Search results for: deep mixing method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20360

Search results for: deep mixing method

20360 Numerical Investigation of Embankment Settlement Improved by Method of Preloading by Vertical Drains

Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

Abstract:

Time dependent settlement due to loading on soft saturated soils produces many problems such as high consolidation settlements and low consolidation rates. Also, long term consolidation settlement of soft soil underlying the embankment leads to unpredicted settlements and cracks on soil surface. Preloading method is an effective improvement method to solve this problem. Using vertical drains in preloading method is an effective method for improving soft soils. Applying deep soil mixing method on soft soils is another effective method for improving soft soils. There are little studies on using two methods of preloading and deep soil mixing simultaneously. In this paper, the concurrent effect of preloading with deep soil mixing by vertical drains is investigated through a finite element code, Plaxis2D. The influence of parameters such as deep soil mixing columns spacing, existence of vertical drains and distance between them, on settlement and stability factor of safety of embankment embedded on soft soil is investigated in this research.

Keywords: preloading, soft soil, vertical drains, deep soil mixing, consolidation settlement

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20359 Effect of Deep Mixing Columns and Geogrid on Embankment Settlement on the Soft Soil

Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

Abstract:

Embankment settlement on soft clays has always been problematic due to the high compaction and low shear strength of the soil. Deep soil mixing and geosynthetics are two soil improvement methods in such fields. Here, a numerical study is conducted on the embankment performance on the soft ground improved by deep soil mixing columns and geosynthetics based on the data of a real project. For this purpose, the finite element method is used in the Plaxis 2D software. The Soft Soil Creep model considers the creep phenomenon in the soft clay layer while the Mohr-Columb model simulates other soil layers. Results are verified using the data of an experimental embankment built on deep mixing columns. The effect of depth and diameter of deep mixing columns and the stiffness of geogrid on the vertical and horizontal movements of embankment on clay subsoil will be investigated in the following.

Keywords: PLAXIS 2D, embankment settlement, horizontal movement, deep soil mixing column, geogrid

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20358 A Review on New Additives in Deep Soil Mixing Method

Authors: Meysam Mousakhani, Reza Ziaie Moayed

Abstract:

Considering the population growth and the needs of society, the improvement of problematic soils and the study of the application of different improvement methods have been considered. One of these methods is deep soil mixing, which has been developed in the past decade, especially in soft soils due to economic efficiency, simple implementation, and other benefits. The use of cement is criticized for its cost and the damaging environmental effects, so these factors lead us to use other additives along with cement in the deep soil mixing. Additives that are used today include fly ash, blast-furnace slag, glass powder, and potassium hydroxide. The present study provides a literature review on the application of different additives in deep soil mixing so that the best additives can be introduced from strength, economic, environmental and other perspectives. The results show that by replacing fly ash and slag with about 40 to 50% of cement, not only economic and environmental benefits but also a long-term strength comparable to cement would be achieved. The use of glass powder, especially in 3% mixing, results in desirable strength. In addition to the other benefits of these additives, potassium hydroxide can also be transported over longer distances, leading to wider soil improvement. Finally, this paper suggests further studies in terms of using other additives such as nanomaterials and zeolite, with different ratios, in different conditions and soils (silty sand, clayey sand, carbonate sand, sandy clay and etc.) in the deep mixing method.

Keywords: deep soil mix, soil stabilization, fly ash, ground improvement

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20357 A Numerical Study for Mixing Depth and Applicability of Partial Cement Mixing Method Utilizing Geogrid and Fixing Unit

Authors: Woo-seok Choi, Eun-sup Kim, Nam-Seo Park

Abstract:

The demand for new technique in soft ground improvement continuously increases as general soft ground methods like PBD and DCM have a application problem in soft grounds with deep depth and wide distribution in Southern coast of Korea and Southeast. In this study, partial cement mixing method utilizing geogrid and fixing unit(CMG) is suggested and Finite element analysis is performed for analyzing the depth of surface soil and deep soil stabilization and comparing with DCM method. In the result of the experiment, the displacement in DCM method were lower than the displacement in CMG, it's because the upper load is transferred to deep part soil not treated by cement in CMG method case. The differential settlement in DCM method was higher than the differential settlement in CMG, because of the effect load transfer effect by surface part soil treated by cement and geogrid. In conclusion, CMG method has the advantage of economics and constructability in embankment road, railway, etc in which differential settlement is the important consideration.

