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Cost-effectiveness and economic growth potential evaluation of olive pomace gasification process to sustainable fuel: Comparison study of different gasifying agent

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2024年 187卷 533-548页

作者： Hosseingholilou, Behnam Tavakoli, Navid Saidi, Majid Univ Tehran Coll Sci Sch Chem POB 14155-6455 Tehran Iran Univ Tehran Fac New Sci & Technol Tehran Iran

This research addresses the growing global demand for sustainable and renewable energy solutions, focusing on biomass gasification (BG) as a promising avenue. Olive pomace is explored as a primary feedstock, assessing its potential as a plentiful and renewable energy source. The study aims to bridge existing gaps in the literature, particularly in the simultaneous and comparative examination of CO2, steam, and air as traditional gasifying agents. Utilizing Aspen Plus, a validated simulation tool, the research models the gasification process (GP) while considering key parameters such as gasifying agent, feed composition, and temperature. Through meticulous simulation and validation against experimental data, the goal is to develop a robust model tailored for gasification. A thorough sensitivity analysis evaluates critical parameters' impact on exergy efficiency, levelized cost of hydrogen (LCOH), and molar flow of hydrogen (H2). Parameters include temperature variations (600 degrees C to 1000 degrees C), equivalence ratio (ER) for the air agent (0.15-0.3), C/CO2 ratio for the CO2 agent (1-2.5), and SBR for the steam agent (0.5-2). The aim is to provide a nuanced understanding of these parameters and their influence on system performance, offering valuable insights for process optimization. The response surface methodology is employed to optimize critical parameters for distinct gasification agents, aiming to identify the most economically efficient agent. The study's findings are crucial for enhancing BG efficiency and developing sustainable energy systems. An economic evaluation underscores the cost-effectiveness of the GP, emphasizing its potential for economic growth in the renewable energy sector and long-term savings. In the concluding phase, optimization of the GP aimed at minimizing LCOH and maximizing molar flow of H2 and exergy efficiency was conducted. Upon scrutinizing the optimization results, a compelling conclusion arose: The steam agent emerged as the

关键词： Biomass gasification Process Aspen Plus simulation Exergy efficiency analysis modeling and optimization Economic analysis

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Technological challenges and optimization efforts of the Stirling machine: A review

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ENERGY CONVERSION AND MANAGEMENT 2018年 171卷 1365-1387页

作者： Hachem, Houda Gheith, Ramla Aloui, Fethi Ben Nasrallah, Sassi Univ Monastu Ecole Natl Ingenieurs Monastir Lab LESTE Ave Ibn El Jazzar Monastir 5019 Tunisia Univ Valenciennes UVHC Univ Lille North France Dept Mech LAMIH CNRS UMR 8201 Campus Mt Houy F-59313 Valenciennes 9 France

The Stirling engines are being carried out worldwide, used for divers' application such as solar generator, micro cogeneration and cryogenic uses. The present paper is an over view of Stirling technologies researches. Several possibilities of resolving technical challenges encountered when manufacturing or using Stirling machines will be discussed. The most appropriate models and optimizations strategies are reported. Stirling engine performances are derived as function of geometric parameters (swept volumes, dead volumes, heat exchange areas, compression ratio...) for several working conditions (speed, mean pressure, temperature difference and working fluid). The effect of each parameter on the Stirling performances when using numerical and/or experimental approaches are presented. It is concluded that multi-objective optimizations methods are useful for predicting geometric and working parameters that corresponding to the optimal performances of the Stirling engine.

关键词： Challenge modeling and optimization Applications Stirling machine

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More mixed-integer linear programming models for solving three-stage remanufacturing system scheduling problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 194卷

作者： Wang, Wenjie Tian, Guangdong Luo, Mengqi Zhang, Honghao Yuan, Gang Niu, Kejia Zhengzhou Univ Sch Mech & Power Engn Zhengzhou 450001 Peoples R China Beijing Univ Civil Engn & Architecture Sch Machinery & Vehicles Beijing 100044 Peoples R China Shandong Univ Sch Mech Engn Jinan 250061 Peoples R China Southeast Univ Sch Mech Engn Nanjing 212000 Peoples R China Henan Univ Sci & Technol Sch Appl Engn Sanmenxia 472199 Peoples R China

