Fuel Processing Technology最新文献_第7页

Optimization of advanced biogas production via the DiCOM bioprocess utilizing the biogas test plant BTP2: Insights from multifactorial analysis 利用沼气测试厂BTP2通过DiCOM生物工艺优化先进沼气生产：来自多因素分析的见解

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-30 DOI: 10.1016/j.fuproc.2025.108343

Mansuur Husein , Liang Cheng , Francis Kwaku Attiogbe , Abdallah Abdelfattah , Hany S. El-Mesery , Emmanuel Nkudede

This study introduces an innovative optimization of the DiCOM bioprocess, which integrates aerobic composting and anaerobic digestion, utilizing the Biogas Test Plant BTP2 configured as a continuous stirred-tank reactor (CSTR). The research seeks to enhance biogas production from sewage sludge by examining the effects of key operational parameters, including temperature, pH, inoculum-to-substrate ratio, and stirrer speed. This investigation is pioneering in its use of a DiCOM-CSTR configuration, distinguishing it from previous studies that focused on fixed-bed or sequential systems. This approach facilitates continuous operation and enhances process control. A multifactorial experimental design was employed, utilizing Box-Behnken Design (BBD) and Response Surface Methodology (RSM), along with Principal Component Analysis (PCA), to evaluate the combined impacts of critical parameters such as temperature, pH, inoculum-to-substrate ratio (ISR), and stirrer speed. Under optimized conditions, a thermophilic temperature of 65 °C, neutral pH (7.0–7.5), ISR of 0.63, and controlled stirring speed of 100 rpm contributed to achieving a methane yield of up to 64.2 % and hydrogen sulfide concentrations as low as 3.9 ppm. The results surpass previously reported values, confirming the effectiveness of the proposed configuration and methodological approach. The integrated PCA-RSM framework provided enhanced multivariate insight into parameter interactions and process dynamics. Future studies should deepen the understanding of microbial community dynamics, assess the long-term operational stability of the DiCOM process, and evaluate its adaptability across diverse organic waste streams. This study not only advances the design and optimization of DiCOM systems but also offers a scalable approach for sustainable energy recovery from organic waste.

本研究介绍了DiCOM生物工艺的创新优化，该工艺将好氧堆肥和厌氧消化结合起来，利用沼气试验装置BTP2配置为连续搅拌槽反应器（CSTR）。该研究旨在通过检查关键操作参数的影响，包括温度、pH值、接种物与底物比和搅拌速度，来提高污水污泥的沼气产量。这项研究在使用DiCOM-CSTR配置方面是开创性的，与之前专注于固定床或顺序系统的研究不同。这种方法有利于连续操作，并加强过程控制。采用Box-Behnken设计（BBD）和响应面分析法（RSM），结合主成分分析（PCA），对温度、pH、接种物与底物比（ISR）和搅拌速度等关键参数的综合影响进行了评价。在优化条件下，亲热温度为65°C，中性pH值（7.0-7.5），ISR为0.63，控制搅拌速度为100 rpm，甲烷收率高达64.2%，硫化氢浓度低至3.9 ppm。结果超过了先前报道的值，证实了所建议的配置和方法方法的有效性。集成的PCA-RSM框架为参数交互和过程动力学提供了增强的多变量洞察。未来的研究应深化对微生物群落动态的理解，评估DiCOM工艺的长期运行稳定性，并评估其在不同有机废物流中的适应性。这项研究不仅推进了DiCOM系统的设计和优化，而且为有机废物的可持续能源回收提供了一种可扩展的方法。

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引用次数: 0

Exploration on physicochemical properties and combustion behaviors of hydrochar from co-hydrothermal carbonization of swine manure and tea waste 猪粪与茶渣共水热炭化烃类的理化性质及燃烧行为探讨

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-27 DOI: 10.1016/j.fuproc.2025.108345

