Design of a deep learning based nonlinear aerodynamic surrogate model for UAVs

In this paper, we present a deep learning based surrogate model to determine non-linear aerodynamic characteristics of UAVs. The main advantage of this model is that it can predict the aerodynamic properties of the configurations very quickly by using only geometric configuration parameters without the need for any special input data or pre-process phase. This provides a crucial and explicit design and synthesis tool for mini and small UAVs. To achieve this goal, a large data set, which includes thousands of wing-tail configurations geometry parameters and performance coefficients, was generated using the previously developed and computationally very efficient non-linear lifting line method. This data is used for training the artificial neural network model. The preliminary results show that the neural network model has generalization capability. The aerodynamic model predictions show almost 1-1 coincidence with the numerical data even for configurations with different 2D profiles that are not used in model training. Specifically, the results of test cases are found to capture both the linear and non-linear region of the lift curves, by predicting the maximum lift coefficient, the stall angle of attack, and the characteristics of post-stall region correctly. Similarly, total drag and pitching moment coefficients are predicted successfully. The developed methodology provides the basis for bidirectional design optimization and offers insight for an inverse tool that can calculate geometry parameters for a given design condition

An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes

The zebrafish is ideal for studying embryogenesis and is increasingly applied to model human disease. In these contexts, RNA-sequencing (RNA-seq) provides mechanistic insights by identifying transcriptome changes between experimental conditions. Application of RNA-seq relies on accurate transcript annotation for a genome of interest. Here, we find discrepancies in analysis from RNA-seq datasets quantified using Ensembl and RefSeq zebrafish annotations. These issues were due, in part, to variably annotated 3\u27 untranslated regions and thousands of gene models missing from each annotation. Since these discrepancies could compromise downstream analyses and biological reproducibility, we built a more comprehensive zebrafish transcriptome annotation that addresses these deficiencies. Our annotation improves detection of cell type-specific genes in both bulk and single cell RNA-seq datasets, where it also improves resolution of cell clustering. Thus, we demonstrate that our new transcriptome annotation can outperform existing annotations, providing an important resource for zebrafish researchers

A study of factors affecting on the zeta potential of kaolinite and quartz powder

The purpose of this study was to determine the effects of pH, ion type (salt and metal cations), ionic strength, cation valence, hydrated ionic radius, and solid concentration on the zeta potential of kaolinite and quartz powder in the presence of NaCl, KCl, CaCl2, CuCl2, BaCl2, and AlCl3 solutions. The kaolinite and quartz powder have no isoelectric point (iep) within the entire pH range (3 < pH < 11). In the presence of hydrolysable metal ions, kaolinite and quartz powder have two ieps. As the cationic valence increases, the zeta potential of kaolinite and quartz powder becomes less negative. Monovalent cation, K+, yields more negative zeta potential values than the divalent cation Ba2+. As concentration of solid increases, the zeta potential of the minerals becomes more positive under acidic conditions; however, under alkaline conditions as solid concentration increases the zeta potential becomes more negative. Hydrated ionic radius also affects the zeta potential; the larger the ion, the thicker the layer and the more negative zeta potential for both kaolinite and quartz powder

