01. School of Engineering and Digital Sciences
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Item Open Access 2D SKELETON-BASED HUMAN ACTION RECOGNITION USING ACTION-SNIPPET REPRESENTATION AND DEEP SEQUENTIAL NEURAL NETWORK(Nazarbayev University School of Engineering and Digital Sciences, 2022-05) Askar, AizadaHuman action recognition is one of the crucial and important tasks in data science. It aims to understand human behavior and assign a label on performed action and has diverse applications. Domains, where this application is used, includes visual surveillance, human–computer interaction and video retrieval. Hence, discriminating human actions is a challenging problem with a lot of issues like motion performance, occlusions and dynamic background, and different data representations. There are many researches that explore various types of approaches for human action recognition. In this work we propose advanced geometric features and adequate deep sequential neural networks (DSNN) for 2D skeleton-based HAR. The 2D skeleton data used in this project are extracted from RGB video sequences, allowing the use of the proposed model to enrich contextual information. The 2D skeleton joint coordinates of the human are used to capture the spatial and temporal relationship between poses. We employ BiLSTM and Transformer models to classify human actions as they are capable of concurrently modeling spatial relationships between geometric characteristics of different body parts.Item Restricted 2D/3D NOVEL MATERIALS FOR HIGH PERFORMANCE PEROVSKITE SOLAR CELLS(Nazarbayev University School of Engineering and Digital Sciences, 2022-04) Aidarkhanov, DamirThe continuous increase of energy demand and emission of greenhouse gases from the conventional fossil fuels signifies the importance of renewable energy. The solar radiation is a readily available renewable energy source. If the amount of solar energy irradiated on the earth can be converted into electrical energy very efficiently, the energy demand of our daily life can be satisfied. The photovoltaics (i.e. solar cells) are the devices directly converting the solar irradiation into the electrical energy. Among the existing photovoltaic technologies, the metal halide perovskite solar cells (PSCs) demonstrate a huge potential of realizing cost-effective and high-performance devices for future practical applications. The theoretical calculations demonstrate that a single junction PSC can reach a power conversion efficiency (PCE) above 30%. However, there are still a number of challenges hindering the commercialization of PSCs for the practical use. This work focuses on enhancing the performance of PSCs via application of novel 2D/3D materials and engineering of device architectures. A multilayer structure for electron-transporting layer (ETL) has been developed for high performance PSCs. It is shown that a triple-layer ETL consisted of SnO2 quantum dots, SnO2 nanoparticles, and fullerene-derivative based passivation layer can facilitate the carrier transports due to optimization of surface morphology of ETL which yields a better interface quality for subsequently deposited perovskite absorber layer. The defect states residing the interface between the ETL and perovskite are also reduced by optimizing the architecture of ETL in PSCs. Further, a two-dimensional material, black phosphorus (BP) in form of nanoflakes was used to modify the interface between the ETL and the perovskite layer. The application of BP in PSCs demonstrates an increase of the device efficiency and stability. The positive effect introduced by BP is attributed to the improved perovskite crystallization on BP modified ETL and passivation of interfacial defects by lone-pair electrons of BP. Meanwhile, the photovoltaic properties of multiple cations mixed-halide perovskite layer can be improved by incorporation of a cross-linking material, 2,2′-(Ethylenedioxy) bis(ethylammonium iodide). The PSCs incorporated with an optimized concentration of cross-linking material demonstrate an enhancement of PCE and improvement in stability, which are attributed to the passivation of the defect states located at the surface and grain boundaries of perovskite by the cross-linking molecules. The cross linker assisted crystallization also leads to the formation of compact perovskite thin films, which could suppress the penetration of various species such as moisture, oxygen etc. from the atmosphereItem Open Access 3D CFD-DEM-IBM SIMULATIONS OF SAND PRODUCTION IN OIL WELLS(Nazarbayev University School of Engineering and Digital Sciences, 2021-09-16) Rakhimzhanova, AigerimSand production is particularily prominent in sandstone reservoirs, which are common to observe in the majority of oil and gas fields. When sand particles start to erode from weak sandstone formations for different reasons, their impact could lead to the decline of the production flow rate and equipment degradation, which will results in a huge economical loss. In