Records with Subject: Process Control
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Lessons Learned from Three Decades of Global Automation Experience Across Five Industries
Lane Desborough
October 21, 2021 (v1)
Keywords: artificial pancreas, automated insulin delivery, diabetes
My current work on Automated Insulin Delivery (the so-called “artificial pancreas”) directly benefits from two decades of experience gained implementing and remotely monitoring automation in complex and challenging industrial cyberphysical systems all over the world; systems upon which society depends. This talk will cover topics including experimentation, modeling, simulation, and outcome measure sample statistics, as well as controller design considerations including human factors, objective functions, and final control element challenges.
Bypass Control of HEN Under Uncertainty in Inlet Temperature of Hot Stream
Chaitanya Manchikatla, Zukui Li, Biao Huang
October 21, 2021 (v1)
Keywords: Affine Control Policy, Heat Exchanger Network, Model Predictive Control, Uncertain Optimization
The dynamic control of Heat Exchanger Network is significant for developing energy efficient and safe industrial processes. In this project, the hot stream's inlet temperature is considered uncertain because it is common in industries. The cold stream is bypassed around the heat exchanger. This project aims to track the setpoint temperature of the mixed stream by manipulating the bypass fraction of the cold stream around the Heat Exchanger given uncertainty in the inlet temperature of the hot stream. The control is implemented in Nonlinear Model Predictive Control (NMPC) framework. The uncertainty in the optimal control problem (OCP)is dealt by using scenario tree based approximation as well as affine policy based method. The model of the system considered is based on the first principles model, i.e. dynamic model of shell and tube heat exchanger. The Orthogonal collocation technique is used to discretize the first principles model into the system of algebraic equations. The results... [more]
Adaptive State Feedback Stabilization of Generalized Hamiltonian Systems with Unstructured Components
Seyedabbas Alavi, Nicolas Hudon
October 21, 2021 (v1)
Keywords: Adaptive stabilization, Hamiltonian system, Lyapunov stability, Parameter Estimation
This paper considers the problem of adaptive state feedback controller design for stabilizing the generalized Hamiltonian systems with unstructured components. This class of models enables one to exploit the dissipative-conservative structure of generalized Hamiltonian systems for feedback control design while relaxing the burden of deriving an exact structured model representation. First, an efficient adaptation law is designed such that a correct value of parameters is estimated. Assuming that the overall system is stabilizable, and under mild assumptions on the unstructured part of the dynamics, a stabilizing adaptive control law is designed to stabilize systems to the desired steady-state. The stability of the closed-loop system is demonstrated using Lyapunov stability arguments. A numerical illustration of the proposed approach is presented to demonstrate the potential of the design method.
Experimental Study on Ramp Shock Wave Control in Ma3 Supersonic Flow Using Two-Electrode SparkJet Actuator
Wei Xie, Zhenbing Luo, Yan Zhou, Lin Wang, Wenqiang Peng, Tianxiang Gao
July 29, 2021 (v1)
Keywords: dynamic pressure measurement, schlieren images, shock wave control, SparkJet actuator, supersonic flow
The control of a shock wave produced by a ramp (ramp shock) in Ma3 supersonic flow using a two-electrode SparkJet (SPJ) actuator in a single-pulse mode is studied experimentally. Except for schlieren images of the interaction process of SPJ with the flow field, a dynamic pressure measurement method is also used in the analysis of shock wave control. In a typical experimental case, under the control of single-pulsed SPJ, the characteristic of ramp shock changes from “short-term local upstream motion” in the initial stage to “long-term whole downstream motion” in the later stage. The angle and position of the ramp shock changes significantly in the whole control process. In addition, the dynamic pressure measurement result shows that the ramp pressure is reduced by a maximum of 79% compared to that in the base flow field, which indicates that the ramp shock is significantly weakened by SPJ. The effects of some parameters on the control effect of SPJ on the ramp shock are investigated and... [more]
Permeate Flux Control in SMBR System by Using Neural Network Internal Model Control
Norhaliza Abdul Wahab, Nurazizah Mahmod, Ramon Vilanova
July 29, 2021 (v1)
Keywords: artificial neural network, fouling, internal model control, membrane bioreactor