This paper aims to deal with the three-stage remanufacturing system scheduling problem (3T-RSSP) that minimizes the maximum completion time i.e., makespan. To this end, inspired by distinct modeling ideas, four mixedinteger linear programming (MILP) models are formulated. The modeling ideas used in this paper are sequencebased idea, position-based idea, time-based idea, and adjacent sequence-based idea. Numerical experiments are executed on a set of small-scaled, medium-scaled and large-scaled instances to test the performance of these formulated MILP models in terms of size complexity and computation complexity. Experimental results demonstrate that the sequence-based MILP model (Model 1) is the most efficient one while the time-based MILP model (Model 3) is worst one. The Wilcoxon signed-rank test is also conducted to evaluate the four models. Model 1 is further compared with different optimization solvers, heuristic and some state-of-art heuristics. Comparison results verify the effectiveness and good portability of the MILP model. Moreover, some key parameters contained in 3T-RSSP including end-of-life (EOL) products count, reprocessing lines count, disassembly workstations/reassembly workstations count are also evaluated. Notably, it is concluded that the increase of disassembly workstations/reassembly workstations count can improve the three-stage remanufacturing system's flexibility and contribute to the enhancement of production efficiency.

关键词： Three-stage remanufacturing system scheduling Makespan Mixed-integer linear programming modeling and optimization

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Cost-effective analyses for emergency medical services deployment: A case study in Shanghai

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2015年 163卷 112-123页

作者： Su, Qiang Luo, Qinyi Huang, Samuel H. Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China Univ Cincinnati Dept Mech & Mat Engn Cincinnati OH 45221 USA

The response speed of emergency medical services (EMS) is extremely critical for pre-hospital lifesaving. Each second plays a vital role in emergent cases. Therefore, the EMS network should be careffilly designed to provide timely and reliable services. This paper focuses on improving the classical ambulance deployment method to optimize the distribution of first-aid resources. We refine the double coverage model with a new objective function that minimizes the expected cost for delayed emergencies plus the operational cost for EMS. EMS operators can use this refined model to analyze the cost-effectiveness of the emergency network, as demonstrated in a real-world EMS deployment case study. To solve this large-scale integer-programming problem, we compared several heuristic algorithms and finally chose ant colony optimization algorithm. Several modifications are made to adapt the traditional ant colony algorithm to solve our problem. The paper concludes with an optimized and cost-effective plan for ambulance deployment in the downtown area of Shanghai. After optimization, the objective cost is lowered by about 11% each year and 10% less emergency calls are missed or delayed. In addition, we use our modified model to test scenarios with relaxed limit of resources. Potential improvement of future EMS network is discovered. It turns out that increasing the number of first-aid stations from 35 (current number of stations) to 50 and adding 10 vehicles will achieve a surprising 49% cost saving while maintaining a satisfactory service level. (C) 2015 Elsevier B.V. All rights reserved.

关键词： EMS facility location Ambulance assignment modeling and optimization Heuristic algorithm

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Comparative study of pulsed Nd:YAG laser welding of AISI 304 and AISI 316 stainless steels

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OPTICS AND LASER TECHNOLOGY 2017年 88卷 24-39页

作者： Kumar, Nikhil Mukherjee, Manidipto Bandyopadhyay, Asish Jadavpur Univ Dept Mech Engn Kolkata 700032 India Jadavpur Univ Met & Mat Engn Dept Kolkata 700032 India

Laser welding is a potentially useful technique for joining two pieces of similar or dissimilar materials with high precision. In the present work, comparative studies on laser welding of similar metal of AISI 304SS and AISI 316SS have been conducted forming butt joints. A robotic control 600 W pulsed Nd:YAG laser source has been used for welding purpose. The effects of laser power, scanning speed and pulse width on the ultimate tensile strength and weld width have been investigated using the empirical models developed by RSM. The results of ANOVA indicate that the developed models predict the responses adequately within the limits of input parameters. 3-D response surface and contour plots have been developed to find out the combined effects of input parameters on responses. Furthermore, microstructural analysis as well as hardness and tensile behavior of the selected weld of 304SS and 316SS have been carried out to understand the metallurgical and mechanical behavior of the weld. The selection criteria are based on the maximum and minimum strength achieved by the respective weld. It has been observed that the current pulsation, base metal composition and variation in heat input have significant influence on controlling the microstructural constituents (i.e. phase fraction, grain size etc.). The result suggests that the low energy input pulsation generally produce fine grain structure and improved mechanical properties than the high energy input pulsation irrespective of base material composition. However, among the base materials, 304SS depict better microstructural and mechanical properties than the 316SS for a given parametric condition. Finally, desirability function analysis has been applied for multi-objective optimization for maximization of ultimate tensile strength and minimization of weld width simultaneously. Confirmatory tests have been conducted at optimum parametric conditions to validate the optimization techniques. (C) 2016 Elsevier Ltd. All rights

关键词： Laser welding Response surface methodology modeling and optimization Microstructure Mechanical properties

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Comparison of computational fluid dynamics (CFD) and pressure drop correlations in laminar flow regime for packed bed reactors and columns

