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Design Expert® assisted process optimization of biodiesel production via biotransesterification from inedible oils using Candida rugosa lipases Design Expert®通过使用念珠菌脂肪酶对不食用油脂进行生物酯交换,帮助优化生物柴油的生产过程
Pub Date : 2025-12-22 DOI: 10.1016/j.jfueco.2025.100154
Anil Kumar, Aradhana Srivastava, Vishwender Pratap Singh
Rubber seed and Kusum oils are inedible feedstocks unveiling potential of bioenergy valorisation. Biodiesel via transesterification using lipases is industrially lucrative if process is optimized for economical utilization of feedstock and other resources. The inedible oils as feedstock in the present study, fulfils the global mission towards a resource rich and environment friendly circular economy. This research paper focuses on green energy production. The selected feedstocks, rubber seed oil and kusum oil were biotransesterified with methanol as acyl acceptor using lipases from Candida rugosa as catalyst. The interactive process parameters affecting the biodiesel yield are temperature, factor to methanol to oil ratio, percentage of lipase and buffer, pH, and the agitation speed. Since the process parameters are interactive, hence were statistically optimized using Design Expert®. The high specificity of lipases from C. rugosa has not been reported in literature for biotransesterification of rubber seed oil and kusum oil. The optimized process parameters for rubber seed oil and kusum oil produced biodiesel yields as 95.92 % and 94.70 %, respectively, using free lipases. The properties of produced biodiesel such as density, kinematic viscosity and gross calorific value also supported the set norms as per US standards, ASTM-D6751. The two step addition of acyl acceptor during biotransesterification of rubber seed oil and kusum oil, improved the biodiesel yield by 1.50 % and 3.14 %, respectively. It proved the adverse effect of methanol concentration on lipases activity can be mitigated. The present research on biodiesel aligns to United Nations-SDG7 ‘Green Energy Technology’ from unused/underutilised feedstocks.
橡胶籽和豆油是不可食用的原料,揭示了生物能源增值的潜力。如果对原料和其他资源的经济利用进行优化,利用脂肪酶酯交换制备生物柴油在工业上是有利可图的。本研究以食用油为原料,实现了资源丰富、环境友好型循环经济的全球使命。这篇研究论文的重点是绿色能源生产。以橡胶籽油和豆油为原料,以甲醇为酰基受体,念珠菌脂肪酶为催化剂进行酯交换反应。影响生物柴油产率的交互工艺参数有温度、因子与甲醇油比、脂肪酶与缓冲液的比例、pH和搅拌速度。由于工艺参数是交互的,因此使用Design Expert®进行统计优化。在橡胶籽油和菜籽油的生物酯交换反应中,尚无文献报道红草脂肪酶的高特异性。优化后的橡胶籽油和菜籽油以游离脂肪酶为原料,产率分别为95.92%和94.70%。生产的生物柴油的特性,如密度、运动粘度和总热值也符合美国标准ASTM-D6751的规定。在橡胶籽油和菜籽油的生物酯交换过程中,两步加入酰基受体可使生物柴油的收率分别提高1.50%和3.14%。证明甲醇浓度对脂肪酶活性的不利影响是可以减轻的。目前对生物柴油的研究符合联合国可持续发展目标g7“绿色能源技术”,即利用未使用/未充分利用的原料。
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引用次数: 0
Optimizing fuel cell selection: An AHP-driven multi-criteria framework 优化燃料电池选择:ahp驱动的多标准框架
Pub Date : 2025-12-01 DOI: 10.1016/j.jfueco.2025.100153
Seyed Taher Kermani Alghorayshi , Ali Rezapouranghahfarokhi , Erfan Abolhasani , Masoud Dorfeshan , Milad Imandoust , Samaneh Ayoubi , Rahim Zahedi
To systematically rank fuel cells (FCs) based on their performance, this study utilizes the Analytic Hierarchy Process (AHP), a commonly used approach for multi-criteria decision-making. To assess the pros and cons of eight different FC types, we analyzed 21 parameters that affect FC functionality. With global weights of 0.155, 0.133, and 0.114, metal efficiency, durability/cycle life, and cost were the most important factors. According to the assessment, Proton Exchange Membrane Fuel Cells (PEMFCs) were the most promising, with a global weight of 0.186. The study further examined five different PEMFC options, employing a multi-index evaluation model that considered fifteen important factors. The most important factors here were Proton Conductivity, Activity, Water Management, and Fuel/Oxidant Purity, which were weighted at 0.186, 0.156, 0.129, and 0.106, respectively. According to the combined assessment, low-temperature PEMFCs (LT-PEMFCs) showed the best performance, with a total score of 0.298. These results emphasize that fuel cell performance could be improved by increasing utilization, and research into LT-PEMFCs appears to be a good way to achieve optimization.