This paper presents a design of a data-driven-based neural network internal model control for a submerged membrane bioreactor (SMBR) with hollow fiber for microfiltration. The experiment design is performed for measurement of physical parameters from an actuator input (permeate pump voltage), which gives the information (outputs) of permeate flux and trans-membrane pressure (TMP). The palm oil mill effluent is used as an influent preparation to depict fouling phenomenon in the membrane filtration process. From the experiment, membrane fouling potential is observed from flux decline pattern, with a rapid increment of TMP (above 200 mbar). Membrane fouling is a complex process and the available models in literature are not designed for control system (filtration performance). Therefore, this work proposes an aeration fouling control strategy to measure the filtration performance. The artificial neural networks (Feed-Forward Neural Network—FFNN, Radial Basis Function Neural Network—RBFNN... [more]
Global Internal Recirculation Alternative Operation to Reduce Nitrogen and Ammonia Limit Violations and Pumping Energy Costs in Wastewater Treatment Plants
Ignacio Santín, Ramon Vilanova, Carles Pedret, Marian Barbu
July 19, 2021 (v1)
Keywords: benchmark simulation model no. 2, control strategies, fuzzy control, wastewater treatment plant
The internal recirculation plays an important role in different areas of the biological treatment of wastewater treatment plants because it has a great influence on the concentration of pollutants, especially nutrients. A usual manipulation of the internal recirculation flow rate is based on the target of controlling the nitrate concentration in the last anoxic tank. This work proposes an alternative for the manipulation of the internal recirculation flow rate instead of nitrate control, with the objective of avoiding limit violations of nitrogen and ammonia concentrations and reducing operational costs. A fuzzy controller is proposed to achieve it based on the effects of the internal recirculation flow rate in different areas of the biological treatment. The proposed manipulation of the internal recirculation flow rate is compared to the application of the usual nitrate control in an already established and published operation strategy by using the internationally known benchmark simu... [more]
Distributed Model Predictive Control Applied to a Sewer System
Antonio Cembellín, Mario Francisco, Pastora Vega
July 12, 2021 (v1)
Keywords: Distributed Model Predictive Control (DMPC), fuzzy logic, sewer system
In this work, a Distributed Model Predictive Control (MPC) methodology with fuzzy negotiation among subsystems has been developed and applied to a simulated sewer network. The wastewater treatment plant (WWTP) receiving this wastewater has also been considered in the methodology by means of an additional objective for the problem. In order to decompose the system into interconnected local subsystems, sectorization techniques have been applied based on structural analysis. In addition, a dynamic setpoint generation method has been added to improve system performance. The results obtained with the proposed methodology are compared to those obtained with standard centralized and decentralized model predictive controllers.
Special Issue on “Modelling and Process Control of Fuel Cell Systems”
Mohd Azlan Hussain, Wan Ramli Wan Daud
July 12, 2021 (v1)
The ever increasing energy consumption, rising public awareness for environmental protection, and higher prices of fossil fuels have motivated many to look for alternative and renewable energy sources [...]
Experimental Study of Substrate Limitation and Light Acclimation in Cultures of the Microalgae Scenedesmus obliquus—Parameter Identification and Model Predictive Control
Federico Alberto Gorrini, Jesús Miguel Zamudio Lara, Silvina Inés Biagiola, José Luis Figueroa, Héctor Hernández Escoto, Anne-Lise Hantson, Alain Vande Wouwer
June 21, 2021 (v1)
Keywords: mathematical modeling, microalgae, parameter estimation, photobioreactor, predictive control, process control
In this study, the parameters of a dynamic model of cultures of the microalgae Scenedesmus obliquus are estimated from datasets collected in batch photobioreactors operated with various initial conditions and light illumination conditions. Measurements of biomass, nitrogen quota, bulk substrate concentration, as well as chlorophyll concentration are achieved, which allow the determination of parameters with satisfactory confidence intervals and model cross-validation against independent data. The dynamic model is then used as a predictor in a nonlinear model predictive control strategy where the dilution rate and the incident light intensity are simultaneously manipulated in order to optimize the cumulated algal biomass production.
