Browsing by Author "Wang, Siqi"

Now showing 1 - 9 of 9
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    Design of a distributed hybrid electric propulsion system for a light aircraft based on genetic algorithm
    (AIAA, 2019-08-16) Economou, John T.; Tsourdos, Antonios; Wang, Siqi
    Hybrid aircraft is a new attempt for next-generation aircraft, they are environmentally friendly and highly efficient. This paper proposes a new type of hybrid electric propulsion system for light aircraft, which integrated distributed propulsion concept and more electric aircraft concept together to improve aircraft performance. Based on the mission requirements and unique system configuration, all components, including engine, generator and motors are intelligently selected. The sizing problem can be divided into two parts. The power source part applied a non-dominated sorting genetic algorithm to choose components and simultaneously minimized total weight and fuel consumption. The rest of the system used a conventional genetic algorithm, which minimized weight and guaranteed that all selected motors can output enough power. In the end, by applying a simple deterministic energy management strategy, the new system achieved a 12% fuel consumption reduction.
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    Development of bimetallic catalysts for (sorption-enhanced) steam methane reforming
    (Cranfield University, 2023-12) Wang, Siqi; Clough, Peter T.; Nabavi, Seyed Ali
    Hydrogen has gained increasing attention in recent years as one of the most promising solutions to decarbonize the energy sector, as it emits zero carbon when combusted. The demand for clean hydrogen continues to rise as government, industry, and academia endeavour to meet the net zero goal by the year 2050. Steam methane reforming is currently the predominant hydrogen production pathway and is predicted to remain so for the years to come. Many techniques exist for the optimization and decarbonization of the steam methane reforming process. Two of the most widely employed methods include using more efficient and stable catalysts and adding in an in-situ carbon capture step using solid CO₂ sorbents. The overall aim of this PhD study is to develop and evaluate the performance of novel bimetallic catalysts for the (sorption-enhanced) steam methane reforming process. Starting from a comprehensive literature review, recent advances in the field of bimetallic SMR catalysts were summarized and reviewed, based on their catalytic activity, stability, and physical-chemical properties. Based on the review, three bimetallic catalysts (Ni₃M ₁ /Al₂ O₃, M = Cu, Fe, and Ge) were synthesized, characterized using different techniques, and tested in a laboratory-scale fixed bed reactor under typical steam methane reforming conditions. CaO particles were then added to the system and the performance of the catalysts under sorption-enhanced steam methane reforming conditions was evaluated. A study on the influence of Cu loading on the bimetallic Ni-Cu catalysts was also carried out. The experimental studies were also accompanied by Density Functional Theory calculations of the carbon and oxygen adsorption energies on the bimetallic surfaces, and microkinetic modelling of the SMR reaction based on previous literature on its reaction mechanism. Finally, machine learning models were developed for the prediction of atomic adsorption energies using readily available elemental properties. Together with the previously developed microkinetic model, a fast high throughput screening of bimetallic alloys was carried out and catalysts with high sulphur resistance were successfully identified. Overall, the addition of Cu was found to be highly beneficial for promoting the catalytic activity of the conventional Ni catalysts, and the addition of Ge promotes the activity and can potentially improve the sulphur resistance of the catalysts. The wide application of these cost-effective and highly active bimetallic catalysts will contribute significantly to the decarbonisation of the energy sector by enabling the efficient production of hydrogen.
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    Experimental and DFT study of (sorption-enhanced) steam methane reforming over bimetallic Ni-Cu catalysts
    (Elsevier, 2025-02-01) Wang, Siqi; Shen, Ziqi; Osatiashtiani, Amin; Nabavi, Seyed Ali; Clough, Peter T.
    The catalytic performance of a monometallic Ni/Al2O3 and three bimetallic Ni-Cu catalysts (with Cu loading of 2.5, 5, and 7.5 mol%, respectively) for the (sorption-enhanced) steam methane reforming reaction was evaluated. Physico-chemical characterization of the materials confirmed the formation of Ni-Cu alloy and the even distribution of active metals within the porous high-surface area support. All three bimetallic catalysts showed enhanced methane conversion compared to the conventional Ni/Al2O3 catalyst at higher temperatures (800 °C), which was attributed to the promotion of the water–gas shift reaction by the addition of Cu. The experimental observations were supported by the Density Functional Theory calculations of carbon and oxygen adsorption on the mono and bimetallic surfaces. Ni3Cu1 and Ni1Cu1 were calculated to have a similar level of catalytic activity as Ni, based on results from a microkinetic model of the steam methane reforming reaction. Ni1Cu3 showed slightly lower activity, potentially due to its low carbon adsorption ability which impedes the rate-determining methane decomposition process. The SMR reaction was further improved by adding calcium oxide as the CO2 sorbent, which increased both methane conversion and hydrogen yield. Ni3Cu1/Al2O3 and Ni1Cu1/Al2O3 were identified as promising SMR catalysts with a high methane conversion of approximately 90 % at 800 °C and 97 % at 700 °C, without and with the sorbent, respectively.