为了根据燃料电池(fc)的性能对其进行系统排名,本研究采用了层次分析法(AHP),这是一种常用的多标准决策方法。为了评估8种不同FC类型的优缺点,我们分析了影响FC功能的21个参数。当总重量分别为0.155、0.133和0.114时,金属效率、耐久性/循环寿命和成本是最重要的因素。根据评估,质子交换膜燃料电池(pemfc)是最有前途的,其全球重量为0.186。该研究进一步研究了五种不同的PEMFC方案,采用了考虑了15个重要因素的多指标评估模型。这里最重要的因素是质子电导率、活度、水管理和燃料/氧化剂纯度,权重分别为0.186、0.156、0.129和0.106。综合评价,低温PEMFCs (LT-PEMFCs)表现最好,总分为0.298。这些结果强调燃料电池的性能可以通过提高利用率来提高,而对lt - pemfc的研究似乎是实现优化的好方法。
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引用次数: 0
Information needs and the effect of information on the social acceptance of innovative solar fuels 信息需求和信息对社会接受创新太阳能燃料的影响
Pub Date : 2025-12-01 DOI: 10.1016/j.jfueco.2025.100151
Eva-Maria Schomakers, Wiktoria Wilkowska, Martina Ziefle
This study examines public information needs and the role of information and perceived knowledge in shaping the acceptance of solar fuels produced through artificial photosynthesis. Using a mixed-method approach that includes qualitative interviews and a quasi-experimental online survey, we identify specific information needs and assess the influence of information on solar fuel acceptance using structural equation modeling. Our findings reveal that richer informational content significantly enhances perceived knowledge. In turn, this fosters more positive affective and cognitive evaluations. Although information shows no direct effect on societal perceptions and acceptance, its significant indirect effect through perceived knowledge on perceptions and acceptance underscores its importance. Our findings contribute to an understanding of which information is prioritized regarding solar fuels by the public and how feelings of knowledgeability enhance positive perceptions. These insights provide clear recommendations for tailored communication strategies for solar fuels and related sustainable innovations.
本研究考察了公众信息需求以及信息和感知知识在塑造接受通过人工光合作用生产的太阳能燃料方面的作用。采用混合方法,包括定性访谈和准实验在线调查,我们确定具体的信息需求,并使用结构方程模型评估信息对太阳能燃料接受度的影响。我们的研究结果表明,更丰富的信息内容显著提高感知知识。反过来,这会培养更积极的情感和认知评价。虽然信息对社会认知和接受度没有直接影响,但它通过感知知识对认知和接受度的显著间接影响强调了它的重要性。我们的研究结果有助于理解公众对太阳能燃料的哪些信息优先考虑,以及知识的感受如何增强积极的看法。这些见解为定制太阳能燃料和相关可持续创新的传播策略提供了明确的建议。
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引用次数: 0
Benchmarking machine learning models against full-scale acoustic absorption measurements in gas turbine liners 将机器学习模型与燃气轮机衬垫的全尺寸声吸收测量相比较
Pub Date : 2025-11-20 DOI: 10.1016/j.jfueco.2025.100152
Abdullah Shahjalal, Roy Kalawsky, Demetrios Joannou, Faruk Ozdemir
Accurate prediction of acoustic energy absorption in gas turbine combustors is critical for enhancing performance, mitigating thermoacoustic instabilities, and reducing emissions. Traditional experimental and mathematical modeling approaches often struggle to capture the nonlinear and frequency-dependent behaviour of combustor liners, especially under varying operational conditions. This study presents a comprehensive evaluation of four machine learning (ML) models—Random Forest (RF), Extreme Gradient Boosting (XGB), Convolutional Neural Networks (CNN), and K-Nearest Neighbors (KNN)—against full-scale experimental measurements across six double-liner and three single-liner gas turbine configurations. A total of 615 operational records were used