Dog Rabies in Dhaka, Bangladesh, and Implications for Control
Masud M A, Md Hamidul Islam, Muhaiminul Islam Adnan, Chunyoung Oh
June 10, 2021 (v1)
Keywords: carrying capacity control, dhaka, free-roaming, mathematical model, optimal control, rabies, stray dog, vaccination, waste management
Controlling rabies among free-roaming street dogs has been a huge challenge in many parts of the world. Vaccination is a commonly used strategy to control rabies, however, sufficient vaccination coverage is very challenging when it comes to street dogs. Also, dog rabies data is scarce, making it difficult to develop proper strategies. In this study, we use a logistic growth incorporated epidemic model to understand the prevalence of rabies in the dog population of Dhaka, Bangladesh. The study shows that, the basic reproduction number for dog rabies in Dhaka lies between 1.1 to 1.249 and the environmental carrying capacity lies approximately between 58,110 to 194,739. Considering the vaccination and neuter programs administered in the last decade, we attempt to explain rabies transmission among dogs in this population. We found that the high basic reproduction number is associated with high environmental carrying capacity and vice versa. Further, we compare different type of control str... [more]
Collaborative Control Applied to BSM1 for Wastewater Treatment Plants
Keidy Morales-Rodelo, Mario Francisco, Hernan Alvarez, Pastora Vega, Silvana Revollar
May 27, 2021 (v1)
Keywords: collaborative control, hierarchical control, mass transfer model, Model Predictive Control, wastewater treatment plant
This paper describes a design procedure for a collaborative control structure in Plant Wide Control (PWC), taking into account the existing controllable parameters as a novelty in the procedure. The collaborative control structure includes two layers, supervisory and regulatory, which are determined according to the dynamics hierarchy obtained by means of the Hankel matrix. The supervisory layer is determined by the main dynamics of the process and the regulatory layer comprises the secondary dynamics and controllable parameters. The methodology proposed is applied to a wastewater treatment plant, particularly to the Benchmark Simulation Model No 1 (BSM1) for the activated sludge process, comparing the results with the use of a Model Predictive Controller in the supervisory layer. For determining controllable parameters in the BSM1 control, a new specific oxygen mass transfer model in the biological reactor has been developed, separating the kLa volumetric mass transfer coefficient int... [more]
Study on the Nonlinear Dynamics of the Continuous Stirred Tank Reactors
Liangcheng Suo, Jiamin Ren, Zemeng Zhao, Chi Zhai
May 26, 2021 (v1)
Keywords: bifurcation analysis, output multiplicity, Process Intensification, torus dynamics
Chemical processes often exhibit nonlinear dynamics and tend to generate complex state trajectories, which present challenging operational problems due to complexities such as output multiplicity, oscillation, and even chaos. For this reason, a complete knowledge of the static and dynamic nature of these behaviors is required to understand, to operate, to control, and to optimize continuous stirred tank reactors (CSTRs). Through nonlinear analysis, the possibility of output multiplicity, self-sustained oscillation, and torus dynamics are studied in this paper. Specifically, output multiplicity is investigated in a case-by-case basis, and related operation and control strategies are discussed. Bifurcation analysis to identify different dynamic behaviors of a CSTR is also implemented, where operational parameters are identified to obtain self-oscillatory dynamics and possible unsteady-state operation strategy through designing the CSTR as self-sustained periodic. Finally, a discussion on... [more]
A New Control Performance Evaluation Based on LQG Benchmark for the Heating Furnace Temperature Control System
Haisheng Li, Rongxuan Li, Feng Wu
May 25, 2021 (v1)
Keywords: control performance assessment, FO-PFC control, fractional order system, linear quadratic Gaussian (LQG) benchmark
Temperature control systems are a series of processes with large time-delay and non-linear characteristics. Research shows that using fractional-order modeling and corresponding control strategies can better control these processes. At the same time, the existing studies for control performance assessment are almost committed to the integer order control systems, and the methods used in few literatures on performance assessment of fractional order systems are also one-sided. This paper applies the linear quadratic Gaussian (LQG) evaluation benchmark to the performance evaluation of fractional-order control systems for the first time, starting with the LQG evaluation benchmark considering the input and output performance. The LQG benchmark can be obtained by the analytical algorithm, which simplifies the complexity of LQG solution. Finally, taking the application of the fractional predictive function control (FO-PFC) controller in the experiment of industrial heating furnace temperature... [more]
Double-Loop Control Structure for Rotary Drum Granulation Loop
Ludmila Vesjolaja, Bjørn Glemmestad, Bernt Lie
May 25, 2021 (v1)
Keywords: automatic control, dynamic simulation, granulation, oscillatory behaviour, PID controller, population balance
The operation of granulation plants on an industrial scale is challenging. Periodic instability associated with the operation of the granulation loop causes the particle size distribution of the particles flowing out from the granulator to oscillate, thus making it difficult to maintain the desired product quality. To address this problem, two control strategies are proposed in this paper, including a novel approach, where product-sized particles are recycled back to maintain a stable granulation loop process. A dynamic model of the process that is based on a population balance equation is used to represent the process dynamics. Both of the control strategies utilize a double-loop control structure that is suitable for highly oscillatory systems. The simulation results show that both control strategies, including the novel approach, are able to remove the oscillating behaviour and stabilize the granulation plant loop.