Keywords: soft ground, geogrid, fixing unit, partial cement mixing, finite element analysis

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20356 Improvement of Soft Clay Soil with Biopolymer

Authors: Majid Bagherinia

Abstract:

Lime and cement are frequently used as binders in the Deep Mixing Method (DMM) to improve soft clay soils. The most significant disadvantages of these materials are carbon dioxide emissions and the consumption of natural resources. In this study, three different biopolymers, guar gum, locust bean gum, and sodium alginate, were investigated for the improvement of soft clay using DMM. In the experimental study, the effects of the additive ratio and curing time on the Unconfined Compressive Strength (UCS) of stabilized specimens were investigated. According to the results, the UCS values of the specimens increased as the additive ratio and curing time increased. The most effective additive was sodium alginate, and the highest strength was obtained after 28 days.

Keywords: deep mixing method, soft clays, ground improvement, biopolymers, unconfined compressive strength

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20355 Characteristics of Nanosilica-Geopolymer Nanocomposites and Mixing Effect

Authors: H. Assaedi, F. U. A. Shaikh, I. M. Low

Abstract:

This paper presents the effects of mixing procedures on mechanical properties of flyash-based geopolymer matrices containing nanosilica (NS) at 0.5%, 1.0%, 2.0%, and 3.0% by wt.. Comparison is made with conventional mechanical dry-mixing of NS with flyash and wet-mixing of NS in alkaline solutions. Physical and mechanical properties are investigated using X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM). Results show that generally the addition of NS particles enhanced the microstructure and improved flexural and compressive strengths of geopolymer nanocomposites. However, samples prepared using dry-mixing approach demonstrate better physical and mechanical properties than wet-mixing of NS.

Keywords: geopolymer, nano-silica, dry mixing, wet mixing, physical properties, mechanical properties

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20354 The Effect of Ingredients Mixing Sequence in Rubber Compounding on the Formation of Bound Rubber and Cross-Link Density of Natural Rubber

Authors: Abu Hasan, Rochmadi, Hary Sulistyo, Suharto Honggokusumo

Abstract:

This research purpose is to study the effect of Ingredients mixing sequence in rubber compounding onto the formation of bound rubber and cross link density of natural rubber and also the relationship of bound rubber and cross link density. Analysis of bound rubber formation of rubber compound and cross link density of rubber vulcanizates were carried out on a natural rubber formula having masticated and mixing, followed by curing. There were four methods of mixing and each mixing process was followed by four mixing sequence methods of carbon black into the rubber. In the first method of mixing sequence, rubber was masticated for 5 min and then rubber chemicals and carbon black N 330 were added simultaneously. In the second one, rubber was masticated for 1 min and followed by addition of rubber chemicals and carbon black N 330 simultaneously using the different method of mixing then the first one. In the third one, carbon black N 660 was used for the same mixing procedure of the second one, and in the last one, rubber was masticated for 3 min, carbon black N 330 and rubber chemicals were added subsequently. The addition of rubber chemicals and carbon black into masticated rubber was distinguished by the sequence and time allocated for each mixing process. Carbon black was added into two stages. In the first stage, 10 phr was added first and the remaining 40 phr was added later along with oil. In the second one to the fourth one, the addition of carbon black in the first and the second stage was added in the phr ratio 20:30, 30:20, and 40:10. The results showed that the ingredients mixing process influenced bound rubber formation and cross link density. In the three methods of mixing, the bound rubber formation was proportional with crosslink density. In contrast in the fourth one, bound rubber formation and cross link density had contradictive relation. Regardless of the mixing method operated, bound rubber had non linear relationship with cross link density. The high cross link density was formed when low bound rubber formation. The cross link density became constant at high bound rubber content.