some cases, it results in the end of production life of a well and reservoir. The key to overcome this problem and achieve accurate prediction of sand production may lie in the understanding of the cause of sanding mechanism. The current numerical approaches to predict the sanding mechanism are based on continuum and non-continuum models. The majority of developed models are based on the continuum approach, while a few discontinuum-based (DEM – Discrete Element Method) have been developed in the last two decades. Sand production is a dynamic and continuous process, which starts from microscopic scales where the rock is discontinuous in nature. It is impossible to capture local discontinuous phenomena using continuum-based models. The DEM models can capture the interaction and motion of each sand grain, the failure micro mechanism in a dynamic process at micro and macro scales, which makes it possible to simulate the sanding phenomena. In this research the DEM is firstly used for the rock characterization, where a simple 3D bond contact model for cemented sandstone material is developed by modifying the previous existing JKR (Johnson-Kendall-Roberts) model for auto-adhesive silt size sand particles, and the model parameter is the bond strength in terms of the interface energy. The material properties of the synthetic sandstone specimens equivalent to the Ustyurt-Buzachi Sedimentary Basin core samples were reproduced for the numerical specimens and the triaxial compression test results show that the numerically simulated macroscopic response is in good agreement with the experimental results of the cemented sandstone. The main aim of this research is to develop the sample preparation procedure/method with physical perforation penetration and sand production modelling in a periodic cell and by developing and using the combined 3D CFD-DEM-IBM modelling techniques (CFD – Computational Fluid Dynamics; IBM – Immersed Boundary Method). The application of the IBM is proposed to simulate the complex interaction between the geometry of the cased horizontal well completion opening and the weakly cemented sandstone under the overburden pressure and drawdown. The capability of developed methods to capture sand arching, damage zone (due to the perforation penetration) and sanding mechanism (erosion near the perforation hole) due to the pressure drawdown are presented. This study shows the mechanism of sand production in a bottom-up approach in the first 0.1 sec of sanding initiation immediately after the perforation penetration in oil wells, which will help engineers to better understand the sanding mechanism at the micro levels and how the problem of sanding can eventually be overcome though better insight into the phenomenon.Item Open Access A 3d multidisciplinary automated design optimization toolbox for wind turbine blades based on ns solver and experimental data(Nazarbayev University School of Engineering and Digital Sciences, 2018) Sagimbayev, SagiThis thesis attempts to develop a framework to optimize wind turbine blades automatically by a multidisciplinary 3D modeling and simulation methods. The original NREL Phase VI wind turbine blade and its experimental measurements are used to validate the Computational Fluid Dynamics (CFD) model developed in ANSYS Fluent and based on the 3D Navier-Stokes (NS) solver with a realizable k-epsilon turbulence model, which is later used in the automation process. The automated design optimization process involves multiple modeling and simulation methods using Solidworks and ANSYS Mesher and ANSYS Fluent NS solver, which are integrated and controlled through Matlab by implementing the scripting capabilities of each software package. Then all scripts are integrated into one optimization cycle, with its optimization objective being the highest mean value of 3D Lift/Drag ratio (3DLDR) across the blade. A 3DLDR distribution across the blade can be calculated by the Inverse Blade Element Momentum (IBEM) Method based on experimental measurements. The optimization process is performed to find optimized twist angles across the blade using the Angle of Attack (AOA) with the highest 3DLDR as a reference, in order to 3 achieve the optimization objective. Therefore, the automatic optimization framework is based on 3D solid modeling and 3D aerodynamic simulation and guided by IBEM and experimental data. Thus the design tool is capable of exploiting the 3D stall delay of blades designed by the traditional 2D BEM method to enhance their performances. It is found that this automated framework can result in optimized blade geometries with the improvement of performance parameters compared to the original ones.Item Open Access 3D PRINTING OF BIOCOMPATIBLE CRYOGELS FOR BONE TISSUE ENGINEERING(School of Engineering and Digital Sciences, 2023) Moazzam, MuhammadNatural biopolymers are highly valued and commonly utilized in tissue engineering to create scaffolds that support living cells. This is due to their exceptional