Modeling, Control, and Prediction of the Spread of COVID-19 Using Compartmental, Logistic, and Gauss Models: A Case Study in Iraq and Egypt
Mahmoud A. Ibrahim, Amenah Al-Najafi
May 25, 2021 (v1)
Keywords: compartmental model, control measures, COVID-19, Gaussian model, logistic growth model, parameter estimation, second wave, sensitivity analysis
In this paper, we study and investigate the spread of the coronavirus disease 2019 (COVID-19) in Iraq and Egypt by using compartmental, logistic regression, and Gaussian models. We developed a generalized SEIR model for the spread of COVID-19, taking into account mildly and symptomatically infected individuals. The logistic and Gaussian models were utilized to forecast and predict the numbers of confirmed cases in both countries. We estimated the parameters that best fit the incidence data. The results provide discouraging forecasts for Iraq from 22 February to 8 October 2020 and for Egypt from 15 February to 8 October 2020. To provide a forecast of the spread of COVID-19 in Iraq, we present various simulation scenarios for the expected peak and its timing using Gaussian and logistic regression models, where the predicted cases showed a reasonable agreement with the officially reported cases. We apply our compartmental model with a time-periodic transmission rate to predict the possibl... [more]
A Reference-Model-Based Neural Network Control Method for Multi-Input Multi-Output Temperature Control System
Yuan Liu, Song Xu, Seiji Hashimoto, Takahiro Kawaguchi
May 17, 2021 (v1)
Keywords: multi-input multi-output temperature system, neural network control, temperature uniformity, transient response
Neural networks (NNs), which have excellent ability of self-learning and parameter adjusting, has been widely applied to solve highly nonlinear control problems in industrial processes. This paper presents a reference-model-based neural network control method for multi-input multi-output (MIMO) temperature system. In order to improve the learning efficiency of the NN control, a reference model is introduced to provide the teaching signal for the NN controller. The control inputs for the MIMO system are given by the sum of the output of the conventional integral-proportional-derivative (I-PD) controller and the outputs of the neural network controller. The proposed NN control method can not only improve the transient response of the system, but can also realize temperature uniformity in MIMO temperature systems. To verify the proposed method, simulations are carried out in MATLAB/SIMULINK environment and experiments are carried out on the DSP (Digital Signal Processor)-based experimenta... [more]
Control-Oriented Modeling and Experimental Validation of a Deoiling Hydrocyclone System
Mads V. Bram, Stefan Jespersen, Dennis S. Hansen, Zhenyu Yang
April 30, 2021 (v1)
Keywords: droplet trajectories, experimental validation, hydrocyclone, Modelling, oil-in-water measurements, separation efficiency
As the treated water from offshore oil and gas production is discharged to the surrounding sea, there is an incentive to improve the performance of the offshore produced water treatment, to reduce the environmental pollutants to the sea. Regulations determine both the maximum allowed oil concentration and the total annual quantity. It is reasonable to assume that when better separation equipment or methods are developed, the regulation will become more strict, and force other producers to follow the trend towards zero harmful discharge. This paper develops and validates a hydrocyclone model to be used as a test-bed for improved control designs. The modeling methodology uses a combination of first-principles to define model structure and data-driven parameter identification. To evaluate and validate the separation performance, real-time fluorescence-based oil-in-water (OiW) concentration monitors, with dual redundancy, are installed and used on sidestreams of a modified pilot plant. The... [more]
NMPC-Based Workflow for Simultaneous Process and Model Development Applied to a Fed-Batch Process for Recombinant C. glutamicum
Philipp Levermann, Fabian Freiberger, Uma Katha, Henning Zaun, Johannes Möller, Volker C. Hass, Karl Michael Schoop, Jürgen Kuballa, Ralf Pörtner
April 30, 2021 (v1)
Keywords: C. glutamicum, digitalization, model-based process development, NMPC algorithm, process modeling, process optimization
For the fast and improved development of bioprocesses, new strategies are required where both strain and process development are performed in parallel. Here, a workflow based on a Nonlinear Model Predictive Control (NMPC) algorithm is described for the model-assisted development of biotechnological processes. By using the NMPC algorithm, the process is designed with respect to a target function (product yield, biomass concentration) with a drastically decreased number of experiments. A workflow for the usage of the NMPC algorithm as a process development tool is outlined. The NMPC algorithm is capable of improving various process states, such as product yield and biomass concentration. It uses on-line and at-line data and controls and optimizes the process by model-based process extrapolation. In this study, the algorithm is applied to a Corynebacterium glutamicum process. In conclusion, the potency of the NMPC algorithm as a powerful tool for process development is demonstrated. In pa... [more]