Ke Huang , Xin Zhang , Xiaozhen Li , Renxin Liu , Ke Wu

Co-hydrothermal carbonization (co-HTC) of animal manure and lignocellulosic biomass is recognized as an innovative approach to improve the quality of hydrochar derived from the HTC of animal manure. This study explored the effects of mass mixing ratio and temperature on the physicochemical properties and combustion behaviors of hydrochar from co-HTC of swine manure (SM) and tea waste (TW). The synergistic effect between SM and TW promoted the deoxygenation of SM and the aromatization of hydrochar. Compared to hydrochar from HTC of SM, the carbon content and higher heating value increased considerably, reaching the maximum of 48.64 % and 19.94 MJ/kg, respectively. Less lamellar structure and numerous microspheres were observed on the surface of hydrochar produced at 250 °C with 1/1 mass ratio. Additionally, the combustion performance of hydrochars from co-HTC were improved, as indicated by increases in the comprehensive combustion index and combustion stability index. Kinetic analysis showed that the activation energy of hydrochar increased with the increasing TW proportion and temperature. These findings provided valuable insights into the co-HTC of SM and TW, supporting the effective upgrading of animal manure and lignocellulosic biomass.

动物粪便和木质纤维素生物质的共水热碳化（co-HTC）被认为是提高动物粪便共水热碳化所得碳氢化合物质量的一种创新方法。研究了质量配比和温度对猪粪（SM）和茶渣（TW）共混氢炭理化性质和燃烧行为的影响。SM和TW的协同作用促进了SM的脱氧和烃类的芳构化。与SM的HTC生成的烃类相比，含碳量和高热值显著增加，最高分别达到48.64%和19.94 MJ/kg。在250℃条件下以1/1的质量比制备的碳氢化合物表面具有较少的片层结构和大量的微球。此外，通过综合燃烧指数和燃烧稳定性指数的提高，co-HTC的碳氢化合物的燃烧性能得到了改善。动力学分析表明，随着TW比例的增加和温度的升高，烃类的活化能增大。这些发现为SM和TW的共同htc提供了有价值的见解，支持了动物粪便和木质纤维素生物质的有效升级。

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引用次数: 0

Upcycling of EVA resin from photovoltaics into supercapacitor material and combustible gas by autogenic pressure pyrolysis 利用自生压力热解法将光伏EVA树脂升级为超级电容器材料和可燃气体

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-26 DOI: 10.1016/j.fuproc.2025.108344

Yadi Jia , Pinjing He , Fan Lü , Wei Peng , Hua Zhang , Khamphe Phoungthong

In response to the growing challenge of photovoltaic waste management, developing sustainable and value-added treatment strategies is imperative. In this study, ethylene-vinyl acetate (EVA) resins sourced from waste photovoltaic modules and virgin materials were utilized for the production of hierarchical porous carbon (HPC) and methane-rich combustible gas via autogenic pressure pyrolysis coupled with KOH activation. Temperature-dependent pyrolysis revealed that 700 °C was the optimal condition, yielding pyrolysis gas with a high methane content (43.39 vol%) and producing graphitized carbon spheres. Subsequent KOH activation generated HPC with a large specific surface area of 765.4 m²/g. When applied as a supercapacitor electrode in 6 mol/L KOH electrolyte, the HPC exhibited a high specific capacitance of 152 F/g at 0.2 A/g. Additionally, EVA resins with higher vinyl acetate content and melt index (MI) produced greater amounts of methane and pyrolytic carbon, while the resins with lower MI values showed enhanced reactivity toward chemical activation. This work offers a green and efficient route for the high-value recycling of EVA in PV waste and contributes to the sustainable synthesis of advanced HPC materials for energy storage applications.