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POWDER TECHNOLOGY 2018年 328卷 130-139页

作者： Pavlisic, Andraz Ceglar, Rok Pohar, Andrej Likozar, Blaz Natl Inst Chem Dept Catalysis & Chem React Engn Hajdrihova 19 Ljubljana 1001 Slovenia

Empirical correlation (EC) equations are still of a great designing importance for industrial plant construction. They are an indispensable modeling tool for engineers, reducing the time to find the optimal operating conditions. Nonetheless, numerical method complexity and product yield optimisation are advancing. Computational fluid dynamics (CFD) is thus nowadays applicable for optimizing chemical reactors. In contrast to EC, CFD acknowledges specific vessel geometry, where local physical and chemical phenomena, contributing to apparent catalytic turnover, prevail. Presently, EC and CFD were compared considering the pressure drop predictions within the packed bed columns for spherical, cylindrical, trilobe and quadrilobe particle packing, in order to determine the limits of EC accuracy. 52 configurations were simulated and the estimations within EC validity range margins were in agreement with CFD (<15%), while in extremes (non-negligible entrance and exit patterns), a 70% deviation could be exceeded. Furthermore, boundary wall effects were found to be dependent on the stacked pellet shape and orientation, and did not necessarily lead to an increase of viscous friction loss, relative to the infinitely wide systems, for the column-to-particle diameter ratios, lower than 10, which is contradictory to non mechanistic relationship models. While the induced pressure difference within realistic fixed beds is elevated due to gas or liquid surface interaction and back-mixing, it can also be decreased by channeling/tunneling, which is why the effective net influence should be analyzed with CFD simulations, particularly in novel intensified and micronized processes, in which momentum, mass and heat transfer resistances are far from bulk medium continuity. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Computational fluid mechanics modeling and optimization Laminar flow pattem Friction loss correlations Continuous packed-bed reactor Irregular particle packing

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Implementing Digital Twin in Field-Deployed Optical Networks: Uncertain Factors, Operational Guidance, and Field-Trial Demonstration

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IEEE NETWORK 2024年第1期38卷 38-45页

作者： Song, Yuchen Zhang, Min Zhang, Yao Shi, Yan Shen, Shikui Guo, Bingli Huang, Shanguo Wang, Danshi Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China China Unicom Res Inst Beijing 100044 Peoples R China

Digital twin has revolutionized optical communication networks by enabling their full life-cycle management, including design, troubleshooting, optimization, upgrade, and prediction. While extensive literature exists on frameworks, standards, and applications of digital twin, there is a pressing need in implementing digital twin in field-deployed optical networks operating in real-world environments, as opposed to controlled laboratory settings. This paper addresses this challenge by examining the uncertain factors behind the inaccuracy of digital twin in field-deployed optical networks from three main challenges and proposing operational guidance for implementing accurate digital twin in field-deployed optical networks. Through the proposed guidance, we demonstrate the effective implementation of digital twin in a field-trial C+L-band optical transmission link, showcasing its capabilities in performance recovery in a fiber cut scenario.

关键词： Optical fiber networks Optical fiber amplifiers Optical fiber devices Erbium-doped fiber amplifiers Digital twins Indexes Connectors Digital twin wideband optical networks modeling and optimization field deployed networks

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Investigating the effect of dianhydride type and pyrolysis condition on the gas separation performance of membranes derived from blended polyimides through statistical analysis

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JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY 2014年第3期20卷 1061-1070页

作者： Pirouzfar, Vahid Moghaddam, Abdolsamad Zarringhalam Omidkhah, Mohammad Reza Hosseini, Seyed Saeid Tarbiat Modares Univ Dept Chem Engn Tehran Iran

In this study, properly designed experiments are utilized to improve and optimize the main parameters including the selection of precursors with different molecular structures, blend composition of precursors and conditions of carbonization. Optimum conditions are met for UIP-R/PBI, at blend composition of 94% and pyrolysis temperature of 620 degrees C at 10(-7) Torr. Under such conditions, the model estimated permeability of CH4 and CO2 equal to 26.7 and 310 Barrer, while measured selectivity responses of CO2/CH4 is 77.5, respectively. As a result, greater values of separation efficiency are achieved in the range of 0.88-0.97 polyimide content in these blends. (C) 2013 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

关键词： Gas permeability and selectivity CMS membranes modeling and optimization Factorial design Carbonization

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optimization of biofuel production from biomass using montmorillonite catalyst by development of predictive models

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JOURNAL OF MOLECULAR LIQUIDS 2024年 403卷

