Multiobjective Dynamic Optimization of an Industrial Steam Reformer with Genetic Algorithms

2007 ◽  
Vol 5 (1) ◽  
Author(s):  
Ali Alizadeh ◽  
Navid Mostoufi ◽  
Farhang Jalali-Farahani
Keyword(s):  
Steady State ◽  
Dynamic Optimization ◽  
Synthesis Gas ◽  
Transition Period ◽  
Dynamic Condition ◽  
Homogeneous Model ◽  
Operating Conditions ◽  
Reactor Performance ◽  
Steady State Condition ◽  
Steam Reformer

An industrial steam reformer of a methanol plant was modeled at a dynamic condition in which a one dimensional homogeneous model was coupled with a verified kinetics from the literature. A close agreement was observed between the results of the model and industrial data from a real plant at steady state conditions. The open loop response of the system to switching between two operating conditions was investigated and shown that the produced synthesis gas during the transition period would be unsuitable for the downstream methanol converter. The genetic algorithm was then employed to perform a multi-objective dynamic optimization on the reactor performance in case of switching the feed and operating conditions. Maximization of methane conversion and minimization of a stoichiometric parameter, were considered as the two objectives' functions that were optimized for a fixed feed rate of methane to the existing unit. The results of the dynamic optimization for the specified reformer configuration were achieved after switching the operating condition. Results of the optimization showed that the produced synthesis gas would stay in its acceptable limits in terms of quality of the feed of the methanol converter and also, the final conversion of the reformer would be improved compared to the steady state condition. This procedure could be applied to the advanced process control of the methanol plant.

Thermo-structural analysis of a honeycomb-type volumetric absorber for concentrated solar power applications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Masoud Behzad ◽  
Benjamin Herrmann ◽  
Williams R. Calderón-Muñoz ◽  
José M. Cardemil ◽  
Rodrigo Barraza
Keyword(s):  
Heat Transfer ◽  
Thermal Stress ◽  
Steady State ◽  
Discrete Model ◽  
Continuum Model ◽  
Transient State ◽  
Operating Conditions ◽  
Steady State Condition ◽  
Content Type ◽  
The Continuum

Purpose Volumetric air receivers experience high thermal stress as a consequence of the intense radiation flux they are exposed to when used for heat and/or power generation. This study aims to propose a proper design that is required for the absorber and its holder to ensure efficient heat transfer between the fluid and solid phases and to avoid system failure due to thermal stress. Design/methodology/approach The design and modeling processes are applied to both the absorber and its holder. A multi-channel explicit geometry design and a discrete model is applied to the absorber to investigate the conjugate heat transfer and thermo-mechanical stress levels present in the steady-state condition. The discrete model is used to calibrate the initial state of the continuum model that is then used to investigate the transient operating states representing cloud-passing events. Findings The steady-state results constitute promising findings for operating the system at the desired airflow temperature of 700°C. In addition, we identified regions with high temperatures and high-stress values. Furthermore, the transient state model is capable of capturing the heat transfer and fluid dynamics phenomena, allowing the boundaries to be checked under normal operating conditions. Originality/value Thermal stress analysis of the absorber and the steady/transient-state thermal analysis of the absorber/holder were conducted. Steady-state heat transfer in the explicit model was used to calibrate the initial steady-state of the continuum model.

scholarly journals Dynamic Modeling of Single-Shaft Industrial Gas Turbine

1996 ◽  
Author(s):  
R. Bettocchi ◽  
P. R. Spina ◽  
F. Fabbri
Keyword(s):  
Steady State ◽  
Gas Turbine ◽  
Dynamic Modeling ◽  
Operating Conditions ◽  
Steady State Condition ◽  
On Line ◽  
Working Parameters ◽  
Industrial Gas Turbine ◽  
And Control ◽  
Measurement And Control

In the paper the dynamic non-linear model of single shaft industrial gas turbine was developed as the first stage of a methodology aimed at the diagnosis of measurement and control sensors and gas turbine operating conditions. The model was calibrated by means of reference steady-state condition data of a real industrial gas turbine and was used to simulate various machine transients. The model is modular in structure and was carried out in simplified form, but not so as to compromise its accuracy, to reduce the calculation time and thus make it more suitable for on-line simulation. The comparison between values of working parameters obtained by the simulations and measurements during some transients on the gas turbine in operation provided encouraging results.

