Estimating the Thermal State and Methodological Issues in Gas Dynamic Testing of Refractory Ceramic Samples

2020 ◽  
pp. 45-65
Author(s):  
V.A. Tovstonog ◽  
V.I. Tomak ◽  
A.S. Burkov
Keyword(s):  
Real World ◽  
Gas Flow ◽  
Thermal Stresses ◽  
Dynamic Testing ◽  
Thermal State ◽  
Material Selection ◽  
Integral Methods ◽  
Wide Range ◽  
State Models ◽  
And Performance

Material selection for aerospace structural and power plant units subjected to thermal stresses is based on thorough investigation of their physical, mechanical and optical properties in a wide range of temperatures up to 2500--3000 K, which are in practice the highest possible. However, it is exceptionally difficult and expensive to obtain the whole extent of data on the properties of structural and refractive materials currently in development that is required to analytically estimate the thermal state and performance of the structures designed to be subjected to thermal stresses. Moreover, the theoretical thermal state models in use are most often based on a number of assumptions, which means that they will need to be validated against experimental investigation data. As a result, integral methods of estimating material performance under intended real-world thermal and force loads become highly important. Ground-based development testing using simulation installations will solve this problem. While testing, it is important to ensure that the simulated thermal modes of the object being tested match its real-world thermal modes. The paper considers these issues regarding estimating refractory ceramics performance subjected to a high-temperature gas flow

Analysis of organic removal rates in the aerated submerged fixed film process

1998 ◽  
Vol 38 (8-9) ◽  
pp. 213-221 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain
Keyword(s):  
Pilot Plant ◽  
Removal Rate ◽  
Domestic Wastewater ◽  
Removal Rates ◽  
Hydraulic Loading ◽  
Organic Removal ◽  
Wide Range ◽  
Fixed Film ◽  
Cod Removal Rate ◽  
And Performance

Performance data from a pilot-plant employing the four-stage aerated submerged fixed film (ASFF) process treating domestic wastewater were analyzed to examine the organic removal rates. The process has shown high BOD removal efficiencies (> 90%) over a wide range of hydraulic loading rates (0.04 to 0.68 m3/m2·d). It could also cope with high hydraulic and organic loadings with minimal loss in efficiency due to the large amount of immobilized biomass attained. The organic (BOD and COD) removal rate was influenced by the hydraulic loadings applied, but organic removal rates of up to 104 kg BOD/ m2·d were obtained at a hydraulic loading rate of 0.68 m3/m2·d. A Semi-empirical model for the bio-oxidation of organics in the ASFF process has been formulated and rate constants were calculated based on statistical analysis of pilot-plant data. The relationships obtained are very useful for analyzing the design and performance of the ASFF process and a variety of attached growth processes.

On the Influence of Fluctuating Flow Rate Upon the Performance and Behaviour of Isothermal Reacting Systems

1998 ◽  
Vol 63 (6) ◽  
pp. 881-898
Author(s):  
Otakar Trnka ◽  
Miloslav Hartman
Keyword(s):  
Flow Rate ◽  
Gas Flow ◽  
Fluidized Bed Reactor ◽  
Computational Techniques ◽  
Continuous Stirred Tank Reactor ◽  
Gas Flow Rate ◽  
Solid Reaction ◽  
Continuous Stirred Tank ◽  
And Performance ◽  
Reacting Systems

Three simple computational techniques are proposed and employed to demonstrate the effect of fluctuating flow rate of feed on the behaviour and performance of an isothermal, continuous stirred tank reactor (CSTR). A fluidized bed reactor (FBR), in which a non-catalytic gas-solid reaction occurs, is also considered. The influence of amplitude and frequency of gas flow rate fluctuations on reactant concentrations at the exit of the CSTR is shown in four different situations.

scholarly journals Atmospheric Pressure Plasma Deposition of TiO2: A Review

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2931
Author(s):  
Soumya Banerjee ◽  
Ek Adhikari ◽  
Pitambar Sapkota ◽  
Amal Sebastian ◽  
Sylwia Ptasinska
Keyword(s):  
Atmospheric Pressure ◽  
Gas Flow ◽  
Plasma Deposition ◽  
Atmospheric Pressure Plasma ◽  
Cost Savings ◽  
Historical Background ◽  
Pressure Plasma ◽  
Wide Range ◽  
The Status ◽  
Deposition Techniques