to train and validate model performance. In the double liner configuration, the RF and CNN models achieved the lowest average RMSE of 0.044, closely followed by XGB (0.045). However, XGB demonstrated the highest predictive accuracy (R² = 0.896), outperforming RF (0.891) and CNN (0.895), whose performance was partly constrained by limited dataset size. In the single liner configuration, XGB again delivered superior results (RMSE = 0.077, R² = 0.782) compared with RF (0.081, 0.580) and KNN (0.092, 0.470). The KNN model exhibited poor generalisation in the high-dimensional feature space, with R² dropping to 0.32 in certain tests. Overall, the machine learning framework reduced prediction error by approximately 31–56.2 % compared with conventional semi-empirical models (COS and COT), while requiring significantly lower computational effort to achieve comparable or superior accuracy. This is the first study to benchmark ML models against full-scale acoustic absorption data, introducing a validated data-driven framework with implications for combustor liner design, predictive maintenance, and real-time diagnostics. The integration of ML models into simulation workflows promises substantial reductions in experimental cost and improved design responsiveness. These findings offer a scalable, computationally efficient solution for aeroacoustic optimization—supporting the broader goal of cleaner, quieter, and more efficient gas turbine systems.
准确预测燃气轮机燃烧室的声能量吸收对提高性能、减轻热声不稳定性和减少排放至关重要。传统的实验和数学建模方法往往难以捕捉燃烧室衬套的非线性和频率依赖行为,特别是在不同的操作条件下。本研究对四种机器学习(ML)模型——随机森林(RF)、极端梯度增强(XGB)、卷积神经网络(CNN)和k近邻(KNN)——进行了全面的评估,并对六个双衬板和三个单衬板燃气轮机配置进行了全面的实验测量。总共使用了615个操作记录来训练和验证模型的性能。在双线性配置中,RF和CNN模型的平均RMSE最低,为0.044,XGB紧随其后(0.045)。然而,XGB表现出最高的预测精度(R²= 0.896),优于RF(0.891)和CNN(0.895),后者的性能在一定程度上受到数据集大小的限制。在单线性配置中,与RF(0.081, 0.580)和KNN(0.092, 0.470)相比,XGB再次提供了更好的结果(RMSE = 0.077, R²= 0.782)。KNN模型在高维特征空间中的泛化性较差,在某些测试中R²降至0.32。总体而言,与传统的半经验模型(COS和COT)相比,机器学习框架将预测误差降低了约31 - 56.2%,同时需要显着降低的计算工作量来达到相当或更高的精度。这是第一次将ML模型与全尺寸声吸收数据进行基准测试,引入了一个经过验证的数据驱动框架,该框架对燃烧室衬垫设计、预测性维护和实时诊断具有重要意义。将机器学习模型集成到仿真工作流程中可以大幅降低实验成本并提高设计响应能力。这些发现为气动声学优化提供了一个可扩展的、计算效率高的解决方案——支持更清洁、更安静、更高效的燃气轮机系统这一更广泛的目标。
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引用次数: 0
Techno-enviro-socio-economic assessment and sensitivity analysis of an off-grid Tidal/Fuel Cell/Electrolyzer/Photovoltaic hybrid system for hydrogen and electricity production in Cameroon coastal areas 喀麦隆沿海地区用于氢气和电力生产的离网潮汐/燃料电池/电解槽/光伏混合系统的技术-环境-社会经济评估和敏感性分析
Pub Date : 2025-10-26 DOI: 10.1016/j.jfueco.2025.100150
Pascalin Tiam Kapen
<div><div>Coastal regions in Cameroon, including Douala, Kribi, Campo, Dibamba, and Limbe, faced persistent electricity challenges driven by grid instability, growing demand, and dependence on fossil fuels. Solar resource availability was high but intermittent, whereas tidal energy was predictable and energy-dense yet underused. This pilot delivers the first Cameroonian assessment of an off-grid tidal/PV/electrolyzer/hydrogen-storage/fuel-cell architecture, explicitly co-optimizing electricity service and green hydrogen production, and evaluating performance with a tri-metric economic lens (net present cost, levelized cost of electricity, and the levelized cost of hydrogen). The system was optimized to minimize net present cost (NPC), levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH) and three tidal-flow scenarios were analyzed to represent hydrokinetic variability. The design served households, small businesses, fishing activities, schools, and health facilities with a baseline demand of 389.50 kWh/day; surplus renewable power drove the electrolyzer to produce hydrogen for later reconversion in the fuel cell. Under the first scenario (1.25 m/s average speed), the optimal mix comprised 137 PV modules (600 W each), a 100 kW fuel cell, six 40 kW tidal turbines, six 10 kW electrolyzers, a 19.5 kW converter, and 41 hydrogen tanks (40 L each), yielding an NPC of US$ 2.16 million, an LCOE of US$ 0.782/kWh, and a LCOH of US$ 19.2/kg of hydrogen. The second scenario (1.47 m/s) required only 12 PV modules, one electrolyzer, and an 11.3 kW converter, lowering costs to an NPC of US$ 1.52 million, an LCOE of US$ 0.553/kWh, and a LCOH of US$ 15.4/kg of hydrogen. In the third scenario (1.61 m/s), the configuration shifted to 298 PV modules, three tidal turbines, eight electrolyzers, and a 39.6 kW converter, resulting in the highest NPC (US$ 2.47 million) and LCOE (US$ 0.901/kWh), with a LCOH of US$ 18.8/kg of hydrogen. The study also contributes a transparent, component-wise employment indicator linking installed capacities/energies to jobs; deployment is expected to create about seven local jobs during installation and early operation, tidal turbines (3), solar panels (1), electrolyzers (1), hydrogen tanks (1), and fuel cell (1), with additional minor operation and maintenance positions thereafter. Social analysis indicated improved energy access, support for local livelihoods, and job creation; environmental results confirmed clean operation with limited marine disturbance. A sensitivity study varying capital and replacement-cost multipliers showed robust performance across economic conditions. Taken together, these contributions provide a decision-ready blueprint for coastal communities: a first-of-its-kind Cameroonian hybrid that quantifies both electricity and hydrogen costs (including feasible LCOH) and demonstrates socio-economic co-benefits, offering a cost-effective pathway to strengthen energy security, foster local development,
喀麦隆的沿海地区,包括杜阿拉、克里比、坎波、迪班巴和林贝,由于电网不稳定、需求不断增长和对化石燃料的依赖,面临着持续的电力挑战。太阳能资源的可用性很高,但断断续续,而潮汐能是可预测的,能量密集,但未得到充分利用。该试点项目首次在喀麦隆对离网潮汐/光伏/电解槽/储氢/燃料电池体系结构进行了评估,明确地对电力服务和绿色制氢进行了协同优化,并采用三指标经济视角(净现值成本、电力成本和氢气成本)对性能进行了评估。对系统进行优化,以最小化净当前成本(NPC)、平准化电力成本(LCOE)、平准化氢成本(LCOH),并分析了三种潮汐流情景,以表示水动力学变异性。该设计服务于家庭、小型企业、渔业活动、学校和卫生设施,基线需求为389.50千瓦时/天;剩余的可再生能源驱动电解槽产生氢气,稍后在燃料电池中进行再转化。在第一种情况下(平均速度为1.25米/秒),最佳组合包括137个光伏组件(每个600瓦),一个100千瓦的燃料电池,6个40千瓦的潮汐涡轮机,6个10千瓦的电解槽,一个19.5千瓦的转换器和41个氢罐(每个40升),产生的NPC为216万美元,LCOE为0.782美元/千瓦时,LCOH为19.2美元/千克氢。第二种方案(1.47米/秒)只需要12个光伏组件,一个电解槽和一个11.3千瓦的转换器,将成本降低到NPC 152万美元,LCOE为0.553美元/千瓦时,LCOH为15.4美元/千克氢。在第三种方案(1.61米/秒)中,配置转变为298个光伏组件,3个潮汐涡轮机,8个电解槽和一个39.6千瓦的转换器,产生最高的NPC(249万美元)和LCOE(0.901美元/千瓦时),LCOH为18.8美元/千克氢。该研究还提供了一个透明的、明智的就业指标,将装机容量/能源与就业联系起来;在安装和早期操作期间,预计将在当地创造约7个工作岗位,包括潮汐涡轮机(3个)、太阳能电池板(1个)、电解槽(1个)、氢罐(1个)和燃料电池(1个),以及随后的小型操作和维护岗位。社会分析表明,能源获取得到改善,支持了当地生计,创造了就业机会;环境测试结果证实了清洁作业,海洋干扰有限。一项敏感性研究表明,在不同的经济条件下,不同的资本和替代成本乘数表现出强劲的表现。综上所述,这些贡献为沿海社区提供了一个现成的决策蓝图:这是喀麦隆首个将电力和氢成本(包括可行的LCOH)量化并展示社会经济协同效益的混合能源,为加强能源安全、促进当地发展和减少环境影响提供了一条具有成本效益的途径。
