Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m³.     

Hydrogen-rich gas generation via the exhaust gas-fuel reformer for the marine LNG engine

Reformed exhaust gas recirculation technology has attracted great attention in internal combustion engines. A platform of an exhaust gas-fuel reformer connected with the marine LNG engine was set up for generating on-board hydrogen. Based on the platform, effects of the methane to oxygen ratio (M/O) and reformed exhaust gas ratio (R_EG) from the reformer and excess air ratio (λ) from the engine on the components, hydrogen yield, thermal efficiency and reforming process of the reformer were experimentally investigated. Results shown that hydrogen-rich gases (reformate) can be generated by reforming the mixture of engine exhaust gas (about 400 °C) and methane supplied via the reformer with Ni/Al₂O₃ catalyst, and the hydrogen concentration of reformate was between 6.2% and 12.6% by volume. The methane supplied rate and λ affected the components and temperature of the reactant in the reformer, while R_EG changed the gas hour space velocity during the exhaust gas-fuel reforming processes, resulting in the difference in the components of the reformate and thermal efficiency. At the present experimental condition, the highest H₂ concentration reformate was generated under the M/O of 2.0, λ of 1.55 and R_EG of 6%.     

Use of La2O3 with 8YSZ as thermal barrier coating and its effect on thermal cycle behavior,microstructure, mechanical properties and performance of diesel engine operated by hydrogen-algae biodiesel blend

In this present work, the effect of lanthanum oxides (La₂O₃) on the thermal cycle behavior of TBC coatings and mechanical properties such as adhesion strength and microhardness of 8% Yttria Stabilized Zirconia (8YSZ) TBCs were investigated. CoNiCrAlY and aluminium alloy (Al–13%Si) were used as bond coat and substrate materials. 8YSZ and different wt % of La₂O₃ (10, 20, and 30%) top coatings were applied using the atmospheric plasma spray (APS) method. The thermal cycling test for TBC coated samples were conducted at 800 °C in the electric furnace. The XRD pattern shows that the La₂O₃ doped 8YSZ material transformed to cubic pyrochloric structured La₂Zr₂O₇ during thermal cycling. Further, the Taguchi-based grey relation analysis (GRA) method was applied to optimize the TBC coating parameters to achieve better mechanical properties such as adhesion strength and microhardness. And the optimized La₂O₃/8YSZ TBC coating was coated on CRDI engine combustion chamber components. The engine was tested with microalgae biodiesel and hydrogen, and the results were promising for the TBC-coated engine. The engine performance increased while using La₂O₃/8YSZ coated components, and the emissions from engine exhaust gas such as CO, HC, and smoke reduced considerably. It was found that there was no separation crack and spallation of the coating layer in the microstructure. Ultimately, the microstructural analysis of the optimized TBC coated piston sample after 50 h of running in the diesel engine confirmed that the developed coating had a superior thermal insulation effect and longer life.     

基于等压差水膜的柴油机尾气净化装置研究

开发设计了一款新型尾气颗粒物过滤净化装置,该装置利用颗粒物惯性作用和水膜吸附效应实现颗粒物与柴油机尾气的分离。通过分析计算得到形成湿润壁面连续水膜的条件。选择合适的波形板面,搭建柴油机尾气颗粒物检测系统。试验结果表明,设计的柴油机尾气颗粒净化装置可以起到很好地净化颗粒物的作用,尤其是在柴油机刚刚启动低速运转的情况下净化效率高。     

A Comprehensive Review of Genetically Engineered Mouse Models for Prader-Willi Syndrome Research

Prader-Willi syndrome (PWS) is a neurogenetic multifactorial disorder caused by the deletion or inactivation of paternally imprinted genes on human chromosome 15q11-q13. The affected homologous locus is on mouse chromosome 7C. The positional conservation and organization of genes including the imprinting pattern between mice and men implies similar physiological functions of this locus. Therefore, considerable efforts to recreate the pathogenesis of PWS have been accomplished in mouse models. We provide a summary of different mouse models that were generated for the analysis of PWS and discuss their impact on our current understanding of corresponding genes, their putative functions and the pathogenesis of PWS. Murine models of PWS unveiled the contribution of each affected gene to this multi-facetted disease, and also enabled the establishment of the minimal critical genomic region (PWScr) responsible for core symptoms, highlighting the importance of non-protein coding genes in the PWS locus. Although the underlying disease-causing mechanisms of PWS remain widely unresolved and existing mouse models do not fully capture the entire spectrum of the human PWS disorder, continuous improvements of genetically engineered mouse models have proven to be very powerful and valuable tools in PWS research.     

