The relationship between 100Cr6 steelmaking, inclusion microstructure and rolling contact fatigue performance

A processing-microstructure-performance approach is followed to study three bearing steel samples manufactured from the most frequently used continuous casting routes. The inclusion microstructures of the samples were altered by varying the metallurgy and hot working conditions. Inclusion size distribution information is obtained, showing the steel-making route that results in the highest cleanliness. 3D analysis of inclusion morphologies using electrolytic extraction indicates the irregularities on the surface to be favourable sites for crack nucleation under RCF. Flat-washer and ball-on-rod tests were conducted to study the rolling contact fatigue life of the steels, with the results from the flat-washer testing method being more representative for bearing life. This research suggests that early fatigue of bearings is governed by silicate fragmentation and late fatigue by TiN inclusions

Forecasting Realized Volatility of Agricultural Commodities

We forecast the realized and median realized volatility of agricultural commodities using variants of the Heterogeneous AutoRegressive (HAR) model. We obtain tick-by-tick data for five widely traded agricultural commodities (Corn, Rough Rice, Soybeans, Sugar, and Wheat) from the CME/ICE. Real out-of-sample forecasts are produced for 1- up to 66-days ahead. Our in-sample analysis shows that the variants of the HAR model which decompose volatility measures into their continuous path and jump components and incorporate leverage effects offer better fitting in the predictive regressions. However, we convincingly demonstrate that such HAR extensions do not offer any superior predictive ability in the out-of-sample results, since none of these extensions produce significantly better forecasts compared to the simple HAR model. Our results remain robust even when we evaluate them in a Value-at-Risk framework. Thus, there is no benefit by adding more complexity, related to volatility decomposition or relative transformations of volatility, in the forecasting models

Speed-loop bandwidth design method for controller parameters of ship hydrogen storage DC electric propulsion system

ObjectivesThis paper aims to study the problems that the external electrical characteristics of a hydrogen fuel cell are soft, its dynamic characteristics are poor and its system stability is susceptible to the influence of propulsion load in marine hydrogen storage DC electric propulsion systems. MethodsFirst, an analysis is performed of the output external electrical characteristics of the hydrogen fuel cell and the propeller load conditions of the marine electric propulsion system, then a ship-engine-propeller model and a frequency-domain model of drive control system for a permanent magnet synchronous motor (PMSM) are set up. Next, a speed-loop bandwidth design method is proposed, considering the external electrical characteristics of hydrogen fuel cell and propeller load conditions. Finally, on basis of the parameters of a mother ship, an electric propulsion system for a hydrogen-battery DC electric propulsion ship in a hardware-in-loop experimental platform is established to verify the proposed method.ResultsThe experimental results show that the speed response of the motor has no overshoot under this method, and the speed-loop fluctuation is reduced by 5 r/min when the load torque disturbance occurs. ConclusionsThe speed-loop bandwidth design method proposed in this paper improves the comprehensive characteristics of the ship hydrogen storage DC electric propulsion system, and is easy to implement in engineering

The Structure, Expression, and Function Prediction of DAZAP2, A Down-Regulated Gene in Multiple Myeloma

In our previous studies, DAZAP2 gene expression was down-regulated in untreated patients of multiple myeloma (MM). For better studying the structure and function of DAZAP2, a full-length cDNA was isolated from mononuclear cells of a normal human bone marrow, sequenced and deposited to Genbank (AY430097). This sequence has an identical ORF (open reading frame) as the NM_014764 from human testis and the D31767 from human cell line KG-1. Phylogenetic analysis and structure prediction reveal that DAZAP2 homologues are highly conserved throughout evolution and share a polyproline region and several potential SH2/SH3 binding sites. DAZAP2 occurs as a single-copy gene with a four-exon organization. We further noticed that the functional DAZAP2 gene is located on Chromosome 12 and its pseudogene gene is on Chromosome 2 with electronic location of human chromosome in Genbank, though no genetic abnormalities of MM have been reported on Chromosome 12. The ORF of human DAZAP2 encodes a 17-kDa protein, which is highly similar to mouse Prtb. The DAZAP2 protein is mainly localized in cytoplasm with a discrete pattern of punctuated distribution. DAZAP2 may associate with carcinogenesis of MM and participate in yet-to-be identified signaling pathways to regulate proliferation and differentiation of plasma cells

