A Compressor Fouling Review Based on an Historical Survey of ASME Turbo Expo Papers

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Alessio Suman ◽  
Mirko Morini ◽  
Nicola Aldi ◽  
Nicola Casari ◽  
Michele Pinelli ◽  
...  
Keyword(s):  
Particle Deposition ◽  
State Of The Art ◽  
Operational Experience ◽  
Technological Evolution ◽  
Historical Survey ◽  
Air Contaminants ◽  
Compressor Inlet ◽  
Asme Turbo Expo ◽  
High Level ◽  
First Time

Fouling afflicts gas turbine operation from first time application. Filtration systems and washing operations work against air contaminants in order to limit the particles entering the compressor inlet and remove the existing deposits. In this work, a global overview of the operational experience of the manufacturer, the filtration systems, and the particle deposition of the compressor are reported. The data reported in this review have been collected from 60 years (1956–2015) of ASME Turbo Expo proceedings. This conference is recognized as the must-attend event for turbomachinery professionals. Through the years, many issues have been resolved by the contributions of this conference. Regarding the compressor fouling phenomenon, the contributions presented at the ASME Turbo Expo mark the high level of development in this field of research, thanks to the simultaneous presence of manufacturers, government, and academia attendees. The goal of the authors is to describe the technological evolution and challenges faced by manufacturers and researchers through the years, highlighting the state of the art in the knowledge of fouling, and defining the background on which further studies will be based.

scholarly journals Sim-to-Real Quadrotor Landing via Sequential Deep Q-Networks and Domain Randomization

Robotics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 8 ◽  
Author(s):  
Riccardo Polvara ◽  
Massimiliano Patacchiola ◽  
Marc Hanheide ◽  
Gerhard Neumann
Keyword(s):  
State Of The Art ◽  
Control Policy ◽  
Divide And Conquer ◽  
Level Control ◽  
Autonomous Landing ◽  
Aerial Vehicle ◽  
Noisy Conditions ◽  
High Level ◽  
Technical Solutions ◽  
First Time

The autonomous landing of an Unmanned Aerial Vehicle (UAV) on a marker is one of the most challenging problems in robotics. Many solutions have been proposed, with the best results achieved via customized geometric features and external sensors. This paper discusses for the first time the use of deep reinforcement learning as an end-to-end learning paradigm to find a policy for UAVs autonomous landing. Our method is based on a divide-and-conquer paradigm that splits a task into sequential sub-tasks, each one assigned to a Deep Q-Network (DQN), hence the name Sequential Deep Q-Network (SDQN). Each DQN in an SDQN is activated by an internal trigger, and it represents a component of a high-level control policy, which can navigate the UAV towards the marker. Different technical solutions have been implemented, for example combining vanilla and double DQNs, and the introduction of a partitioned buffer replay to address the problem of sample efficiency. One of the main contributions of this work consists in showing how an SDQN trained in a simulator via domain randomization, can effectively generalize to real-world scenarios of increasing complexity. The performance of SDQNs is comparable with a state-of-the-art algorithm and human pilots while being quantitatively better in noisy conditions.

A Confrontation between Two Doctrines: The Birth of Struggle for Hegemony in Hebrew Children's Literature during the 1930s and 1940s

2008 ◽  
Vol 1 (2) ◽  
pp. 139-155 ◽  
Author(s):  
YAEL DARR
Keyword(s):  
Children's Literature ◽  
Educational System ◽  
Single Channel ◽  
Children’S Literature ◽  
The Political ◽  
Literary Creation ◽  
History Of ◽  
High Level ◽  
First Time ◽  
Literary Quality