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    High-throughput screening of sulfur-resistant catalysts for steam methane reforming using machine learning and microkinetic modeling
    (American Chemical Society, 2024-03-12) Wang, Siqi; Saravan, Satya; Kasarapu, Kumar; Clough, Peter T.
    The catalytic activity of bimetallic catalysts for the steam methane reforming (SMR) reaction was extensively studied previously. However, the performance of these materials in the presence of sulfur-containing species is yet to be investigated. In this study, we propose a novel process aided by machine learning (ML) and microkinetic modeling for the rapid screening of sulfur-resistant bimetallic catalysts. First, various ML models were developed to predict atomic adsorption energies (C, H, O, and S) on bimetallic surfaces. Easily accessible physical and chemical properties of the metals and adsorbates were used as input features. The Ensemble learning, artificial neural network, and support vector regression models achieved the best performance with R2 values of 0.74, 0.71, and 0.70, respectively. A microkinetic model was then built based on the elementary steps of the SMR reaction. Finally, the microkinetic model, together with the atomic adsorption energies predicted by the Ensemble model, were used to screen over 500 bimetallic materials. Four Ge-based alloys (Ge3Cu1, Ge3Ni1, Ge3Co1, and Ge3Fe1) and the Ni3Cu1 alloy were identified as promising and cost-effective sulfur-resistant catalysts.
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    Indirect engine sizing via distributed hybrid-electric unmanned aerial vehicle state-of-charge-based parametrisation criteria
    (SAGE Publications, 2019-04-28) Wang, Siqi; Economou, John T.; Tsourdos, Antonios
    This paper presents a design process for the challenging problem of sizing the engine pack for a Distributed Series Hybrid Electric Propulsion System (DSHEPS) of Unmanned Aircraft Vehicle (UAV). Sizing the propulsion system for hybrid electric UAVs is a demanding problem because of the two different categories of propulsion, (the engine and the motor), and the electrical system characteristics. Furthermore, what adds to the difficulty is that the Internal Combustion Engine (ICE) does not directly drive the propellers, but it is connected to an electrical generator and therefore provides electrical power to the Electric Motors (EM) and propellers. Hence there is a clear distinction from the traditional engine solutions which are mechanically coupled to the propeller. This paper addresses this specific distinction and proposes an indirect solution based on properties on the electrical part of the system. In particular, a novel parametric characterisation engine sizing approach is presented using the battery pack State-of-Charge (SOC) during a realistic UAV flight scenario. Five candidate engine options were considered with different starting conditions for the electrical system. The results show that by using the SOC properties it is possible to select an appropriate size of engine pack while carrying a suitable electrical propulsion pack. However, the solutions are not unique and are appropriate for given design criteria clearly indicated in the paper.
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    Intelligent-based hybrid-electric propulsion system for aero vehicle
    (Cranfield University, 2020-03) Wang, Siqi; Tsourdos, Antonios; Economou, John T.
    To address the sustainability challenges for air transport, electrified aviation delivers promising benefits to the whole air transportation system. Focusing on reducing environmental impact and raising competitiveness, this thesis presents a research regarding the Distributed Series Hybrid-electric Propulsion System for aero vehicles, which involves study fields of system configuration design, component sizing and energy management strategies. Based on the state-of-art of hybrid-electric aircraft and hybrid-electric propulsion systems, the study firstly improved the conventional series hybrid configuration by adopting distributed propulsion technology and more electric aircraft concept. These improvements can compensate for the drawbacks caused by the conventional series hybrid layout, so that the new designed propulsion system has the potential to reduce system weight and increase fuel economy. After that, a comprehensive sizing method was particularly designed for the proposed system. The engine, as the primary power source, was firstly selected via the battery parametrisation criteria. Then, other components were selected according to a proposed sizing flowchart by using the genetic algorithm. System performance can also be demonstrated during the sizing process. Finally, three different control methods had been applied to manage energy flows. The first supervisory controller is a deterministic rule-based controller, which was designed based on human experiences and can reduce 12% fuel consumption. The second is a battery-friendly fuzzy controller. It was particularly designed to improve the battery operating environment and can simultaneously achieve a 5% improvement on fuel economy compared to the rule-based. The third controller applied model predictive control algorithm, which can further improve the fuel efficiency by 4% and reveal the relationship between the fuel consumption and emissions.
