折臂式随车起重机转台的拓扑优化设计

为了使折臂式随车起重机转台在最大应力不超过材料许用应力的前提下实现轻量化设计的目的,通过ADAMS软件仿真确定其极限工况,对转台进行静力学分析及拓扑优化。通过拓扑优化得到了理想的材料分布。基于优化结果调整转台结构,并对改进后的转台进行静力学分析。结果表明,优化后的转台能够满足实际的使用需求。同时,转台质量降低了12%,证明了优化设计的有效性和可行性,并为折臂式随车起重机的相关设计提供了一定的借鉴。     

三种硫化氢吸收剂吸收效率对比及碘酸钾体系吸收条件优化研究

硫化氢具有腐蚀性与毒性，采用吸收剂吸收硫化氢气体是重要的脱硫处理方式。不同的吸收剂在吸收效率上存在较大差别。首先对比了三氯化铁体系、碘酸钾体系和碱性铁氰化钾体系三种不同硫化氢吸收剂的吸收效率。在此基础上重点优化了碘酸钾体系吸收条件参数，讨论了包含浓度、温度、pH、气体流量及时间等因素对硫化氢吸收效率的影响。并建立了四因素三水平正交试验研究较优吸收条件，得到正交试验优化吸收条件为：温度55℃，pH 6.01，硫化氢流量0.3 L·min^-1，吸收时间1 min，该条件下8%（质量）碘酸钾体系的三级吸收效率为51.56%。研究结果对硫化氢吸收处理提供了理论参考，也为间接电解法循环处理研究提供了支持。     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.     

Research on optimization design of PWR flow distribution device based on numerical simulation

ABSTRACT

In the lower chamber of pressurized water reactor (PWR), the flow distribution device is the core module to distribute coolant into the core. It has complex structure and numerous design parameters. Therefore, it has important theoretical and practical significance to optimize the device. The mesh independence verification, turbulence model selection, and data processing all can influence the numerical simulation results of the lower chamber, in order to research the influence, a numerical simulation method based on the original model of CNP1000 reactor lower chamber is proposed in this paper. In the method, an optimization design method of flow distribution device is established based on surrogate model. The main design variables and optimization objectives are determined based on the device’s structure and function characteristics. And then it respectively adopts Kriging algorithm and multi-objective genetic algorithm to establish a surrogate model of flow distribution device and optimize it globally. Finally, the optimal design variables are obtained. Compared with the device’s performance before optimization, the after optimization has smaller total pressure loss and more uniform flow. The effectiveness and practicability of proposed optimization design method can be verified.     

Etching characteristics of thin SiON films using a liquefied perfluorocarbon precursor of C6F12O with a low global warming potential

Perfluorocarbon gas is widely used in the semiconductor industry. However, perfluorocarbon has a negative effect on the global environment owing to its high global warming potential (GWP) value. An alternative solution is essential. Therefore, we evaluated the possibility of replacing conventional perfluorocarbon etching gases such as CHF₃ with C₆F₁₂O, which has a low GWP and is in a liquid state at room temperature. In this study, silicon oxynitride (SiON) films were plasma-etched using inductively coupled CF₄ +C₆F₁₂O+O₂ mixed plasmas. Subsequently, the etching characteristics of the film, such as etching rate, etching profile, selectivity over Si, and photoresist, were investigated. A double Langmuir probe was used and optical emission spectroscopy was performed for plasma diagnostics. In addition, a contact angle goniometer and x-ray photoelectron spectroscope were used to confirm the change in the surface properties of the etched SiON film surface. Consequently, the etching characteristics of the C₆F₁₂O mixed plasma exhibited a lower etching rate, higher SiON/Si selectivity, lower plasma damage, and more vertical etched profiles than the conventional CHF₃ mixed plasma. In addition, the C₆F₁₂O gas can be recovered in the liquid state, thereby decreasing global warming. These results confirmed that the C₆F₁₂O precursor can sufficiently replace the conventional etching gas.     

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition-based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters.     

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.     

Theoretical framework for formulating MIP scheduling models with multiple and non-uniform discrete-time grids

We present a framework for the formulation of MIP scheduling models based on multiple and nonuniform discrete time grids. In a previous work we showed that it is possible to use different (possibly non-uniform) time grids for each task, unit, and material. Here, we generalize these ideas to account for general resources, and a range of processing characteristics such as limited intermediate storage and changeovers. Each resource has its own grid based on resource consumption and availability allowing resource constraints to be modeled more accurately without increasing the number of binary variables. We develop algorithms to define the unit-, task-, material-, and resource-specific grids directly from problem data. Importantly, we prove that the multi-grid formulation is able to find a schedule with the same optimal objective as the discrete-time single-grid model with an arbitrarily fine grid. The proposed framework leads to the formulation of models with reduced number of binary variables and constraints, which are able to find good solutions faster than existing models.     

Sustainable ammonia production through process synthesis and global optimization

Current ammonia production technologies have a significant carbon footprint. In this study, we present a process synthesis and global optimization framework to discover the efficient utilization of renewable resources in ammonia production. Competing technologies are incorporated in a process superstructure where biomass, wind, and solar routes are compared with the natural gas-based reference case. A deterministic global optimization-based branch-and-bound algorithm is used to solve the resulting large-scale nonconvex mixed-integer nonlinear programming problem (MINLP). Case studies for Texas, California, and Iowa are conducted to examine the effects of different feedstock prices and availabilities. Results indicate that profitability of ammonia production is highly sensitive to feedstock and electricity prices, as well as greenhouse gas (GHG) restrictions. Under strict 75% GHG reductions, biomass to ammonia route is found to be competitive with natural gas route, whereas wind and solar to ammonia routes require further improvement to compete with those two routes. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16498 2019     

On the performance of improved quadrature spatial modulation

Quadrature spatial modulation (QSM) utilizes the in‐phase and quadrature spatial dimensions to transmit the real and imaginary parts of a single signal symbol, respectively. The improved QSM (IQSM) transmits two signal symbols per channel use through a combination of two antennas for each of the real and imaginary parts. The main contributions of this study can be summarized as follows. First, we derive an upper bound for the error performance of the IQSM. We then design constellation sets that minimize the error performance of the IQSM for several system configurations. Second, we propose a double QSM (DQSM) that transmits the real and imaginary parts of two signal symbols through any available transmit antennas. Finally, we propose a parallel IQSM (PIQSM) that splits the antenna set into equal subsets and performs IQSM within each subset using the same two signal symbols. Simulation results demonstrate that the proposed constellations significantly outperform conventional constellations. Additionally, DQSM and PIQSM provide a performance similar to that of IQSM while requiring a smaller number of transmit antennas and outperform IQSM with the same number of transmit antennas.