scholarly journals Optimizing TEG Dehydration Process under Metamodel Uncertainty

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6177
Author(s):  
Rajib Mukherjee ◽  
Urmila M. Diwekar

Natural gas processing requires the removal of acidic gases and dehydration using absorption, mainly conducted in tri-ethylene glycol (TEG). The dehydration process is accompanied by the emission of volatile organic compounds, including BTEX. In our previous work, multi-objective optimization was undertaken to determine the optimal operating conditions in terms of the process parameters that can mitigate BTEX emission using data-driven metamodeling and metaheuristic optimization. Data obtained from a process simulation conducted using the ProMax® process simulator were used to develop a metamodel with machine learning techniques to reduce the computational time of the iterations in a robust process simulation. The metamodels were created using limited samples and some underlying phenomena must therefore be excluded. This introduces the so-called metamodeling uncertainty. Thus, the performance of the resulting optimized process variables may be compromised by the lack of adequately accounting for the uncertainty introduced by the metamodel. In the present work, the bias of the metamodel uncertainty was addressed for parameter optimization. An algorithmic framework was developed for parameter optimization, given these uncertainties. In this framework, metamodel uncertainties are quantified using real model data to generate distribution functions. We then use the novel Better Optimization of Nonlinear Uncertain Systems (BONUS) algorithm to solve the problem. BTEX mitigation is used as the objective of the optimization. Our algorithm allows the determination of the optimal process condition for BTEX emission mitigation from the TEG dehydration process under metamodel uncertainty. The BONUS algorithm determines optimal process conditions compared to those from the metaheuristic method, resulting in BTEX emission mitigation up to 405.25 ton/yr.

2016 ◽  
Vol 866 ◽  
pp. 196-200
Author(s):  
Sun Ho Jung ◽  
S. Lee ◽  
J. Lee

Band structures with pearlite and ferrite aligned as stripes can be created during the heat treatment of carbon steel. Since band structures undermine the mechanical quality of end products, it is highly important to select a process condition that will not create band structures as a result of heat treatment. This study verified the effect of temperature and cooling rate on the creation of band structures during heat treatment of 35MnB and 25Mn steel tubes for drive shafts and also considered the optimal process conditions to remove band structures or prevent their creation. The experimental results suggest that, during heat treatment of 35MnB and 25Mn steel tubes, it is most effective to ensure a cooling rate faster than furnace cooling in order to prevent band structures.


2014 ◽  
Vol 31 (3) ◽  
pp. 193-200
Author(s):  
Dominik Jurków

Purpose – The paper aims to present the influence of the co-firing process conditions of low temperature co-fired ceramics (LTCC) on the deformation of thin LTCC membranes. Design/methodology/approach – The statistical design of the experiment methodology was used in the frame of these investigations to reduce the time and costs of the experiments and to ensure easier interpretation of the obtained results. Moreover, this conception permits the rough estimation of the membrane deflection fired at optimal process conditions. Findings – The applied design of the experiment methodology allowed the researchers to find the optimal co-firing process conditions and to estimate the membrane deflection at the optimal process conditions. The estimation fits well with the results of real measurement that was conducted to confirm the estimation precision. Research limitations/implications – The experiment was conducted for only one type of LTCC, DP951. The precision of the design of the experiment optimization and estimation of the response at optimal conditions depend on the described object. Therefore, the findings of this paper do not have to be generally true for other LTCC tapes, and if other LTCC tapes deformation should be investigated, then similar analysis shall be conducted for them. Practical implications – The deformation of LTCC membranes affects the sensitivity and repeatability of LTCC acceleration and pressure sensors. Hence, the decrease of membrane deflection increases the usability of LTCC in such applications. Originality/value – This paper presents simple optimization of co-firing process conditions of LTCC devices using statistical design of the experiment.


Crystals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 532
Author(s):  
Manuela Galati ◽  
Oscar Di Mauro ◽  
Luca Iuliano

Macroscale modeling plays an essential role in simulating additive manufacturing (AM) processes. However, models at such scales often pay computational time in output accuracy. Therefore, they cannot forecast local quality issues like lack of fusion or surface roughness. For these reasons, this kind of model is never used for process optimization, as it is supposed to work with optimized parameters. In this work, a more accurate but still simple three-dimensional (3D) model is developed to estimate potential faulty process conditions that may cause quality issues or even process failure during the electron beam melting (EBM) process. The model is multilayer, and modeling strategies are developed to have fast and accurate responses. A material state variable allows for the molten material to be represented. That information is used to analyze process quality issues in terms of a lack of fusion and lateral surface roughness. A quiet element approach is implemented to limit the number of elements during the calculation, as well as to simulate the material addition layer by layer. The new material is activated according to a predefined temperature that considers the heat-affected zone. Heat transfer analysis accuracy is comparatively demonstrated with a more accurate literature model. Then, a multilayer simulation validates the model capability in predicting the roughness of a manufactured Ti6Al4V sample. The model capability in predicting a lack of fusion is verified under a critical process condition.


2021 ◽  
Vol 9 (7) ◽  
pp. 1457
Author(s):  
Julia Hassa ◽  
Johanna Klang ◽  
Dirk Benndorf ◽  
Marcel Pohl ◽  
Benedikt Hülsemann ◽  
...  