为了应对日益增长的光伏废弃物管理挑战，开发可持续和增值处理策略势在必行。在这项研究中，利用来自废旧光伏组件和原始材料的乙烯-醋酸乙烯酯（EVA）树脂，通过自生压力热解结合KOH活化，生产分层多孔碳（HPC）和富含甲烷的可燃气体。温度相关热解实验结果表明，700℃为最佳热解条件，热解气体甲烷含量较高（43.39 vol%），热解产物为石墨化碳球。随后KOH活化生成的HPC具有765.4 m2/g的大比表面积。在6 mol/L KOH电解液中作为超级电容器电极时，在0.2 a /g下，HPC的比电容高达152 F/g。此外，具有较高醋酸乙烯含量和熔融指数（MI）的EVA树脂产生更多的甲烷和热解碳，而具有较低MI值的树脂对化学活化的反应性增强。这项工作为光伏废弃物中EVA的高价值回收提供了一条绿色高效的途径，并有助于可持续合成用于储能应用的先进高性能计算材料。

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引用次数: 0

Comparative chemiluminescence investigation of OH* radicals in laminar and turbulent multi-fuel air- and oxy-fuel flames on semi-industrial and laboratory scale including NOX-formation 层流和湍流多燃料空气和全氧燃料火焰中OH*自由基在半工业和实验室规模下的化学发光对比研究，包括nox的形成

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-26 DOI: 10.1016/j.fuproc.2025.108342

Stefan Schwarz , Georg Daurer , Joshua Slawatycki , Matthias Urban , René Prieler , Christian Gaber , Martin Demuth , Christoph Hochenauer

Chemiluminescence emitted by the de-excitation of excited hydroxyl radicals (OH*), allows for several insights into combustion processes. The presented study investigates air- and oxy-fuel combustion of natural gas with hydrogen enrichment up to 100%, using both small-scale laminar flames and turbulent high-impulse flames (50–100 kW). The obtained results from the laminar 1 kW flames from the laboratory burner are then used, to interpret the influence of turbulence and chemistry influence from an industrial scale multi-fuel multi-oxidizer burner. The measurements performed for the laboratory burner were also compared to simulations. Experimental data were compared to 1D simulations, showing good agreement in trends. However, in turbulent flames, turbulence effects far exceeded those of combustion chemistry. While laminar flames exhibited the highest chemiluminescence intensity in CH₄-air combustion in both experiments and simulations, the maximum in turbulent combustion experiments occurred in oxy-fuel combustion, with hydrogen and natural gas performing similarly. Oxy-fuel flames showed similar chemiluminescence intensities, increased by 2 orders of magnitude, compared to turbulent air-fuel combustion. Additionally, the changes in flame shape and reaction zone size for hydrogen-enrichment in air-fuel combustion were investigated in terms of NO_X formation, where OH* imaging proved its potential for emission reduction.

化学发光发射激发羟基自由基（OH*）的去激发，允许几个洞察燃烧过程。本研究利用小型层流火焰和湍流高冲量火焰（50-100千瓦），研究了富氢率高达100%的天然气在空气和氧气燃料下的燃烧。然后使用实验室燃烧器层流1 kW火焰获得的结果来解释工业规模多燃料多氧化剂燃烧器的湍流影响和化学影响。对实验室燃烧器进行的测量也与模拟进行了比较。将实验数据与一维模拟数据进行了比较，结果表明趋势一致。然而，在湍流火焰中，湍流效应远远超过了燃烧化学效应。在实验和模拟中，层流火焰在ch4 -空气燃烧中表现出最高的化学发光强度，而在湍流燃烧实验中，最大的化学发光强度出现在氧燃料燃烧中，氢气和天然气的化学发光强度相似。与湍流空气燃料燃烧相比，全氧燃料火焰表现出相似的化学发光强度，提高了2个数量级。此外，从NOX形成的角度研究了空气燃料燃烧中富氢火焰形状和反应区大小的变化，其中OH*成像证明了其减少排放的潜力。

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引用次数: 0

Analysis of configurations for coupling an active magnetic regenerator with heat exchangers for hydrogen liquefaction 氢液化用主动磁蓄热器与热交换器耦合结构分析

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-25 DOI: 10.1016/j.fuproc.2025.108337

