Microstructure and mechanical properties of Mo-Nb microalloyed medium Manganese trip Steel by cyclic quenching

A novel cyclic quenching (CQ) and austenite reverse transformation (ART) was proposed for a Fe-0.25C-3.98Mn-1.22Al-0.20Si-0.19Mo-0.03Nb (wt.%) Mo-Nb microalloyed medium-Mn TRIP steel to improve strength and ductility. The results show that after twice cyclic quenching and ART exhibited optimum comprehensive properties, characterized by an ultimate tensile strength of 838 MPa, a total elongation of 90.8%, a product of strength and elongation (PSE) of 76.1 GPa ·%, and the volume fraction of austenite of approximately 62 vol.%

Optimisation over the non-dominated set of a multi-objective optimisation problem

In this thesis we are concerned with optimisation over the non-dominated set of a multiobjective optimisation problem. A multi-objective optimisation problem (MOP) involves multiple conflicting objective functions. The non-dominated set of this problem is of interest because it is composed of the “best” trade-off for a decision maker to choose according to his preference. We assume that this selection process can be modelled by maximising a function over the non-dominated set. We present two new algorithms for the optimisation of a linear function over the non-dominated set of a multi-objective linear programme (MOLP). A primal method is developed based on a revised version of Benson’s outer approximation algorithm. A dual method derived from the dual variant of the outer approximation algorithm is proposed. Taking advantage of some special properties of the problem, the new methods are designed to achieve better computational efficiency. We compare the two new algorithms with several algorithms from the literature on a set of randomly generated instances. The results show that the new algorithms are considerably faster than the competitors. We adapt the two new methods for the determination of the nadir point of (MOLP). The nadir point is characterized by the componentwise worst values of the non-dominated points of (MOP). This point is a prerequisite for many multi-criteria decision making (MCDM) procedures. Computational experiments against another exact method for this purpose from the literature reveal that the new methods are faster than the competitor. The last section of the thesis is devoted to optimising a linear function over the non-dominated set of a convex multi-objective problem. A convex multi-objective problem (CMOP) often involves nonlinear objective functions or constraints. We extend the primal and the dual methods to solve this problem. We compare the two algorithms with several existing algorithms from the literature on a set of randomly generated instances. The results reveal that the new methods are much faster than the others

Numerical analysis of the performance of flapping foil power generators

An innovative concept of wind turbines, the flapping foil power generator that exploits dynamic stall, is numerically studied at Reynolds number of 1100. The combination of the kinematic parameters and the coupling between the foil deformation and aerodynamic loads are investigated to uncover the physical mechanism for high performance. Firstly, the discrete vortex method (DVM) is improved to capture flow separations at the leading and trailing edges of the foil. Its results compare well with those of immersed boundary-lattice Boltzmann method (IB-LBM) and experiments. Its computational cost is at least two orders of magnitude less than that of the IB-LBM. Then, kinematic parameters are optimized using a multi-fidelity evolutionary algorithm implemented with a dynamic stall model and the improved DVM. The results show that despite the use of low fidelity models and limited budget of computational resources, the multi-fidelity strategy is capable of finding kinematic conditions suitable for high performance. In addition, detailed flow analysis using IB-LBM has revealed that high efficiency and power output are associated with the detachment of the leading edge vortex (LEV) near stroke reversal, resulting in a horseshoe-shaped vorticity wake with a width approximating the swept distance of foil behind the turbine plane. When the LEV detaches from the foil near mid stroke, both efficiency and power output suffer. Finally, a flexible system consisting of a rigid foil and a passively actuated flat plate tail connected through a torsional spring to the trailing edge of the rigid foil is studied numerically using the IB-LBM for different mass densities and natural frequencies under different kinematic conditions. The results show that a tail with appropriate mass density and resonant frequency can improve the maximum efficiency by 7.24% compared to the rigid system. This is because the deflection of the tail reduces the low pressure region on the pressure surface caused by the LEV after the stroke reversal, resulting in a higher efficiency. In addition, a spring-connected tail with a low resonant frequency improves the performance significantly at high flapping frequencies