PA6B柴油机进排气阀断裂原因分析

针对PA6B柴油机进排气阀断裂故障,根据现场勘验情况并结合该柴油机当时的热工参数,建立相应的故障树;对制造质量、装配质量、配气定时、异物进入、热工参数等因素进行逐一排查。结果表明:导致PA6B柴油机进排气阀断裂的原因为喷油器制造质量存在问题。     

“电网一张图”时空信息管理系统

文章首先总结了电力企业信息管理系统的现状,提出了多源信息管理系统融合集成的邦联、子集和完全融合3种方式,分析了3种方式的优缺点,以建设企业"互联网搜索"型数字引擎为目标,提出了融合基于本体的图数据库建模,多维关联与路径因果分析,和人机共生互动可视化决策于一体的企业信息管理系统技术发展趋势;在系统分析目前正在快速发展的图数据库技术与传统关系数据库之间的本质区别基础上,总结原创的电力图计算平台技术的特点;在此基础上讨论"电网一张图"在建设能源互联网时空信息管理平台数据关联索引图中的核心作用,提出了支持能源互联网建设的"电网一张图"时空信息管理系统的技术架构与特点,最后总结"电网一张图"时空信息管理系统在提高电网安全运行水平、提升客户服务水平、增强清洁能源消纳水平、改善经营绩效水平、以及为综合能源服务和建设能源生态等提供数据服务方面的广阔应用场景。     

某船用柴油机排气管路流-固耦合计算与保温效果研究

对某船用柴油机排气管路的流动与传热过程开展流-固耦合仿真分析。结果表明:受排气管路结构影响，管内流动方向和流速发生变化，局部区域产生明显的回流现象；排气管路外表面温度分布差异较大，平均温度高达534 ℃。为达到柴油机安全设计要求，在排气管路外壁敷设保温材料。分析结果表明:气凝胶纳米材料的保温效果优于硅酸铝纤维材料，在相同的运行条件和使用要求下，气凝胶纳米材料的敷设厚度更薄。     

某型发动机自反馈调节阀动态仿真分析

基于FLUENT软件提供的计算方法和物理模型，利用动网格技术及用户自定义函数（User-define Function，UDF），对发动机预燃室调节阀的自反馈调节过程进行动态数值模拟，并分析阻尼参数对调节效果的影响。结果表明：自反馈机构可实现对不同压力扰动的及时响应，具有稳定流量的效果，改变阻尼参数可对调节响应速度和流量稳定性进行优化，其中摩擦力对调节影响最显著。     

Exploiting Bayesian networks for fault isolation: A diagnostic case study of diesel fuel injection system

Fault isolation is known to be a challenging problem in machinery troubleshooting. It is not only because the isolation of multiple faults contains considerable number of uncertainties due to the strong correlation and coupling between different faults, but often massive prior knowledge is needed as well. This paper presents a Bayesian network-based approach for fault isolation in the presence of the uncertainties. Various faults and symptoms are parameterized using state variables, or the so-called nodes in Bayesian networks (BNs). Probabilistically causality between a fault and a symptom and its quantization are described respectively by a directed edge and conditional probability. To reduce the qualitative and quantitative knowledge needed, particular considerations are given to the simplification of Bayesian networks structures and conditional probability expressions using rough sets and noisy-OR/MAX model, respectively. By adopting the simplified approach, symptoms under multiple-fault are decoupled into the ones under every single fault, while the quantity of the conditional probabilities is simplified into the linear form of the faults quantity. Prior knowledge needed in Bayesian network-based diagnostic model is reduced significantly, which decreases the complexity in establishing and applying this diagnosis model. The computational efficiency is improved accordingly in the simplified BN model, after eliminating the redundant symptoms. The fault isolation methodology is illustrated through an example of diesel engine fuel injection system to verify the developed model.