Determination Of Optimal Operating Conditions Research Articles

Multidimensional Scenario Calculations Using Cloud‐Based Co‐Simulation

AbstractAs part of the joint research project Carbon2Chem®, mathematical models are used to simulate operating scenarios of cross‐industry networks, in particular chemical plants in industrial environments with high CO2 emissions. In this context, a cloud‐based distributed co‐simulation is used to enable the parallelized simulation of a large number of different variants. This enables optimal design of the plant networks and the efficient determination of optimal operating conditions. The architecture of this approach is described, and its performance is examined and evaluated.

Optimised phycoerythrin extraction method from Porphyridium sp. combining imidazolium-based ionic liquids

Phycoerythrin (PE) extraction from Porphyridium sp. was studied employing ultrasound-assisted extraction combined with aqueous mixtures of two imidazolium-based ionic liquids (ILs) simultaneously, marking a significant novelty. A face-centred central composite design and response surface optimised PE yield (EPE), considering the effects of ionic liquid concentration (IL), [Emim][EtSO4]/[Bmim][EtSO4] mass ratio (E/B), biomass concentration (BM), and time (t). Improvements in EPE by 300 % and 115 % were achieved compared to a phosphate buffer solution and the freeze-thaw method, respectively. Temperature and pH effects were examined independently, leading to the determination of optimal operating conditions: BM = 10 mg mL−1, IL = 18.6 wt%, E/B = 0.78/0.22, t = 10 min, T = 35 °C, and pH = 7.5. Results indicated the potential for reusing the ILs for at least five consecutive extraction cycles, maintaining an EPE of 94.2 % compared to fresh ones. This underscores the success and innovation of the developed technology in enhancing PE extraction from Porphyridium sp.

Determination of optimal operating conditions for AC-powered electrocoagulation process coupling green additive Tartaric Acid to remove Ni2+: Pyomo and RSM approach

A novel Python-based open-source optimization framework, namely Pyomo (Python optimization modeling objects), alongside a conventional optimization method, RSM (response surface methodology), was utilized to determine the optimal operating conditions of an alternating current-powered electrocoagulation (ACPE) process for nickel removal. In this regard, four mutable operating factors, current density (5–9 mA/cm2), initial nickel concentration (200–400 mg/L), initial pH of the solution (5–9), and electrolysis time (30–60 min), along with a fixed amount of an additional eco-friendly substance, Tartaric Acid (155 mg/L) were considered. Metal removal efficiency (OF1) and operating costs (OF2) were monitored and evaluated as objective functions with the aim of maximization and minimization, respectively. Experiments were conducted according to the central composite design (CCD), and validation outcomes established a reasonable agreement between the predicted models and the experimental data. The multi-objective optimization process yielded two sets of 30-optimal-solution obtained through Pyomo and RSM. Accordingly, the proposed solutions by the Pyomo were found to be more flexible and eclectic, supplying the local decision maker(s) with a diverse spectrum of optimal operating conditions. Adding TA was also effective in reducing electrical energy consumption by up to 46%.

Exploration of optimal operating conditions for a natural gas combined-cycle power plant integrated with post-combustion CO2 capture using 2-amino-2-methyl-1-propanol/piperazine considering the propagation effect

Integrating post-combustion CO2 capture (PCC) into thermal power plants can reduce CO2 emissions but results in a significant decrease in net thermal efficiency. Optimizing PCC operating conditions, such as the ratio of the liquid flow rate to the gas flow rate (L/G) and stripper bottom temperature, reduces the net efficiency penalty. However, previous studies partially neglected the propagation effects of altered operating conditions on process performance, such as the effect of altered L/G and resultant change in fluid velocity on the heat transfer and pressure drop in the rich and lean solution heat exchanger. This study simulated amine-based PCC integrated into a natural gas combined cycle and explored optimal operating conditions comprehensively considering the propagation effects. The net efficiency penalty was minimized to 6.02%-pts. at a stripper bottom temperature of 130 °C and L/G of 0.82 for PCC operation with CO2 compression. Meanwhile, neglecting propagation effects of altered L/G led to underestimation of the efficiency penalty and erroneous determination of optimal operating conditions. The system evaluation methods suggested in this paper contribute to correctly optimizing PCC operating conditions and can be broadly applied to amine-based PCC studies employing novel amine solutions or process modifications.