This article describes a crucial and fundamental stage in the transformation of Hebrew children's literature, during the late 1930s and 1940s, from a single channel of expression to a multi-layered polyphony of models and voices. It claims that for the first time in the history of Hebrew children's literature there took place a doctrinal confrontation between two groups of taste-makers. The article outlines the pedagogical and ideological designs of traditionalist Zionist educators, and suggests how these were challenged by a group of prominent writers of adult poetry, members of the Modernist movement. These writers, it is argued, advocated autonomous literary creation, and insisted on a high level of literary quality. Their intervention not only dramatically changed the repertoire of Hebrew children's literature, but also the rules of literary discourse. The article suggests that, through the Modernists’ polemical efforts, Hebrew children's literature was able to free itself from its position as an apparatus controlled by the political-educational system and to become a dynamic and multi-layered field.

scholarly journals Efficient End-to-End Sentence-Level Lipreading with Temporal Convolutional Networks

2021 ◽  
Vol 11 (15) ◽  
pp. 6975
Author(s):  
Tao Zhang ◽  
Lun He ◽  
Xudong Li ◽  
Guoqing Feng
Keyword(s):  
Performance Improvement ◽  
State Of The Art ◽  
Error Rates ◽  
Convolutional Network ◽  
Convolutional Networks ◽  
Sentence Level ◽  
End To End ◽  
High Level ◽  
Improved Accuracy ◽  
Talking Face

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

scholarly journals State-of-the-Art Char Production with a Focus on Bark Feedstocks: Processes, Design, and Applications

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 87
Author(s):  
Ali Umut Şen ◽  
Helena Pereira
Keyword(s):  
State Of The Art ◽  
Lignocellulosic Materials ◽  
Heating Rates ◽  
Production Methods ◽  
Slow Pyrolysis ◽  
Production Studies ◽  
Lignocellulosic Feedstocks ◽  
Thermochemical Method ◽  
Superior Surface ◽  
First Time

In recent years, there has been a surge of interest in char production from lignocellulosic biomass due to the fact of char’s interesting technological properties. Global char production in 2019 reached 53.6 million tons. Barks are among the most important and understudied lignocellulosic feedstocks that have a large potential for exploitation, given bark global production which is estimated to be as high as 400 million cubic meters per year. Chars can be produced from barks; however, in order to obtain the desired char yields and for simulation of the pyrolysis process, it is important to understand the differences between barks and woods and other lignocellulosic materials in addition to selecting a proper thermochemical method for bark-based char production. In this state-of-the-art review, after analyzing the main char production methods, barks were characterized for their chemical composition and compared with other important lignocellulosic materials. Following these steps, previous bark-based char production studies were analyzed, and different barks and process types were evaluated for the first time to guide future char production process designs based on bark feedstock. The dry and wet pyrolysis and gasification results of barks revealed that application of different particle sizes, heating rates, and solid residence times resulted in highly variable char yields between the temperature range of 220 °C and 600 °C. Bark-based char production should be primarily performed via a slow pyrolysis route, considering the superior surface properties of slow pyrolysis chars.

scholarly journals UV Inscription and Pressure Induced Long-Period Gratings through 3D Printed Amplitude Masks

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1977
Author(s):  
Ricardo Oliveira ◽  
Liliana M. Sousa ◽  
Ana M. Rocha ◽  
Rogério Nogueira ◽  
Lúcia Bilro
Keyword(s):  
State Of The Art ◽  
Low Cost ◽  
Resonance Wavelength ◽  
Complex Structures ◽  
Pressing Method ◽  
Long Period ◽  
Long Period Gratings ◽  
3D Printed ◽  
Mechanical Pressing ◽  
First Time

In this work, we demonstrate for the first time the capability to inscribe long-period gratings (LPGs) with UV radiation using simple and low cost amplitude masks fabricated with a consumer grade 3D printer. The spectrum obtained for a grating with 690 µm period and 38 mm length presented good quality, showing sharp resonances (i.e., 3 dB bandwidth < 3 nm), low out-of-band loss (~0.2 dB), and dip losses up to 18 dB. Furthermore, the capability to select the resonance wavelength has been demonstrated using different amplitude mask periods. The customization of the masks makes it possible to fabricate gratings with complex structures. Additionally, the simplicity in 3D printing an amplitude mask solves the problem of the lack of amplitude masks on the market and avoids the use of high resolution motorized stages, as is the case of the point-by-point technique. Finally, the 3D printed masks were also used to induce LPGs using the mechanical pressing method. Due to the better resolution of these masks compared to ones described on the state of the art, we were able to induce gratings with higher quality, such as low out-of-band loss (0.6 dB), reduced spectral ripples, and narrow bandwidths (~3 nm).