Atmospheric pressure plasma (APP) deposition techniques are useful today because of their simplicity and their time and cost savings, particularly for growth of oxide films. Among the oxide materials, titanium dioxide (TiO2) has a wide range of applications in electronics, solar cells, and photocatalysis, which has made it an extremely popular research topic for decades. Here, we provide an overview of non-thermal APP deposition techniques for TiO2 thin film, some historical background, and some very recent findings and developments. First, we define non-thermal plasma, and then we describe the advantages of APP deposition. In addition, we explain the importance of TiO2 and then describe briefly the three deposition techniques used to date. We also compare the structural, electronic, and optical properties of TiO2 films deposited by different APP methods. Lastly, we examine the status of current research related to the effects of such deposition parameters as plasma power, feed gas, bias voltage, gas flow rate, and substrate temperature on the deposition rate, crystal phase, and other film properties. The examples given cover the most common APP deposition techniques for TiO2 growth to understand their advantages for specific applications. In addition, we discuss the important challenges that APP deposition is facing in this rapidly growing field.

scholarly journals Goal-driven active learning

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Nicolas Bougie ◽  
Ryutaro Ichise
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Process ◽  
Real World ◽  
Imitation Learning ◽  
Learning Approaches ◽  
Wide Range ◽  
Fixed Set ◽  
Complex Decision Making ◽  
Complex Decision

AbstractDeep reinforcement learning methods have achieved significant successes in complex decision-making problems. In fact, they traditionally rely on well-designed extrinsic rewards, which limits their applicability to many real-world tasks where rewards are naturally sparse. While cloning behaviors provided by an expert is a promising approach to the exploration problem, learning from a fixed set of demonstrations may be impracticable due to lack of state coverage or distribution mismatch—when the learner’s goal deviates from the demonstrated behaviors. Besides, we are interested in learning how to reach a wide range of goals from the same set of demonstrations. In this work we propose a novel goal-conditioned method that leverages very small sets of goal-driven demonstrations to massively accelerate the learning process. Crucially, we introduce the concept of active goal-driven demonstrations to query the demonstrator only in hard-to-learn and uncertain regions of the state space. We further present a strategy for prioritizing sampling of goals where the disagreement between the expert and the policy is maximized. We evaluate our method on a variety of benchmark environments from the Mujoco domain. Experimental results show that our method outperforms prior imitation learning approaches in most of the tasks in terms of exploration efficiency and average scores.

A CFD Study of Focused Extreme Wave Impact on Decks of Offshore Structures

2014 ◽  
Author(s):  
Xin Lu ◽  
Pankaj Kumar ◽  
Anand Bahuguni ◽  
Yanling Wu
Keyword(s):  
Real World ◽  
Offshore Structures ◽  
Air Gap ◽  
Irregular Waves ◽  
Linear Wave ◽  
Extreme Wave ◽  
Wave Impact ◽  
Loading Test ◽  
Wide Range ◽  
Wave Maker

The design of offshore structures for extreme/abnormal waves assumes that there is sufficient air gap such that waves will not hit the platform deck. Due to inaccuracies in the predictions of extreme wave crests in addition to settlement or sea-level increases, the required air gap between the crest of the extreme wave and the deck is often inadequate in existing platforms and therefore wave-in-deck loads need to be considered when assessing the integrity of such platforms. The problem of wave-in-deck loading involves very complex physics and demands intensive study. In the Computational Fluid Mechanics (CFD) approach, two critical issues must be addressed, namely the efficient, realistic numerical wave maker and the accurate free surface capturing methodology. Most reported CFD research on wave-in-deck loads consider regular waves only, for instance the Stokes fifth-order waves. They are, however, recognized by designers as approximate approaches since “real world” sea states consist of random irregular waves. In our work, we report a recently developed focused extreme wave maker based on the NewWave theory. This model can better approximate the “real world” conditions, and is more efficient than conventional random wave makers. It is able to efficiently generate targeted waves at a prescribed time and location. The work is implemented and integrated with OpenFOAM, an open source platform that receives more and more attention in a wide range of industrial applications. We will describe the developed numerical method of predicting highly non-linear wave-in-deck loads in the time domain. The model’s capability is firstly demonstrated against 3D model testing experiments on a fixed block with various deck orientations under random waves. A detailed loading analysis is conducted and compared with available numerical and measurement data. It is then applied to an extreme wave loading test on a selected bridge with multiple under-deck girders. The waves are focused extreme irregular waves derived from NewWave theory and JONSWAP spectra.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

scholarly journals Fabrication and Compressive Behavior of a Micro-Lattice Composite by High Resolution DLP Stereolithography