Determination of Optimal Operating Conditions for Ac-Powered Electrocoagulation Process Coupling Green Additive Tartaric Acid to Remove Ni2+: Pyomo and Rsm Approach

Determination of Optimal Operating Conditions for Ac-Powered Electrocoagulation Process Coupling Green Additive Tartaric Acid to Remove Ni2+: Pyomo and Rsm Approach

Determination of Optimum Operating Conditions of Different Types of Intercooler Designs in Supercharged Engines

In the rapidly developing automotive technology, the efforts to achieve high performance with less fuel consumption is one of the most important issues today. The purpose of the supercharged systems developed for this reason is to send more air into the cylinder. For high engine performance and low exhaust emission values, the intake air temperature, which is heated in the turbo-compressor and has the oxygen concentration (the amount of oxygen in the unit air) decreased, must be kept at certain levels. Therefore, the heated air between the compressor outlet and the cylinder inlet must be cooled. In this study, different types of intercoolers were designed and analyzed with the help of ANSYS Fluent (CFD) program, and optimum conditions were tried to be obtained by comparing them with each other.

The Determination of Optimal Operating Condition For an Off-Grid Hybrid Renewable Energy Based Micro-Grid: A Case Study in Izmir, Turkey

Nowadays, off-grid systems, which do not require grid connection investment instead of grid connected systems, have become quite feasible. In this study, a feasibility analysis was carried out for a hybrid energy system using solar and wind energy sources to supply to uninterrupted electricity demand of a region with 100 villas in Izmir, Turkey. It has been shown that how changes cost of the hybrid energy system sizing according to the control strategies by using the HOMER software. In the paper, two different control strategies are determined as Cycle Charging (CC) and Load Following (LF), and then the control strategies are compared. According to the results obtained as a result of the simulations, it has been revealed that the research region to operate with CC can supply to the electrical energy demand with lower capacity system architecture. The CC was found to be more suitable for the research region than LF in terms of both Cost of Energy (COE) and Net Preset Cost (NPC).

Dewatering of Golden Horn sludge with geotextile tube and determination of optimum operating conditions: A novel approach

Environmental concerns about Golden Horn's polluted sediments have led to 320,000 m3 of sea dredging, generated annually by bucket dredgers to be stored in landfills without dewatering. This study presents an efficient dewatering methodology and a beneficial alternative to store the sludge. In this scenario, the sludge of a suction-cutter dredger is transported to a pond. The beneficial use of geotextile tubes filled with the sludge at circumferential embankments of pond is evaluated. An anionic polyacrylamide (APAM) is used for conditioning the high plastic silt sludge with 10% solid content. APAM dosage is optimized by Rapid Dewatering Test (RDT) for geotextile material. Microscale SEM-EDS analyzes depicted the flocculated form of the sludge. Laboratory-scale Geotextile Dewatering Test (GDT) shows improvements in the turbidity of filtrate, the quantity of solid particles retained in the tube, and the filtration efficiency, determined to be 92 NTU, 18.5% and 90.5% respectively. In accordance with the ICP-OES analysis, the discharge of the filtrate to the aquatic media is admissible. Undrained shear strength of the dewatered sludge is assessed as low, by Vane and undrained unconsolidated triaxial compression tests. Further improvements of the dewatered sludge with vacuum preloading method were projected by completion of the consolidation tests.

Model-Free Extremum Seeking Control of Bioprocesses: A Review with a Worked Example

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.

Synthesis of polar copolymers by the process of emulsion via free radicals (FRP)

At present, the polymer industry has gained increasing importance due to the versatility of its properties, as well as the impact they have on the environment. The present investigation provides the determination of optimal operating conditions for the polymerization of styrene and vinyl propionate in a Batch reactor, as well as the copolymerization of styrene with propionate monomers by the process of emulsion via free radicals, allowing to observe the variations with respect to Reaction yields and molecular weights. Another important factor is the activation of the initiator so that the polymerization process begins within each of the micelles. Likewise, it was found that, in the copolymerizations, there are considerable variations with respect to reaction yields and molecular weights as the concentrations are modified. In addition, it was found that there are higher yields in styrene polymerizations per solution than emulsion.