Keywords: bound-rubber, cross-link density, natural rubber, rubber mixing process

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20353 Bubble Point Pressures of CO2+Ethyl Palmitate by a Cubic Equation of State and the Wong-Sandler Mixing Rule

Authors: M. A. Sedghamiz, S. Raeissi

Abstract:

This study presents three different approaches to estimate bubble point pressures for the binary system of CO2 and ethyl palmitate fatty acid ethyl ester. The first method involves the Peng-Robinson (PR) Equation of State (EoS) with the conventional mixing rule of Van der Waals. The second approach involves the PR EOS together with the Wong Sandler (WS) mixing rule, coupled with the Uniquac Ge model. In order to model the bubble point pressures with this approach, the volume and area parameter for ethyl palmitate were estimated by the Hansen group contribution method. The last method involved the Peng-Robinson, combined with the Wong-Sandler Method, but using NRTL as the GE model. Results using the Van der Waals mixing rule clearly indicated that this method has the largest errors among all three methods, with errors in the range of 3.96–6.22 %. The Pr-Ws-Uniquac method exhibited small errors, with average absolute deviations between 0.95 to 1.97 percent. The Pr-Ws-Nrtl method led to the least errors where average absolute deviations ranged between 0.65-1.7%.

Keywords: bubble pressure, Gibbs excess energy model, mixing rule, CO2 solubility, ethyl palmitate

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20352 A Technical Solution for Micro Mixture with Micro Fluidic Oscillator in Chemistry

Authors: Brahim Dennai, Abdelhak Bentaleb, Rachid Khelfaoui, Asma Abdenbi

Abstract:

The diffusion flux given by the Fick’s law characterizethe mixing rate. A passive mixing strategy is proposed to enhance mixing of two fluids through perturbed jet low. A numerical study of passive mixers has been presented. This paper is focused on the modeling of a micro-injection systems composed of passive amplifier without mechanical part. The micro-system modeling is based on geometrical oscillators form. An asymmetric micro-oscillator design based on a monostable fluidic amplifier is proposed. The characteristic size of the channels is generally about a few hundred of microns. The numerical results indicate that the mixing performance can be as high as 99 % within a typical mixing chamber of 0.20 mm diameter inlet and 2.0 mm distance of nozzle - spliter. In addition, the results confirm that self-rotation in the circular mixer significantly enhances the mixing performance. The novel micro mixing method presented in this study provides a simple solution to mixing problems in microsystem for application in chemistry.

Keywords: micro oscillator, modeling, micro mixture, diffusion, size effect, chemical equation

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20351 Code-Switching and Code Mixing among Ogba-English Bilingual Conversations

Authors: Ben-Fred Ohia

Abstract:

Code-switching and code-mixing are linguistic behaviours that arise in a bilingual situation. They limit speakers in a conversation to decide which code they should use to utter particular phrases or words in the course of carrying out their utterance. Every human society is characterized by the existence of diverse linguistic varieties. The speakers of these varieties at some points have various degrees of contact with the non-speakers of their variety, which one of the outcomes of the linguistic contact is code-switching or code-mixing. The work discusses the nature of code-switching and code-mixing in Ogba-English bilinguals’ speeches. It provides a detailed explanation of the concept of code-switching and code-mixing and explains the typology of code-switching and code-mixing and their manifestation in Ogba-English bilingual speakers’ speeches. The findings reveal that code-switching and code-mixing are functionally motivated and being triggered by various conversational contexts.

Keywords: bilinguals, code-mixing, code-switching, Ogba

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20350 The Effects of Different Types of Cement on the Permeability of Deep Mixing Columns

Authors: Mojebullah Wahidy, Murat Olgun

Abstract:

In this study, four different types of cement are used to investigate the permeability of DMC (Deep Mixing Column) in the clay. The clay used in this research is in the kaolin group, and the types of cement are; CEM I 42.5.R. normal portland cement, CEM II/A-M (P-L) pozzolan doped cement, CEM III/A 42.5 N blast furnace slag cement and DMFC-800 fine-grained portland cement. Firstly, some rheological tests are done on every cement, and a 0.9 water/cement ratio is selected as the appropriate ratio. This ratio is used to prepare the small-scale DMCs for all types of cement with %6, %9, %12, and %15, which are determined as the dry weight of the clay. For all the types of cement, three samples were prepared in every percentage and were kept on curing for 7, 14, and 28 days for permeability tests. As a result of the small-scale DMCs, permeability tests, a %12 selected for big-scale DMCs. A total of five big scales DMC were prepared by using a %12-cement and were kept for 28 days curing for permeability tests. The results of the permeability tests show that by increasing the cement percentage and curing time of all DMCs, the permeability coefficient (k) is decreased. Despite variable results in different cement ratios and curing time in general, samples treated by DMFC-800 fine-grained cement have the lowest permeability coefficient. Samples treated with CEM II and CEM I cement types were the second and third lowest permeable samples. The highest permeability coefficient belongs to the samples that were treated with CEM III cement type.

Keywords: deep mixing column, rheological test, DMFC-800, permeability test

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20349 A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model

Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

Abstract:

The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: DBSCAN, potential function, speech signal, the UBSS model

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20348 Genetic Algorithm Based Deep Learning Parameters Tuning for Robot Object Recognition and Grasping

Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

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20347 Settlement of the Foundation on the Improved Soil: A Case Study

Authors: Morteza Karami, Soheila Dayani

Abstract:

Deep Soil Mixing (DSM) is a soil improvement technique that involves mechanically mixing the soil with a binder material to improve its strength, stiffness, and durability. This technique is typically used in geotechnical engineering applications where weak or unstable soil conditions exist, such as in building foundations, embankment support, or ground improvement projects. In this study, the settlement of the foundation on the improved soil using the wet DSM technique has been analyzed for a case study. Before DSM production, the initial soil mixture has been determined based on the laboratory tests and then, the proper mix designs have been optimized based on the pilot scale tests. The results show that the spacing and depth of the DSM columns depend on the soil properties, the intended loading conditions, and other factors such as the available space and equipment limitations. Moreover, monitoring instruments installed in the pilot area verify that the settlement of the foundation has been placed in an acceptable range to ensure that the soil mixture is providing the required strength and stiffness to support the structure or load. As an important result, if the DSM columns touch or penetrate into the stiff soil layer, the settlement of the foundation can be significantly decreased. Furthermore, the DSM columns should be allowed to cure sufficiently before placing any significant loads on the structure to prevent excessive deformation or settlement.

Keywords: deep soil mixing, soil mixture, settlement, instrumentation, curing age

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20346 An Event Relationship Extraction Method Incorporating Deep Feedback Recurrent Neural Network and Bidirectional Long Short-Term Memory

Authors: Yin Yuanling

Abstract:

A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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20345 Innovative Method for Treating Oil-Produced Water with Low Operating Cost

Authors: Maha Salman, Gada Al-Nuwaibit, Ahmed Al-Haji, Saleh Al-Haddad, Abbas Al-Mesri, Mansour Al-Rugeeb

Abstract:

The high salinity of oil-produced water and its complicated chemical composition, makes designing a suitable treatment system for oil-produced water is extremely difficult and costly. On the current study, a new innovative method was proposed to treat the complicated oil-produced water through a simple mixing with brine stream produced from waste water treatment plant. The proposal will investigate the scaling potential of oil-produce water, seawater and the selected brine water (BW) produced from Sulaibiya waste water treatment and reclamation plant (SWWTRP) before and after the mixing with oil-produced water, and will calculate the scaling potential of all expected precipitated salts using different conversion and different % of mixing to optimize the % of mixing between the oil-produced water and the selected stream. The result shows a great, feasible and economic solution to treat oil produced with a very low capital cost.