biocompatibility and the fact that their degradation rate can be controlled. However, the shape and average pore size are crucial in biological processes that influence the kinetics of cell proliferation and tissue regeneration processes linked to the production of extracellular matrix. For the construction of high-accuracy hydrogel scaffolds via 3D printing, the shear thinning characteristics of the bioinks used frequently result in morphological compromises like smaller pore diameters. Here, we introduced a new mixture of gelatin and oxidized alginate (Gel/OxAlg) that has been optimized for use in 3D printing and cryogelation techniques. This composite formulation allows for the creation of highly porous and biocompatible hydrogel scaffolds with extra-large pore sizes (d > 100 μm) using a combination of 3D printing and cryogelation techniques. These scaffolds have the potential to serve as a platform for various tissue engineering applications, and their morphological properties and cell viability data can be tailored accordingly. Overall, our approach offers a simple and cost-effective method for constructing hydrogel scaffolds with high accuracy.Item Restricted 3D PRINTING OF GELATIN/OXIDIZED CARBOXYMETHYL CELLULOSE SCAFFOLDS WITH GRADIENT POROSITY FOR BONE TISSUE REGENERATION APPLICATIONS(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-23) Dyussenbinov, AibekThis master thesis investigates the development and evaluation of 3D-printed gelatin/oxidized carboxymethyl cellulose (OxCMC) scaffolds with gradient porosity for applications in bone tissue regeneration. Recognizing the limitations of current bone repair methodologies, this research aims to mimic the natural extracellular matrix of bone through advanced scaffold engineering techniques. The thesis explores the synthesis and optimization of bioinks from gelatin and OxCMC, chosen for their biocompatibility, biodegradability, and mechanical properties conducive to 3D printing. Through extensive experimentation, including rheological tests, Fourier-transform infrared spectroscopy (FTIR) analysis, and scanning electron microscopy (SEM) imaging, scaffold formulations were tailored to achieve desired porosity gradients and mechanical strength. The novel approach of utilizing a complex 3D printing model with different pinheads for varying ink compositions is highlighted as a key innovation. This method allowed for the creation of scaffolds that not only support cell adhesion and proliferation but also replicate the porosity gradient inherent to natural bone, thereby addressing a critical aspect of scaffold design in bone tissue engineering. Results indicated a direct correlation between the polymer content in the scaffolds and their swelling ability, degradation rates, and mechanical properties. Scaffolds with higher polymer content showed less swelling but greater mechanical strength, aligning with the requirements for supporting bone tissue regeneration. The gradient scaffold, in particular, demonstrated a balance between swelling behavior and mechanical integrity, suggesting its suitability for bone tissue engineering applications. This research contributes to the field of regenerative medicine by offering a promising scaffold design strategy for bone tissue regeneration. By closely mimicking the structural and mechanical properties of natural bone, the developed scaffolds hold potential for improving the outcomes of bone repair and regeneration procedures, paving the way for future clinical applications.Item Open Access 3D-PRINTED OSTEOCHONDRAL GRAFTS AND THEIR CHARACTERIZATION(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-25) Effanga, Victoria EffiongThe osteochondral (OC) interface is a complex tissue with a hierarchical structure found at the ends of the bones of the knee joint consisting of a layer of soft tissue (cartilage) overlaying hard tissue in the subchondral bone. It exhibits a gradient of its constituents, especially in terms of mineral concentration, cell phenotype, collagens, and glycosaminoglycans, with a thickness of around 0.5 mm. The tidemark, a critical yet often overlooked component of OC interface tissue, plays a pivotal role in maintaining tissue function by acting as a barrier against vascular invasion of the cartilage. Fabricating scaffolds that mimic the complex physiology and functionalities of the OC tissue within the physiological thickness remains a challenge. This study aimed at fabricating a unitary composite scaffold that is similar of the OC interface in terms of distribution of its mineral content. It was hypothesized that the interface formed between the layers of the multilayer graft will possess a thickness of hydroxyapatite (HAP) gradient similar to that seen at the native rabbit OC tissue. To test the hypothesis, a multilayer composite OC graft was fabricated using gelatin and oxidized alginate (OXA) compositions with and without HAP for the bone and cartilage regions, respectively, and a gradient of HAP was