A novel comprehensive procedure for determination of optimum operating conditions for cleaner energy production system

Cleaner energy production system such as direct alcohol fuel cells (DAFCs) are considered as an alternative source for generating cleaner energy. Studies based on design of catalysts, electrodes design, proton exchange membrane, and flow field were conducted for improving its performance characteristic such as power density. However, the less focus was paid on determining the operating conditions considering the uncertainties that will result in an increase of power density of DAFCs. Therefore, the present work proposes a novel comprehensive procedure involving experimental study and evolutionary approach of genetic programming (GP) in formulation of robust power density models for DAFCs. Two uncertainties such as the selection of objective function and variations in measurement of operating conditions are incorporated in framework of GP. The power density models incorporate the formulation of new objective function in GP that will result in higher accuracy of the models. Experiments performed on DAFCs validate performance of the models. Simulation profiler is then generated for models to verify its robustness in uncertain operating conditions. The inferences on relationships between power density and operating conditions for DAFCs are made by surface analysis of the models.

Kinetic study of hydrodeoxygenation of palmitic acid as a model compound for microalgae oil over Pt/γ-Al2O3

The kinetics of hydrodeoxygenation (HDO) of palmitic acid over the 1% Pt/γ-Al2O3 catalyst was investigated in a microreactor using integral method. Kinetic data were collected under process conditions of industrial interest but in the regime with negligible heat and mass transfer limitations. For the first time, rate equations derived from three kinetic models (Power law, Langmuir-Hinshelwood, and Eley-Rideal) were investigated in data fitting through nonlinear regression using Levenberg-Marquardt algorithm, and evaluated based on proposed statistical and thermodynamics criteria. H2 was found to be adsorbed on the catalyst surface without dissociation, which is different from gaseous reaction with consistent dissociative adsorption of H2. The apparent activation energy is 60.3kJ/mol, which is lower than the intrinsic activation energy of 92.9kJ/mol due to the exothermic adsorption of reactants. The proposed rate equations are expected to be applicable to liquid phase HDO of fatty acids, and not limited to palmitic acid. This complete kinetic study (including rate equations with specified kinetic parameters) fills an important knowledge gap in green diesel production from algae, and can be used for rational design of reactors and the determination of optimum operating conditions. Moreover, the presented work develops a systematic procedure for kinetic study by identifying the challenges that need to be overcome to obtain meaningful kinetic data.

Response Surface Optimization of an Ammonia–Water Combined Power/Cooling Cycle Based on Exergetic Analysis

Finding optimal operating conditions of solar-based power and cooling systems is always a challenge. Performance of these systems is highly dependent on several important parameters, which influence not only the long-term efficiency but also its technical and economic feasibility. This paper studies the operation/configuration problem of an ammonia–water power and cooling cycle using an exergetic and statistical analysis. The Modeling developed in Matlab® and REFPROP 9.0 was used to calculate the thermodynamic properties of the ammonia–water mixture. The thermodynamic model and properties of the ammonia/water mixture were validated with previous models found in the literature. Optimal operating conditions of the combined cycle were obtained by using response surface technique and the ratio between exergetic efficiency and exergy destruction was used as response variable. The results showed that the response variable is highly influenced by the ammonia concentration, pressure ratio (PR), turbine efficiency, and pinch point temperature in the heat exchanger. Finally, the combined cycle was integrated with a solar field using two types of concentrated solar collectors.

Modeling Closed Nuclear Fuel Cycle Processes

Determination of optimal operating conditions for closed nuclear fuel cycle processes requires computer models that are used to evaluate and modify the design solution at earlier stages of technology development and the engineering and project documentation as more data from experimental research are obtained. The computational models being developed will significantly accelerate the design process, project commissioning as well as improve quality, performance and safety characteristics of the product.

Levelized cost of energy (LCOE) metric to characterize solar absorber coatings for the CSP industry

The contribution of each component of a power generation plant to the levelized cost of energy (LCOE) can be estimated and used to increase the power output while reducing system operation and maintenance costs. The LCOE is used in order to quantify solar receiver coating influence on the LCOE of solar power towers. Two new parameters are introduced: the absolute levelized cost of coating (LCOC) and the LCOC efficiency. Depending on the material properties, aging, costs, and temperature, the absolute LCOC enables quantifying the cost-effectiveness of absorber coatings, as well as finding optimal operating conditions. The absolute LCOC is investigated for different hypothetic coatings and is demonstrated on Pyromark 2500 paint. Results show that absorber coatings yield lower LCOE values in most cases, even at significant costs. Optimal reapplication intervals range from one to five years. At receiver temperatures greater than 700 °C, non-selective coatings are not always worthwhile while durable selective coatings consistently reduce the LCOE—up to 12% of the value obtained for an uncoated receiver. The absolute LCOC is a powerful tool to characterize and compare different coatings, not only considering their initial efficiencies but also including their durability.

