Fatigue behavior and damage evolution of SiC/SiC composites under high-temperature anaerobic cyclic loading

In the present study, the fatigue behavior and damage evolution of SiC/SiC minicomposites at elevated temperatures in oxygen-free environment are investigated which are important for their application and are still unclear. The high-temperature fatigue test platform is developed and the fatigue stress-life curve and the stress-strain response are obtained. The test result shows that the life of the material at elevated temperature is shorter than that at room temperature under the same stress level. Moreover, the hysteresis loop width and the residual strain increase with the increasing of the cycles while the hysteresis modulus decreases during the fatigue cycling. The evolution process of matrix cracks is observed using the real-time remote detection system. It is found that matrix cracking is insensitive to the cyclic loading which is similar to room temperature and is due to that the degeneration of the interfacial shear stress reduces the area of high stress in matrix. The fiber/matrix interfacial shear stress under different cycles is determined based on the fatigue modulus of each hysteresis loop. The result shows a fatigue enhancement phenomenon for the interface which is not observed at room temperature.     

Research on Circular Area Search algorithm of multi-robot service based on SOA cloud platform

Considering autonomous mobile robots with a variety of specific functions as a kind of service, when there are many types and quantities of services and the density of regional services is large, proposing an algorithm of Circular Area Search (CAS) because of the problem of multi-robot service scheduling in various areas. Firstly, Django is used as the web framework to build the Service-Oriented Architecture (SOA) multi-robot service cloud platform, which is the basic platform for multi-service combination. Then, the service type, the latitude and longitude and the scoring parameters of the service are selected as the service search metrics to design the CAS algorithm that based on the existing service information registered in MySQL and the Gaode Map for screening optimal service, and then providing the service applicant with the best service. Finally, the service applicant applies for the self-driving tour service as an example to perform performance simulation test on the proposed CAS algorithm. The results show that the CAS algorithm of the multi-robot service cloud platform proposed in this paper is practical compared to the global search. And compared with the Greedy Algorithm experiment, the service search time is reduced about 58% compared with the Greedy Algorithm, which verifies the efficiency of CAS algorithm.     

Recent advancement and prospective of waste plastics as biodiesel additives: A review

Recently, commodity plastics have been shown to be a promising additive to improve the fuel properties of biodiesel, which offers a promising solution to the plastic pandemic. As many environmental and societal issues arise from plastic pollution, repurposing technologies are paramount in order to meet Sustainable Development Goals (SDG). A potentially cost-effective approach can be achieved by using waste plastics as biodiesel additives – resonating to the expression ‘to kill two birds with one stone’. However, given the novelty of such investigation, current optimization studies show varying results on the ideal plastic-to-biodiesel ratio as well as the reaction parameters. The difficulty in determining the exact optimum values is due to the many variations of biodiesel properties and the complex behaviour of plastic polymers, which are seldom discussed in review papers. Hence, to address the literature gap, this paper offers the necessary fundamentals of biodiesel and plastic dissolution; facilitating future researches to advance the application of plastics as viable biodiesel additives. Accordingly, the topics covered include the fuel and solvent properties of biodiesel related to its' composition, as well as the polymer dissolution phenomena. Finally, as the focal aim of the paper, a synopsis on the recent advancement of plastic-added biodiesel is presented; in particular, those that are related to the blend characteristics, fuel properties, combustion quality, and environmental impact.     

MIMO-GFDM系统中低复杂度动态禁忌搜索检测算法的改进

针对多输入多输出的广义频分复用（MIMO-GFDM）系统的等效信道矩阵维度极大，传统的MIMO检测算法复杂度高且性能不佳的问题，将大规模MIMO系统中的动态禁忌搜索（RTS）检测算法运用到MIMO-GFDM系统中，并解决了RTS算法初始值的求解复杂度高的问题。首先利用最小均方误差（MMSE）检测算法所用到矩阵的正定对称性将矩阵Cholesky分解，并结合Sherman-Morrison公式迭代计算初始值，降低了初始值求逆的高复杂度；然后以改进的MMSE检测结果作为RTS算法的初始值，从初始值逐步全局搜索最优解；最后通过仿真，对不同算法的迭代次数和误码率（BER）性能进行了研究。理论分析与仿真结果表明：在MIMO-GFDM中，所提改进RTS信号检测算法误码率远低于传统信号检测算法。在4QAM时，RTS算法大约有低于MMSE检测6 dB的信噪比性能增益（误码率在10^-3时）；在16QAM时，RTS算法大约有低于MMSE检测4 dB的信噪比性能增益（误码率在10^-2时）。与传统RTS算法性相比，所提改进算法在不影响误码率性能的同时降低了算法复杂度。     

基于深度概率图模型的鲁棒人脸画像合成

针对基于数据驱动的人脸画像合成算法像素特征缺乏对光照变化和复杂背景的鲁棒性,常合成低质量的画像的问题,文中提出基于深度概率图模型的鲁棒人脸画像合成算法.采用预处理方法调整测试照片的光照亮度和人脸姿态,使之与训练照片一致.采用深度特征代替像素特征进行近邻匹配,采用深度概率图模型对画像重建权重和深度特征权重联合建模,得到合成画像的最佳重构表示.为了提高画像合成速度,提出快速近邻搜索方法.实验验证文中算法的鲁棒性和快速性.     