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    Ni-based bimetallic catalysts for hydrogen production via (sorption-enhanced) steam methane reforming
    (Elsevier, 2024-04-15) Wang, Siqi; Shen, Ziqi; Osatiashtiani, Amin; Nabavi, Seyed Ali; Clough, Peter T.
    The catalytic performance of a monometallic Ni/Al2O3 and three bimetallic catalysts (Ni3M1/Al2O3, with M = Cu, Fe, and Ge) for the (sorption-enhanced) steam methane reforming reaction was evaluated. Ni3Cu1/Al2O3 was found to be the optimal catalyst in terms of methane conversion, hydrogen yield, and purity. Ge also has a promoting effect on the monometallic Ni catalyst, whereas the addition of Fe negatively influenced its performance. Physico-chemical characterization of the materials indicated the formation of alloys upon activation of the materials with hydrogen. The addition of Cu increased the surface area and metal dispersion, and improved the overall morphology of the catalyst. The experimental observations were also supported by a numerical study combining Density Functional Theory-based calculations and Microkinetic modelling of the SMR process. Ni3Cu1 and Ni3Ge1 were calculated to have a similar level of catalytic activity as Ni, whereas Ni3Fe1 was unsuitable for the reaction. The SMR reaction was further improved by adding calcium oxide as the CO2 sorbent, which increased methane conversion, CO selectivity, hydrogen yield, and hydrogen purity. The highest methane conversion of 97 % was achieved by Ni/Al2O3 and Ni3Cu1/Al2O3 at 700 °C.
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    Process mechanisms of nanobubble technology enhanced hydrolytic acidification of anaerobic digestion of lignocellulosic biomass
    (Elsevier, 2024-01-15) Zhu, Yali; Lyu, Tao; Li, Daoyu; Zhang, Zongqin; Guo, Jianbin; Li, Xin; Xiong, Wei; Dong, Renjie; Wang, Siqi
    This study explored the efficiency of CO2-, N2-, and H2- nanobubble treatment in anaerobic digestion (AD) of rice straw, with a focus on the processes and metabolic pathways of hydrolytic acidification, and revealed the underlying mechanisms. Mechanistic investigations revealed that nanobubbles, particularly CO2 nanobubbles, significantly increased the degradation of amorphous cellulose, resulting in higher levels of soluble carbohydrates (6.27 % – 11.13 %), VFAs (4.39 % – 24.50 %), and a remarkable cumulative H2 yield (74 – 94 times) Microbial community analysis indicated that the CO2 nanobubble promoted the growth of acidifying bacterial communities, such as Mobilitalea, unclassified_f_Lachnospiraceae, and Bacteroides. This indicates that the introduction of CO2 nanobubbles improved the total abundance of predicted functional enzymes were increased by 14 %, resulting in the production of more easily degradable intermediates. Based on the analysis of total methane production and kinetic analysis, it can be concluded that nanobubble addition enhanced methane production levels of 4.22 %−7.79 % with lower lag time (λ) (0.88–1.06 day) compared to the control group (1.09 day). The results also elucidated changes in relative enzymatic activities involved in the bioconversion of cellulose and hemicellulose during the hydrolysis stage with nanobubble treatment. This work is more beneficial for understanding the promoting effect and mechanism of nanobubbles on AD, facilitating the more precise application of nanobubble technology in the field of renewable energy.
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    A review on bi/polymetallic catalysts for steam methane reforming
    (Elsevier, 2023-01-30) Wang, Siqi; Nabavi, Seyed Ali
    Blue hydrogen production by steam methane reforming (SMR) with carbon capture is by far the most commercialised production method, and with the addition of a simultaneous in-situ CO2 adsorption process, sorption-enhanced steam methane reforming (SESMR) can further decrease the cost of H2 production. Ni-based catalysts have been extensively used for SMR because of their excellent activity and relatively low price, but carbon deposition, sulphation, and sintering can lead to catalyst deactivation. One effective solution is to introduce additional metal element(s) to improve the overall performance. This review summarizes recent developments on bi/polymetallic catalysts for SMR, including promoted nickel-based catalysts and other transition metal-based bi/polymetallic materials. The review mainly focuses on experimental studies, but also includes results from simulations to evaluate the synergistic effects of selected metals from an atomic point of view. An outlook is provided for the future development of bi/polymetallic SMR catalysts.