formed in between. The two layers were formed using a 3D bioprinting method, while a porous electrospun mesh of polycaprolactone was placed in the graded region between cartilage and bone to represent the tidemark. The change in mineral content across the rabbit OC interface tissue and the OC graft interface was investigated using energy dispersive X-ray (EDX) and micro computed tomography (CT) characterization. The printability of the bioinks was verified by a strain sweep test, and volumetric expansion of both inks, with and without HAP, was examined using a swelling test. Findings revealed that both bioinks exhibited a shear thinning behavior. In addition, swelling test showed that both inks possessed similar volumetric expansion when immersed in water, demonstrating its feasibility to be used as a defect filler. EDX scan for calcium (Ca) and phosphorus (P) verified the gradient of mineral in both OC grafts and native rabbit OC tissue. The CT characterization verified a HAP gradient created in the OC graft within 168m thickness similar to the mineral gradient thickness determined for rabbit OC interface. Furthermore, the electrospun membrane was found to have pore diameters less than 1m that is sufficient to prevent vascular invasion of the articular cartilage tissue. Overall, the OC graft fabricated using combined bioprinting and electrospinning techniques demonstrated a potential to serve as a biomimetic hydrogel filler for regenerating OC defects to restore the function of the knee joint. It is expected that the proposed OC graft will be effectively used to address a significant clinical problem that affects millions of people, with significant societal and economic impacts.Item Restricted 60 GHZ PHASED ARRAY PHASE SHIFTER DESIGN FOR 5G APPLICATION(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-24) Shaimerden, YernurThe purpose of this research work is to design a phase shifter and antenna for integration into a 60 GHz phased array transceiver designed specifically for 5G applications. A phased array transceiver consists of an active device (e.g. amplifier), phased array matrix, and antenna. This thesis focuses on the design of a 60 GHz phased antenna array with no active device. A butler matrix is implemented for the phased array matrix. In the methodology part, the development process of the butler matrix and patch antenna is presented. In this study, various types of beamforming networks are examined and written in the literature review section. The fundamental components of the Butler matrix are systematically designed, showing each step of the process. At the implementation step, CST software was used. Design is implemented on a substrate material known as Rogers RT/duroid 5880, with a 0.127 mm thickness. The results indicate the good reflection coefficient at the operating frequency of 60 GHz. Proposed design with patch antenna results in four orthogonal beams, each directed at +5°, +37°, -37°, and −5°.Item Restricted ACTION-DRIVEN TACTILE OBJECT EXPLORATION FOR SHAPE RECONSTRUCTION VIA OPTICAL TACTILE SENSORS(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-19) Mussin, TleukhanWe introduce an action-driven tactile exploration system using novel optical tactile sensors integrated into the gripper of a robot arm. These sensors consist of multiple silicone layers, with one layer featuring alternating yellow and red patterns. When this layer deforms — typically by stretching and reducing in thickness—the colored patterns shift. These changes are captured by an onboard camera and analyzed using a Convolutional Neural Network (CNN) algorithm. The gripper for the sensor was specifically designed and 3D printed to ensure the sensors operate correctly. The colored part of the sensor was isolated from the external light. We tested the sensor’s effectiveness in edge detection and localization using four different geometric objects. We evaluated our system using a diverse collection of objects in both medium and large sizes.Item Restricted ACTIVE OBJECT TRACKING USING REINFORCEMENT LEARNING(Nazarbayev University School of Engineering and Digital Sciences, 2022-05) Alimzhanov, BexultanThe concept of "smart cities" has rapidly emerged as the means by which urban planners can improve the quality of life of citizens, providing better services at lower cost. Typical objectives include the optimization of traffic routing, the automatic detection of emergency "events" and related improvement in the response time of emergency services, and overall optimization of resource allocation and energy consumption. A core component of the smart city concept is the widespread deployment of closedcircuit cameras for purposes of monitoring and event detection. A typical application is to locate and track a vehicle as it moves through crowded urban scenarios. Usually, tracking and camera control tasks are separated, which induces problems for the construction of a coherent system. Reinforcement learning can be used to unify the