Understanding the Effect of the Transition Period during the Air Gasification of Dried Sewage Sludge in a Fluidized Bed Reactor

2007 ◽  
Vol 5 (1) ◽  
Author(s):  
María Aznar ◽  
Ángel E. González ◽  
Joan J Manyà ◽  
José L. Sánchez ◽  
M Benita Murillo
Keyword(s):  
Steady State ◽  
Sewage Sludge ◽  
Fluidized Bed ◽  
Atmospheric Pressure ◽  
Transition Period ◽  
Fluidized Bed Reactor ◽  
Operating Conditions ◽  
Polycyclic Aromatic ◽  
Reactor Temperature ◽  
Composition Changes

Air gasification of dried sewage sludge (DSS) in a fluidized bed has been studied as an effective alternative for the management of this material in a usable way. Nevertheless, one of the major issues in this technology is to deal with the tar formed during the process. To minimize the tar production, it is very important to optimize the operating conditions. In a previous work (Manyà et al., Energy Fuels, Vol. 19, 629–636, 2005) some unexpected results, in which tar production increases with the equivalence ratio, have been obtained. As it has been mentioned in that work, tar production could present unexpected trends while the bed composition changes from sand to a mixture of char and sand. Ashes contained in char have catalytic active metals which could promote gasification reactions. As the char content in the bed increases, the catalytic activity in the reactor could increase too, until the steady state is achieved. The aim of this work is to characterize the non-stationary period and its influence on the overall results obtained from gasification tests. Experiments have been carried out in a laboratory-scale BFB reactor at atmospheric pressure and at a reactor temperature of 1123 K with an equivalent ratio of 30%. Results show that at the beginning of the experiments the tar production was higher, until the steady state is reached. The gasification study has been enhanced with an analysis of tar composition by means of GC/MS and GC/FID. An effect of the transition period has been observed in tar composition also. The nitrogen aromatics percent increased with time whereas the polycyclic aromatic hydrocarbon decreased.

Real-Time Dynamics Modeling of Cryogenic Ball Bearings With Thermal Coupling

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Pradeep K. Gupta ◽  
Howard G. Gibson
Keyword(s):  
Steady State ◽  
Real Time ◽  
Dynamic Modeling ◽  
Heat Generation ◽  
Step Change ◽  
Operating Conditions ◽  
Thermal Time ◽  
Ball Bearings ◽  
Thermal Coupling ◽  
Steady State Condition

Abstract Real-time dynamic modeling of cryogenic ball bearings, where the rotating inner race accelerates to the operating speed, is based on integration of classical differential equations of motion of bearing elements, when experimentally measured ball/race traction behavior is used to compute the imposed acceleration on the rolling elements. The dynamic performance simulation provides a realistic coupling between traction behavior in the ball-to-race contacts and dynamics of bearing element motion as the bearing goes through the transient speed variation. However, due to vastly different mechanical and thermal time scales, heat generation in the bearing is time-averaged over a relatively large thermal time-step to model temperature fields as a step change, while the bearing motion is simulated in real-time. The emphasis is on dynamic modeling with thermal coupling in a static sense. Under stable conditions, the step change in temperature field converges to operating value as the bearing approaches a dynamic steady-state condition, which demonstrates acceptable significance of the dynamic simulation with coupled thermal interactions. Both all steel and hybrid ball bearings for liquid oxygen (LOX) turbo pump applications are modeled. Bearing performance simulations are closely modeled over experimental time cycles in both transient and steady-state domains. Steady-state solutions are shown to be independent of initial conditions to demonstrate acceptable convergence of time domain integrations. Model predictions of heat transferred to circulating LOX is within the range of variation in experimental data. Parametric evaluation of bearing performance as a function of operating conditions demonstrate that while the ball/race contact stress is higher in a hybrid bearing, contact heat generation is significantly lower in comparison with that in the all steel bearings.

Deep learning procedure for knock, performance and emission prediction at steady-state condition of a gasoline engine

2020 ◽  
Vol 234 (14) ◽  
pp. 3347-3361
Author(s):  
Seunghyup Shin ◽  
Sangyul Lee ◽  
Minjae Kim ◽  
Jihwan Park ◽  
Kyoungdoug Min
Keyword(s):  
Deep Learning ◽  
Steady State ◽  
Gasoline Engine ◽  
Pressure Rise ◽  
Learning Model ◽  
Operating Conditions ◽  
Cylinder Pressure ◽  
Steady State Condition ◽  
Brake Mean Effective Pressure ◽  
Deep Learning Model