Off-line optimization of baker׳s yeast production process

A macroscopic model describing the influence of nitrogen on a fed-batch baker׳s yeast production process was used for the determination of optimal operating conditions in the sense of a production criterion. To this end, two different approaches were used: a control vector parameterization approach with mesh refinement and an approach based on the mathematical analysis of optimal operating policy (semi-analytical approach). The results of the two approaches lead to the determination of similar optimal operation conditions, which have been implemented for a new experimental phase. Moreover, these optimal conditions are in agreement with the profiles obtained by industrial manufacturers through an empirical optimization of the process (trial and error method). The model predictions are in good accordance with experimental data. This conclusion was supported by an uncertainty analysis on the model outputs with respect to the parameter estimation errors.

Troubleshooting a Full-scale Wastewater Treatment Plant for Biological Nutrient Removal

The International Association of Water Quality (IAWQ) Activated Sludge Model No.2 (ASM2) was applied to troubleshoot an existing underperforming full-scale wastewater treatment plant (WWTP) built for biological nutrient removal. The WWTP is operated in a 3-stage pho-redox process configuration (A2O). This study was undertaken with the aim of finding optimal operating conditions that will meet TP and TN concentration requirements in the effluent of the WWTP under study without the use of either chemical or external carbon sources and also to verify the applicability, capability and predictability of ASM2 as implemented in STOAT software. ASM2 was successfully used to troubleshoot bottle neck areas and to define the operational schedule for optimal performance of the wastewater treatment plant. Consequently, the costs of chemical and external carbon sources were eliminated and the effect of residual chemicals on the environment reduced.

A Simple Procedure for Searching Pareto Optimal Front in Machining Process: Electric Discharge Machining

Optimum control parameter setting in complex and stochastic type processes is one of the most challenging problems to the process engineers. As such, effective model development and determination of optimal operating conditions of electric discharge machining process (EDM) are reasonably difficult. In this apper, an easy to handle optimization procedure, weight-varying multiobjective simulated annealing, is proposed and is applied to optimize two conflicting type response parameters in EDM—material removal rate (MRR) and average surface roughness (Ra) simultaneously. A solution set is generated. The Pareto optimal front thus developed is further modeled. An inverse solution procedure is devised so that near-optimum process parameter settings can be determined for specific need based requirements of process engineers. The results are validated.

Multi-objective optimisation of abrasive water jet machining responses by simulated annealing and particle swarm

Optimum control parameter settings in complex and stochastic type processes are one of the most challenging problems to the process engineers. As such, effective model development and determination of optimal operating conditions of abrasive water jet machining process (AWJM) are reasonably difficult. In this article new modifications are proposed on two single-objective optimisation techniques, simulated annealing and particle swarm optimisation and applied to optimise two response parameters in AWJM – material removal rate (MRR) and depth of cut (DOC) simultaneously. For the optimisation purpose statistical models are developed from experimental data obtained from AWJ machining of amorphous material – borosilicate glass. Optimum results are validated and it is suggested to employ particle swarm-based proposed multi-objective optimisation technique in present case for newly modelled system due to its fast convergence and low memory space requirement.

Determination of optimal operating conditions for a polymer electrolyte membrane fuel cell stack: optimal operating condition based on multiple criteria

SUMMARY A methodology for optimal control of the polymer electrolyte membrane fuel cell (PEMFC) with multiple criteria is presented here. In this regard, thermoelectric objectives and thermoeconomic objective are considered, simultaneously. The proposed fuel cell is a 1200 W Ballard PEMFC namely Nexa™ power module. The net power density and exergetic efficiency of the PEMFC are maximized, and the unit cost of the generated power is minimized in a multi-objective optimization procedure using the NSGA-II (non-dominated sorting genetic algorithm). Operating temperature and pressure, air stoichiometric coefficient at the cathode and the current density are considered as controlling parameters in order to acquire optimal performance of the PEMFC. A set of optimal solution namely the Pareto frontier is obtained, and a final optimal solution is selected from available solutions located on the Pareto frontier using the fuzzy decision-making process based on the Bellman–Zadeh approach. Results are compared with corresponding results obtained previously in single objective optimization scenarios. It has been shown that the optimal operating condition obtained based on the multiple criteria approach has least deviation from the ideal features of the fuel cell in comparison to the corresponding optimal solution obtained in conventional single-objective optimization approaches. Copyright © 2013 John Wiley & Sons, Ltd.