Numerical simulation on flow of ice slurry in horizontal straight tubes was conducted in this paper to improve its transportation characteristics and application. This paper determined the influence of the diameter and length of tubes, the ice packing factors (IPF) and the flow velocity of ice slurry on pressure loss by using numerical simulation, based on two-phase flow and the granular dynamic theory. Furthermore, it was found that the deviation between the simulation results and experimental data could be reduced from 20% to 5% by adjusting the viscosity which was reflected by velocity. This confirmed the reliability of the simulation model. Thus, two mathematical correlations between viscosity and flow velocity were developed eventually. It could also be concluded that future rheological model of ice slurry should be considered in three sections clarified by the flow velocity, which determined the fundamental difference from single-phase fluid.

The autonomous exploration and mapping of an unknown environment is useful in a wide range of applications and thus holds great significance. Existing methods mostly use range sensors to generate two-dimensional (2D) grid maps. Red/green/blue-depth (RGB-D) sensors provide both color and depth information on the environment, thereby enabling the generation of a three-dimensional (3D) point cloud map that is intuitive for human perception. In this paper, we present a systematic approach with dual RGB-D sensors to achieve the autonomous exploration and mapping of an unknown indoor environment. With the synchronized and processed RGB-D data, location points were generated and a 3D point cloud map and 2D grid map were incrementally built. Next, the exploration was modeled as a partially observable Markov decision process. Partial map simulation and global frontier search methods were combined for autonomous exploration, and dynamic action constraints were utilized in motion control. In this way, the local optimum can be avoided and the exploration efficacy can be ensured. Experiments with single connected and multi-branched regions demonstrated the high robustness, efficiency, and superiority of the developed system and methods.

Ethylene production by the thermal cracking of naphtha is an energy-intensive process (up to 40 GJ heat per tonne ethylene), leading to significant formation of coke and nitrogen oxide (NO_x), along with 1.8–2 kg of carbon dioxide (CO₂) emission per kilogram of ethylene produced. We propose an alternative process for the redox oxy-cracking (ROC) of naphtha. In this two-step process, hydrogen (H₂) from naphtha cracking is selectively combusted by a redox catalyst with its lattice oxygen first. The redox catalyst is subsequently re-oxidized by air and releases heat, which is used to satisfy the heat requirement for the cracking reactions. This intensified process reduces parasitic energy consumption and CO₂ and NO_x emissions. Moreover, the formation of ethylene and propylene can be enhanced due to the selective combustion of H₂. In this study, the ROC process is simulated with ASPEN Plus® based on experimental data from recently developed redox catalysts. Compared with traditional naphtha cracking, the ROC process can provide up to 52% reduction in energy consumption and CO₂ emissions. The upstream section of the process consumes approximately 67% less energy while producing 28% more ethylene and propylene for every kilogram of naphtha feedstock.

Computer vision techniques, in conjunction with acquisition through remote cameras and unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure condition assessment. The ultimate goal of such a system is to automatically and robustly convert the image or video data into actionable information. This paper provides an overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment. In particular, relevant research in the fields of computer vision, machine learning, and structural engineering are presented. The work reviewed is classified into two types: inspection applications and monitoring applications. The inspection applications reviewed include identifying context such as structural components, characterizing local and global visible damage, and detecting changes from a reference image. The monitoring applications discussed include static measurement of strain and displacement, as well as dynamic measurement of displacement for modal analysis. Subsequently, some of the key challenges that persist towards the goal of automated vision-based civil infrastructure and monitoring are presented. The paper concludes with ongoing work aimed at addressing some of these stated challenges.

The internal flow field study of car compartments is an important step in railroad vehicle design and optimization. The flow field profile has a significant impact on the temperature distribution and passenger comfort level. Experimental studies on flow field can yield accurate results but carry a high time and computational cost. In contrast, the numerical simulation method can yield an internal flow field profile in less time than an experimental study. This study aims to improve the computational efficiency of numerical simulation by adapting two simplified models—the porous media model and the porous jump face model—to study the internal flow field of a railroad car compartment. The results provided by both simplified models are compared with the original numerical simulation model and with experimental data. Based on the results, the porous media model has a better agreement with the original model and with the experimental results. The flow field parameters (temperature and velocity) of the porous media model have relatively small numerical errors, with a maximum numerical error of 4.7%. The difference between the numerical results of the original model and those of the porous media model is less than 1%. By replacing the original numerical simulation model with the porous media model, the flow field of subway car compartments can be calculated with a reduction of about 25% in computing resources, while maintaining good accuracy.

