Improved components for engine fuel savings

The Engine Component Improvement (ECI) Project formulated to address near term improvements for current engines is described with emphasis on the development of component technologies to reduce the fuel consumption of CF6, JT9D, and JT8D engines. The technical and economical acceptability and the fuel saving potential of nine concepts are demonstrated. Descriptions of these concepts, results of testing, and the status as to entering airline service are presented. Also presented is the status of the remaining concepts still under development

Some Operating Experience and Problems Encountered During Operation of a Free-jet Facility

During a free-jet investigation of a 28-inch ram-jet engine at a Mach number of 2.35, flow pulsation at the engine inlet were discovered which proved to have an effect on the engine performance and operational characteristics, particularly the engine rich blowout limits. This report discusses the finding of the flow pulsations, their elimination, and effect. Other facility characteristics, such as the establishment of flow simulation and the degree of subcritical operation of the diffuser, are also explained

An in situ XAS study of the cobalt rhenium catalyst for ammonia synthesis

A cobalt rhenium catalyst active for ammonia synthesis at 400 °C and ambient pressure was studied using in situ XAS to elucidate the reducibility and local environment of the two metals during reaction conditions. The ammonia reactivity is greatly affected by the gas mixture used in the pre-treatment step. Following H2/Ar pre-treatment, a subsequent 20 min induction period is also observed before ammonia production occurs whereas ammonia production commences immediately following comparable H2/N2 pre-treatment. In situ XAS at the Co K-edge and Re LIII-edge show that cobalt initiates reduction, undergoing reduction between 225 and 300 °C, whereas reduction of rhenium starts at 300 °C. The reduction of rhenium is near complete below 400 °C, as also confirmed by H2-TPR measurements. A synergistic co-metal effect is observed for the cobalt rhenium system, as complete reduction of both cobalt and rhenium independently requires higher temperatures. The phases present in the cobalt rhenium catalyst during ammonia production following both pre-treatments are largely bimetallic Co–Re phases, and also monometallic Co and Re phases. The presence of nitrogen during the reduction step strongly promotes mixing of the two metals, and the bimetallic Co–Re phase is believed to be a pre-requisite for activity

Controlling And Understanding Single And Multicomponent Supramolecular Gels

Supramolecular gels can be prepared by the self-assembly of small molecules into fibrous structures. The properties of the resulting gels depend on how the gels are formed, such that gels with very different properties can be prepared from a single gelator if different gelation methods are used. We have been working to understand this, and for example can prepare gels that can or cannot be 3D-printed from the same gelator by varying gelation method. Here, we will focus on explaining the design rules. As specific examples, we will discuss how varying the chirality of our dipeptide-based gelators can be used to control the self-assembled aggregates, leading to differences in the final gels. We will also show how our understanding can be expanded to multicomponent systems, where each component gelator can form gels alone. In these mixed systems, we can control assembly such that self-sorted multicomponent gels are formed. We will show how such systems can be characterised to prove this assembly and how this approach can be used to prepare gels with controlled and specific properties

Effect of temporal modulation rate on the intelligibility of phase-based speech

published_or_final_versio

Using small-angle scattering and contrast matching to understand molecular packing in low molecular weight gels

It is difficult to determine exactly the molecular packing in the aggregates in low molecular weight gels. Attempts to understand the packing have been made using X-ray diffraction, but there are complications with drying and questions as to whether the crystal structures represent the packing in the gel phase. Here, we exploit contrast matching in small-angle neutron scattering experiments. By preparing selectively deuterated analogs of the same molecule, the scattering from that section of the molecule decreases compared with the hydrogenated molecule. We examine packing in the pre-gelled solutions at high pH and in the gels at low pH. The data from the final gels show a lack of specific order in the aggregates that form the gel matrix. The packing in these systems is not well ordered in the gel state and so implies that it is likely that current models and cartoons are not correct

Monitoring based on time-frequency tracking of estimated harmonic series and modulation sidebands

International audienceThe installation of a Condition Monitoring System (CMS) on a mechanical machine (e.g., on a wind turbine) aims to reduce the operating costs by applying a predictive maintenance strategy. The CMS is composed of sensors acquiring signals from which system health indicators are computed and monitored. Part of those indicators are predefined depending on the monitored system kinematic and are computed by averaging large or narrow spectral bands. The averaging and the need for predefined thresholds for default detection may induce lots of false alarms while reducing the ability to detect the default early. To get precise health indicators reflecting each local meaningful spectral content, the AStrion software proposes a new data-driven monitoring strategy without any a priori on the measured signals. First, an automatic spectral analysis is applied to detect, characterize and classify the different spectral structures of the successive measured signals. These spectral structures can be either single spectral peaks, either peaks grouped in harmonic series or in modulation sidebands [1]. Second, these spectral structures are characterized by several features, including for example the number of peaks, the characteristic frequencies and the energy. This gives a snapshot of the system health at the signal acquisition time. To perform an automatic diagnosis of the system, the spectral evolution should be tracked along the time snapshots. In this paper, we propose a time tracking method based on McAulay & Quatieri algorithm [2] which has been designed originally for speech signals acquired on a continuous temporal basis. We have adapted [2] in order to account not only for single spectral peak evolution but also for the evolution of more complex structures such as harmonic series or modulation sidebands, even in the case of signals acquired on a non-regular temporal basis, as it is often the case. Moreover, an added sleep state makes the proposed method robust against nondetected spectral structures at a given time. Finally, the temporal evolution of the spectral structure features can be monitored and used as precise health indicators. The following figure is a result of the proposed method applied on real signals coming from a test bench designed in KAStrion project for simulating a wind turbine operation and for which the inner race of the main bearing has been damaged. Above, the time frequency map displays a zoom of the spectral peaks detected (around 20.000 per snapshot, represented by circles) and shows in blue the tracking from 44 to 189 operating hours of a spectral peak at 3.45 Hz. This particular peak evolves at 129 hours to become an harmonic series with more and more peaks and energy. Its energy evolution (plotted below) shows an increase which mirrors out a failure. In a following step [3], this spectral structure has been associated with the ball pass frequency of the inner ring of the main bearing. A dismantling of this bearing has confirmed the failure. This result shows the potential of the proposed data-driven method to create automatically relevant health indicators

Plant species roles in pollination networks: an experimental approach

Pollination is an important ecosystem service threatened by current pollinator declines, making flower planting schemes an important strategy to recover pollination function. However, ecologists rarely test the attractiveness of chosen plants to pollinators in the field. Here, we experimentally test whether plant species roles in pollination networks can be used to identify species with the most potential to recover plant–pollinator communities. Using published pollination networks, we calculated each plant's centrality and chose five central and five peripheral plant species for introduction into replicate experimental plots. Flower visitation by pollinators was recorded in each plot and we tested the impact of introduced central and peripheral plant species on the pollinator and resident plant communities and on network structure. We found that the introduction of central plant species attracted a higher richness and abundance of pollinators than the introduction of peripheral species, and that the introduced central plant species occupied the most important network roles. The high attractiveness of central species to pollinators, however, did not negatively affect visitation to resident plant species by pollinators. We also found that the introduction of central plant species did not affect network structure, while networks with introduced peripheral species had lower centralisation and interaction evenness than networks with introduced central species. To our knowledge, this is the first time species network roles have been tested in a field experiment. Given that most restoration projects start at the plant community, being able to identify the plants with the highest potential to restore community structure and functioning should be a key goal for ecological restoration