Additive Manufacturing of Alloys and Composites

The emergence and development of high-performance materials have benefited from the revolution in modern manufacturing technology, in which additive manufacturing (AM) is the most representative over the last four decades [...

Expansion Planning Method of the Industrial Park Integrated Energy System Considering Regret Aversion

Industrial parks have various sources and conversion forms of energy. The many uncertainties in the planning of industrial park integrated energy systems (IPIES) pose a great risk of regret in planning schemes; thus, an expansion planning method for an IPIES, considering regret aversion, is proposed. Based on comprehensive regret value consisting of min–max regret aversion and the min average regret value, the method optimizes the comprehensive cost of the expansion planning scheme in IPIES under different natural gas price fluctuation scenarios, including costs of construction, operation and maintenance, and environmental protection. A multi-stage expansion planning scheme and typical daily operation plans under multiple natural gas price fluctuation scenarios of the IPIES in an economic and technological development zone in southeast China are used to demonstrate the validity of the method. The results show that, compared with a traditional planning method based on expectation, the proposed expansion planning method could reduce the maximum regret value by 14% on average, and greatly reduces the risk of decision-making regret by up to 18%. At the same time, the influence of natural gas price on expansion planning of the IPIES is discussed

Analysis and Forecast of Traffic Flow between Urban Functional Areas Based on Ride-Hailing Trajectories

Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functional areas are of great significance for detecting urban traffic flow directions and traffic congestion causes, as well as helping commuters plan routes in advance. Existing methods based on ride-hailing trajectories are relatively effective solution schemes, but they often lack in-depth analyses on time and space. In the paper, to explore the rules and trends of traffic flow among functional areas, a new spatiotemporal characteristics analysis and forecast method of traffic flow among functional areas based on urban ride-hailing trajectories is proposed. Firstly, a city is divided into areas based on the actual urban road topology, and all functional areas are generated by using areas of interest (AOI); then, according to the proximity and periodicity of inter-area traffic flow data, the periodic sequence and the adjacent sequence are established, and the topological structure is learned through graph convolutional neural (GCN) networks to extract the spatial correlation of traffic flow among functional areas. Furthermore, we propose an attention-based gated graph convolutional network (AG-GCN) forecast method, which is used to extract the temporal features of traffic flow among functional areas and make predictions. In the experiment, the proposed method is verified by using real urban traffic flow data. The results show that the method can not only mine the traffic flow characteristics among functional areas under different time periods, directions, and distances, but also forecast the spatiotemporal change trend of traffic flow among functional areas in a multi-step manner, and the accuracy of the forecasting results is higher than that of common benchmark methods, reaching 96.82%

Creep-induced heterogeneous precipitation of Laves phase with two morphologies in tempered martensite ferritic steels

We report two typical morphologies (elongated- and blocky-shaped) of the Laves phase in tempered martensite ferritic steels during creep process, originating from the two independent formation paths, i.e. along grain boundaries (GBs) and neighboring M23C6. This is attributed to the multi-element segregation (Cr, Mn, Si and W) at GBs and adjacent M23C6 that serves as suppliers of Laves phase formers. Furthermore, the subsequent different growth mechanisms play crucial roles in the two typical morphologies. Our findings improve the understanding of Laves phase heterogeneous precipitation and provide new insights for the innovation of novel heat-resistant steels with superior creep strength