Utilization of pyrolytic oil and hydrogen enriched syngas from single feedstock (delonix regia) through pyrolysis process and its influence on performance and emission characteristics in CI engine

The main objective of the present investigation is to conduct the performance, combustion and emission analysis of CI engine operated using hydrogen enriched syngas (pyrolytic gas) and biodiesel (pyrolytic oil) as dual fuel mode condition. Both the pyrolytic oil and syngas is obtained from single feedstock delonix regia fruit pod through pyrolysis process and then pyrolytic oil is converted into biodiesel through esterification. Initially biomass is subjected to thermal degradation at various pyrolysis temperature ranges like 350–600 °C. During the pyrolysis process syngas, pyrolytic oil and char are produced. The syngas is directly used in the CI engine and pyrolytic oil is converted into biodiesel and then used in the CI engine. The pyrolytic oil and syngas is subjected to FTIR and GC/TCD analysis respectively. The syngas analysis confirms the presence of various gases like H₂, CH₄, CO₂, CO and C₂H₄ in different proportions. The various proportions of the syngas is mainly depending upon the reactor temperature and moisture content in the biomass. The syngas composition varies with increase in the temperature and at 400 °C, higher amount of hydrogen is present and its composition are H₂ 28.2%, CO is 21.9%, CH₄ is 39.1% and other gases in smaller amounts. The biodiesel of B20 and syngas of 8lpm produced from the same feedstock are considered as test sample fuels in the CI engine under dual fuel mode operation to study the performance and emission characteristics. The study reveals that BTE has slight increase than diesel of 1.5% at maximum load. On the another hand emission like CO, HC and smoke are reduced by 15%,25% and 32% respectively at full load condition, whereas NO_x emission is increased at all loads in the range of 10–15%. Therefore B20+syngas of 8lpm can be used as an alternative fuel in CI engine without any modification and major products from pyrolysis process with waste biomass is fully used as fuel in the CI engine.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

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.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Phase constitution,microstructure and mechanical properties of a Ni-based superalloy specially designed for additive manufacturing

In this study, a kind of Ni-based superalloy specially designed for additive manufacturing (AM) was investigated. Thermo-Calc simulation and differential scanning calorimetry (DSC) analysis were used to determine phases and their transformation temperature. Experimental specimens were prepared by laser metal deposition (LMD) and traditional casting method. Microstructure, phase constitution and mechanical properties of the alloy were characterized by scanning electron microscopy (SEM), transmission scanning electron microscopy (TEM), X-ray diffraction (XRD) and tensile tests. The results show that this alloy contains two basic phases, γ/γ', in addition to these phases, at least two secondary phases may be present, such as MC carbides and Laves phases. Furthermore, the as-deposited alloy has finer dendrite, its mean primary dendrite arm space (PDAS) is about 30-45 μm, and the average size of γ' particles is 100-150 nm. However, the dendrite size of the as-cast alloy is much larger and its PDAS is 300-500 μm with secondary and even third dendrite arms. Correspondingly, the alloy displays different tensile behavior with different processing methods, and the as-deposited specimen shows better ultimate tensile stress (1,085.7±51.7 MPa), yield stress (697±19.5 MPa) and elongation (25.8%±2.2%) than that of the as-cast specimen. The differences in mechanical properties of the alloy are due to the different morphology and size of dendrites, γ', and Laves phase, and the segregation of elements, etc. Such important information would be helpful for alloy application as well as new alloy development.     