systems, such that control and tracking can be resolved simultaneously. However, there are issues related to the collection and use of comprehensive real-world data sets for purposes of research. To avoid this problem, it is feasible to conduct the agent training using synthetic data, and then transfer the results to real-world settings. This approach also serves to address the issue of domain invariance. For the thesis, I investigate active object tracking using reinforcement learning by first developing a synthetic environment based on the videogame Cities: Skylines, using the extensive Unity engine, which accurately simulates vehicle traffic in urban settings. The complete system consisting of a trained object detector and a reinforcement learning agent is tuned in this environment with corresponding reward functions and action space. The resulting agent is capable of tracking the objects in the scene without relying on domain-specific data, such as spatial information. The thesis includes the creation of the synthetic environment, the development of the agent, and the evaluation of the resulting system.Item Restricted ADAPTING TO LEARNER’S COGNITIVE DIFFERENCES USING REINFORCEMENT LEARNING(Nazarbayev University School of Engineering and Digital Sciences, 2023) Nurgazy, Symbat; Issa, Ilyas; Kassymbekov, Saparkhan; Kuangaliyev, ZholamanItem Open Access ADDRESSES STANDARDIZATION AND GEOCODING USING NATURAL LANGUAGE PROCESSING(Nazarbayev University School of Engineering and Digital Sciences, 2022-07) Mussylmanbay, MeiirgaliGeocoding, the process of converting the textual addresses into a pair of coordinates, is a preliminary step in spatial analysis. However, converting addresses into latitude and longitude is not a trivial task as they are presented as arbitrary text, mostly lacking completeness, and do not follow a concrete fixed structure. Therefore, the thesis discusses the theoretical fundamentals of textual data normalization and standardization techniques and presents adequate practical approaches to how addresses written in various ways can be brought to a single standard. For binding the textual addresses with their appropriate geocodes, we have conducted practical experiments using the data collected from 5 publicly available sources and such tools as Elasticsearch, including its built-in BM25 similarity algorithm, as well as a state-of-the-art algorithm - BERT. Also, we have admitted Open Street Map address structure as a golden standard and cosine similarity algorithm as a text similarity algorithm. The practical outcomes of the models were verified on randomly chosen 100 records. The results were visualized on the map to illustrate the applicable cases of geocoding usage. Further, the raw address data and address standardization results serve as train and test data to predict the closest address and adequate geocodes for given arbitrary address representations. For the thesis, we used models based on Transformer architecture, namely T5 and BART, for predicting ’correct’ addresses. In addition, BLEU was used as a reference metric to compare the models’ accuracy. Overall, the thesis can boast rich theoretical background information and be a practical reference to how clean addresses can be revealed using state-of-the-art models given non-standard addresses.Item Open Access Adiabatically Tapered Fiber-Optic Microsensor: Fabrication and Characterization(Nazarbayev University School of Engineering and Digital Sciences, 2020-05) Yelikbayev, SultanAs of late, the various techniques from the materials science and biophysics are utilized to study the physical properties of the microstructure of the chemical and biological specimen. Through a considerable many of them give phenomenal sensibility, they have a few requirements concerning electromagnetic interference, fabrication complexity and specific laboratory conditions for operating. Hence, to overcome these constraints the new family of micro-scale fiber optical sensors was introduced. There are several methods to fabricate microfibers with different microtechbology. However, the techniques with more simple, economical and robust fabrication process are still developing. Therefore, this study proposes the fabrication process of widely interested tapered fiber optic microsensor via Laser Splicing System and characterization of produced tapered microfibers in terms of external RI sensitivity. The final product that was achieved is the fiber with the least waist diameter 19 mm has RI sensitivity of 156.8215 nm/RIU and agreeable linear correlation between the wavelength shift and RI change. In addition, the detailed fabrication process with characterization method is presented in the following sections. Moreover, the observed trends in fabrication process and recommendations based on the practice experience are also suggested in this report.Item Restricted ADOPTING VISUAL ODOMETRY FOR INDOOR MOBILE ROBOT LOCALIZATION(Nazarbayev University School of Engineering and