Search results for: reactor model

Authors: Urmi Khatri

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Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Abdelouaheb Rouabhi

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In order to study the plastic resource of structures, the elastic-plastic single degree of freedom model described by Prandtl diagram is widely used. The generalization of this model to tow degree of freedom beyond the scope of a simple rigid-plastic system allows investigating the plastic resource of structures under complex disproportionate by individual components of deformation (earthquake). This macro-model greatly increases the accuracy of the calculations carried out. At the same time, the implementation of the proposed macro-model calculations easier than the detailed dynamic elastic-plastic calculations existing software systems such as ANSYS.

Keywords: elastic-plastic, single degree of freedom model, rigid-plastic system, plastic resource, complex plastic deformation, macro-model

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Arash Rafiei, Carroll Moore

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Leaching process as the first stage of hydrometallurgy is a multidisciplinary system including material properties, chemistry, reactor design, mechanics and fluid dynamics. Therefore, doing leaching system optimization by pure scientific methods need lots of times and expenses. In this work, a mixture of two titanium ores and one titanium slag are used for extracting titanium for leaching stage of TiO2 pigment production procedure. Optimum titanium extraction can be obtained from following strategies: i) Maximizing titanium extraction without selective digestion; and ii) Optimizing selective titanium extraction by balancing between maximum titanium extraction and minimum impurity digestion. The main difference between two strategies is due to process optimization framework. For the first strategy, the most important stage of production process is concerned as the main stage and rest of stages would be adopted with respect to the main stage. The second strategy optimizes performance of more than one stage at once. The second strategy has more technical complexity compared to the first one but it brings more economical and technical advantages for the leaching system. Obviously, each strategy has its own optimum operational zone that is not as same as the other one and the best operational zone is chosen due to complexity, economical and practical aspects of the leaching system. Experimental design has been carried out by using Taguchi method. The most important advantages of this methodology are involving different technical aspects of leaching process; minimizing the number of needed experiments as well as time and expense; and concerning the role of parameter interactions due to principles of multifactor-at-time optimization. Leaching tests have been done at batch scale on lab with appropriate control on temperature. The leaching tank geometry has been concerned as an important factor to provide comparable agitation conditions. Data analysis has been done by using reactor design and mass balancing principles. Finally, optimum zone for operational parameters are determined for each leaching strategy and discussed due to their economical and practical aspects.

Keywords: titanium leaching, optimization, experimental design, performance analysis

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Authors: Md. Asif Ullah, M. A. R. Sarkar

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This paper illustrates 2-D and 3-D simulations of sub-channels of a Pressurized Water Reactor (PWR) having hexagonal array of fuel rods. At a steady state, the temperature of outer surface of the cladding of fuel rod is kept about 1200°C. The temperature of this isothermal surface is taken as boundary condition for simulation. Water with temperature of 290°C is given as a coolant inlet to the primary water circuit which is pressurized upto 157 bar. Turbulent flow of pressurized water is used for heat removal. In 2-D model, temperature, velocity, pressure and Nusselt number distributions are simulated in a vertical sectional plane through the sub-channels of a hexagonal fuel rod assembly. Temperature, Nusselt number and Y-component of convective heat flux along a line in this plane near the end of fuel rods are plotted for different Reynold’s number. A comparison between X-component and Y-component of convective heat flux in this vertical plane is analyzed. Hexagonal fuel rod assembly has three types of sub-channels according to geometrical shape whose boundary conditions are different too. In 3-D model, temperature, velocity, pressure, Nusselt number, total heat flux magnitude distributions for all the three sub-channels are studied for a suitable Reynold’s number. A horizontal sectional plane is taken from each of the three sub-channels to study temperature, velocity, pressure, Nusselt number and convective heat flux distribution in it. Greater values of temperature, Nusselt number and Y-component of convective heat flux are found for greater Reynold’s number. X-component of convective heat flux is found to be non-zero near the bottom of fuel rod and zero near the end of fuel rod. This indicates that the convective heat transfer occurs totally along the direction of flow near the outlet. As, length to radius ratio of sub-channels is very high, simulation for a short length of the sub-channels are done for graphical interface advantage. For the simulations, Turbulent Flow (K-Є ) module and Heat Transfer in Fluids (ht) module of COMSOL MULTIPHYSICS 5.0 are used.

Keywords: sub-channels, Reynold’s number, Nusselt number, convective heat transfer

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Authors: Martin Goubej, Tomas Popule, Alois Krejci

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This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Changtong Wang, Lingyun Wei

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The combination of auctions and supply chains is of great significance in improving the supply chain management system and enhancing the efficiency of economic and social operations. To address the gap in research on supply chain strategies under the auction mechanism, a model is developed for the 1-N auction model in a complete information environment, and it is concluded that the two-part contract auction model for retailers in this model can achieve supply chain coordination. The model is validated by substituting the model into the scenario of a fresh-cut flower industry flower auction in exchange for arithmetic examples to further prove the validity of the conclusions.