Angelica Liponi , Mathieu Tenda , Rasmus Bjørk , Umberto Desideri

This paper presents a study of four different configurations for performing the heat exchange between helium—supplied by an active magnetic regenerator (AMR)—and hydrogen in the 82–20 K range for hydrogen liquefaction. We evaluate helium mass flow requirements and analyse the configurations considering both technical and exergetic aspects. Results show a strong influence of the temperature difference of helium at the AMR cold end on the required helium mass flow rate, which ranges from 35 to over 75 times the liquid hydrogen mass flow rate. The exergy efficiency of the cooling stage, not including AMR losses, ranges between 33 % and 49 %. The use of a single AMR causes significant temperature differences between helium and hydrogen in the heat exchangers leading to large exergy losses (representing over 95 % of the overall losses). We finally show that this issue can be overcome using multiple AMR in parallel with increasing cold-end temperatures.

本文研究了在82 ~ 20k范围内，由主动磁再生器（AMR）提供的氦与氢之间进行热交换的四种不同配置。我们评估了氦气的质量流量要求，并从技术和燃烧两个方面分析了配置。结果表明，AMR冷端氦气温差对所需氦气质量流量的影响较大，其范围为液氢质量流量的35 ~ 75倍以上。冷却阶段的火用效率（不包括AMR损失）在33%到49%之间。使用单个AMR会导致热交换器中氦和氢之间的显著温差，从而导致巨大的火用损失（占总损失的95%以上）。我们最后表明，这个问题可以通过增加冷端温度同时使用多个AMR来克服。

引用次数: 0

Techno-economic assessment of biomass-to-liquid fuel production via chemical looping in comparison to conventional pathways 与传统途径相比，通过化学循环对生物质制液体燃料生产的技术经济评估

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-20 DOI: 10.1016/j.fuproc.2025.108341

Krutarth Pandit, Ishani Karki Kudva, Shekhar G. Shinde, Christian Boose, Liang-Shih Fan

Rising liquid fuel demand is increasing CO₂ emissions, making renewable biomass technologies vital for a low-carbon future. This study presents a chemical looping-based biomass conversion process integrated with Fischer-Tropsch synthesis (CLFT) for liquid fuel production and evaluates its techno-economic performance against two established biomass-based pathways: biomass gasification to liquid fuels (GFT) and biomass pyrolysis to liquid fuels (PHP). A minimum fuel selling price (MFSP) analysis, conducted using a discounted cash flow approach, estimates MFSP values of $3.59/GGE for CLFT, $5.26/GGE for GFT, and $4.54/GGE for PHP. The energy efficiencies of CLFT, GFT, and PHP are at 37.7 %, 37.3 %, and 46.4 %, respectively, while their carbon conversion efficiencies are 32.3 %, 30.5 %, and 40.4 %. Sensitivity analyses reveal that feedstock cost exerts the greatest influence on MFSP, followed by the internal rate of return and capital expenditures. Additionally, a 50 % increase in plant capacity (from the baseline 2000 dry tons/day of biomass) results in only an 11 % reduction in MFSP, whereas a 50 % decrease in plant size leads to a 17 % increase in MFSP. These findings highlight CLFT's economic and technical advantages, reinforcing its promise as a cost-effective, sustainable fuel generation alternative.

不断增长的液体燃料需求增加了二氧化碳排放量，使可再生生物质技术对低碳未来至关重要。本研究提出了一种基于化学环的生物质转化过程，结合费托合成（CLFT）用于液体燃料的生产，并针对两种已建立的生物质转化途径：生物质气化制液体燃料（GFT）和生物质热解制液体燃料（PHP），评估了其技术经济性能。使用贴现现金流方法进行的最低燃料销售价格（MFSP）分析估计，CLFT的MFSP值为3.59美元/GGE， GFT为5.26美元/GGE， PHP为4.54美元/GGE。CLFT、GFT和PHP的能源效率分别为37.7%、37.3%和46.4%，而它们的碳转换效率分别为32.3%、30.5%和40.4%。敏感性分析表明，原料成本对MFSP的影响最大，其次是内部收益率和资本支出。此外，植物容量增加50%（以2000干吨/天生物量为基准）只会导致MFSP减少11%，而植物规模减少50%则会导致MFSP增加17%。这些发现突出了CLFT的经济和技术优势，加强了其作为具有成本效益的可持续燃料发电替代品的承诺。