Keywords: brine water, oil-produced water, scaling potential, Sulaibiyah waste water and reclaminatin plant

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20344 Experimental Investigations on the Mechanism of Stratified Liquid Mixing in a Cylinder

Authors: Chai Mingming, Li Lei, Lu Xiaoxia

Abstract:

In this paper, the mechanism of stratified liquids’ mixing in a cylinder is investigated. It is focused on the effects of Rayleigh-Taylor Instability (RTI) and rotation of the cylinder on liquid interface mixing. For miscible liquids, Planar Laser Induced Fluorescence (PLIF) technique is applied to record the concentration field for one liquid. Intensity of Segregation (IOS) is used to describe the mixing status. For immiscible liquids, High Speed Camera is adopted to record the development of the interface. The experiment of RTI indicates that it plays a great role in the mixing process, and meanwhile the large-scale mixing is triggered, and subsequently the span of the stripes decreases, showing that the mesoscale mixing is coming into being. The rotation experiments show that the spin-down process has a great role in liquid mixing, during which the upper liquid falls down rapidly along the wall and crashes into the lower liquid. During this process, a lot of interface instabilities are excited. Liquids mix rapidly in the spin-down process. It can be concluded that no matter what ways have been adopted to speed up liquid mixing, the fundamental reason is the interface instabilities which increase the area of the interface between liquids and increase the relative velocity of the two liquids.

Keywords: interface instability, liquid mixing, Rayleigh-Taylor Instability, spin-down process, spin-up process

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20343 Foot Recognition Using Deep Learning for Knee Rehabilitation

Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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20342 A Corpus-Based Analysis on Code-Mixing Features in Mandarin-English Bilingual Children in Singapore

Authors: Xunan Huang, Caicai Zhang

Abstract:

This paper investigated the code-mixing features in Mandarin-English bilingual children in Singapore. First, it examined whether the code-mixing rate was different in Mandarin Chinese and English contexts. Second, it explored the syntactic categories of code-mixing in Singapore bilingual children. Moreover, this study investigated whether morphological information was preserved when inserting syntactic components into the matrix language. Data are derived from the Singapore Bilingual Corpus, in which the recordings and transcriptions of sixty English-Mandarin 5-to-6-year-old children were preserved for analysis. Results indicated that the rate of code-mixing was asymmetrical in the two language contexts, with the rate being significantly higher in the Mandarin context than that in the English context. The asymmetry is related to language dominance in that children are more likely to code-mix when using their nondominant language. Concerning the syntactic categories of code-mixing words in the Singaporean bilingual children, we found that noun-mixing, verb-mixing, and adjective-mixing are the three most frequently used categories in code-mixing in the Mandarin context. This pattern mirrors the syntactic categories of code-mixing in the Cantonese context in Cantonese-English bilingual children, and the general trend observed in lexical borrowing. Third, our results also indicated that English vocabularies that carry morphological information are embedded in bare forms in the Mandarin context. These findings shed light upon how bilingual children take advantage of the two languages in mixed utterances in a bilingual environment.

Keywords: bilingual children, code-mixing, English, Mandarin Chinese

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20341 Longitudinal Vortices Mixing in Three-Stream Micromixers with Two Inlets

Authors: Yi-Tun Huang, Chih-Yang Wu, Shu-Wei Huang

Abstract:

In this work, we examine fluid mixing in a full three-stream mixing channel with longitudinal vortex generators (LVGs) built on the channel bottom by numerical simulation and experiment. The effects of the asymmetrical arrangement and the attack angle of the LVGs on fluid mixing are investigated. The results show that the micromixer with LVGs at a small asymmetry index (defined by the ratio of the distance from the center plane of the gap between the winglets to the center plane of the main channel to the width of the main channel) is superior to the micromixer with symmetric LVGs and that with LVGs at a large asymmetry index. The micromixer using five mixing modules of the LVGs with an attack angle between 16.5 degrees and 22.5 degrees can achieve excellent mixing over a wide range of Reynolds numbers. Here, we call a section of channel with two pairs of staggered asymmetrical LVGs a mixing module. Besides, the micromixer with LVGs at a small attack angle is more efficient than that with a larger attack angle when pressure losses are taken into account.