Keywords: auction mechanism, supply chain coordination strategy, fresh cut flowers industry, supply chain management

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Authors: B. T. Chew, S. N. Kazi, A. Amiri

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This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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Authors: Hend Mesbah, Yehia Youssef, Ibrahim Hassan, Shaaban Nosier, Ahmed El-Shazly, Ahmed Helal

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The problem of drinking water shortage is becoming more crucial nowadays as a result of the increased demand due to the population growth and the rise in the standard living. In recent years, desalination using electrodialysis powered by solar energy (PV-ED) is being widely used to help provide treated water and reduce the scarcity in water supply. In the present study, a water desalination laboratory scale ED cell with a fixed bed circulation system was designed, developed, and tested. The effect of three parameters (namely, cell voltage , flowrate, and salt concentration) on the removal percentage of salt ions was studied. The cell voltage was adjusted at 3 , 4 and 6 V. A flow rate of 5, 10, and 20 ml/s and an initial salt concentration of 2000, 5000, and 7000 ppm were investigated. The maximum salt percentage removal obtained was 52.5% at the lowest initial concentration (2000 ppm) and at the highest cell voltage (6 V). There was no significant effect of the flow rate on the removal percentage. A model of PV module has also been developed to calculate the dimensions of a solar cell based on the amount of energy consumed and it was calculated from the Overall ED cell voltage.

Keywords: desalination, electrodialysis, solar desalination, photovoltaic electrodialysis

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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Authors: Seung-Yeon Kim

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The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field.

Keywords: Ising ferromagnet, magnetic field, partition function zeros, Yang-Lee edge singularity

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Authors: K. Khanafer

Abstract:

The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

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Authors: Eti Dwi Wiraningsih, Folashade Agusto, Lina Aryati, Syamsuddin Toaha, Suzanne Lenhart, Widodo, Willy Govaerts

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This paper considers a deterministic model for the transmission dynamics of rabies virus in the wild dogs-domestic dogs-human zoonotic cycle. The effect of vaccination and culling in dogs is considered on the model, then the stability was analysed to get basic reproduction number. We use the next generation matrix method and Routh-Hurwitz test to analyze the stability of the Disease-Free Equilibrium and Endemic Equilibrium of this model.

Keywords: stability analysis, rabies model, vaccination effect, culling in dogs

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Authors: Lakrim Abderrazak, Tahri Driss

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This paper presents a new behavioural electrothermal model of power Silicon Carbide (SiC) MOSFET under SPICE. This model is based on the MOS model level 1 of SPICE, in which phenomena such as Drain Leakage Current IDSS, On-State Resistance RDSon, gate Threshold voltage VGSth, the transconductance (gfs), I-V Characteristics Body diode, temperature-dependent and self-heating are included and represented using behavioural blocks ABM (Analog Behavioural Models) of Spice library. This ultimately makes this model flexible and easily can be integrated into the various Spice -based simulation softwares. The internal junction temperature of the component is calculated on the basis of the thermal model through the electric power dissipated inside and its thermal impedance in the form of the localized Foster canonical network. The model parameters are extracted from manufacturers' data (curves data sheets) using polynomial interpolation with the method of simulated annealing (S A) and weighted least squares (WLS). This model takes into account the various important phenomena within transistor. The effectiveness of the presented model has been verified by Spice simulation results and as well as by data measurement for SiC MOS transistor C2M0025120D CREE (1200V, 90A).

Keywords: SiC power MOSFET, DC electro-thermal model, ABM Spice library, SPICE modelling, behavioural model, C2M0025120D CREE.

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Authors: S. O. Oyamakin, A. U. Chukwu,

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

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Authors: Mengying Wang, Xiaohui Wang, Chun Deng, Bei Liu, Changyu Sun, Guangjin Chen, Mahmoud El-Halwagi

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Significant amounts of natural gas hydrates (NGHs) are considered potential new sustainable energy resources in the future. However, common used methods for methane gas recovery from hydrate sediments require high investment but with low gas production efficiency, and may cause potential environment and security problems. Therefore, there is a need for effective gas production from hydrates. The natural gas hydrate production method by CO₂/H₂ replacement coupling steam methane reforming can improve the replacement effect and reduce the cost of gas separation. This paper develops a simulation model of the gas production process integrated with steam reforming and membrane separation. The process parameters (i.e., reactor temperature, pressure, H₂O/CH₄ ratio) and the composition of CO₂ and H₂ in the feed gas are analyzed. Energy analysis is also conducted. Two design scenarios with different composition of CO₂ and H₂ in the feed gas are proposed and evaluated to assess the energy efficiency of the novel system. Results show that when the composition of CO₂ in the feed gas is between 43 % and 72 %, there is a certain composition that can meet the requirement that the flow rate of recycled gas is equal to that of feed gas, so as to ensure that the subsequent production process does not need to add feed gas or discharge recycled gas. The energy efficiency of the CO₂ in feed gas at 43 % and 72 % is greater than 1, and the energy efficiency is relatively higher when the CO₂ mole fraction in feed gas is 72 %.