To reveal the unsteady flow characteristics of a vaneless counter-rotating turbine (VCRT), a three-dimensional, viscous, unsteady computational fluid dynamics (CFD) analysis was performed. The results show that unsteady simulation is superior to steady simulation because more flow characteristics can be obtained. The unsteady effects in upstream airfoil rows are weaker than those in downstream airfoil rows in the VCRT. The static pressure distribution along the span in the pressure surface of a high pressure turbine stator is more uniform than that in the suction surface. The static pressure distributions along the span in the pressure surfaces and the suction surfaces of a high pressure turbine rotor and a low pressure turbine rotor are all uneven. The numerical results also indicate that the load of a high pressure turbine rotor will increase with the increase of the span. The deviation is very big between the direction of air flow at the outlet of a high pressure turbine rotor and the axial direction. A similar result can also be obtained in the outlet of a low pressure turbine rotor. This means that the specific work of a high pressure turbine rotor and a low pressure turbine rotor is big enough to reach the design objectives.

Lung cancer is among the most frequently diagnosed cancers worldwide and the leading cause of cancer death in both males and females. Screening for lung cancer coupled with earlier intervention has long been studied as an approach to mortality reduction. However, minimal progress was achieved until recently, when low-dose spiral computed tomography (LDCT) screening demonstrated a 20% reduction in mortality from lung cancer in a randomized controlled trial (RCT), the National Lung Screening Trial, from the United States. On the basis of this finding, LDCT has been recommended for lung cancer screening in high-risk populations by several clinical guidelines. However, results from the following independent RCTs in Europe failed to show consistent conclusions. In addition, intractable problems gradually emerged with the progress of LDCT screening. This paper summarizes and discusses the main observations and challenges of LDCT screening for lung cancer. Before spreading implementation of LDCT screening, challenges, including high false-positive rates, overdiagnosis, enormous costs, and radiation risk, must be addressed. Complementary biomarkers and technical improvement are expected in the field of lung cancer screening in the near future.

The main purpose of this research is to perform a magnetic analysis on the magnetic equipment of permanent magnet retarder (PMR) and optimize the structure of magnetic equipment with the commercial FEM software ANSYS and its design optimization module. The FEM model is built as an axisymmetric model according to the characteristics of the structure of magnetic equipment. Using this model, the magnetic field distribution and magnetic force are calculated by ANSYS. The mathematical model of structure optimization is also built. The design variables are structural parameters including the dimensions of permanent magnets and magnetic yoke, and the objective function is the magnetic force. The unconstrained optimization model takes the maximum value of magnetic force as the objective. A first-order optimization method is used to determine the optimum design of this problem. The optimization process works entirely with the ANSYS parametric design language (APDL). The design tools are used to understand design space and the behavior of the dependent variables. It is shown that designing a structure with the ANSYS optimization module and its design tools is an effective means to improve the structure.

This paper investigates the impact spreading of a droplet on a solid substrate using numerical simulation on the basis of a volume-of-fluid (VOF) model. The process of droplet spreading is described, the analysis of low speed and high speed droplet spreading, and more than one droplet spreading simultaneously is performed. The pressure, velocity, and spreading factor during the droplet spreading are reported. According to the spreading factor’s evolvement, the process of droplet spreading can be classified into spreading phase and recoiling phase. The spreading factors are almost the same at the low speed droplet spreading; however, the pressures on the substrate are quite different and air entrainment may be found as the impact speeds in a certain range. The impact speed impacts on the spreading factors in high speed droplet spreading. The spreading factor obviously increases with increasing impact speed; however, splashing will appear in the status when the speed is high enough in the high speed droplet spreading. The distance between the neighbor droplets affects the film’s quality, and only the distance between the static diameter and the maximum diameter can ensure the film’s quality. The results could help in understanding the process of droplet spreading and provide advice on the operation of a spray coating process.

This paper addresses the problem of a numerical evaluation of the stiffness performance for multibody robotic systems. An overview is presented with basic formulation concerning indices that are proposed in literature. New indices are also outlined. Stiffness indices are computed and compared for a case study. Results are used for comparing the effectiveness of the stiffness indices. The main goal is to propose a performance index describing synthetically the elastostatic response of a multibody robotic system and also for design purposes.