Keywords: microfluidics, mixing, longitudinal vortex generators, two stream interfaces

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20340 Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds

Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

Abstract:

Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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20339 Effect of Using Baffles Inside Spiral Micromixer

Authors: Delara Soltani, Sajad Alimohammadi, Tim Persoons

Abstract:

Microfluidic technology reveals a new area of research in drug delivery, biomedical diagnostics, and the food and chemical industries. Mixing is an essential part of microfluidic devices. There is a need for fast and homogeneous mixing in microfluidic devices. On the other hand, mixing is difficult to achieve in microfluidic devices because of the size and laminar flow in these devices. In this study, a hybrid passive micromixer of a curved channel with obstacles inside the channel is designed. The computational fluid dynamic method is employed to solve governing equations. The results show that using obstacles can improve mixing efficiency in spiral micromixers. the effects of Reynolds number, number, and position of baffles are investigated. In addition, the effect of baffles on pressure drop is presented. this novel micromixer has the potential to utilize in microfluidic devices.

Keywords: CFD, micromixer, microfluidics, spiral, reynolds number

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20338 Health Trajectory Clustering Using Deep Belief Networks

Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

Abstract:

We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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20337 Black-Box-Base Generic Perturbation Generation Method under Salient Graphs

Authors: Dingyang Hu, Dan Liu

Abstract:

DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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20336 Mentha piperita Formulations in Natural Deep Eutectic Solvents: Phenolic Profile and Biological Activity

Authors: Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović, Boris M. Popović

Abstract:

Natural deep eutectic solvents (NADES) represent a class of modern systems that have been developed as a green alternative to toxic organic solvents, which are commonly used as extraction media. It has been considered that hydrogen bonding is the main interaction leading to the formation of NADES. The aim of this study was phytochemical characterization and determination of the antioxidant and antibacterial activity of Mentha piperita leaf extracts obtained by six choline chloride-based NADES. NADES were prepared by mixing choline chloride with different hydrogen bond donors in 1:1 molar ratio following the addition of 30% (w/w) water. The mixtures were then heated (60 °C) and stirred (650 rpm) until the clear homogenous liquids were obtained. The Mentha piperita extracts were prepared by mixing 75 mg of peppermint leaves with 1 mL of NADES following by the heating and stirring (60 °C, 650 rpm) within 30 min. The content of six phenolics in extracts was determined using HPLC-PDA. The dominant compounds presented in peppermint leaves - rosmarinic acid and luteolin 7-O-glucoside, were extracted by NADES at a similar level as 70% ethanol. The microdilution method was applied to test the antibacterial activity of extracts. Compared with 70% ethanol, all NADES systems showed higher antibacterial activity towards Pseudomonas aeruginosa (Gram -), Staphylococcus aureus (Gram +), Escherichia coli (Gram -), and Salmonella enterica (Gram -), especially NADES containing organic acids. The majority of NADES extracts showed a better ability to neutralize DPPH radical than conventional solvent and similar ability to reduce Fe3+ to Fe2+ ions in FRAP assay. The obtained results introduce NADES systems as the novel, sustainable, and low-cost solvents with a variety of applications.

Keywords: antibacterial activity, antioxidant activity, green extraction, natural deep eutectic solvents, polyphenols

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20335 Mechanistic Modelling to De-risk Process Scale-up

Authors: Edwin Cartledge, Jack Clark, Mazaher Molaei-Chalchooghi

Abstract:

The mixing in the crystallization step of active pharmaceutical ingredient manufacturers was studied via advanced modeling tools to enable a successful scale-up. A virtual representation of the vessel was created, and computational fluid dynamics were used to simulate multiphase flow and, thus, the mixing environment within this vessel. The study identified a significant dead zone in the vessel underneath the impeller and found that increasing the impeller speed and power did not improve the mixing. A series of sensitivity analyses found that to improve mixing, the vessel had to be redesigned, and found that optimal mixing could be obtained by adding two extra cylindrical baffles. The same two baffles from the simulated environment were then constructed and added to the process vessel. By identifying these potential issues before starting the manufacture and modifying the vessel to ensure good mixing, this study mitigated a failed crystallization and potential batch disposal, which could have resulted in a significant loss of high-value material.