Keywords: Gas production, hydrate, process integration, steam reforming

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Authors: Razieh Khalafi

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The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.

Keywords: brain, stimuli, partial differential equation, response, EEG signal

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: phase locked loop, voltage source inverter, single phase inverter, model predictive control, Matlab/Simulink

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Authors: Muneer Abbad

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This research explains the e-learning usage in a university in Jordan. Unified theory of acceptance and use of technology (UTAUT) model has been used as a base model to explain the usage. UTAUT is a model of individual acceptance that is compiled mainly from different models of technology acceptance. This research is the initial part from full explanations of the users' acceptance model that use Structural Equation Modelling (SEM) method to explain the users' acceptance of the e-learning systems based on UTAUT model. In this part data has been collected and prepared for further analysis. The main factors of UTAUT model has been tested as different factors using exploratory factor analysis (EFA). The second phase will be confirmatory factor analysis (CFA) and SEM to explain the users' acceptance of e-learning systems.

Keywords: e-learning, moodle, adoption, Unified Theory of Acceptance and Use of Technology (UTAUT)

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Authors: V. Benedico, C. Anacleto, A. Bearzi, L. Brice, V. Delahaye

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The aim in present paper is to construct an affordable and reliable commodity prices based on a recalculation of its cost through time which allows visualize the potential risks and thus, take more appropriate decisions regarding forecasts. Here attention has been focused on Levy model, more reliable and realistic than classical random Gaussian one as it takes into consideration observed abrupt jumps in case of sudden price variation. In application to Energy Trading sector where it has never been used before, equations corresponding to Levy model have been written for electricity pricing in European market. Parameters have been set in order to predict and simulate the price and its evolution through time to remarkable accuracy. As predicted by Levy model, the results show significant spikes which reach unconventional levels contrary to currently used Brownian model.

Keywords: commodity pricing, Lévy Model, price spikes, electricity market

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Authors: Chandan Kundu, Sankar Bhattacharya

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A significant disadvantage of fossil fuel energy production is the considerable amount of carbon dioxide (CO₂) released, which is one of the contributors to climate change. Apart from environmental concerns, changing fossil fuel prices have pushed society gradually towards renewable energy sources in recent years. Biomass is a plentiful and renewable resource and a source of carbon. Recent years have seen increased research interest in generating fuels and chemicals from biomass. Unlike fossil-based resources, biomass is composed of lignocellulosic material, which does not contribute to the increase in atmospheric CO₂ over a longer term. These considerations contribute to the current move of the chemical industry from non-renewable feedstock to renewable biomass. This presentation focuses on generating bio-oil and two major platform chemicals that can potentially improve the environment. Thermochemical processes such as pyrolysis are considered viable methods for producing bio-oil and biomass-based platform chemicals. Fluidized bed reactors, on the other hand, are known to boost bio-oil yields during pyrolysis due to their superior mixing and heat transfer features, as well as their scalability. This review and the associated experimental work are focused on the thermochemical conversion of biomass to bio-oil and two high-value platform chemicals, Levoglucosenone (LGO) and 5-Chloromethyl furfural (5-CMF), in a fluidized bed reactor. These two active molecules with distinct features can potentially be useful monomers in the chemical and pharmaceutical industries since they are well adapted to the manufacture of biologically active products. This process took several meticulous steps. To begin, the biomass was delignified using a peracetic acid pretreatment to remove lignin. Because of its complicated structure, biomass must be pretreated to remove the lignin, increasing access to the carbohydrate components and converting them to platform chemicals. The biomass was then characterized by Thermogravimetric analysis, Synchrotron-based THz spectroscopy, and in-situ DRIFTS in the laboratory. Based on the results, a continuous-feeding fluidized bed reactor system was constructed to generate platform chemicals from pretreated biomass using hydrogen chloride acid-gas as a catalyst. The procedure also yields biochar, which has a number of potential applications, including soil remediation, wastewater treatment, electrode production, and energy resource utilization. Consequently, this research also includes a preliminary experimental evaluation of the biochar's prospective applications. The biochar obtained was evaluated for its CO₂ and steam reactivity. The outline of the presentation will comprise the following: Biomass pretreatment for effective delignification Mechanistic study of the thermal and thermochemical conversion of biomass Thermochemical conversion of untreated and pretreated biomass in the presence of an acid catalyst to produce LGO and CMF A thermo-catalytic process for the production of LGO and 5-CMF in a continuously-fed fluidized bed reactor and efficient separation of chemicals Use of biochar generated from the platform chemicals production through gasification

