Physical characteristics of AFEX-pretreated and densified switchgrass,prairie cord grass,and corn stover

The goal of the study was to evaluate and compare the physical properties of control, pretreated and densified corn stover, switchgrass, and prairie cord grass samples. Ammonia Fiber Expansion (AFEX) pretreated switchgrass, corn stover, and prairie cord grass samples were densified by using the comPAKco device developed by Federal Machine Company of Fargo, ND. The densified biomass were referred as “PAKs” in this study. All feedstocks were ground into three different grind size of 2, 4 and 8 mm prior to AFEX pretreatment and the impact of grinding on pellet properties was studied. The results showed that the physical properties of AFEX-PAKed material were not influenced by the initial grind size of the feedstocks. The bulk density of the AFEX-PAKed biomass increased by 1.2–6 fold as compared to untreated and AFEX-pretreated materials. The durability of the AFEX-PAKed materials were between 78.25 and 95.2%, indicating that the AFEX-PAKed biomass can be transported easily. To understand the effect of storage on the physical properties of these materials, samples were stored in the ambient condition (20 ± 2 °C and 70 ± 5% relative humidity) for six months. After storage, thermal properties of the biomass did not change but glass transition temperature decreased. The water absorption index and water solubility index of AFEX-treated and AFEX-PAKed biomass showed mixed trends after storage. Moisture content decreased and durability increased upon storage.     

Impact behavior and fractographic study of carbon nanotubes grafted carbon fiber-reinforced epoxy matrix multi-scale hybrid composites

Carbon nanotubes are the most promising reinforcement for high performance composites. Multiwall carbon nanotubes were directly grown onto the carbon fiber surface by catalytic thermal chemical vapor deposition technique. Multi-scale hybrid composites were fabricated using the carbon nanotubes grown fibers with epoxy matrix. Morphology of the grown carbon nanotubes was investigated using field emission scanning electron microscopy and transmission electron microscopy. The fabricated composites were subjected to impact tests which showed 48.7% and 42.2% higher energy absorption in Charpy and Izod impact tests respectively. Fractographic analysis of the impact tested specimens revealed the presence of carbon nanotubes both at the fiber surface and within the matrix which explained the reason for improved energy absorption capability of these composites. Carbon nanotubes presence at various cracks formed during loading provided a direct evidence of micro crack bridging. Thus the enhanced fracture strength of these composites is attributed to stronger fiber–matrix interfacial bonding and simultaneous matrix strengthening due to the grown carbon nanotubes.     

Comparison of xylo-oligosaccharides production by autohydrolysis of fibers separated from ground corn flour and DDGS

Xylo-oligosaccharides (XOS) are known to have beneficial health properties, and are considered to be functional food ingredients. The objective of this study is to compare corn fibers separated from ground corn flour and distillers dried grains with solubles (DDGS) for XOS yield and optimum autohydrolysis conditions. Based on the initial xylan content, the fiber separated from ground corn flour (FC) resulted in higher XOS yield (71.5%) than the fiber separated from DDGS (FD) (54.6%) at the maximum XOS production conditions. XOS produced were mainly xylobiose and xylotriose. Based on total initial material also, FC resulted in higher XOS yield (8.9%) than FD (8.0%), based on total original masses. Thus, fiber separated from ground corn flour would be a better feedstock for production of XOS than fiber separated from DDGS. The conditions for maximum XOS production from FD and FC were 180 °C with 20 min hold-time and 190 °C with 10 min hold-time, respectively.     

Electrophoretic deposition of graphene oxide on carbon brush as bioanode for microbial fuel cell operated with real wastewater

Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm^?2 to 381 mWm^?2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.     

Epidemic contact tracing with smartphone sensors

ABSTRACT

Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.     

基于随机光栅的可调谐随机光纤激光器

提出一种基于随机光栅与高反射布拉格光栅(FBG)相结合的可调谐随机光纤激光器。利用980nm泵浦光源泵浦一段7m长的掺铒光纤(EDF)进行增益放大,由随机光栅提供随机反馈。随机光栅长7cm,具有约10000个折射率修改点,这些点由飞秒激光逐点写入,并沿光纤方向随机分布,两点相邻间隔小于10μm。同时,利用中心波长为1548nm的高反射FBG来组成半开放腔结构,实现了随机激光的输出。实验测得的泵浦阈值功率仅为18mW,斜率效率高达13.2%,并通过改变FBG的中心波长,实现了输出激光波长的可调谐,调谐范围为4.45nm(1548.04~1552.49nm)。得益于半开放式激光腔的设计和EDF的高增益,整个系统具有阈值低、效率高、结构简单等优点。     

燃煤锅炉除尘专用滤料的开发

介绍机械制造厂燃煤锅炉的烟尘特点,分析滤料失效的原因,提出一套针对该工况的滤料解决方案。介绍针对复杂工况条件所选用的纤维种类以及复合面层原料成分配比的确定,最终选用针刺工艺加工并对该新产品的基本性能进行了测试分析。     

Design criterion for fatigue strengthening of riveted beams in a 120-year-old railway metallic bridge using pre-stressed CFRP plates

This study presents a design criterion developed for fatigue strengthening of a 120-year-old metallic railway bridge in Switzerland and presents a pre-stressed un-bonded reinforcement (PUR) system developed to apply the strengthening. The PUR system uses carbon fiber reinforced polymer (CFRP) plates; however, unlike conventional pre-stressed CFRP reinforcement methods, preparation of the existing metallic bridge surface is not required. This decreases the time required for on-site strengthening procedures. The principle of the constant life diagram (CLD) and two fatigue failure criteria (Johnson and Goodman) are described. Analytical formulations are developed based on the CLD method to determine the minimum CFRP pre-stress level required to prevent fatigue crack initiation. The PUR system uses an applied pre-stress force to reduce the mean stress level (and stress ratio) to shift an existing fatigue-susceptible metallic detail from the ‘at risk’ finite life regime to the ‘safe’ infinite life regime. The applied CLD method is particularly valuable when the stress history of the detail is not known and it is difficult to assess the remaining fatigue life. Moreover, it is shown that the currently adopted approach in many structural codes which emphasizes stress range as the dominant parameter influencing fatigue life are non-conservative for tension–tension stress patterns (i.e., stress ratios of 0 < R < 1). Analyses show that the modified Johnson formula accurately reflects the combined effect of stress range, mean stress level, and material properties, and offers a relatively easy design procedure. Details of a retrofit field application on members of a riveted wrought iron railway bridge are given. A wireless sensor network (WSN) system is used for long-term monitoring of the on-site CFRP stress levels and temperature of the retrofitted details. WSN measurements indicate that increases in ambient temperature result in increased CFRP pre-stress levels.     

玄武岩纤维填料应用于两种混合生长反应器的评价

采用单丝直径微米级的伞状玄武岩纤维(BF)作为填料,将其引入序批式反应器(SBR)和后置缺氧反硝化SBR外聚合物(EPS)含量和扫描电子显微镜形貌图,考察了两种SHBR的污水处理效果。试验结果表明:基于SBR的SHBR的出水COD、氨氮、总氮去除率分别为83.2%、89.9%、86.8%;基于后置缺氧反硝化SBR的SHBR优良,而基于后置缺氧反硝化SBR的SHBR的脱氮效果得到进一步的优化和提升。两种SHBR的BF填料中EPS含量分析结果显示:在好氧环境下,蛋白质(PN)的含量高于多糖(PS)的含量;在缺氧条件下,PS的含量明显高于PN的含量。     

A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.