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引用次数: 0
Multi-parameter simulation and comparative analysis of low-temperature proton exchange membrane fuel cell performance and electrode water management across different climatic zones in Africa 非洲不同气候区低温质子交换膜燃料电池性能和电极水管理的多参数模拟与对比分析
Pub Date : 2025-09-09 DOI: 10.1016/j.jfueco.2025.100148
Pascalin Tiam Kapen
In the pursuit of clean and efficient energy solutions tailored to Africa’s diverse environmental conditions, this study presents a multi-parameter simulation and comparative performance analysis of low-temperature proton exchange membrane fuel cells (PEMFC) across the main climatic zones of the African continent. The work addresses the critical challenge of how temperature and humidity variations, specific to different geographic regions, influence proton exchange membrane fuel cells behavior, efficiency, and water management. Using a robust mathematical model inspired by the COMSOL Multiphysics® fuel cell module, the study incorporates charge conservation, mass transport, species diffusion, electrochemical reaction kinetics, and water activity dynamics in the gas diffusion layers and polymer membrane. Key operating parameters, such as inlet relative humidity on both anode and cathode sides, as well as cell temperature, are varied to reflect the real-world climate data derived from NASA's global meteorological database. Ten representative African climate zones, including tropical rainforest, arid desert, temperate, and polar tundra, are mapped and parametrized based on long-term averages of temperature and humidity conditions. The simulations revealed notable performance disparities across climatic zones, with membrane hydration, water management efficiency, and voltage stability strongly influenced by ambient temperature and humidity. Hot and humid regions supported more favorable operating conditions, while arid and cold climates exhibited signs of membrane dehydration, uneven current distribution, and increased electrochemical losses. These results highlight the necessity of climate-specific design and operational strategies for proton exchange membrane fuel cells, especially in decentralized, off-grid applications across diverse African environments. By contextualizing PEMFC behavior within Africa’s climatic diversity, this study offers a robust framework for guiding the integration of hydrogen-based energy systems into the continent’s sustainable development agenda. It contributes to key objectives such as improving access to clean energy, enhancing system resilience, reducing greenhouse gas emissions, and supporting Sustainable Development Goal 7 (Affordable and Clean Energy). Moreover, the approach paves the way for climate-resilient fuel cell deployment, encouraging innovation in renewable energy solutions tailored to local environmental and socio-economic conditions.