Context Matters: A Strategy to Pre-train Language Model for Science Education

This study aims at improving the performance of scoring student responses in science education automatically. BERT-based language models have shown significant superiority over traditional NLP models in various language-related tasks. However, science writing of students, including argumentation and explanation, is domain-specific. In addition, the language used by students is different from the language in journals and Wikipedia, which are training sources of BERT and its existing variants. All these suggest that a domain-specific model pre-trained using science education data may improve model performance. However, the ideal type of data to contextualize pre-trained language model and improve the performance in automatically scoring student written responses remains unclear. Therefore, we employ different data in this study to contextualize both BERT and SciBERT models and compare their performance on automatic scoring of assessment tasks for scientific argumentation. We use three datasets to pre-train the model: 1) journal articles in science education, 2) a large dataset of students' written responses (sample size over 50,000), and 3) a small dataset of students' written responses of scientific argumentation tasks. Our experimental results show that in-domain training corpora constructed from science questions and responses improve language model performance on a wide variety of downstream tasks. Our study confirms the effectiveness of continual pre-training on domain-specific data in the education domain and demonstrates a generalizable strategy for automating science education tasks with high accuracy. We plan to release our data and SciEdBERT models for public use and community engagement

Survey on Individual Differences in Visualization

Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people's understanding of data, but also the general understanding of people themselves, and how they interact with visualization systems. In particular, researchers have gradually come to recognize the deficiency of having one-size-fits-all visualization interfaces, as well as the significance of individual differences in the use of data visualization systems. Unfortunately, the absence of comprehensive surveys of the existing literature impedes the development of this research. In this paper, we review the research perspectives, as well as the personality traits and cognitive abilities, visualizations, tasks, and measures investigated in the existing literature. We aim to provide a detailed summary of existing scholarship, produce evidence-based reviews, and spur future inquiry

The Relationship between Public Service Efficiency of Government and Residential Political Trust in Hong Kong

Hong Kong has a long history with its high efficiency and clean and self-disciplined government. Within the past over 20 years, different social development trend has occurred in Hong Kong. The article observed the relationship between political trust from residence and public service efficiency of government in Hong Kong from 1992 to 2015 and found that the value of public service efficiency has a significant effect on political trust in Hong Kong government, the higher the efficiency of public services, the higher the political trust. The author tried to find the path for the Hong Kong government to improve its public service quality and efficiency after testifying the positive correlation between public service efficiency and residential political trust with empirical analysis

MedEdit: Model Editing for Medical Question Answering with External Knowledge Bases

Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-specific tasks like medical question answering (QA). Moreover, they tend to function as "black-boxes," making it challenging to modify their behavior. Addressing this, our study delves into model editing utilizing in-context learning, aiming to improve LLM responses without the need for fine-tuning or retraining. Specifically, we propose a comprehensive retrieval strategy to extract medical facts from an external knowledge base, and then we incorporate them into the query prompt for the LLM. Focusing on medical QA using the MedQA-SMILE dataset, we evaluate the impact of different retrieval models and the number of facts provided to the LLM. Notably, our edited Vicuna model exhibited an accuracy improvement from 44.46% to 48.54%. This work underscores the potential of model editing to enhance LLM performance, offering a practical approach to mitigate the challenges of black-box LLMs.Comment: 6 page

Primal and Dual Algorithms for Optimization over the Efficient Set

Optimisation over the efficient set of a multi-objective optimisation problem is a mathematical model for the problem of selecting a most preferred solution that arises in multiple criteria decision making to account for trade-offs between objectives within the set of efficient solutions. In this paper we consider a particular case of this problem, namely that of optimising a linear function over the image of the efficient set in objective space of a convex multi-objective optimisation problem. We present both primal and dual algorithms for this task. The algorithms are based on recent algorithms for solving convex multi-objective optimisation problems in objective space with suitable modifications to exploit specific properties of the problem of optimisation over the efficient set. We first present the algorithms for the case that the underlying problem is a multi-objective linear programme. We then extend them to be able to solve problems with an underlying convex multiobjective optimisation problem.We compare the new algorithms with several state of the art algorithms from the literature on a set of randomly generated instances to demonstrate that they are considerably faster than the competitors

Study on rolling process and heat treatment of high strength ship plate steel EH40

Means of a tensile test studied the mechanical properties and microstructure of the experimental steel plate under different rolling processes, Charpy impact test, optical microscopy and scanning electron microscopy (SEM). The results show that the optimum thermomechanical control process (TMCP) is a heating temperature of 1200 °C, the best rolling temperature of 1180 °C. The thickness of the ship plate steel was rolled from 170 mm to 40 mm in the recrystallization zone by multi-channel time deformation, and then the thickness was decreased from 40 mm to 15mm in the non-recrystallization zone, the temperature waiting for a range 980 °C ~ 920 °C, the finish rolling temperature of 830 °C. After rolling and being cooled rapidly by laminar cooling, the cooling rate is about 12 °C/s and the final target temperature of 600 °C, which maintains the best state of steels. All data of the experimental steels have accelerated the international level, high-strength ship plate EH40 has been successfully trialed and met the practical requirements, all of these provide a solid foundation for further scientific research