scholarly journals Electro-Quasistatic Animal Body Communication for Untethered Rodent Biopotential Recording

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shreeya Sriram ◽  
Shitij Avlani ◽  
Matthew P. Ward ◽  
Shreyas Sen
Keyword(s):  
Lower Energy ◽  
Sensor Node ◽  
State Of The Art ◽  
The Body ◽  
Animal Body ◽  
Current State ◽  
Communication Modalities ◽  
First Time ◽  
Biopotential Recording

AbstractContinuous multi-channel monitoring of biopotential signals is vital in understanding the body as a whole, facilitating accurate models and predictions in neural research. The current state of the art in wireless technologies for untethered biopotential recordings rely on radiative electromagnetic (EM) fields. In such transmissions, only a small fraction of this energy is received since the EM fields are widely radiated resulting in lossy inefficient systems. Using the body as a communication medium (similar to a ’wire’) allows for the containment of the energy within the body, yielding order(s) of magnitude lower energy than radiative EM communication. In this work, we introduce Animal Body Communication (ABC), which utilizes the concept of using the body as a medium into the domain of untethered animal biopotential recording. This work, for the first time, develops the theory and models for animal body communication circuitry and channel loss. Using this theoretical model, a sub-inch$$^3$$ 3 [1″ × 1″ × 0.4″], custom-designed sensor node is built using off the shelf components which is capable of sensing and transmitting biopotential signals, through the body of the rat at significantly lower powers compared to traditional wireless transmissions. In-vivo experimental analysis proves that ABC successfully transmits acquired electrocardiogram (EKG) signals through the body with correlation $$>99\%$$ > 99 % when compared to traditional wireless communication modalities, with a 50$$\times$$ × reduction in power consumption.

Caged-electron States and Split-electron States in Endohedral Alkali C60

2021 ◽  
Author(s):  
yifan yang ◽  
Lorenz S Cederbaum
Keyword(s):  
State Of The Art ◽  
Electronic States ◽  
Electron States ◽  
The Common ◽  
High Level

The low-lying electronic states of neutral X@C60(X=Li, Na, K, Rb) have been computed and analyzed by employing state-of-the-art high level many-electron methods. Apart from the common charge-separated states, well known...

scholarly journals Aberrant Expression of TLR2, TLR7, TLR9, Splicing Variants of TLR4 and MYD88 in Chronic Lymphocytic Leukemia Patients

2021 ◽  
Vol 10 (4) ◽  
pp. 867
Author(s):  
Katarzyna Skorka ◽  
Paulina Wlasiuk ◽  
Agnieszka Karczmarczyk ◽  
Krzysztof Giannopoulos
Keyword(s):  
Bone Marrow ◽  
Chronic Lymphocytic Leukemia ◽  
Cytotoxic T Cells ◽  
Lymphocytic Leukemia ◽  
Aberrant Expression ◽  
Downstream Signaling ◽  
Splicing Variants ◽  
High Level ◽  
Time To First Treatment ◽  
First Time