Denitrification Control in a Recirculating Aquaculture System—A Simulation Study
Pedro Almeida, Laurent Dewasme, Alain Vande Wouwer
April 30, 2021 (v1)
Keywords: denitrification, mathematical modeling, process control, wastewater treatment
The recirculating aquaculture system (RAS) is a land-based water treatment technology, which allows for farming aquatic organisms, such as fish, by reusing the water in the production (often less than 5%). This technology is based on the use of filters, either mechanical or biological, and can, in principle, be used for any species grown in aquaculture. Due to the low recirculation rate, ammonia accumulates in the system and must be converted into nitrate using nitrification reactors. Although less toxic for fish, nitrate can also be further reduced into nitrogen gas by the use of denitrification biofilters which may create several issues, such as incomplete denitrification, resulting in toxic substances, such as nitrite and nitric oxide, or a waste of carbon source in excess. Control of the added quantity of carbon source in the denitrification biofilter is then mandatory to keep nitrate/nitrite concentrations under toxic levels for fish and in accordance with local effluent regulatio... [more]
Dynamic Modeling and Control of a Coupled Reforming/Combustor System for the Production of H2 via Hydrocarbon-Based Fuels
Dimitris Ipsakis, Theodoros Damartzis, Simira Papadopoulou, Spyros Voutetakis
April 27, 2021 (v1)
Keywords: C1–C4 feedstock, distributed control system, Dynamic Modelling, hydrogen production, PID control, Steam Reforming
The present work aims to provide insights into the dynamic operation of a coupled reformer/combustion unit that can utilize a variety of saturated hydrocarbons (HCs) with 1−4 C atoms towards H2 production (along with CO2). Within this concept, a preselected HC-based feedstock enters a steam reforming reactor for the production of H2 via a series of catalytic reactions, whereas a sequential postprocessing unit (water gas shift reactor) is then utilized to increase H2 purity and minimize CO. The core unit of the overall system is the combustor that is coupled with the reformer reactor and continuously provides heat (a) for sustaining the prevailing endothermic reforming reactions and (b) for the process feed streams. The dynamic model as it is initially developed, consists of ordinary differential equations that capture the main physicochemical phenomena taking place at each subsystem (energy and mass balances) and is compared against available thermodynamic data (temperature and concent... [more]
A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters
Moksadur Rahman, Anders Avelin, Konstantinos Kyprianidis
April 27, 2021 (v1)
Keywords: control, diagnostics, Kraft pulping, Modelling, pulp digester
Being at the heart of modern pulp mills, continuous pulp digesters have attracted much attention from the research community. In this article, a comprehensive review in the area of modeling, control and diagnostics of continuous pulp digesters is conducted. The evolution of research focus within these areas is followed and discussed. Particular effort has been devoted to identifying the state-of-the-art and the research gap in a summarized way. Finally, the current and future research directions in the areas have been analyzed and discussed. To date, digester modeling following the Purdue approach, Kappa number control using model predictive controllers and health index-based diagnostic approaches by utilizing different statistical methods have dominated the field. While the rising research interest within the field is evident, we anticipate further developments in advanced sensors and integration of these sensors for improving model prediction and controller performance; and the explo... [more]
Model-Free Extremum Seeking Control of Bioprocesses: A Review with a Worked Example
Laurent Dewasme, Alain Vande Wouwer
April 26, 2021 (v1)
Keywords: adaptive control, biological systems, biotechnology, Hammerstein model, real-time optimization
Uncertainty is a common feature of biological systems, and model-free extremum-seeking control has proved a relevant approach to avoid the typical problems related to model-based optimization, e.g., time- and resource-consuming derivation and identification of dynamic models, and lack of robustness of optimal control. In this article, a review of the past and current trends in model-free extremum seeking is proposed with an emphasis on finding optimal operating conditions of bioprocesses. This review is illustrated with a simple simulation case study which allows a comparative evaluation of a few selected methods. Finally, some experimental case studies are discussed. As usual, practice lags behind theory, but recent developments confirm the applicability of the approach at the laboratory scale and are encouraging a transfer to industrial scale.