There are almost 9500 biogas plants in Germany, which are predominantly operated with energy crops and residues from livestock husbandry over the last two decades. In the future, biogas plants must be enabled to use a much broader range of input materials in a flexible and demand-oriented manner. Hence, the microbial communities will be exposed to frequently varying process conditions, while an overall stable process must be ensured. To accompany this transition, there is the need to better understand how biogas microbiomes respond to management measures and how these responses affect the process efficiency. Therefore, 67 microbiomes originating from 49 agricultural, full-scale biogas plants were taxonomically investigated by 16S rRNA gene amplicon sequencing. These microbiomes were separated into three distinct clusters and one group of outliers, which are characterized by a specific distribution of 253 indicative taxa and their relative abundances. These indicative taxa seem to be adapted to specific process conditions which result from a different biogas plant operation. Based on these results, it seems to be possible to deduce/assess the general process condition of a biogas digester based solely on the microbiome structure, in particular on the distribution of specific indicative taxa, and without knowing the corresponding operational and chemical process parameters. Perspectively, this could allow the development of detection systems and advanced process models considering the microbial diversity.


Author(s):  
Aristide Giuliano ◽  
Enrico Catizzone ◽  
Cesare Freda

The production of dimethyl ether from renewables or waste is a promising strategy to push towards a sustainable energy transition of alternative eco-friendly diesel fuel. In this work, we simulate the synthesis of dimethyl ether from a syngas (a mixture of CO, CO2 and H2) produced from gasification of digestate. In particular, a thermodynamic analysis was performed to individuate the best process conditions and syngas conditioning processes to maximize yield to dimethyl etehr (DME). Process simulation was carried out by ChemCAD software, and it was particularly focused on the effect of process conditions of both water gas shift and CO2 absorption by Selexol® on the syngas composition, with a direct influence on DME productivity. The final best flowsheet and the best process conditions were evaluated in terms of CO2 equivalent emissions. Results show direct DME synthesis global yield was higher without the WGS section and with a carbon capture equal to 85%. The final environmental impact was found equal to −113 kgCO2/GJ, demonstrating that DME synthesis from digestate may be considered as a suitable strategy for carbon dioxide recycling.


2018 ◽  
Vol 06 (02) ◽  
pp. 95-118 ◽  
Author(s):  
Mohammadreza Radmanesh ◽  
Manish Kumar ◽  
Paul H. Guentert ◽  
Mohammad Sarim

Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information.


2017 ◽  
Vol 18 (9) ◽  
pp. 951-970 ◽  
Author(s):  
Riccardo Amirante ◽  
Elia Distaso ◽  
Paolo Tamburrano ◽  
Rolf D Reitz

The laminar flame speed plays an important role in spark-ignition engines, as well as in many other combustion applications, such as in designing burners and predicting explosions. For this reason, it has been object of extensive research. Analytical correlations that allow it to be calculated have been developed and are used in engine simulations. They are usually preferred to detailed chemical kinetic models for saving computational time. Therefore, an accurate as possible formulation for such expressions is needed for successful simulations. However, many previous empirical correlations have been based on a limited set of experimental measurements, which have been often carried out over a limited range of operating conditions. Thus, it can result in low accuracy and usability. In this study, measurements of laminar flame speeds obtained by several workers are collected, compared and critically analyzed with the aim to develop more accurate empirical correlations for laminar flame speeds as a function of equivalence ratio and unburned mixture temperature and pressure over a wide range of operating conditions, namely [Formula: see text], [Formula: see text] and [Formula: see text]. The purpose is to provide simple and workable expressions for modeling the laminar flame speed of practical fuels used in spark-ignition engines. Pure compounds, such as methane and propane and binary mixtures of methane/ethane and methane/propane, as well as more complex fuels including natural gas and gasoline, are considered. A comparison with available empirical correlations in the literature is also provided.


2012 ◽  
Vol 524-527 ◽  
pp. 1078-1081
Author(s):  
Jian Guo Song ◽  
Xin Zhi Wang ◽  
Shao Dan Xiao ◽  
Wei Liu

This article aims to study the technology of extracting potassium from potassium feldspar with molten salt leaching method and to analyze the effects of temperature, reaction time and other factors on extracting potassium, concluding the optimal process conditions of extracting potassium with molten leaching method from potash feldspar.


Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 946
Author(s):  
Chunlian Wang ◽  
Xiaojie Sun ◽  
Huijun Shan ◽  
Hongxia Zhang ◽  
Beidou Xi

This study explored the performance of TiO2 nanoparticles in combination with aged waste reactors to treat landfill leachate. The optimum conditions for synthesis of TiO2 were determined by a series of characterizations and removal rates of methyl orange. The effect of the ultraviolet irradiation time, amount of the catalyst, and pH on the removal efficiency for the chemical oxygen demand (COD) and color in the leachate was explored to determine the optimal process conditions, which were 500 min, 4 g/L and 8.88, respectively. The removal rates for COD and chroma under three optimal conditions were obtained by the single factor control method: 89% and 70%; 95.56% and 70%; and 85% and 87.5%, respectively. Under optimal process conditions, the overall average removal rates for ammonium nitrogen (NH4+–N) and COD in the leachate for the combination of TiO2 nanoparticles and an aged waste reactor were 98.8% and 32.5%, respectively, and the nitrate (NO3−–N) and nitrite nitrogen (NO2–N) concentrations were maintained at 7–9 and 0.01–0.017 mg/L, respectively. TiO2 nanoparticles before and after the photocatalytic reaction were characterized by emission scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction, and Fourier transform infrared spectrometry. In addition, TiO2 nanoparticles have excellent recyclability, showing the potential of the photocatalytic/biological combined treatment of landfill leachate. This simulation of photocatalysis-landfilling could be a baseline study for the implementation of technology at the pilot scale.


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