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引用次数: 0

Experimental investigation and machine learning-based estimation of oxyhydrogen (HHO) gas production using KOH electrolyte in a flat plate electrolyser 平板电解槽中KOH电解液产氢氧（HHO）气的实验研究及基于机器学习的估计

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-20 DOI: 10.1016/j.fuproc.2025.108339

Mohammad Amin Adoul , Balaji Subramanian , Naveen Venkatesh Sridharan , Ramin Karim , Ravdeep Kour

Hydrogen gas has gained significant attention as a cleaner alternative to fossil fuels offering a sustainable energy solution. This study explores the production efficiency of oxyhydrogen (HHO) gas using a flat plate electrolyser with potassium hydroxide (KOH) as the electrolyte. Machine learning regression models were employed to estimate hydrogen generation rates and system efficiency based on key operational parameters that includes voltage, current and electrolyte concentration. A set of gradient-boosting algorithms was evaluated utilizing raw experimental data to predict (i) hydrogen output in liters per minute (LPM) and (ii) system efficiency. The results indicate that Categorical Boosting (CatBoost) excelled in forecasting system efficiency (R² = 0.9748, RMSE = 1.6567 on testing data) and predicting HHO gas generation rate (R² = 0.9936, RMSE = 0.0090). The experimental results show that with the increase in KOH concentration there is increase in production of Hydrogen. Maximum efficiency was noted with 0.5 N of KOH with the peak efficiency of 99.8 % because of its optimal conductivity and power consumption. It can also be absorbed that higher concentration such 0.75 N and 1 N have shown significant improvement in hydrogen production. Experimental findings further revealed that moderate operating conditions maximize hydrogen production with efficiency varying as a function of applied current and electrolyte concentration. This study highlights the advantages of integrating machine learning models with electrolysis-based hydrogen production offering a scalable and data-driven approach to optimizing energy efficiency. The results underscore the potential of KOH-based electrolysis for sustainable hydrogen generation and reinforce the role of predictive modeling in enhancing system performance.

氢气作为一种更清洁的化石燃料替代品，提供了一种可持续的能源解决方案，已经引起了人们的极大关注。本研究探讨了以氢氧化钾（KOH）为电解液的平板电解槽生产氢氧（HHO）气体的效率。基于电压、电流和电解质浓度等关键操作参数，采用机器学习回归模型估算氢气生成率和系统效率。利用原始实验数据评估了一组梯度增强算法，以预测(i)每分钟公升（LPM）的氢气输出和（ii）系统效率。结果表明，CatBoost在预测系统效率（R2 = 0.9748, RMSE = 1.6567）和预测HHO产气率（R2 = 0.9936, RMSE = 0.0090）方面表现优异。实验结果表明，随着KOH浓度的增加，制氢量增加。当KOH浓度为0.5 N时，电导率和功耗均达到最佳，效率最高达99.8%。还可以看出，0.75 N和1 N等较高浓度对产氢效果有显著改善。实验结果进一步表明，适度的操作条件下，氢气产量最大，效率随施加电流和电解质浓度的变化而变化。这项研究强调了将机器学习模型与电解制氢相结合的优势，为优化能源效率提供了一种可扩展和数据驱动的方法。研究结果强调了koh电解在可持续制氢方面的潜力，并加强了预测建模在提高系统性能方面的作用。

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引用次数: 0

Co-Zn bimetallic oxide & hydroxyfluoride nanowires: highly active catalyst for catalytic transfer hydrogenation of furfural 钴锌双金属氧化物&羟基氟化物纳米线：用于糠醛催化转移加氢的高活性催化剂

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-19 DOI: 10.1016/j.fuproc.2025.108330

