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2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： He, Jun Niu, Yuqian Qin, Ze Yin, Hao Yang, Xingyu School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China College of Design and Engineering National University of Singapore Singapore119077 Singapore School of Future Technology Harbin Institute of Technology Harbin150000 China

In the process of rebar tying operations conducted by multiple robots, the flexibility and operability of the robot's end effector directly influence the overall performance of the rebar tying system. This reflects the crucial role of the coordinated working capability of multiple robots in the trajectory planning of the rebar tying system. Utilizing an eight degrees of freedom rebar tying system composed of two collaborative robots and a truss structure, the D-H (Denavit-Hartenberg) dynamic model for each robotic arm is established. The working area of the system is ascertained via Monte Carlo methods. Flexibility and operability are adopted as metrics to evaluate the system's performance, subsequently leading to the formulation of a mathematical model for assessing the system's flexibility. MATLAB is employed to delineate the robotic working range and simulate analysis of flexibility and operability when operating on the rebar tying plane, yielding an intuitive distribution of system flexibility. By analysing the distribution of flexibility and operability across the working plane at varying robot spacing intervals, an optimal robot movement distance can be determined. This ensures that during operational tasks, the rebar tying system not only possesses a larger total working area but also maintains a high level of flexibility and operability within the collaborative region, thereby fulfilling the objective of enhancing workspace utilization and improving rebar tying efficiency. © Published under licence by IOP Publishing Ltd.

关键词： Degrees of freedom (mechanics)

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design Environment for Lunar Operations and Systems Architecting

Design Environment for Lunar Operations and Systems Architec...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Boyer, Paul Park, Sean A. Jerresand, Cornelia Ramkumar, Siddharth Sambath Balchanos, Michael Pinon Fischer, Olivia J. Mavris, Dimitri N. Aerospace Systems Design Laboratory School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The interest in the space domain is on a steady rise since the last Apollo mission in 1972. This time, focus lies on the lunar South Pole and the establishment of a permanent lunar base for long-term human presence lead by NASAs Artemis missions. The new focus is a multi-level problem leveraging multiple stakeholders with collaborative/competitive interests and objectives. Developing a lunar base with city-level growth potential that exhibits complex interactions between assets and system processes requires the ability to rapidly explore, evaluate, prioritize, and select lunar architecture alternatives. To that end an architecting and sizing approach is proposed that enables the representation, modeling and simulation of a lunar base and its main components. Starting from the mission definition, a requirements flow-down process towards an executable modeling and simulation platform is adopted, following the R-F-L-P (Requirements-Functional-Logical-Physical) approach for defining the system architecting views. The outcome of this model-based exercise will result in a requirements-driven parametric interactive tradeoff environment, which will allow for exploration, prioritization, and selection of lunar architecture alternatives. The selection process is driven by tradeoff analysis and results which can address questions related to power demand and supply options, In-Situ Resource Utilization (ISRU) strategies, etc., and the broader aspect of technology selection of resource availability vs. mission-level risks. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

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Trade Studies for Evaluating Lunar Surface Power Architectures

Trade Studies for Evaluating Lunar Surface Power Architectur...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Thakar, Bhargavi V. McNabb, Jeffrey T. Robertson, Bradford E. Mavris, Dimitri N. School of Aerospace Engineering Aerospace Systems Design Laboratory Georgia Institute of Technology AtlantaGA30308 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

It is necessary to have a flexible power architecture for the implementation of a sustainable lunar base at the lunar South Pole. Several power architectures alternatives consisting of several technology options have been proposed. However, there is a lack of a comprehensive trade analysis of comparative sizing for those options. This paper presents a comparative evaluation of surface and elevated solar panels for power generation, DC cables, AC cables, and power beaming for power distribution, and batteries and fuel cells for energy storage, which helps understand the configuration for power architectures that provide the most optimal solution with regards to landed mass. The comparison is done by using illumination profiles of specific lunar sites and evaluating that at differing heights above the ground. The method of combining time-dependent illumination data with static system sizing is detailed in the paper. The case study compares the different architectures that are possible using all combinations of the technologies that are discussed. This study evaluated each architecture across a wide range of customer power demands, transmission distances, and transmission voltages. Elevated solar panels and regenerative fuel cells were found to be the best option across all cases. The case study determined that there is no best-in-class power distribution system and that each one has portion of the design space in which they are most mass efficient. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Regenerative fuel cells

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Journal of Chemical Education Call for Papers: Special Issue on Teaching Innovation in Materials Science and engineering design

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JOURNAL OF CHEMICAL EDUCATION 2024年第12期101卷 5139-5141页

作者： Dong, Zhili Silva, Arlindo Lim, Teik-Cheng Ng, Leonard W. T. Goncalves, Rui A. School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Engineering Product Development Pillar Singapore University of Technology and Design Singapore 487372 Singapore School of Science and Technology Singapore University of Social Sciences Singapore 599494 Singapore

The Journal of Chemical Education announces a call for papers for an upcoming special issue on Teaching Innovation in Materials Science and engineering design. This issue aims to highlight innovative approaches in teaching materials science and engineering, with a focus on integrating design principles, sustainability, and artificial intelligence into educational programs.