为了寻求适合非洲不同环境条件的清洁高效能源解决方案,本研究提出了跨非洲大陆主要气气带的低温质子交换膜燃料电池(PEMFC)的多参数模拟和比较性能分析。这项工作解决了温度和湿度变化(特定于不同地理区域)如何影响质子交换膜燃料电池的行为、效率和水管理的关键挑战。利用受COMSOL Multiphysics®燃料电池模块启发的强大数学模型,该研究结合了气体扩散层和聚合物膜中的电荷守恒、质量传递、物质扩散、电化学反应动力学和水活度动力学。关键的操作参数,如阳极和阴极两侧的入口相对湿度,以及电池温度,都是不同的,以反映来自美国宇航局全球气象数据库的真实气候数据。根据温度和湿度条件的长期平均值,绘制了包括热带雨林、干旱沙漠、温带和极地冻土带在内的十个具有代表性的非洲气候带的地图并进行了参数化。模拟结果显示,不同气候带的膜的水合作用、水管理效率和电压稳定性受到环境温度和湿度的强烈影响。炎热和潮湿的地区支持更有利的操作条件,而干旱和寒冷的气候则表现出膜脱水、电流分布不均匀和电化学损失增加的迹象。这些结果强调了质子交换膜燃料电池的气候特异性设计和操作策略的必要性,特别是在非洲不同环境中的分散、离网应用中。通过将PEMFC行为置于非洲气候多样性的背景下,本研究为指导将氢基能源系统纳入非洲大陆的可持续发展议程提供了一个强有力的框架。它有助于实现关键目标,如改善获得清洁能源的机会、增强系统抵御能力、减少温室气体排放,以及支持可持续发展目标7(负担得起的清洁能源)。此外,该方法为气候适应型燃料电池的部署铺平了道路,鼓励根据当地环境和社会经济条件量身定制可再生能源解决方案的创新。
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引用次数: 0
The impact of H2S on Hg accumulation on non-corroded pipelines and the implications for assessing risks of offshore decommissioning H2S对未腐蚀管道中汞积累的影响以及对海上退役风险评估的影响
Pub Date : 2025-09-09 DOI: 10.1016/j.jfueco.2025.100149
Lhiam Paton , Sandra Kiesel , Jörg Feldmann
In the event of decommissioned oil and gas infrastructure being left in place the operators will have to guarantee that contaminant concentrations are as low as reasonably practicable. To achieve this for a persistent contaminant like mercury (Hg), there are several aspects which must be well understood. Including concentrations of Hg present on infrastructure like pipelines, the species present, how to assess the risk associated with each compound and which analytical methods are available to achieve these knowledge targets. The work displayed in this article aims to shed light on the first two points, specifically, when pipelines have been kept free of corrosion and when exposed to hydrogen sulphide (H2S) over a long term. Here, it was identified that the kinetics of Hg uptake onto carbon steel resulted in high Hg accumulation on the timescale of months and years with total Hg levels being as high as 0.8 g Hg∙m-2 after 36 months of exposure to elemental mercury (Hg0). Across a 5-month period the impact of H2S on Hg species was investigated finding that the presence of H2S reduced the fraction of labile Hg species which were most likely to enter the marine environment. Nevertheless, even after co-exposure of Hg0 and H2S, 15 % of Hg was mobilised with seawater and was, therefore, potentially bioavailable. This study holds critical information for future risk assessments, particularly of dry gas pipelines, by showing that Hg will accumulate on polished steel surfaces and that a significant fraction of the total may be available to local marine environments.
如果退役的石油和天然气基础设施被留在原地,运营商必须保证污染物浓度尽可能低。要对汞(Hg)这样的持久性污染物实现这一目标,必须充分了解几个方面。包括管道等基础设施中汞的浓度,汞的种类,如何评估每种化合物的风险以及有哪些分析方法可以实现这些知识目标。本文展示的工作旨在阐明前两点,特别是当管道处于无腐蚀状态以及长期暴露于硫化氢(H2S)中时。本研究发现,在数月和数年的时间尺度上,碳钢对汞的吸收动力学导致汞的高积累,暴露于单质汞(Hg0) 36个月后,总汞水平高达0.8 g Hg∙m-2。在5个月的时间里,研究人员对H2S对汞物种的影响进行了研究,发现H2S的存在减少了最有可能进入海洋环境的不稳定汞物种的比例。然而,即使在Hg0和H2S共同暴露后,仍有15%的汞被海水调动,因此具有潜在的生物可利用性。这项研究为未来的风险评估提供了关键信息,特别是对干气管道的风险评估,因为它表明汞会积聚在抛光的钢铁表面上,而且总量的很大一部分可能会进入当地的海洋环境。
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引用次数: 0
Erratum regarding missing Declaration of Competing Interest statements in previously published articles 关于先前发表的文章中缺少竞争利益声明的勘误表
Pub Date : 2025-09-01 DOI: 10.1016/j.jfueco.2025.100140
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引用次数: 0
Retraction Notice to “Kinetic Analysis of Monomolecular Cracking of Normal Alkanes (C4-C6) over Brønsted Acid Site of Zeolitic Type Catalyst with Energetic Evaluation of Transition States Using Quantum-Chemical Modeling” [Fuel Communications volume 19 (2024)/JFUECO 100116] “正构烷烃(C4-C6)在沸石型催化剂br约nsted酸位上的单分子裂解动力学分析及使用量子化学模型对过渡态的能量评价”[燃料通讯第19卷(2024)/JFUECO 100116]的撤销通知
Pub Date : 2025-09-01 DOI: 10.1016/j.jfueco.2025.100141
Saba Foroutan Ghazvini, Elena Ivashkina Nikolaevna
This article has been retracted: please see Elsevier policy on Article Correction, Retraction and Removal (https://www.elsevier.com/about/policies-and-standards/article-withdrawal).