Zeta potential of clay minerals and quartz contaminated by heavy metals

Laboratory and in situ test results show that electrokinetic decontamination is a promising subsurface decontamination method. However, it has also been reported that several problems arise, such as reverse flow and pH gradient across the anode and the cathode during the electrokinetic decontamination process. Variation in pH alters the zeta (zeta) potential of soils, which is one of the factors affecting the efficiency of contaminant removal by the electrokinetic method. The magnitude of the zeta potential controls the fluid flow rate, whereas its sign controls the flow direction. However, research on how the zeta potential of soils changes under various chemical conditions is limited. In this paper, the effect of pore-fluid chemistry on the zeta potential of kaolinite, montmorillonite, and quartz powder is determined with NaCl, LiCl, CaCl(2 center dot)2H(2)O, MgCl(2 center dot)6H(2)O, CuCl2, CoCl2, ZnCl2, AlCl3, and Pb(NO3)(2). The test results reveal that the zeta potential of the minerals with alkali and alkaline-earth metals changes according to the diffuse electrical double-layer theory. The hydrolyzable metal ions produce two points of zero charge (PZCs), one of which is that of the soil; and the other, that of hydrolyzable oxide. The zeta potential of minerals with hydrolyzable metal ions becomes increasingly positive and reaches its maximum value at neutral pH. It then decreases and again reaches very negative values at alkaline pH values (pH 10), depending on ion concentration and the bulk precipitation pH of hydrolyzable metals as hydrolyzable oxides. On the basis of the results of this study, it is recommended that the zeta potential of the soils be determined before electrokinetic decontamination

Prediction of cation exchange capacity from soil index properties

In many areas of geotechnical engineering it is necessary to have an estimate of the cation exchange capacity (CEC) of a soil in order to allow preliminary design estimates. Standard methods of CEC determination are time-consuming and involve several steps (e.g. displacement of the saturating cation requires several washings with alcohol). Therefore, a rapid method of CEC estimation would be very useful. During preliminary site investigations, the soil engineering parameters can be estimated from the considerable number of correlations available in the literature. In this study, relationships between CEC and various other soil engineering properties have been investigated, resulting in a quick method for estimating CEC

Zeta potential of soils with surfactants and its relevance to electrokinetic remediation

There are numerous studies on the application of electrokinetic decontamination technique to remediate heavy metal contaminated fine grained soils. In recent studies, surfactants have been used to increase the efficiency of contaminant removal. However, there is limited data available on how physicochernical parameters such as zeta potential () of soils changes in the presence of surfactants. Understanding the potential variations of soils with surfactant addition is important because it controls the direction and magnitude of electro-osmotic permeability. which plays important role on the efficiency of electrokinetic remediation. In this study, zeta potentials of kaolinite, montmorillonite and quartz powder with Li+, Ca+2,CU+2, Pb+2 and Al+3 in the presence of anionic, cationic and non-ionic surfactants were determined. The results indicate that anionic surfactants produce negative potentials. The other surfactants produce both positive and negative potentials depending on soil type and ion present in the system. The results also indicate that the potential of kaolinite and quartz powder with surfactants showed similar trends; however, the absolute magnitude of the potential of quartz powder is higher than that of kaolinite. The potential of montmorillonite commonly shows a different trend from those of kaolinite and quartz powder. Based on the test results, it is recommended that potential of soils be determined before the electrokinetic decontamination in order to maximize the efficiency of the technique. (c) 2005 Elsevier B.V. All rights reserved

Predicting soil swelling behaviour from specific surface area

Some geotechnical index properties, such as the liquid limit, plasticity index, clay content and cation exchange capacity, have been used to predict the swelling potential of soils. However, a literature review indicates that prediction of the swelling potential of soils using these index properties is not completely successful. At the same time, the methods used to determine swelling potential are time-consuming. Thus researchers have been investigating other methods that can predict the swelling potential of soils readily and accurately. To this end, in this study the BET (Brunauer, Emmett and Teller equation)-N-2 adsorption, ethylene glycol monoethyl ether (EGME) and methylene blue (MB) measured specific surface areas (SSA) are correlated with the swell index and modified free swell index of soils. The SSA and swell index of 16 remoulded and 15 undisturbed soils consisting of a wide range of mineralogy were determined. Results indicate that the correlation between the SSA and the swelling behaviour of the clayey soils examined is significant. A linear relationship is observed between the swell index, C-s, and the MB SSA: the swell index of the soils increases as the SSA increases. The correlation coefficient between the SSA and the modified free swell index (MFSI) is 0.93, indicating that the MB SSA does exert a significant influence on the swelling behaviour of clayey soils. Based on the test results obtained, a new swelling potential classification is proposed