关键词： Materials Education designengineering Sustainability Artificial Intelligencein Education Innovative TeachingMethods Industry-Academia Collaboration

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A Process Evaluation and Visualization Framework for Unmanned Aerial System (UAS) Noise Certification Testing

A Process Evaluation and Visualization Framework for Unmanne...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Mali, Hajar Geneti, Nathnael F. Balchanos, Michael Harrison, Evan D. Mavris, Dimitri Aerospace Systems Design Laboratory School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Expanding upon recent research into the effectiveness of noise testing processes for Unmanned Aerial Systems (UAS) [1], this study is seeking to develop methods for process analysis and efficiency assessment for a model-based framework to further optimize noise certification procedures. The original framework is capable of detecting certification testing procedure inefficiencies and analyzing the time and cost of flight testing. In this study, the framework’s capabilities are extended through advanced modeling techniques using Markov Chains and graph theory, extensive Monte Carlo simulations, and a broader application of design of Experiments to capture a wider range of variables and their impact on the noise testing outcomes and overall efficiency. Moreover, The enhanced framework quantifies and assesses the complexity level of testing procedures to provide insights on the associated uncertainty and risks. Additionally, it enables the prediction of process bottlenecks and establishes trade-offs more accurately. This work introduces enhanced decision support relying on different elements including sensitivity analyses, histogram overlays, and operational viewpoints. These capabilities allow stakeholders to interactively explore several noise testing strategies, compare their effectiveness and potential performance gains, and acquire insights on the resulting certification burden from different aspects. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Sensitivity analysis

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design and Evaluation of an Aircraft Family with Diverse Energy Sources for Sustainable Aviation

Design and Evaluation of an Aircraft Family with Diverse Ene...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Almarzooqi, Ranya Vonfeldt, Michela Kallou, Evanthia Xie, Jiacheng Gladin, Jonathan C. Mavris, Dimitri N. Aerospace Systems Design Laboratory School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Aviation activities significantly contribute to global carbon dioxide emissions. To achieve the 2050 net-zero carbon emissions goal set by the International Air Transport Association (IATA), alternative green energy sources are expected to be applied in future aircraft. This paper presents a design study of an aircraft family utilizing both sustainable aviation fuel (SAF) and liquid hydrogen (LH2), aiming to demonstrate the potential of a versatile aircraft family in bridging the transition towards net-zero emissions and balancing immediate improvements with long-term sustainability goals. The study applies a modular, clean-sheet design approach with a focus on common-core engine principles, allowing shared high-pressure components between variants to reduce development complexity. Advanced simulation capabilities, including multi-design point (MDP) analysis, were used to develop six aircraft variants in the aircraft family, including one SAF vehicle and five LH2 vehicles. Trade-off studies between payload, range, and energy storage revealed that optimizing hydrogen storage significantly enhances range and energy efficiency, but comes at the expense of passenger capacity. Conversely, designs prioritizing capacity faced limitations in operational range. These trade-off studies revealed how modular designs can address diverse market demands, with SAF variants offering immediate emissions reductions and LH2 variants enabling long-term sustainability through significant improvements in range and energy efficiency. These findings emphasize the viability of a transitional approach to achieving net-zero in aviation by combining short and long-term transitional solutions. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hydrogen storage

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STUDY ON PERFORMANCE OF DIATOMITE/BASALT FIBER COMPOSITE MODIFIED ASPHALT UNDER THE CONDITION OF ENERGY SAVING, GREEN AND LOW CARBON

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UPB Scientific Bulletin, Series B: Chemistry and Materials Science 2023年第2期85卷 119-130页

作者： Liu, Fuming Ye, Quanming Su, Heng He, Qingde Yang, Zhiping School of Civil and Architectural Engineering Nanchang Institute of Technology Nanchang China School of Civil Engineering Chongqing Jiaotong University Chongqing China Fuzhou Gandong Highway Design Institute Company Ltd Fuzhou China

In order to obtain composite modified asphalt with excellent performance of diatomite and basalt fiber suitable for the humid and hot areas of southern China, meet the requirements of carbon neutralization and carbon peak, and reduce energy consumption, the response surface methodology was taken to perfect the preparation process. The conventional physical properties of composite modified asphalt prepared in divergent basalt fibers and diatomite dosages and shear time conditions were tested separately, such as the penetration, softening point, melleability and viscosity, the optimal level values of each factor were obtained, and the high and low temperature performance of diatomite and basalt fiber modified bitumen at different dosages were evaluated by DSR and BBR tests. The test results show that the levels of various factors in the preparation process were comprehensively optimized by response surface methodology. When diatomite content is 11.18%, basalt fiber content is 3.09%, at 160°C, using 4700r/min rate of high-speed shear 44.2min, the composite modified asphalt has the best performance which is superior to that of SBS modified asphalt, while its low-temperature performance is slightly inferior to that of SBS modified asphalt. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Energy conservation

