Browsing by Author "Wang, Siqi"
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Item Open Access 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, SiqiHybrid 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.Item Open Access High-throughput screening of sulfur-resistant catalysts for steam methane reforming using machine learning and microkinetic modeling(American Chemical Society, 2024-02-28) 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.Item Open Access 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, AntoniosThis 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.Item Open Access 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.Item Embargo Process mechanisms of nanobubble technology enhanced hydrolytic acidification of anaerobic digestion of lignocellulosic biomass(Elsevier, 2023-12-21) Zhu, Yali; Lyu, Tao; Li, Daoyu; Zhang, Zongqin; Guo, Jianbin; Li, Xin; Xiong, Wei; Dong, Renjie; Wang, SiqiThis 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.