This article was retracted at the request of the authors. Even though this article was prepared and submitted prior to the adoption of the new rules, the authors have informed the journal that retraction is required due to the policy adopted in Russian scientific organizations and universities, which prohibits publication of results in any paid journals from April 2024. The authors apologize for the inconvenience.
本文已被撤回:请参见爱思唯尔关于文章更正、撤回和删除的政策(https://www.elsevier.com/about/policies-and-standards/article-withdrawal).This文章应作者要求撤回。尽管这篇文章是在新规则实施之前准备和提交的,但作者已经通知该杂志,由于俄罗斯科学组织和大学采用的政策,从2024年4月起禁止在任何付费期刊上发表研究结果,因此需要撤回。作者为给您带来的不便表示歉意。
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引用次数: 0
Evaluating renewable energy strategies for operational efficiency in seaports 评估海港运营效率的可再生能源战略
Pub Date : 2025-07-22 DOI: 10.1016/j.jfueco.2025.100147
Mahmood Abdoos, Amirali Saifoddin, Hossein Yousefi, Amin Zahedi
This study provides a comprehensive assessment of solar energy integration and fuel efficiency optimization in the Bushehr Commercial Port, addressing a critical research gap in sustainable maritime logistics. While global trade has intensified port energy demand, existing studies lack a comprehensive assessment of operational energy efficiency in commercial ports. This paper introduces an innovative framework that quantifies the technical benefits of solar photovoltaic (PV) systems in port operations. Using pv syst software, including solar radiation analysis and port-specific energy assessments, the study shows that the deployment of 6336 PV panels, each with a power of 585 W, results in a total installed capacity of 3707 kWh. The system exhibits an annual energy generation rate of 7385,951 kWh with a performance ratio (PR) of 83.92 %, indicating high operational efficiency. Furthermore, the analysis of fossil fuel consumption shows significant seasonal fluctuations, with peak diesel consumption exceeding 10,578,132 liters in February due to increased operational demand, while the summer months show lower consumption. The findings highlight the critical role of solar photovoltaics in reducing seaports’ dependence on conventional fuels, thereby reducing greenhouse gas emissions and operating costs. This paper contributes to the strategic transition towards low-carbon port infrastructure and provides a replicable model for implementing sustainable energy in maritime hubs with high solar potential. Future research should focus on long-term energy resilience and optimization strategies for long-term outage scenarios.
本研究对布什尔商业港的太阳能集成和燃油效率优化进行了全面评估,解决了可持续海运物流领域的关键研究空白。虽然全球贸易加剧了港口能源需求,但现有研究缺乏对商业港口运营能源效率的全面评估。本文介绍了一个创新的框架,量化了太阳能光伏(PV)系统在港口运营中的技术效益。利用光伏系统软件,包括太阳辐射分析和港口特定能源评估,该研究表明,部署6336块光伏电池板,每块功率为585瓦,总装机容量为3707千瓦时。系统年发电量为7385 951千瓦时,性能比(PR)为83.92%,运行效率高。此外,对化石燃料消耗的分析显示出明显的季节性波动,由于运营需求增加,2月份柴油消费量峰值超过10,578,132升,而夏季消费量较低。研究结果强调了太阳能光伏发电在减少海港对传统燃料的依赖,从而减少温室气体排放和运营成本方面的关键作用。本文有助于向低碳港口基础设施的战略转型,并为在具有高太阳能潜力的海上枢纽实施可持续能源提供了可复制的模式。未来的研究应侧重于长期停电情景下的长期能源弹性和优化策略。
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引用次数: 0
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Fuel Communications
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