基于蜻蜓翅脉结构的连续碳纤维增强树脂基复合材料仿生设计与增材制造

以具有轻质高强优异性能的蜻蜓翅脉结构为设计灵感，在分析翅脉网格结构抗冲击原理的基础上，设计了传统和仿生两类对比结构。采用熔融挤出3D打印机成功制备了具有不同结构的连续碳纤维增强聚乳酸复合材料试样，并对不同结构复合材料试样的拉伸性能和抗冲击性能进行了测试和对比分析。研究分析结果表明：由于拉伸力方向上的连续碳纤维含量相对较少，限制了仿生结构复合材料抗拉强度的提高，但仿生结构的平均抗拉强度为传统结构的1.18倍；当仿生结构复合材料试样受到冲击力时，其内部六边形结构的连接角度会发生变化，从而极大消耗冲击能量，同时具有六边形网格结构的连续碳纤维可以有效阻碍裂纹的扩展，因此仿生结构的平均冲击韧性可以达到传统结构的2.46倍；仿生蜻蜓翅脉结构可以显著提高增材制造复合材料的综合力学性能，且对于抗冲击性能的提高具体突出效果。连续碳纤维增强树脂基复合材料的有效可行的仿生蜻蜓翅脉结构设计和增材制造，可极大扩展其在高冲击载荷领域中的相应应用。     

增材制造技术在超高膨胀封隔器中的应用

石油和天然气行业不断关注增材制造技术在航空航天和汽车行业的应用发展。研发了利用增材制造技术的超高膨胀封隔器,该封隔器的支承环系统由增材制造。增材制造设计大幅减少了支承系统的构件数量,同时显著提高了膨胀能力和额定压力。密封元件系统与增材制造支承环安装在一起,提供了极端膨胀比、零挤压间隙和对不规则孔的良好适应性。分析和测试结果表明:直径膨胀比高达111%,与常规封隔器相比,提高50%以上; 至少涵盖5种线重的套管(外径相同); 在148.89 ℃的温度下,密封元件能够保持压力68.95 MPa。介绍了增材制造技术、增材制造支承环概念、增材制造材料力学性能、密封元件系统优化和测试情况,以期给我国的完井作业提供借鉴。     

Annual and regional variations of aflatoxin B1 levels seen in grains and feed coming from Croatian dairy farms over a 5-year period

The aim of the study was to investigate annual and regional differences in the level of aflatoxin B₁ (AFB₁) in grains and dairy cattle feed. Maize (n = 972), wheat (n = 201), barley (n = 147), oat (n = 136), grain mixtures (n = 168), and dairy cattle feed (n = 325) were sampled from 2009 to 2013 on different farms and in different farm factories situated in four Croatian regions. The samples were analysed for AFB₁ using the validated ELISA immunoassay. AFB₁ was determined in 16.4% of all investigated samples, among which maize was proven to be the most contaminated, with 21.7% of the samples recovered during 2013 harbouring AFB₁ in concentrations over the permissible ones. Levels higher than permitted were observed in 17.9% and 12.3% of grain mixtures and dairy cattle feed, respectively, whereas concentrations of AFB₁ determined in other crops throughout the investigated period met the stipulated requirements. The results revealed the AFB₁ occurrence to be significantly (p < 0.05) dependent on the cultivation region, with the highest levels generally found in maize harvested in 2013 and consequently in grain mixtures and cattle feed that can most likely be associated with climatic conditions as the most critical factor for mould formation, and thus also AFB₁ production.     

Simplified anode architecture for PEMFC systems based on alternative fuel feeding: Experimental characterization and optimization for automotive applications

The need to reduce PEMFC systems cost as well as to increase their durability is crucial for their integration in various applications and especially for transport applications. A new simplified architecture of the anode circuit called Alternating Fuel Feeding (AFF) offers to reduce the development costs. Requiring a new stack concept, it combines the simplicity of Dead-End Anode (DEA) with the operation advantages of the hydrogen recirculation. The three architectures (DEA, recirculation and AFF) are compared in terms of performance on a 5-kW test bench in automotive conditions, through a sensitivity analysis. A gain of 17% on the system efficiency is observed when switching from DEA to AFF. Moreover, similar performances are obtained both for AFF and for recirculation after an accurate optimization of the AFF tuning parameters. Based on DoE data, a gain of 25% on the weight of the anodic line has been identified compared to pulsed ejector architecture and 43% with the classic recirculation architecture with blower only (Miraï).