Polymers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 785
Author(s):  
Chow Shing Shin ◽  
Yu Chia Chang
Keyword(s):  
High Resolution ◽  
Lattice Structure ◽  
Low Cost ◽  
Hierarchical Structures ◽  
Dip Coating ◽  
Unit Cell ◽  
Digital Light Processing ◽  
Unit Cell Size ◽  
Wide Range ◽  
And Performance

Lattice structures are superior to stochastic foams in mechanical properties and are finding increasing applications. Their properties can be tailored in a wide range through adjusting the design and dimensions of the unit cell, changing the constituent materials as well as forming into hierarchical structures. In order to achieve more levels of hierarchy, the dimensions of the fundamental lattice have to be small enough. Although lattice size of several microns can be fabricated using the two-photon polymerization technique, sophisticated and costly equipment is required. To balance cost and performance, a low-cost high resolution micro-stereolithographic system has been developed in this work based on a commercial digital light processing (DLP) projector. Unit cell lengths as small as 100 μm have been successfully fabricated. Decreasing the unit cell size from 150 to 100 μm increased the compressive stiffness by 26%. Different pretreatments to facilitate the electroless plating of nickel on the lattice structure have been attempted. A pretreatment of dip coating in a graphene suspension is the most successful and increased the strength and stiffness by 5.3 and 3.6 times, respectively. Even a very light and incomplete nickel plating in the interior has increase the structural stiffness and strength by more than twofold.

scholarly journals An information theoretic approach to link prediction in multiplex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Large Scale ◽  
Similarity Measures ◽  
Prediction Method ◽  
General Purpose ◽  
Fast Method ◽  
Theoretic Approach ◽  
Multiplex Networks ◽  
Wide Range

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.

scholarly journals Comparing optical performance of a wide range of perovskite/silicon tandem architectures under real-world conditions

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Manvika Singh ◽  
Rudi Santbergen ◽  
Indra Syifai ◽  
Arthur Weeber ◽  
Miro Zeman ◽  
...  
Keyword(s):  
Solar Cells ◽  
Real World ◽  
Solar Spectrum ◽  
Photocurrent Density ◽  
Angle Of Incidence ◽  
Optical Study ◽  
Optical Performance ◽  
Tandem Solar Cells ◽  
Bottom Cell ◽  
Wide Range

Abstract Since single junction c-Si solar cells are reaching their practical efficiency limit. Perovskite/c-Si tandem solar cells hold the promise of achieving greater than 30% efficiencies. In this regard, optical simulations can deliver guidelines for reducing the parasitic absorption losses and increasing the photocurrent density of the tandem solar cells. In this work, an optical study of 2, 3 and 4 terminal perovskite/c-Si tandem solar cells with c-Si solar bottom cells passivated by high thermal-budget poly-Si, poly-SiOx and poly-SiCx is performed to evaluate their optical performance with respect to the conventional tandem solar cells employing silicon heterojunction bottom cells. The parasitic absorption in these carrier selective passivating contacts has been quantified. It is shown that they enable greater than 20 mA/cm2 matched implied photocurrent density in un-encapsulated 2T tandem architecture along with being compatible with high temperature production processes. For studying the performance of such tandem devices in real-world irradiance conditions and for different locations of the world, the effect of solar spectrum and angle of incidence on their optical performance is studied. Passing from mono-facial to bi-facial tandem solar cells, the photocurrent density in the bottom cell can be increased, requiring again optical optimization. Here, we analyse the effect of albedo, perovskite thickness and band gap as well as geographical location on the optical performance of these bi-facial perovskite/c-Si tandem solar cells. Our optical study shows that bi-facial 2T tandems, that also convert light incident from the rear, require radically thicker perovskite layers to match the additional current from the c-Si bottom cell. For typical perovskite bandgap and albedo values, even doubling the perovskite thickness is not sufficient. In this respect, lower bandgap perovskites are very interesting for application not only in bi-facial 2T tandems but also in related 3T and 4T tandems.

3D Technology – Additive Manufacturing Applications and Prospects (Vol. 24, No. 9, Full Issue)

2020 ◽  
Vol 24 (09) ◽  
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Environmental Impact ◽  
Real World ◽  
Vaccine Development ◽  
Health Screening ◽  
Wide Range ◽  
The World ◽  
Real World Applications ◽  
Manufacturing Applications

For the month of September 2020, APBN dives into the world of 3D printing and its wide range of real-world applications. Keeping our focus on the topic of the year, the COVID-19 pandemic, we explore the environmental impact of the global outbreak as well as gain insight to the top 5 vaccine platforms used in vaccine development. Discover more about technological advancements and how it is assisting innovation in geriatric health screening.

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