohesive Zone Model (CZM). The 3D FEA results showed good agreement with experimental results of DLJ and MMB. FEA results successfully demonstrated bonding strength, stress and strain distribution and plastic deformation; and further details were found using sub models. The rubber toughening mechanism was studied by modelling different face-centred micromodels. The stress distributions ahead of the crack tip in global DLJ models were extracted and used as the loading condition for the micromodels, so that a relationship between macromodel and micromodel has been established. It is found that Von Mises and hydrostatic stress play very important roles in the toughening mechanisms and also predicted that rubber particles with multi-layer structure have more potential to toughen epoxy resin than simple rubber particles

THE EFFECTS OF DISTRIBUTOR DESIGN ON THE SOLIDS DISTRIBUTION IN A CFB RISER

The influence of gas distributor design on the gas-solids flow structure was investigated in a rectangular CFB riser. The gas distributor was altered five different ways. The results show that the distributor design had significant effects on the solids distribution. The changed flow structure was maintained from the entrance to the riser top. Altering the gas distributor was an effective and practical method to change the flow structure. This study may be beneficial to CFB design and operation

The Research on Operation of Obstructed Total Anomalous Pulmonary Venous Connection in Neonates

Objectives. Total anomalous pulmonary venous connection (TAPVC) is a rare congenital heart disease. This study aimed to evaluate the outcomes of TAPVC repair in neonates, controlling for anatomic subtypes and surgical techniques. Methods. Between 1997 and 2013, 88 patients (median age: 16 days) underwent repair for supracardiac (31), cardiac (18), infracardiac (36), or mixed (3) TAPVC. All the patients underwent emergency operation due to obstructed drainage. Supracardiac and infracardiac TAPVC repair included a side-to-side anastomosis between the pulmonary venous confluence and left atrium. Coronary sinus unroofing was preferred for cardiac TAPVC repair. Results. The early mortality rate was 2.3% (2/88 patients). The echocardiogram showed no obstruction in the pulmonary vein anastomosis, and flow rate was 1.1–1.42 m/s in the 3-year follow-up period. Conclusions. The accurate preoperative diagnosis, improved protection of heart function, use of pulmonary vein tissue to anastomose and avoid damage of the pulmonary vein, and delayed sternum closure can reduce the risk of mortality. The preoperative severity of pulmonary vein obstruction, the timing of the emergency operation, and infracardiac or mixed-type TAPVC can affect prognosis. Using our surgical technique, the TAPVC mortality among our patients was gradually reduced with remarkable results. However, careful monitoring of the patient with pulmonary vein restenosis and the timing and method of reoperation should also be given importance

Contributors to linkage between Arctic warming and East Asian winter climate

Previous modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.publishedVersio

Feedback RoI Features Improve Aerial Object Detection

Neuroscience studies have shown that the human visual system utilizes high-level feedback information to guide lower-level perception, enabling adaptation to signals of different characteristics. In light of this, we propose Feedback multi-Level feature Extractor (Flex) to incorporate a similar mechanism for object detection. Flex refines feature selection based on image-wise and instance-level feedback information in response to image quality variation and classification uncertainty. Experimental results show that Flex offers consistent improvement to a range of existing SOTA methods on the challenging aerial object detection datasets including DOTA-v1.0, DOTA-v1.5, and HRSC2016. Although the design originates in aerial image detection, further experiments on MS COCO also reveal our module's efficacy in general detection models. Quantitative and qualitative analyses indicate that the improvements are closely related to image qualities, which match our motivation

The Role of Mid-latitude Westerly Jet in the Impacts of November Ural Blocking on Early-Winter Warmer Arctic-Colder Eurasia Pattern