作者： Dong, Li Sharma, Pawan Abass, Russul Reidh Al-shuwaili, Saeb Jasim Kumar, Abhishek Al-Abdeen, Salah Hassan Zain Qassem, Laith Yassen Alam, Mohammad Mahtab Qingdao Huanghai Univ Inst Intelligent Mfg Qingdao 266427 Shandong Peoples R China Jain Univ Sch Sci Dept Chem Bengaluru 560069 Karnataka India Vivekananda Global Univ Dept Sci Jaipur 303012 Rajasthan India Al Farahidi Univ Med Lab Coll Med Technol Tech Dept Baghdad Iraq Al Hadi Univ Coll Dept Engn Baghdad 10011 Iraq Shobhit Univ Gangoh Adarsh Vijendra Inst Pharmaceut Sci Sch Pharm Gangoh 247341 Uttar Pradesh India Arka Jain Univ Dept Pharm Jamshedpur 831001 Jharkhand India AL Nisour Univ Coll Dept Med Labs Technol Baghdad Iraq AlNoor Univ Coll Dept Med Lab Tech Nineveh Iraq King Khalid Univ Coll Appl Med Sci Dept Basic Med Sci Abha Saudi Arabia

Fossil fuel depletion and their environmental problems lead to new research for production of alternative fuels. Biofuels are promising nontoxic and biodegradable energies obtained from renewable sources. Experimental studies of biofuel production and optimizing the properties are very time-consuming, cost-intensive, and difficult. Thus, recently there have been major interests in application of Machine Learning (ML) techniques to develop models for predicting biofuel production process and optimization. This study proposed novel ML approach based on Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), and Adaboost on SVM base (Adaboost + SVM) algorithms optimized the production of biofuel from waste cooking oil through transesterification process and under montmorillonite (MMT) catalyst. The input variables for the models were chosen to be the temperature of the reaction (ranging from 100 to 200 degrees C), treatment time (ranging from 3 to 9 h), catalyst loading (ranging from 2 to 6 wt%), and methanol to oil molar ratio (ranging from 8 to 16). Meanwhile, the output of the models was selected to be the yield of biofuel production. The obtained results of three models were evaluated and compared and it was confirmed that the Adaboost + SVM model with highest regression coefficient (R-2) of 0.971, was more accurate and could predict the biofuel production more properly. Additionally, the SVM model exhibited the highest maximum error with an MAE of 6.504 and an RMSE of 7.462. On the other hand, the Adaboost + SVM model showed the lowest error, with an MAE of 3.151 and an RMSE of 4.484. The MLP model had an MAE of 4.423 and an RMSE of 6.008, which falls between the other two models in terms of error. The optimization results obtained by the Adaboost + SVM model demonstrated that the optimal conditions giving the highest biofuel production of 96.79 % were found to be: reaction time of 8.62 h, catalyst loading of 4.88 wt%, methanol/oil molar ratio of 11.2, and re

关键词： Biodiesel Waste cooking oil Montmorillonite clay Transesterification modeling and optimization Renewable energy

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Optimized formulation of NiFe₂O₄@Ca-alginate composite as a selective and magnetic adsorbent for cationic dyes: Experimental and modeling study

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REACTIVE & FUNCTIONAL POLYMERS 2018年 125卷 57-69页

作者： Cojocaru, Corneliu Humelnicu, Andra Cristina Samoila, Petrisor Pascariu, Petronela Harabagiu, Valeria Petru Poni Inst Macromol Chem Aleea Grigore Ghica Voda 41A Iasi 700487 Romania

This paper reports a data-driven modeling methodology undertaken to establish the optimal formulation of NiFe2O4@Ca-alginate composite designed for adsorption applications. Adsorbents were produced as anisotropic plate-like particles that were applied for removal of Rhodamine-6G (Rh6G) and Methylene Blue (MB) cationic dyes from aqueous solutions. Data-driven models were developed to establish the composition-performance relationships and to optimize the formulation of the composite adsorbent. The optimal formulation of NiFe2O4@Ca-alginate composite implied a content of 16% (w/w) NiFe2O4 nanoparticles into the alginate matrix. Likewise, kinetics, isotherms and thermodynamics studies were carried out and reported in this paper. The optimal adsorbent (NiFe2O4@Ca-alginate) yielded a remarkable maximal sorption capacity equal to 1243 mg/g (for MB uptake) and 845 mg/g (for Rh6G) at the room temperature (298 K). Dubinin-Radushkevich (D-R) isotherms revealed the mean free energy of sorption ranging from 7.23 to 9.26 (kJ/mol) suggesting that the mechanism of adsorption was based on both physical interactions and ion exchange. This evidence was also corroborated by the molecular docking simulations that highlighted valuable insights regarding the intermolecular interactions between alginate chains and cationic dyes.

关键词： Alginate Spinel ferrite Dye adsorption modeling and optimization Molecular docking simulation

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