Recently, deep learning has played an important role in the rise of artificial intelligence, and its accuracy has gained recognition in various research fields. Although engine phenomena are very complicated, they can be predicted with high accuracy using deep learning because they are based on the fundamentals of physics and chemistry. In this research, models were built with deep neural networks for gasoline engine prediction. The model consists of two sub-models. The first predicts the knock occurrence, and the second predicts performance, combustion, and emissions. This includes maximum cylinder pressure, crank angle at maximum cylinder pressure, maximum pressure rise rate, and brake mean effective pressure, brake-specific fuel consumption, brake-specific nitrogen oxides, and brake-specific carbon oxide, which are representative results of the engine (for normal combustion cases without knock). Model input parameters were selected considering engine operating conditions, and physically measurable sensor values. For test cases, the accuracy of the first model for knock classification is 99.0%, and the coefficient of determination (R2) values for the second model are all above 0.99. Test times of both models were approximately 2 ms. The robustness of all the models was verified using K-fold cross-validation. A sensitivity study of accuracy, according to the amount of training utilized, was also conducted to determine how many data points are required to effectively train the deep learning model. Accordingly, a deep learning approach was applied to predict the steady-state conditions of a gasoline engine. Achieved model accuracies and robustness proved deep learning to be an effective modeling approach, and test time was recognized to be able to apply for the real-time prediction. The sensitivity analysis can be applied for the preliminary study to define the number of experimental points for the deep learning model.

scholarly journals Dynamic optimization of methanol synthesis section in the dual type configuration to increase methanol production

2019 ◽  
Vol 74 ◽  
pp. 90
Author(s):  
Samane Masoudi ◽  
Mohammad Farsi ◽  
Mohammad Reza Rahimpour
Keyword(s):  
Dynamic Optimization ◽  
Methanol Synthesis ◽  
Catalyst Deactivation ◽  
Dynamic Condition ◽  
Production Capacity ◽  
Operating Conditions ◽  
Second Step ◽  
Methanol Production ◽  
Equilibrium Conversion ◽  
Plant Data

The main object of this research is dynamic modeling and optimization of the methanol synthesis section in the dual type configuration considering catalyst deactivation to improve methanol production capacity. In the methanol unit, deactivation of CuO/ZnO/Al2O3 catalyst by sintering and low equilibrium conversion of reactions limit the production capacity, and changing operating temperature is a practical solution to overcome the production decay. In the first step, the considered process is modeled based on the mass and energy balance equations at dynamic condition. To prove the accuracy of developed model, the simulation results are compared with the plant data at the same operating conditions. In the second step, a dynamic optimization problem is formulated, and the optimal trajectories of manipulated variables are determined considering methanol production rate as the objective function. Finally, the performance of optimized process is compared with the conventional system at the same design conditions. The results show that operating at the optimal conditions increases methanol production capacity about 6.45%.

Anomaly detection for heavy power generation gas turbine considering the effect of output power variation

2019 ◽  
Vol 234 (6) ◽  
pp. 795-803
Author(s):  
Zhong Wang ◽  
Yujiong Gu ◽  
Xudong Han ◽  
Junjie Zhu ◽  
Jiaohui Xu
Keyword(s):  
Power Generation ◽  
Steady State ◽  
Anomaly Detection ◽  
Gas Turbine ◽  
Output Power ◽  
Operating Conditions ◽  
Operating Parameters ◽  
Unsteady State ◽  
Steady State Condition ◽  
Positive Rate

In the frequency modulation process of the heavy power generation gas turbine, the variation of output power will cause the fluctuation of the operating parameters. In order to detect the anomaly of the true performance deterioration accurately, a novel statistical anomaly detection model was developed. First, the mathematical description of the operating parameters under three different operating conditions—unsteady-state, steady-state and normal, steady-state and anomaly—was presented according to the characteristics of parameters and output power. Second, the new characteristic test statistic P-ratio based on the T-statistic was proposed for the anomaly detection under the steady-state condition. Then, the on-line steady-state detection algorithm based on the Gaussian mixture model was built for the unsteady-state identification. Finally, the efficacy of the model was examined on the synthetic deterioration data, which superimposes the anomaly simulation signal data on the real healthy data from a real power generation gas turbine. The testing result is shown to be satisfactory with respect to the false positive rate and the true positive rate. Future research is required to further improve the accuracy of the proposed model.

Experience with UASB reactor start-up under different operating conditions

1996 ◽  
Vol 34 (5-6) ◽  
pp. 421-428 ◽  
Author(s):  
M. M. Ghangrekar ◽  
S. R. Asolekar ◽  
K. R. Ranganathan ◽  
S. G. Joshi
Keyword(s):  
Steady State ◽  
Operating Conditions ◽  
Cod Removal ◽  
Upflow Anaerobic Sludge Blanket ◽  
Anaerobic Sludge ◽  
Operating Parameters ◽  
Reactor Performance ◽  
Loading Rates ◽  
Start Up ◽  
Sludge Production

Four laboratory upflow anaerobic sludge blanket (UASB) reactors were operated at different operating parameters viz., hydraulic retention time (HRT), upflow velocity, organic concentration, and Ca2+ concentration in the wastewater. These operating parameters gave different values of organic loading rates (OLRs) and sludge loading rates (SLRs). The reactor performance during start-up was evaluated at different values of the above listed parameters. Also, the effects of these parameters on the granule characteristics were investigated. It was observed that COD removal efficiency at steady state was profoundly influenced by SLR. The reactor started with SLR of 0.6 kgCOD/ kg VSS.d could result in about 50% COD removal at steady state. The reactor performance could not improve even after three months of operation. Up to 0.3 kgCOD/ kgVSS.d the reactor performance was good with more than 90% COD removal at steady state. The OLD and SLR also determine time required for the reactor to achieve steady state. Different operating conditions also have the bearing on the strength of the granules cultivated. The methanogenic activity measured on acetate for each reactor was observed between 0.259 and 0.909 kg CH4 COD/ kgVSS.d. The sludge production in all the reactors was between 0.087 and 0.13 kgVSS/ kgCODin. The mathematical model was developed in order to predict sludge production.

