Numerical approach to analyze fluid flow in a type C tank for liquefied hydrogen carrier (part 1: Sloshing flow)

The demand for clean energy use has been increasing worldwide, and hydrogen has attracted attention as an alternative energy source. The efficient transport of hydrogen must be established such that hydrogen may be used as an energy source. In this study, we considered the influences of various parameters in the transportation of liquefied hydrogen using type C tanks in shipping vessels. The sloshing and thermal flows were considered in the transportation of liquefied hydrogen, which exists as a cryogenic liquid at ?253 °C. In this study, the sloshing flow was analyzed using a numerical approach. A multiphase sloshing simulation was performed using the volume of fluid method for the observation and analysis of the internal flow. First, a sloshing experiment according to the gas-liquid density ratio performed by other researchers was utilized to verify the simulation technique and investigate the characteristics of liquefied hydrogen. Based on the results of this experiment, a sloshing simulation was then performed for a type C cargo tank for liquefied hydrogen carriers under three different filling level conditions. The sloshing impact pressure inside of the tank was measured via simulation and subjected to statistical analysis. In addition, the influence of sloshing flow on the appendages installed inside of the type C tank (stiffened ring and swash bulkhead) was quantitatively evaluated. In particular, the influence of the sloshing flow inside of the type C tank on the appendages can be utilized as an important indicator at the design stage. Furthermore, if such sloshing impact forces are repeatedly experienced over an extended period of time under cryogenic conditions, the behavior of the tank and appendages must be analyzed in terms of fatigue and brittle failure to ensure the safety of the transportation operation.     

基于误差估值累加开环校正的诱导式欺骗检测方法

诱导式卫星欺骗干扰可诱导航空器逐渐偏离预定航迹，难以被发现，因此及时有效地检测干扰是飞行安全的保障。在现有紧组合导航体制基础上，设计了一种基于误差估值累加开环校正的紧组合导航结构，并证明了其性能与传统闭环校正紧组合导航性能等效。在此结构中，将紧组合导航系统与自适应序贯概率比检测方法结合，提出了一种基于误差估值累加开环校正的诱导式欺骗检测方法，融合紧组合导航信息与其他不受欺骗影响的导航信息，构建欺骗检测统计量进行诱导式欺骗检测。仿真结果表明，开环校正结构可避免随时间累加的惯性导航系统误差所导致的组合导航滤波器发散问题，同时欺骗检测方法可进一步提高算法对“最坏”情形下微小诱导式欺骗的检测效果。     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Transition from random packing to stable state in a continuously avalanching granular flow

We investigate the transition evolution from the initial state with the random packing of the particles to the stable state in which successive avalanches exhibit consistent characteristics under the slumping regime. It is found that there exist three distinct stages in the transition evolution, considering the change of the volume fraction. The coordination number is almost unchanged during the transition evolution, which indicates the particle contact form is consistent in the three stages. The pause phenomena are discovered in some avalanches, and the probability of pause occurrence increases continuously in the three consecutive stages. We also explore the distribution of particles in the passive layer at the stable state. The particles in the middle region of the passive layer have the closest packing status, and the deeper the region is located, the later it reaches the stable state.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Revealing cracking and breakage behaviours of gibbsite particles

Mitigating gibbsite particle cracking and breakage during industrial alumina production can increase the quality of smelter grade alumina product by reducing the ultrafine particle content. Therefore, it is essential to investigate the particle cracking during static calcination and the breakage of calcined gibbsite particles under external force. In this work, we investigated the impact of the calcination ramping rate and the crystallite size on gibbsite particle cracking during static calcination. A slow ramping rate and a large pristine crystallite size tend to increase particle cracking. Apart from the study of particle cracking behaviour, we also investigated the breakage of calcined gibbsite particle under external force. Cracks on the particle surface can initiate breakage within the crystallite and along the grain boundary under external force. The breakage within crystallite occurs as the cleavage of the crystallite, while the breakage along the grain boundary leads to the shedding of a whole crystallite. We further explored the factors influencing the strength of calcined gibbsite particles. With increasing calcination temperature, the strength of particle increases when gibbsite converts to boehmite, and then decreases when boehmite converts into amorphous alumina. Particles containing smaller crystallites and calcined with fast ramping rates exhibit higher resistance to breakage.     

Adaptive GLR-, Rao- and Wald-based CFAR detectors for a subspace signal embedded in structured Gaussian interference

The problem of detecting a subspace signal embedded in subspace Gaussian interference and thermal noise is studied in this paper. In this problem, both the signal-independent and signal-dependent interferences are assumed to be present, therefore the overall interference subspace covers the signal subspace. The approach of this paper extends previous works involving either of those two kinds of interferences. A set of secondary data containing only interference plus noise is employed to estimate the interference covariance matrix and the noise power. Three new detectors are designed via the generalized likelihood ratio (GLR), Rao and Wald tests, respectively. Their probabilities of false alarms (PFAs) and detections are analytically derived. The PFAs show that the new detectors have the constant false alarm rate (CFAR) property against the interference and noise. Numerical results show that the new detectors outperform their counterparts for the studied problem. Furthermore, the new detectors are less sensitive to the secondary data size and to the mismatched subspace signal than some other detectors, such as the GLR detector (GLRD), the adaptive matched filter (AMF), the adaptive subspace detector (ASD), etc.     

Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.