A Study on Optimization of Limited Water Level and Water Impounding Time of Three Gorges Project

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Impact of imperfect angle estimation on spatial and directional modulation

In this paper, we investigate the impact of imperfect angle estimation (IAE) on spatial and directional modulation (SDM) systems, assuming that the signal experiences line of sight (LoS) propagation. In SDM systems with IAE, the variation is analyzed in detail, when there is a mismatch between the beamforming and precise channel matrices. Based on the union bound and statistics theory, the average bit error probabilities (ABEPs) for both the legitimate user and eavesdropper are derived. In addition, the ergodic rate is also quantified with IAE. Simulation results are presented to show that the achieved theoretical ABEPs are useful in quantifying the potential performance penalty. We also show that the mismatch between the beamforming and precise channel matrices will become greater with the increase in direction measurement error (DME), which affects the detection for both the legitimate user and eavesdropper. On the other hand, due to the effect of IAE, the SDM requires more signal-to-noise ratio (SNR) gain to achieve a stable ergodic secrecy rate

The Hydration, Microstructure, And Mechanical Properties Of Vaterite Calcined Clay Cement (VC³)

Limestone (calcite) calcined clay cement (LC3) is a promising low-CO2 binder, but the low activity of calcite cannot compensate the reduction in clinker factor, resulting in low one-day strength and limiting its broad applications. As recent carbon capture and utilization technologies allow scalable production of vaterite, a more reactive CaCO3 polymorph, we overcome the challenge by introducing vaterite calcined clay cement (VC3), inspired by the vaterite-calcite phase change. In the present study, VC3 exhibits higher compressive strengths and faster hydration than LC3. Compared to hydrated LC3, hydrated VC3 exhibits increased amount of hemi- and mono-carboaluminate formation and decreased amount of strätlingite formation. With gypsum adjustment, the 1-day strength of VC3 is higher than that of pure cement reference. VC3, a low-CO2 binder, presents great potential as a host of the metastable CaCO3 for carbon storage and utilization and as an enabler of carbon capture at gigaton scales

Upcycling Steel Slag in Producing Eco-Efficient Iron–calcium Phosphate Cement

In the present study, steel slag powder (SSP) was utilized as the raw material to prepare iron-calcium phosphate cement (ICPC) by reacting with ammonium dihydrogen phosphate (ADP). The influences of the raw materials (SSP/ADP) mass ratios ranging from 2.0 to 7.0 on the properties and microstructures of ICPC pastes were investigated. The compressive strengths of ICPC pastes at all ages firstly increased and then decreased with the increase of SSP/ADP, and the SSP/ADP of 6.0 gave the highest strength. Crystalline mundrabillaite and amorphous phases [i.e. Fe(OH)3, Al(OH)3 and H4SiO4] were formed as the dominant binding phases through the reactions of the calcium-containing compounds (brownmillerite, monticellite and srebrodolskite) in the steel slag and ADP. Further, ADP could also react with the free FeO contained in the steel slag to yield amorphous iron phosphate phase. BSE analysis indicated that the hydration products formed and growed on the surface of steel slag particles and connect them to form the continuous, dense microstructure of ICPC paste. The utilization of high-volume steel slag as the base component will potentially bring great economic and environmental benefits for the manufacture of phosphate cement

Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe

Changes in water and nitrogen (N) availability due to climate change and atmospheric N deposition could have significant effects on soil respiration, a major pathway of carbon (C) loss from terrestrial ecosystems. A manipulative experiment simulating increased precipitation and atmospheric N deposition has been conducted for 9 years (2005–2013) in a semiarid grassland in Mongolian Plateau, China. Increased precipitation and N addition interactively affect soil respiration through the 9 years. The interactions demonstrated that N addition weakened the precipitation-induced stimulation of soil respiration, whereas increased precipitation exacerbated the negative impacts of N addition. The main effects of increased precipitation and N addition treatment on soil respiration were 15.8% stimulated and 14.2% suppressed, respectively. Moreover, a declining pattern and 2-year oscillation were observed for soil respiration response to N addition under increased precipitation. The dependence of soil respiration upon gross primary productivity and soil moisture, but not soil temperature, suggests that resources C substrate supply and water availability are more important than temperature in regulating interannual variations of soil C release in semiarid grassland ecosystems. The findings indicate that atmospheric N deposition may have the potential to mitigate soil C loss induced by increased precipitation, and highlight that long-term and multi-factor global change studies are critical for predicting the general patterns of terrestrial C cycling in response to global change in the future