Dynamic navigation : integrating GL-STGCNN and MPC for collision avoidance with future awareness

Existing ship dynamic collision avoidance methods mostly rely on the instantaneous motion information of surrounding ships to make decisions. This makes it difficult to adapt to changes in the motion states of surrounding ships, which may lead to collisions between ships. To improve the safety of dynamic collision avoidance methods, this paper combines the multi-ship trajectory prediction model GL-STGCNN with model predictive control for ship dynamic collision avoidance tasks. Firstly, the interaction between ships is extracted through GL-STGCNN to predict the future trajectories of surrounding ships. Then, the objective function based on the artificial potential field method and the velocity obstacle method is optimized to control the ship to complete the dynamic collision avoidance task. The performance of the dynamic collision avoidance method is verified and analyzed in the ship navigation scenario simulated by AIS data. The experiments show that the new ship dynamic collision avoidance method not only complies with the COLREGs, but also can flexibly select the collision avoidance method according to different scenarios. In addition, the theoretical collision avoidance threshold distance based on the MPC objective function shows a high degree of fit with the actual collision avoidance trigger distance observed in the simulation verification

Evaluation of the Effect of WRF Physical Parameterizations on Typhoon and Wave Simulation in the Taiwan Strait

Typhoons and typhoon waves can cause disasters in coastal areas around the world. The Taiwan Strait often experiences typhoons, especially in summer. Numerical models have been adopted to predict typhoons and reduce losses. The Weather Research and Forecasting (WRF) model is widely used in typhoon simulations, and the Simulating WAves Nearshore (SWAN) model performs well in wave simulations. However, significant uncertainty remains in terms of choosing suitable WRF physical parameterizations in different situations. To evaluate the effect of WRF physical parameterizations on wind and wave simulations, 27 simulation experiments were designed. Three typhoon events (Goni, Dujuan, and Meranti) with different tracks that influenced the Taiwan Strait were simulated. Three parameters (wind speed, wind direction and significant wave height) were assessed using Taylor diagrams, and it was found that the best simulation experiment changed according to typhoon tracks and physical parameters. In wind speed simulation, the best simulation experiment is 12 for typhoon Dujuan and 19 for typhoon Goni and Meranti. From the perspective of wind direction simulation, experiments 26, 23, and 2 performed best for typhoons Goni, Dujuan, and Meranti. And experiments 19, 1, and 20 had the best performances in significant wave height simulation for typhoons Goni, Dujuan, and Meranti. The WRF-SWAN model using the best simulation experiment reduced the error and exhibited good performance in the wind and wave simulations. Skill scores of three parameters were all over 70 for typhoon Goni and 80 for typhoon Dujuan and Meranti. The applicability of the best simulation experiments was demonstrated in typhoon simulations with similar tracks. The accuracy of the wave simulation depended on wind speed, wind direction, and their interaction. In addition, a scheme’s sensitivity changed with different typhoon tracks. This study provides references for designing physical parameterizations for use with the WRF-SWAN model, which may help to simulate typhoons and typhoon waves in the Taiwan Strait more accurately in the future

The Evolution and Future Directions of Green Buildings Research: A Scientometric Analysis

Economic development and urbanization naturally give rise to expanding demand for new buildings, whose construction and operation inevitably lead to significant increases in energy consumption and greenhouse gas emissions. To better conserve resources and protect the environment, technologies for green buildings have evolved significantly in the past two decades. In this study, a scientometric analysis of green buildings research from 2003 to 2023 was performed using CiteSpace. A total of 1986 articles retrieved from the Web of Science (WoS) core collection database were used as the data source for an in-depth analysis of research trends, hotspots, and future directions, showing changes in publication numbers, core journals, key countries, and institutions that have made remarkable contributions in this field. The results showed that the field of green buildings research is in a phase of rapid growth. The current research hotspots include the adoption of the green buildings paradigm, rating systems, energy performance, greenhouse gas emissions, indoor environmental quality, and green roofs/walls. Based on the keywords citation bursts and literature review, we believe that government promotion measures, use of renewable energy, integration with plants, and application of artificial intelligence (AI) in green buildings will be the most promising development directions in the future