Multi-Input Single Output SSSC based damping controller design by a hybrid Improved Differential Evolution-Pattern Search approach

In this paper, a hybrid Improved Differential Evolution and Pattern Search (hIDEPS) approach is proposed for the design of a PI-Type Multi-Input Single Output (MISO) Static Synchronous Series Compensator (SSSC) based damping controller. The improvement in Differential Evolution (DE) algorithm is introduced by a simple but effective scheme of changing two of its most important control parameters i.e. step size and crossover probability with an objective of achieving improved performance. Pattern Search (PS) is subsequently employed to fine tune the best solution provided by modified DE algorithm. The superiority of a proposed hIDEPS technique over DE and improved DE has also been demonstrated. At the outset, this concept is applied to a SSSC connected in a Single Machine Infinite Bus (SMIB) power system and then extended to a multi-machine power system. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with DE and Particle Swarm Optimization (PSO) optimized Single Input Single Output (SISO) SSSC based damping controllers. It is observed that the proposed approach yield superior damping performance compared to some approaches available in the literature.     

Top-k-size keyword search on tree structured data

Keyword search is the most popular technique for querying large tree-structured datasets, often of unknown structure, in the web. Recent keyword search approaches return lowest common ancestors (LCAs) of the keyword matches ranked with respect to their relevance to the keyword query. A major challenge of a ranking approach is the efficiency of its algorithms as the number of keywords and the size and complexity of the data increase. To face this challenge most of the known approaches restrict their ranking to a subset of the LCAs (e.g., SLCAs, ELCAs), missing relevant results.In this work, we design novel top-k-size stack-based algorithms on tree-structured data. Our algorithms implement ranking semantics for keyword queries which is based on the concept of LCA size. Similar to metric selection in information retrieval, LCA size reflects the proximity of keyword matches in the data tree. This semantics does not rank a predefined subset of LCAs and through a layered presentation of results, it demonstrates improved effectiveness compared to previous relevant approaches. To address performance challenges our algorithms exploit a lattice of the partitions of the keyword set, which empowers a linear time performance. This result is obtained without the support of auxiliary precomputed data structures. An extensive experimental study on various and large datasets confirms the theoretical analysis. The results show that, in contrast to other approaches, our algorithms scale smoothly when the size of the dataset and the number of keywords increase.     

Performance indices of a common rail-system CI engine powered by diesel oil and biofuel blends

Conventional fuels used for supplying internal combustion piston engines include petrols and diesel oils produced from petroleum. These are a non-renewable energy source. The environmental policy of the European Union is geared towards increasing the share of renewable fuels in the overall energy consumption. An alternative fuel originating from a renewable source, which could be used for feeding self-ignition internal combustion engines are the fatty acid methyl esters (FAME) of plant oils. The paper reports selected results of testing a 1.3 MULTIJET SDE 90 PS self-ignition engine with the Common Rail reservoir feed system supplied with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME). Tests were carried out on an engine test bed equipped with an eddy-current brake. The purpose of the tests was to determine the economic–energy and ecological indices of engine operation. The concentrations of exhaust gas gaseous components were measured using a MEXA-1600DEGR analyzer, while the particulate concentrations, with a MEXA-1230PM analyzer. In addition, the variations of working medium pressures in the engine chamber and of fuel pressure upstream the injector were recorded as a function of crankshaft rotation angle using the AVL IndiSmart 612 indication system for this purpose. The physicochemical properties of fuels used in the tests were determined using a fuel analyzer. The obtained testing results made it possible to determine and assess the operation indices of the engine fed with mixtures of diesel oil and rape oil fatty acid methyl esters (FAME) with slightly higher ester contents than the requirements of the currently applicable diesel oil standard.     

Experimental investigations on the effect of fuel injection parameters on diesel engine fuelled with biodiesel blend in diesel with hydrogen enrichment

Fuel injection pressure and injection timing are two extensive injection parameters that affect engine performance, combustion, and emissions. This study aims to improve the performance, combustion, and emissions characteristics of a diesel engine by using karanja biodiesel with a flow rate of 10 L per minute (lpm) of enriched hydrogen. In addition, the research mainly focused on the use of biodiesel with hydrogen as an alternative to diesel fuel, which is in rapidly declining demand. The experiments were carried out at a constant speed of 1500 rpm on a single-cylinder, four-stroke, direct injection diesel engine. The experiments are carried out with variable fuel injection pressure of 220, 240, and 260 bar, and injection timings of 21, 23, and 25 °CA before top dead center (bTDC). Results show that karanja biodiesel with enriched hydrogen (KB20H10) increases BTE by 4% than diesel fuel at 240 bar injection pressure and 23° CA bTDC injection timing. For blend KB20H10, the emissions of UHC, CO, and smoke opacity are 33%, 16%, and 28.7% lower than for diesel. On the other hand NOx emissions, rises by 10.3%. The optimal injection parameters for blend KB20H10 were found to be 240 bar injection pressure and 23 °CA bTDC injection timing based on the significant improvement in performance, combustion, and reduction in exhaust emissions.     

Job Search Networks and Strategies in Scattered-site Public Housing

How does poverty dispersal influence the job search tactics and networks of poor women? Using the results of interviews with 253 women living in dispersed and small clusters of public housing, this paper examines how job networks and search tactics may vary. The premise is that the mechanisms involved in connecting poor residents of more affluent areas with opportunity may consist of both social connections and new strategies for accessing opportunity. The paper finds that dispersed residents have job networks containing more diverse information. Second, dispersed residents more often used formal methods to find their most recent job. Third, dispersed residents seek better jobs, net of demographic controls, search method, and search outcome. The paper discusses the implications of these findings for the design of housing mobility and mixed-income housing programmes, the current policy emphasis at the US Department of Housing and Urban Development.