Digital Sciences, 2022-04) Sharipov, MadiyarLocalization problem is one of the primary problems for robot indoor navigation. This work discusses different types of odometry and focuses on the visual one. It implements the localization system based on the RTAB-map and compares it with such a classical approach as AMCL. The paper contain the detailed explanation of robot design for localization system implementation.Item Open Access ADVANCED CIRCUIT CONFIGURATIONS FOR RF WIRELESS POWER TRANSFER(Nazarbayev University School of Engineering and Digital Sciences, 2024-04-26) Kudaibergenova, ZhanelTechnology for wireless power transfer (WPT) has gained more importance in the contemporary world. The upsurge spike can be a result of the WPT system's ability to power devices without the use of traditional connections. In particular, near-field WPTs have a wide range of applications, including wireless sensors, IoT, biomedical implants, RFID, and consumer electronics. It is essential to emphasize that the WPT system can be realized in a number of ways, one of which is a defected ground structure technique. This approach is well-established for its simple design process and compact system. Despite this recently developed DGS-based WPTs demonstrate poor performance, in other words, low power transfer efficiency in practical validations. The inevitable factors, such as imperfections of lumped elements, the in-house fabrication, and energy losses during transfer, have an impact on the experimental results. Therefore, various performance enhancement strategies have to be considered to realize the compact and efficient WPT system. In this regard, one of the promising methods for improving WPT operation is the use of metamaterial, which is an artificial material with unique electromagnetic features. As a result, this thesis work focuses on the development of compact and efficient WPTs applicable to various fields and on performance enhancement strategies based on metamaterial utilizationItem Restricted Advanced Circuit Configurations for RF Wireless Power Transfer(Nazarbayev University School of Engineering and Digital Sciences, 2024) Azhmuratov, SerikItem Restricted ADVANCING BLOOD SAMPLE ANALYSIS: INCORPORATING EXPERT OPINIONS AND EXPLAINABLE AI IN MULTI-LABEL DISEASE PREDICTION(Nazarbayev University School Engineering and Digital Sciences, 2024-04-19) Orynbay, Sultan; Akanova, Inabat; Turmakhan, Diana; Beken, Ulpan; Serikkazhy, IslamBlood sample analysis plays a crucial role in modern medical practice, aiding in the detection of a wide array of diseases. Despite its significance, the potential of blood samples for predicting various diseases has remained largely unexplored. Our project aimed to dive into evaluate the efficacy of blood samples in predicting a broad spectrum of disease using large-scale MIMIC III medical dataset. Given the sparse nature of the data, we combine imputation with multi-task models for which we identify and utilize meaningful auxiliary tasks and are thus able to reach an average state-of-the-art ROC-AUC score of 81% across the 50 most prevalent diseases within the dataset. To further validate our findings, we sought the expertise of five medical doctors, who independently rated the predictability of these diseases from blood samples. Spearman’s rho analysis revealed a substantial agreement ( = 0.61) between the doctors’ ratings and the actual ROCAUC values of our machine learning models. In order to add transparency and reliability, we employed the Local Interpretable Modelagnostic Explanations (LIME) method to identify the most predictive blood sample features. These findings were rigorously cross-checked with medical experts, affirming the robustness and credibility of our predictive models. Our study represents a significant advancement in the field of medical diagnostics, showcasing the untapped potential of blood sample analysis in disease prediction. By integrating cuttingedge machine learning techniques with expert validation, we pave the way for enhanced patient care and improved healthcare outcomes.Item Restricted Aerodynamic analysis of wind farms(Nazarbayev University School of Engineering and Digital Sciences, 2019) Duisenova, Alina; Badanova, NazymWind energy is one of the most promising types of renewable energy and is successfully integrated in our lives. Wind turbines were used in the past centuries, but utilizing the wind energy in a large amount started with the installation of thousands of wind turbines in California in the late 1980s ("History of wind power", 2019). Although the wind energy became popular there are problems causing the wind energy usage to lag behind the wind range of traditional fossil fuel usage. That is, wind turbine operation is not continuous as required because of the failures that cause unscheduled downtime during their intended design lifetime. These failures mainly include the component failures, especially the rotor blades. Rotor blades are ones of the most critical