Chenyu Wang , Xiao Tan , Wei Feng , Peijun Ji

Co-Zn bimetallic hydroxyfluoride nanorods (CoZnF) were synthesized at room temperature in an aqueous solution. After calcination at 330 °C in air, CoZnF was partially decomposed to form CoZn bimetallic oxide & hydroxyfluoride (CoZnO&CoZnF) nanowires. The higher electronegativity of fluorine compared to oxygen reduces the valence electron density of oxygen in CoZnF, thereby weakening the metal‑oxygen bonds, and generating abundant oxygen vacancy sites in CoZnO&CoZnF. Electron transfer between cobalt and zinc maintains cobalt in the Co(II) oxidation state. Catalytic results demonstrate the potential of CoZnO&CoZnF for selective hydrogenation of furfural to furfuryl alcohol (FA). Lewis acid-base pairs (Co²⁺/Zn²⁺-O²⁻) and oxygen vacancy sites act as active sites for catalytic transfer hydrogenation (CTH). The nanowire structure and highly accessible active sites enhance catalytic activity. CoZnO&CoZnF exhibits an excellent catalytic activity, achieving 98.1 % yield of furfuryl alcohol (FA) with a selectivity of 99.2 %. Mechanistic insights from ¹HNMR analysis and kinetic studies elucidate the reaction pathway, including activation energy determination.

在室温条件下，在水溶液中合成了Co-Zn双金属羟基氟化物纳米棒。在330℃空气中煅烧后，CoZnF部分分解生成CoZn双金属氧化物羟基氟化物（CoZnO&CoZnF）纳米线。与氧相比，氟的电负性较高，降低了CoZnF中氧的价电子密度，从而削弱了金属-氧键，并在CoZnO&；CoZnF中产生了丰富的氧空位。钴和锌之间的电子转移使钴保持在Co（II）氧化态。催化结果表明，CoZnO&；CoZnF具有选择性加氢糠醛制糠醇（FA）的潜力。Lewis酸碱对（Co2+/Zn2+-O2−）和氧空位是催化转移氢化反应（CTH）的活性位点。纳米线结构和高度可接近的活性位点增强了催化活性。CoZnO&；CoZnF表现出优异的催化活性，糠醇（FA）的收率为98.1%，选择性为99.2%。从1HNMR分析和动力学研究中获得的机理见解阐明了反应途径，包括活化能的测定。

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引用次数: 0

Machine learning-driven modeling framework for steam co-gasification applications 蒸汽共气化应用的机器学习驱动建模框架

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-19 DOI: 10.1016/j.fuproc.2025.108340

Usman Khan Jadoon, Ismael Díaz, Manuel Rodríguez

Steam co-gasification of biomass and plastic waste is a promising route for syngas production and waste valorization. However, accurately predicting syngas composition remains challenging due to inherent complexity and nonlinearity of the process. This study presents a comprehensive comparative analysis between conventional process simulators-based models (Aspen Plus), namely the thermodynamic equilibrium (TEM), restricted thermodynamic (RTM), and kinetic (KM) modeling approaches, and machine learning (ML) models for the prediction of the syngas composition. Using 208 experimental data points compiled from 20 published studies covering various feedstocks and gasification conditions in bubbling fluidized bed gasifiers (BFBG), the performance of the models was evaluated after extensive data preprocessing. Among several ML algorithms evaluated, the neural network (NN) delivered the lowest average root mean square error in syngas mol fraction predictions (0.0174), outperforming RTM (0.0966), KM (0.1378), and TEM (0.1470). To explore input–output relationships beyond interpolation, a conditional generative adversarial network (cGAN) generated synthetic data, which served as the basis for sensitivity and interpretability analyses. The NN, acting as a surrogate model, was paired with SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDP) to quantify the effects and nonlinear interactions of key features on syngas yields providing actionable insights for process optimization.