Optimal-Setpoint-Based Control Strategy of a Wastewater Treatment Process
Sergiu Caraman, Laurentiu Luca, Iulian Vasiliev, Marian Barbu
April 16, 2021 (v1)
Keywords: fuzzification block, Genetic Algorithm, optimal-setpoint-based control strategy, performance criterion, wastewater treatment process
This paper presents an optimal-setpoint-based control strategy of a wastewater treatment process (WWTP). The treatment plant serves the city of Galati, located in Eastern Romania, a city with a population of 250,000 inhabitants. As the treatment plant includes several control loops (based upon PI controllers), an efficient operation means the establishing of an optimal operating point regardless of the pluviometric regime (DRY, RAIN and STORM) or transitions between regimes. This optimal operating point is given by the optimal setpoint set (setpoints of the dissolved oxygen concentration in the aerated tanks, setpoint of the nitrate concentration, external recirculation flow, sludge flow extracted from the primary clarifier and excess sludge flow from the secondary clarifier) of the treatment plant control loops. The control algorithm has two distinct parts: the first part consists of computing the optimal aforementioned setpoints, based on the mathematical model of the treatment plant... [more]
PID Tuning Method Based on IMC for Inverse-Response Second-Order Plus Dead Time Processes
Duby Castellanos-Cárdenas, Fabio Castrillón, Rafael E. Vásquez, Carlos Smith
April 16, 2021 (v1)
Keywords: internal model control, inverse response, PID tuning, process control, second order plus dead time)
This work addresses a set of tuning rules for PID controllers based on Internal Model Control (IMC) for inverse-response second-order systems with dead time. The transfer function, and some time-response characteristics for such systems are first described. Then, the IMC-based methodology is developed by using an optimization objective function that mixes performance and robustness. A correlation that minimizes the objective function and that allows the user to compute the controller’s tuning parameter is found. The obtained expressions are mathematically simple, which facilitate their application in a ten-step systematic methodology. Finally, the proposed tuning method is compared to other well-known tuning rules that have been reported in literature, for a wide range of parameters of the process. The performance achieved with the proposed method is very good not only for disturbance rejection but for set-point tracking, when considering a wide-range of parameters of the process’ tran... [more]
A Numerical Investigation on De-NOx Technology and Abnormal Combustion Control for a Hydrogen Engine with EGR System
Hao Guo, Song Zhou, Jiaxuan Zou, Majed Shreka
April 16, 2021 (v1)
Keywords: Computational Fluid Dynamics, exhaust gas recirculation, hydrogen engine, knocking, pre-ignition
The combustion emissions of the hydrogen-fueled engines are very clean, but the problems of abnormal combustion and high NOx emissions limit their applications. Nowadays hydrogen engines use exhaust gas recirculation (EGR) technology to control the intensity of premixed combustion and reduce the NOx emissions. This study aims at improving the abnormal combustion and decreasing the NOx emissions of the hydrogen engine by applying a three-dimensional (3D) computational fluid dynamics (CFD) model of a single-cylinder hydrogen-fueled engine equipped with an EGR system. The results indicated that peak in-cylinder pressure continuously increased with the increase of the ignition advance angle and was closer to the top dead center (TDC). In addition, the mixture was burned violently near the theoretical air−fuel ratio, and the combustion duration was shortened. Moreover, the NOx emissions, the average pressure, and the in-cylinder temperature decreased as the EGR ratio increased. Furthermore,... [more]
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