Effects of tree trunks on estimation of clumping index and LAI from HemiView and terrestrial LiDAR

Estimating clumping indices is important for determining the leaf area index (LAI) of forest canopies. The spatial distribution of the clumping index is vital for LAI estimation. However, the neglect of woody tissue can result in biased clumping index estimates when indirectly deriving them from the gap probability and LAI observations. It is difficult to effectively and automatically extract woody tissue from digital hemispherical photos. In this study, a method for the automatic detection of trunks from Terrestrial Laser Scanning (TLS) data was used. Between-crown and within-crown gaps from TLS data were separated to calculate the clumping index. Subsequently, we analyzed the gap probability, clumping index, and LAI estimates based on TLS and HemiView data in consideration of woody tissue (trunks). Although the clumping index estimated from TLS had better agreement (R-2 = 0.761) than that from HemiView, the change of angular distribution of the clumping index affected by the trunks from TLS data was more obvious than with the HemiView data. Finally, the exclusion of the trunks led to a reduction in the average LAI by similar to 19.6% and 8.9%, respectively, for the two methods. These results also showed that the detection of woody tissue was more helpful for the estimation of clumping index distribution. Moreover, the angular distribution of the clumping index is more important for the LAI estimate than the average clumping index value. We concluded that woody tissue should be detected for the clumping index estimate from TLS data, and 3D information could be used for estimating the angular distribution of the clumping index, which is essential for highly accurate LAI field measurements

Limited driving of elevated CO2 on vegetation greening over global drylands

Drylands are the world's largest biome and dominate the trends and interannual variability of global carbon sinks. Although a 'greening' trend of global drylands has been widely reported, large uncertainties remain in attributing its drivers. It is increasingly emphasized that elevated CO2 has greatly contributed to the vegetation greening over global drylands. Here we quantified the contributions of climate change, elevated CO2, and land use and land cover change (LULCC) on leaf area index (LAI) over drylands, using a process-based land surface model Noah-MP to investigate the drivers of vegetation change. The state-of-the-art model shows better performance in simulating the interannual variability of satellite-observed LAI over global drylands compared with that of the multi-model ensemble mean LAI from the TRENDY results. The area that LAI changes dominated by climate change (44.03%) is three times greater than that by CO2 (13.89%), and climate change also contributes most to the global drylands greening trend (55.07%). LULCC shows regional dominance over 13.35% of the global drylands, which is associated with afforestation, woody plant encroachment, and agricultural intensification. Our results imply that the vegetation greening area driven by elevated CO2 is much limited relative to the overwhelming climatic driving, which should be considered in predictions of trends and interannual variations of global carbon sinks

Topological Embedding Feature Based Resource Allocation in Network Virtualization

Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network's nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works

Hazard-evaluation-oriented moving horizon parallel steering control for driver-automation collaboration during automated driving

Prompted by emerging developments in connected and automated vehicles, parallel steering control, one aspect of parallel driving, has become highly important for intelligent vehicles for easing the burden and ensuring the safety of human drivers. This paper presents a parallel steering control framework for an intelligent vehicle using moving horizon optimization. The framework considers lateral stability, collision avoidance and actuator saturation and describes them as constraints, which can blend the operation of a human driver and a parallel steering controller effectively. Moreover, the road hazard and the steering operation error are employed to evaluate the operational hazardous of an intelligent vehicle. Under the hazard evaluation, the intelligent vehicle will be mainly operated by the human driver when the vehicle operates in a safe and stable manner. The automated steering driving objective will play an active role and regulate the steering operations of the intelligent vehicle based on the hazard evaluation. To verify the effectiveness of the proposed hazard-evaluation-oriented moving horizon parallel steering control approach, various validations are conducted, and the results are compared with a parallel steering scheme that does not consider automated driving situations. The results illustrate that the proposed parallel steering controller achieves acceptable performance under both conventional conditions and hazardous conditions