components, what is being verified by the statistics showing 3800 incidents of blade failure each year out of an estimated 700 000 blades operating globally (Dvorak, 2019). The reasons and technical information about such structural failures of rotor blades are not discussed in the media and rarely reported in academic literature because of the unavailability of the technical data due to commercial confidentiality. Meanwhile, this problem became the topic of a great interest for many researchers all around the world.Item Open Access Aerosol formation in CO2 capture plants - molecular dynamics simulation(Nazarbayev University School of Engineering and Digital Sciences, 2017-12) Mansurov, UlanCarbon dioxide capture is becoming a major concern not only from the perspective of traditional sour gas sweetening but also because of adverse effects of CO2 on climate change. The most conventional method to eliminate CO2 is carried out in a post-combustion CO2 capture (PCCC) column using aqueous monoethanolamine (MEA) as a solvent. Numerous reports have manifested significant amount of solvent losses due to formation of aerosols in PCCC columns. This research provides insights into formation mechanisms of aerosols or particulate matter (PM) at a molecular level by emphasizing interaction parameters between participating components. Molecular dynamics (MD) simulations were performed using GROMACS software. Five different systems under ordinary PCCC conditions were considered each of which has unique configuration of components. MD simulations revealed evolution and development of molecular clusters that formed PM which consisted of all gaseous MEA, SO2, major portion of CO2, and water vapor. Furthermore, quantitative analysis of the molecular clusters was carried out in terms of CO2 molecules. Nucleation rates of PM were in the order of 10-30 cm-3s-1. Also, formed aerosol particles were structurally examined using radial distribution functions (RDF) and determining pair potentials between the molecules. It was found that MEA in vapor phase contributes to PM formation. Furthermore, strong attraction potential between water and CO2 and MEA imply that the presence of water in vapor phase might be one of the key factors that forms and sustains PM. Taken together, the results are first of the efforts to understand PM (aerosol) formation in a typical PCCC column based on molecular simulations, and based on the findings of the study, certain practical suggestions were offered to avoid formation of PM.Item Open Access Aerosol formation in CO2 capture plants – aspen plus simulation model(Nazarbayev University School of Engineering and Digital Sciences, 2017-12) Galymzhanov, NursultanOne of the most promising technologies available for decreasing CO2 concentration in the atmosphere is Post Combustion CO2 Capture (PCCC). The process is based on absorption-desorption of carbon dioxide by a solvent. Amine based aqueous solutions are considered as the state of the art solvent for PCCC. However, its use is associated with MEA emissions from an absorber column through vapour and aerosol phases. Aerosol emission has only recently been detected, and reported to be related to the degree of supersaturation of gas. The objective of this study was to develop a new conceptual model to estimate heat and mass transfer rates between gas and particulate phases using Aspen Plus simulation software. Also, validation of the model was performed by comparing it with results of an experimental mini-plant developed by TNO group in Netherlands. In the model presented in this study, interaction between the gas and the solvent, and the gas and the particles was split by modelling the gas-solvent interaction in the absorber and the gas-particles interaction in separate absorber columns representing sections of a discretised absorber. A method was presented to estimate particle formation due to nucleation and to correct the MEA loss predicted by Aspen Plus. The CO2 removal efficiency was estimated to be 95%. The estimated total molecular mass transfer rate from the gas phase at the top of the absorber column to the particle phase was found to be -7.3×10-10 kg/s, indicating net molecular mass transfer from the particle to the gas phase. The mass transfer due to nucleation was estimated to be 1.92487×10-6 kg/s. The amount of particle phase MEA emission was found to depend on the temperature inside the absorber, temperature bulge, gas supersaturation ratio, volume of particles entering the absorber and H2SO4 concentration in the entering gas. The particle phase MEA emission due to the molecular mass transfer from the gas phase to the particle phase was found to be 0.3 mg/Nm3gas, while particle phase MEA emission resulted from the nucleation mass transfer was 697.0 mg/Nm3gas. Thus, the total particle MEA emission was estimated to be 697.3 mg/Nm3gas. The estimated nucleation rate is approximately 2×1015 particles.cm-3.s-1. Gas phase MEA emission was found to be 1.3 mg/Nm3gas.