生物质和塑料垃圾的蒸汽共气化是合成气生产和废物增值的一条很有前途的途径。然而，由于过程固有的复杂性和非线性，准确预测合成气成分仍然具有挑战性。本研究对传统的基于过程模拟器的模型（Aspen Plus），即热力学平衡（TEM）、限制热力学（RTM）和动力学（KM）建模方法，以及用于预测合成气成分的机器学习（ML）模型进行了全面的比较分析。利用从20篇已发表的研究中收集的208个实验数据点，涵盖了鼓泡流化床气化炉（BFBG）的各种原料和气化条件，经过广泛的数据预处理后，对模型的性能进行了评估。在评估的几种ML算法中，神经网络（NN）在合成气摩尔分数预测中的平均均方根误差最低（0.0174），优于RTM（0.0966）、KM（0.1378）和TEM（0.1470）。为了探索插值之外的输入-输出关系，条件生成对抗网络（cGAN）生成了合成数据，作为敏感性和可解释性分析的基础。该神经网络作为代理模型，与SHapley加性解释（SHAP）和部分依赖图（PDP）配对，以量化合成气产量的关键特征的影响和非线性相互作用，为过程优化提供可操作的见解。

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引用次数: 0

Ex-ante life-cycle assessment of biomass-derived hydrogen via fast pyrolysis and sorption enhanced steam reforming: Addressing scale-up uncertainties 通过快速热解和吸附强化蒸汽重整的生物质衍生氢的事前生命周期评估：解决规模扩大的不确定性

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-17 DOI: 10.1016/j.fuproc.2025.108334

Pablo Comendador , Nicolás Martínez-Ramón , Martin Olazar , Gartzen Lopez , Diego Iribarren

Biomass conversion through pyrolysis and sorption enhanced steam reforming (PY-SESR) is a novel alternative for producing hydrogen at bench scale. This study focused on addressing uncertainties linked to its industrial-scale implementation, comparing it to the process without CO₂ capture (PY-SR), and using steam methane reforming (SMR) as benchmark, which is currently the main hydrogen production route. Both PY-SESR and PY-SR scaled-up processes were simulated in Aspen Plus®, based on experimental bench-scale data. Life-cycle assessment based on process simulation-derived inventories showed that the PY-SESR alternative was the only one resulting in renewable hydrogen production according to the European Renewable Energy Directive (RED III) (3 kg_CO₂-eq kg⁻¹_H₂ threshold), attaining net negative emissions (−1.12 kg_CO₂-eq kg⁻¹_H₂). Nevertheless, its higher energy consumption, mainly driven by sorbent calcination and CO₂ pressurization for storage, led to higher environmental burdens with respect to other indicators. Considering fossil resource use, ozone depletion and freshwater eutrophication, PY-SR was found to outperform both PY-SESR and SMR, while SMR performed better in acidification and use of minerals and metals. Monte Carlo simulations and a sensitivity analysis showed that heat demand and electricity consumption highly contributed to PY-SR and PY-SESR variability, as a consequence of the limitations associated to early-stage process scale-up.

通过热解和吸附强化蒸汽重整（PY-SESR）进行生物质转化是一种新的实验规模制氢方法。本研究的重点是解决与工业规模实施相关的不确定性，将其与无二氧化碳捕集（PY-SR）的过程进行比较，并以蒸汽甲烷重整（SMR）为基准，这是目前主要的制氢途径。基于实验规模数据，在Aspen Plus®中模拟了PY-SESR和PY-SR放大过程。基于过程模拟衍生清单的生命周期评估表明，根据欧洲可再生能源指令（RED III）（3 kgCO₂-eq kg - 1H 2阈值），PY-SESR替代方案是唯一产生可再生氢气的替代方案，实现净负排放（- 1.12 kgCO₂-eq kg - 1H 2）。然而，其较高的能耗，主要是由吸附剂煅烧和CO2加压储存驱动，导致其他指标的环境负担较高。考虑化石资源利用、臭氧消耗和淡水富营养化，PY-SR的效果优于PY-SESR和SMR，而SMR在酸化和矿物和金属的利用方面表现更好。蒙特卡罗模拟和敏感性分析表明，由于早期工艺放大的限制，热需求和电力消耗对PY-SR和PY-SESR的变异性有很大贡献。

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引用次数: 0