Based on statistical analysis using observations and idealized model simulations, previous studies have revealed the potential response of early-winter atmospheric circulation and temperature anomalies to November Ural blocking (UB) anomalies. Using a large number of coupled simulations, this study found that the response is sensitive to the intensity of November mid-latitude westerly jet over Eurasia. Stronger-than-normal November UB without a significantly weakened westerly jet could not cause significant atmospheric response in early-winter. By contrast, stronger-than-normal November UB with a significantly weakened jet would be followed by a warmer Arctic-colder Eurasia (WACE) pattern in December. The significantly weakened westerly jet favors stronger upward propagation of planetary waves, which causes stronger weakening and longer persistence of the stratospheric polar vortex. This stratospheric response persists into December and propagates downward into the troposphere interfering with planetary waves (especially wavenumber-1). The lead-lag UB-WACE linkage modulated by mid-latitude jet may have implications for sub-seasonal predictability.publishedVersio

MuseCoco: Generating Symbolic Music from Text

Generating music from text descriptions is a user-friendly mode since the text is a relatively easy interface for user engagement. While some approaches utilize texts to control music audio generation, editing musical elements in generated audio is challenging for users. In contrast, symbolic music offers ease of editing, making it more accessible for users to manipulate specific musical elements. In this paper, we propose MuseCoco, which generates symbolic music from text descriptions with musical attributes as the bridge to break down the task into text-to-attribute understanding and attribute-to-music generation stages. MuseCoCo stands for Music Composition Copilot that empowers musicians to generate music directly from given text descriptions, offering a significant improvement in efficiency compared to creating music entirely from scratch. The system has two main advantages: Firstly, it is data efficient. In the attribute-to-music generation stage, the attributes can be directly extracted from music sequences, making the model training self-supervised. In the text-to-attribute understanding stage, the text is synthesized and refined by ChatGPT based on the defined attribute templates. Secondly, the system can achieve precise control with specific attributes in text descriptions and offers multiple control options through attribute-conditioned or text-conditioned approaches. MuseCoco outperforms baseline systems in terms of musicality, controllability, and overall score by at least 1.27, 1.08, and 1.32 respectively. Besides, there is a notable enhancement of about 20% in objective control accuracy. In addition, we have developed a robust large-scale model with 1.2 billion parameters, showcasing exceptional controllability and musicality

Honor, Goal Setting, and Energy Conservation: Evidence from a Field Experiment in Student Dormitories

Non-monetary incentives are increasingly being studied in encouraging energy conservation. In light of this, we conducted a natural field experiment in student dormitories to assess the effect of honor-based incentives and goal setting on electricity saving and the intrinsic motivation to save energy. Using a difference-in-difference model, we found that goal setting reduced the dormitories' electricity consumption by 15.93\% on average compared to the control group. However, the honor-based incentives were not effective on average. In addition, the study found that both honor-based incentives and goal setting, on average, did not crowd out or crowd in the intrinsic motivation to save electricity in dormitories. The heterogeneity analysis showed that the more the dormitory values honor incentives, the more its intrinsic motivation was crowded in by honor incentives. We also found dormitory characteristics affect the crowding effect on the intrinsic motivation

EmoGen: Eliminating Subjective Bias in Emotional Music Generation

Music is used to convey emotions, and thus generating emotional music is important in automatic music generation. Previous work on emotional music generation directly uses annotated emotion labels as control signals, which suffers from subjective bias: different people may annotate different emotions on the same music, and one person may feel different emotions under different situations. Therefore, directly mapping emotion labels to music sequences in an end-to-end way would confuse the learning process and hinder the model from generating music with general emotions. In this paper, we propose EmoGen, an emotional music generation system that leverages a set of emotion-related music attributes as the bridge between emotion and music, and divides the generation into two stages: emotion-to-attribute mapping with supervised clustering, and attribute-to-music generation with self-supervised learning. Both stages are beneficial: in the first stage, the attribute values around the clustering center represent the general emotions of these samples, which help eliminate the impacts of the subjective bias of emotion labels; in the second stage, the generation is completely disentangled from emotion labels and thus free from the subjective bias. Both subjective and objective evaluations show that EmoGen outperforms previous methods on emotion control accuracy and music quality respectively, which demonstrate our superiority in generating emotional music. Music samples generated by EmoGen are available via this link:https://ai-muzic.github.io/emogen/, and the code is available at this link:https://github.com/microsoft/muzic/.Comment: 12 pages, 7 page