Keywords: active pharmaceutical ingredient, baffles, computational fluid dynamics, mixing, modelling

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20334 Energy Potential of Salinity Gradient Mixing: Case Study of Mixing Energies of Rivers of Goa with the Arabian Sea

Authors: Arijit Chakraborty, Anirban Roy

Abstract:

The Indian peninsula is strategically located in the Asian subcontinent with the Himalayas to the North and Oceans surrounding the other three directions with annual monsoons which takes care of water supply to the rivers. The total river water discharge into the Bay of Bengal and the Arabian Sea is 628 km³/year and 274 km³/year, respectively. Thus huge volumes of fresh water meet saline water, and this mixing of two streams of dissimilar salinity gives rise to tremendous mixing energies which can be harvested for various purposes like energy generation using pressure retarded osmosis or reverse electrodialysis. The present paper concentrates on analyzing the energy of mixing for the rivers in Goa. Goa has 10 rivers of various sizes all which meet the Arabian Sea. In the present work, the 8 rivers and their salinity (NaCl concentrations) have been analyzed along with their seasonal fluctuations. Next, a Gibbs free energy formulation has been implemented to analyze the energy of mixing of the selected rivers. The highest and lowest energies according to the seasonal fluctuations have been evaluated, and this provides two important insights into (i) amount of energy that can be harvested and (ii) decision on the location of such systems.

Keywords: Gibbs energy, mixing energy, salinity gradient energy, thermodynamics

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20333 Robot Movement Using the Trust Region Policy Optimization

Authors: Romisaa Ali

Abstract:

The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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20332 Assessment of Frying Material by Deep-Fat Frying Method

Authors: Brinda Sharma, Saakshi S. Sarpotdar

Abstract:

Deep-fat frying is popular standard method that has been studied basically to clarify the complicated mechanisms of fat decomposition at high temperatures and to assess their effects on human health. The aim of this paper is to point out the application of method engineering that has been recently improved our understanding of the fundamental principles and mechanisms concerned at different scales and different times throughout the process: pretreatment, frying, and cooling. It covers the several aspects of deep-fat drying. New results regarding the understanding of the frying method that are obtained as a results of major breakthroughs in on-line instrumentation (heat, steam flux, and native pressure sensors), within the methodology of microstructural and imaging analysis (NMR, MRI, SEM) and in software system tools for the simulation of coupled transfer and transport phenomena. Such advances have opened the approach for the creation of significant information of the behavior of varied materials and to the event of latest tools to manage frying operations via final product quality in real conditions. Lastly, this paper promotes an integrated approach to the frying method as well as numerous competencies like those of chemists, engineers, toxicologists, nutritionists, and materials scientists also as of the occupation and industrial sectors.

Keywords: frying, cooling, imaging analysis (NMR, MRI, SEM), deep-fat frying

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20331 Mixing Behaviors of Shear-Thinning Fluids in Serpentine-Channel Micromixers

Authors: Rei-Tang Tsai, Chih-Yang Wu, Chia-Yuan Chang, Ming-Ying Kuo

Abstract:

This study aims to investigate the mixing behaviors of deionized (DI) water and carboxymethyl cellulose (CMC) solutions in C-shaped serpentine micromixers over a wide range of flow conditions. The flow of CMC solutions exhibits shear-thinning behaviors. Numerical simulations are performed to investigate the effects of the mean flow speed, fluid properties and geometry parameters on flow and mixing in the micromixers with serpentine channel of the same overall channel length. From the results, we can find the following trends. When fluid mixing is dominated by convection, the curvature-induced vortices enhance fluid mixing effectively. The mixing efficiency of a micromixer consisting of semicircular C-shaped repeating units with a smaller center-line radius is better than that of a micromixer consisting of major-segment repeating units with a larger center-line radius. The viscosity of DI water is less than the overall average apparent viscosity of CMC solutions, and so the effect of curvature-induced vortices on fluid mixing in DI water is larger than that in CMC solutions for the cases with the same mean flow speed.

Keywords: curved channel, microfluidics, mixing, non-newtonian fluids, vortex

Procedia PDF Downloads 413