Dalian University of Technology

About: Dalian University of Technology is a education organization based out in Dalian, China. It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 60890 authors who have published 71921 publications receiving 1188356 citations. The organization is also known as: Dàlián Lǐgōng Dàxué.

Current and future trends in topology optimization for additive manufacturing

Abstract: Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture design solutions. Recently, additive manufacturing (AM) has received significant attention from both academia and industry. AM is characterized by producing geometrically complex components layer-by-layer, and greatly reduces the geometric complexity restrictions imposed on topology optimization by conventional manufacturing. In other words, AM can make near-full use of the freeform structural evolution of topology optimization. Even so, new rules and restrictions emerge due to the diverse and intricate AM processes, which should be carefully addressed when developing the AM-specific topology optimization algorithms. Therefore, the motivation of this perspective paper is to summarize the state-of-art topology optimization methods for a variety of AM topics. At the same time, this paper also expresses the authors' perspectives on the challenges and opportunities in these topics. The hope is to inspire both researchers and engineers to meet these challenges with innovative solutions.

Estimation of Electronegativity Values of Elements in Different Valence States

Abstract: The electronegativities of 82 elements in different valence states and with the most common coordination numbers have been quantitatively calculated on the basis of an effective ionic potential defined by the ionization energy and ionic radius. It is found that for a given cation, the electronegativity increases with increasing oxidation state and decreases with increasing coordination number. For the transition-metal cations, the electronegativity of the low-spin state is higher than that of the high-spin state. The ligand field stabilization, the first filling of p orbitals, the transition-metal contraction, and especially the lanthanide contraction are well-reflected by the relative values of our proposed electronegativity. This new scale is useful for us to estimate some quantities (e.g., the Lewis acid strength for the main group elements and the hydration free energy for the first transition series) and predict the structure and property of materials.

Using support vector machines for long-term discharge prediction

Abstract: Accurate time- and site-specific forecasts of streamflow and reservoir inflow are important in effective hydropower reservoir management and scheduling. Traditionally, autoregressive moving-average (ARMA) models have been used in modelling water resource time series as a standard representation of stochastic time series. Recently, artificial neural network (ANN) approaches have been proven to be efficient when applied to hydrological prediction. In this paper, the support vector machine (SVM) is presented as a promising method for hydrological prediction. Over-fitting and local optimal solution are unlikely to occur with SVM, which implements the structural risk minimization principle rather than the empirical risk minimization principle. In order to identify appropriate parameters of the SVM prediction model, a shuffled complex evolution algorithm is performed through exponential transformation. The SVM prediction model is tested using the long-term observations of discharges of monthly river fl...