Functional toll-like receptors (TLRs) could modulate anti-tumor effects by activating inflammatory cytokines and the cytotoxic T-cells response. However, excessive TLR expression could promote tumor progression, since TLR-induced inflammation might stimulate cancer cells expansion into the microenvironment. Myd88 is involved in activation NF-κB through TLRs downstream signaling, hence in the current study we provided, for the first time, a complex characterization of expression of TLR2, TLR4, TLR7, TLR9, and MYD88 as well as their splicing forms in two distinct compartments of the microenvironment of chronic lymphocytic leukemia (CLL): peripheral blood and bone marrow. We found correlations between MYD88 and TLRs expressions in both compartments, indicating their relevant cooperation in CLL. The MYD88 expression was higher in CLL patients compared to healthy volunteers (HVs) (0.1780 vs. 0.128, p < 0.0001). The TLRs expression was aberrant in CLL compared to HVs. Analysis of survival curves revealed a shorter time to first treatment in the group of patients with low level of TLR4(3) expression compared to high level of TLR4(3) expression in bone marrow (13 months vs. 48 months, p = 0.0207). We suggest that TLRs expression is differentially regulated in CLL but is similarly shared between two distinct compartments of the microenvironment.

scholarly journals Thermoelectric Sensor Coupled Yagi–Uda Nanoantenna for Infrared Detection

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 527
Author(s):  
Waleed Tariq Sethi ◽  
Olivier De Sagazan ◽  
Mohamed Himdi ◽  
Hamsakutty Vettikalladi ◽  
Saleh A. Alshebeili
Keyword(s):  
State Of The Art ◽  
Infrared Detection ◽  
Single Element ◽  
Center Wavelength ◽  
Resonance Response ◽  
Thermal Measurements ◽  
Radiation Induced ◽  
Thermoelectric Sensor ◽  
Junction Array ◽  
First Time

We present an experimental demonstration of a thermoelectric sensor coupled with a nanoantenna as an alternative option for detecting infrared energy. Two nanoantenna design (single element and an array) variations based on Yagi-Uda technology and one separate nano-thermoelectric junction array were fabricated and tested. The nanoantennas were tuned to operate and respond at a center wavelength of 1550 nm (193.5 THz) optical C-band window, but they also exhibited a resonance response when excited by lasers of various wavelengths (650 nm and 940 nm). The radiation-induced electric currents in the nanoantennas, coupled with a nano-thermoelectric sensor, produced a potential difference as per the Seebeck effect. With respect to the uniform thermal measurements of the reference nanoantenna, the experiments confirmed the detection properties of the proposed nanoantennas; the single element detected a peak percentage voltage hike of 28%, whereas the array detected a peak percentage voltage hike of 80% at the center wavelength. Compared to state-of-the-art thermoelectric designs, this was the first time that such peak percentage voltages were experimentally reported following a planar design based on the Seebeck principle.

scholarly journals Domain Adaptation Using a Three-Way Decision Improves the Identification of Autism Patients from Multisite fMRI Data

2021 ◽  
Vol 11 (5) ◽  
pp. 603
Author(s):  
Chunlei Shi ◽  
Xianwei Xin ◽  
Jiacai Zhang
Keyword(s):  
Machine Learning ◽  
Domain Adaptation ◽  
Recognition Accuracy ◽  
State Of The Art ◽  
Autism Spectrum ◽  
Fmri Data ◽  
Target Domain ◽  
Sample Distribution ◽  
Machine Learning Methods ◽  
First Time

Machine learning methods are widely used in autism spectrum disorder (ASD) diagnosis. Due to the lack of labelled ASD data, multisite data are often pooled together to expand the sample size. However, the heterogeneity that exists among different sites leads to the degeneration of machine learning models. Herein, the three-way decision theory was introduced into unsupervised domain adaptation in the first time, and applied to optimize the pseudolabel of the target domain/site from functional magnetic resonance imaging (fMRI) features related to ASD patients. The experimental results using multisite fMRI data show that our method not only narrows the gap of the sample distribution among domains but is also superior to the state-of-the-art domain adaptation methods in ASD recognition. Specifically, the ASD recognition accuracy of the proposed method is improved on all the six tasks, by 70.80%, 75.41%, 69.91%, 72.13%, 71.01% and 68.85%, respectively, compared with the existing methods.

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