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Predicting torsional capacity of reinforced concrete members by data-driven machine learning models

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Frontiers of Structural and Civil engineering 2024年第3期18卷 444-460页

作者： Shenggang CHEN Congcong CHEN Shengyuan LI Junying GUO Quanquan GUO Chaolai LI School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 211116China Jiangsu Key Laboratory Environmental Impact and Structural Safety in Engineering China University of Mining and TechnologyXuzhou 211116China China Nuclear Power Design Co.Ltd. Shenzhen 518031China School of transportation and science engineering Beihang UniversityBeijing 100191China China Construction First Group Corporation Limited Beijing 100161China

Due to the complicated three-dimensional behaviors and testing limitations of reinforced concrete(RC)members in torsion,torsional mechanism exploration and torsional performance prediction have always been *** the present paper,several machine learning models were applied to predict the torsional capacity of RC *** results of a total of 287 torsional specimens were collected through an overall literature *** of extreme gradient boosting machine(XGBM),random forest regression,back propagation artificial neural network and support vector machine,were trained and tested by 10-fold cross-validation *** performances of proposed machine learning models were evaluated and compared,both with each other and with the calculated results of existing design codes,i.e.,GB 50010,ACI 318-19,and Eurocode *** results demonstrated that better predictive performance was achieved by machine learning models,whereas GB 50010 slightly overestimated the torsional capacity,and ACI 318-19 and Eurocode 2 underestimated it,especially in the case of ACI *** XGBM model gave the most favorable predictions with R^(2)=0.999,RMSE=1.386,MAE=0.86,andλ=***,strength of concrete was the most sensitive input parameters affecting the reliability of the predictive model,followed by transverse-to-longitudinal reinforcement ratio and total reinforcement ratio.

关键词： RC members torsional capacity machine learning models design codes

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Sizing Analysis for Non-Terrestrial Aircraft

Sizing Analysis for Non-Terrestrial Aircraft

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Obero, Tyler V. Masset, Alexandre Paulson, Lauren V. Himdi, Nada Garces, Cristobal C. Johnson, Carl C. Ahuja, Jai Mavris, Dimitri N. Aerospace Systems Design Laboratory School of Aerospace Engineering Georgia Institute of Technology AtlantaGA30332 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

designing aircraft for non-terrestrial environments involves unique challenges due to the lack of established benchmarks, the exploration of uncharted territories, and the limited availability of environmental data. To address these challenges, the Sizing Analysis for Non-Terrestrial Aircraft (SANTA) tool employs a rigorous, requirement-driven methodology. This approach includes selecting a relevant use case, defining a specific mission within that context, and sizing the aircraft according to the mission’s parameters. For this analysis, Titan, Saturn’s largest moon, was chosen as the use case. Titan’s solid surface and extensive atmospheric data from the Cassini probe, along with the scientific interest in its methane lakes for potential prebiotic conditions, make it an ideal candidate. The SANTA tool integrates multidisciplinary analysis, three-dimensional modeling, and conventional sizing techniques to optimize the aircraft’s geometry, payload configuration, and energy requirements for Titan’s environment. This study demonstrates the feasibility of designing reliable and efficient aircraft for challenging extraterrestrial missions, thus advancing aerospace engineering and enhancing our understanding of the solar system. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aircraft models

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Deformation Evolution and Perceptual Prediction for Additive Manufacturing of Lightweight Composite Driven by Hybrid Digital Twins

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Chinese Journal of Mechanical engineering 2024年第5期37卷 94-112页

作者： Jinghua Xu Linxuan Wang Mingyu Gao Chen Jia Qianyong Chen Kang Wang Shuyou Zhang Jianrong Tan Shaomei Fei State Key Lab of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310058China Zhejiang Key Lab of Advanced Manufacturing Technology School of Mechanical EngineeringZhejiang UniversityHangzhou 310058China State Key Laboratory of Materials Processing and Die and Mould Technology Huazhong University of Science and TechnologyWuhan 430074China Institute of Design Engineering Zhejiang UniversityHangzhou 310058China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore City 639798Singapore

This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering,the HDT meaning hybridization of physical and digital domains,including deformation and energy efficiency can be built,where the essential parameters can be perceptually predicted in advance,by virtue of the fusion of physical sensors and digital *** long short term memory(LSTM)can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks,thereby laying a foundation for the *** diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service *** effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional *** manufacturing efficiency and comprehensive costs are accounted as consideration factors,which are perceptually predicted via *** designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process *** physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling(FDM).The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction *** dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine(CMM)and 3D optica

关键词： Deformation evolution Perceptual prediction Lightweight composite Hybrid digital twins(HDT) Long short term memory(LSTM)

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