A multiobjective grid interactive solar photovoltaic DSTATCOM system using cascaded observer-based DFLL approach

2020 ◽  
Vol 17 (5) ◽  
pp. 641-659
Author(s):  
Byomakesh Dash ◽  
Renu Sharma ◽  
Bidyadhar Subudhi
Keyword(s):  
Steady State ◽  
Control Algorithm ◽  
Dynamic Condition ◽  
Reference Signal ◽  
Weather Condition ◽  
Voltage Source ◽  
Frequency Variation ◽  
Steady State Condition ◽  
Content Type ◽  
Transfer Delay

Purpose A cascaded observer-based transfer delay frequency locked loop (CODFLL) algorithm is developed to control the distribution static compensator (DSTATCOM) to address various power quality (PQ) issues arise because of distorted grid and load conditions. Moreover, frequency locked loop is included along with the observer to take care of the frequency drift from nominal value and to improve its performance during steady state and transient conditions. During daylight, the proposed system works as photovoltaic (PV) DSTATCOM and performs multiple functions for improving PQ whilst transferring power to grid and load. The system under consideration acts as DSTATCOM during night and bad weather condition to nullify the PQ issues. Design/methodology/approach CODFLL control algorithm generates reference signal for hysteresis controller. This reference signal is compared with an actual grid signal and a gate pulse is produced for a voltage source converter. The system is made frequency adaptive by transfer delay adaptive frequency locked loop (FLL). Peak power is extracted from a PV source using the perturb and observe technique irrespective of disturbances encountered in the system. Findings The PV system’s performance with the proposed controller is studied and compared with conventional control algorithms such as least mean fourth (LMF), improved second-order generalized integrator frequency locked loop (ISOGI-FLL), synchronous reference frame phased lock loop (SRF-PLL) and frequency adaptive disturbance observer (DOB) for different cases, for example, steady-state condition, dynamic condition, variable insolation, voltage sag and swell and frequency wandering in the supply side. It is found that the proposed method tracks the frequency variation faster as compared to ISOGI-FLL without any oscillations. During unbalanced loading conditions, CODFLL exhibits zero oscillations. Harmonics in system parameters are reduced to the level of IEEE standard; unity power factor is maintained at the grid side; hassle-free power flow takes place from the source to the grid and load; and consistent voltage profile is maintained at the coupling point. Originality/value CODFLL control algorithm is developed for PV-DSTATCOM systems to generate a reference grid current.

TRANSIENT OPERATION OF SENSIBLE FIXED-BED REGENERATORS

2022 ◽  
pp. 1-16
Author(s):  
Hadi Ramin ◽  
Easwaran N Krishnan ◽  
Gurubalan Annadurai ◽  
Carey J. Simonson
Keyword(s):  
Steady State ◽  
Fixed Bed ◽  
Operating Conditions ◽  
Design Parameters ◽  
Transient Temperature ◽  
Quasi Steady State ◽  
Transient Operation ◽  
Steady State Condition ◽  
Test Standards ◽  
Wide Range

Abstract Fixed-bed regenerator is a type of air-to-air energy exchanger and recently introduced for energy recovery application in HVAC systems because of their high heat transfer effectiveness. Testing of FBRs is essential for performance evaluation and product development. ASHRAE and CSA recently included guidelines for testing of FBRs in their respective test standards. The experiments on FBRs are challenging as they never attain a steady state condition, rather undergoes a quasi-steady state operation. Before reaching the quasi-steady state, FBRs undergo several transient cycles. Hence, the test standards recommend getting measurements after one hour of operation, assuming FBR attains the quasi-steady state regardless of test conditions. However, the exact duration of the initial transient cycles is unknown and not yet studied so far. Hence, in this paper, the duration of FBR's transient operation is investigated for a wide range of design and operating conditions. The test standards' recommendation for the transient duration is also verified. The major contributions of this paper are (i) quantifying the effect of design parameters (NTUo and Cr*) on the duration of transient operation and (ii) investigation of the effect of sensor time constant on the transient temperature measurements. The results will be useful to predict and understand the transient behavior of FBRs accurately.

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