Keywords: biomass, pretreatment, pyrolysis, levoglucosenone

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Authors: Farzad Sharifi, Raziyeh Shamsi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose molti-objective DEA-R model, because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduces the efficiency score), an efficient DMU is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other case, only the ratio of stochastic data may be available (e.g; the ratio of stochastic inputs to stochastic outputs). Thus, we provide multi objective DEA model without explicit outputs and prove that in-put oriented MOP DEA-R model in the invariable return to scale case can be replacing by MOP- DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model, yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA, MOLP, STOCHASTIC, DEA-R

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Authors: Francisco Vidal Vázquez, Pekka Simell, Christian Frilund, Matti Reinikainen, Ilkka Hiltunen, Tim Böltken, Benjamin Andris, Paolo Piermartini

Abstract:

Carbon capture and utilization (CCU) are one of the key topics in mitigation of CO2 emissions. There are many different technologies that are applied for the production of diverse chemicals from CO2 such as synthetic natural gas, Fischer-Tropsch products, methanol and polymers. Power-to-Gas and Power-to-Liquids concepts arise as a synergetic solution for storing energy and producing value added products from the intermittent renewable energy sources and CCU. VTT is a research and technology development company having energy in transition as one of the key focus areas. VTT has extensive experience in piloting and upscaling of new energy and chemical processes. Recently, VTT has developed and commissioned a Mobile Synthesis Unit (MOBSU) in close collaboration with INERATEC, a spin-off company of Karlsruhe Institute of Technology (KIT, Germany). The MOBSU is a multipurpose synthesis unit for CO2 upgrading to energy carriers and chemicals, which can be transported on-site where CO2 emission and renewable energy are available. The MOBSU is initially used for production of fuel compounds and chemical intermediates by combination of two consecutive processes: reverse Water-Gas Shift (rWGS) and Fischer-Tropsch synthesis (FT). First, CO2 is converted to CO by high-pressure rWGS and then, the CO and H2 rich effluent is used as feed for FT using an intensified reactor technology developed and designed by INERATEC. Chemical equilibrium of rWGS reaction is not affected by pressure. Nevertheless, compression would be required in between rWGS and FT in the case when rWGS is operated at atmospheric pressure. This would also require cooling of rWGS effluent, water removal and reheating. For that reason, rWGS is operated using precious metal catalyst in the MOBSU at similar pressure as FT to simplify the process. However, operating rWGS at high pressures has also some disadvantages such as methane and carbon formation, and more demanding specifications for materials. The main parts of FT module are an intensified reactor, a hot trap to condense the FT wax products, and a cold trap to condense the FT liquid products. The FT synthesis is performed using cobalt catalyst in a novel compact reactor technology with integrated highly-efficient water evaporation cooling cycle. The MOBSU started operation in November 2016. First, the FT module is tested using as feedstock H2 and CO. Subsequently, rWGS and FT modules are operated together using CO2 and H2 as feedstock of ca. 5 Nm3/hr total flowrate. On spring 2017, The MOBSU unit will be integrated together with a direct air capture (DAC) of CO2 unit, and a PEM electrolyser unit at Lappeenranta University of Technology (LUT) premises for demonstration of the SoletAir concept. This would be the first time when synthetic fuels are produced by combination of DAC unit and electrolyser unit which uses solar power for H2 production.

Keywords: CO2 utilization, demonstration, Fischer-Tropsch synthesis, intensified reactors, reverse water-gas shift

Procedia PDF Downloads 270

Authors: Tesfaye Alamirew Dessie

Abstract:

Our study focuses on developing a Model Predictive Controller (MPC) and evaluating it against a traditional PID for a pasteurization process. Utilizing system identification from the experimental data, the dynamics of the pasteurization process were calculated. Using best fit with data validation, residual, and stability analysis, the quality of several model architectures was evaluated. The validation data fit the auto-regressive with exogenous input (ARX322) model of the pasteurization process by roughly 80.37 percent. The ARX322 model structure was used to create MPC and PID control techniques. After comparing controller performance based on settling time, overshoot percentage, and stability analysis, it was found that MPC controllers outperform PID for those parameters.

Keywords: MPC, PID, ARX, pasteurization

Procedia PDF Downloads 132