@article{WilbringEnningPfaffetal.2020, author = {Wilbring, Daniela and Enning, Manfred and Pfaff, Raphael and Schmidt, Bernd}, title = {Neue Perspektiven f{\"u}r die Bahn in der Produktions- und Distributionslogistik durch Prozessautomation}, series = {ETR - Eisenbahntechnische Rundschau}, volume = {69}, journal = {ETR - Eisenbahntechnische Rundschau}, number = {3}, issn = {0013-2845}, pages = {15 -- 19}, year = {2020}, language = {de} } @article{WeiheErnstRoethetal.2013, author = {Weihe, Stefan and Ernst, Ansgar and R{\"o}th, Thilo and Proksch, Johannes}, title = {Aluminium-Stahl-Verbundguss im Nutzfahrzeugbau}, series = {ATZ - Automobiltechnische Zeitschrift}, volume = {115}, journal = {ATZ - Automobiltechnische Zeitschrift}, number = {4}, publisher = {Springer Fachmedien Wiesbaden}, issn = {2192-8800 (Online)}, pages = {312 -- 316}, year = {2013}, abstract = {In modernen Fahrzeugkarosserien der Großserie kommen zunehmend Materialmischbauweisen zur Anwendung. In Zusammenarbeit der Daimler AG, der Tower Automotive Holding GmbH, der Imperia GmbH sowie der Partnerunternehmen KSM Castings GmbH und Schaufler Tooling GmbH \& Co. KG wird das Leichtbaupotenzial von Aluminiumverbundguss-Stahlblech-Hybriden am Beispiel des vorderen Dachquertr{\"a}gers des Mercedes-Benz Viano/Vito ausf{\"u}hrlich untersucht.}, language = {de} } @article{WeiheAnsgarRoethetal.2013, author = {Weihe, Stefan and Ansgar, Ernst and R{\"o}th, Thilo and Proksch, Johannes}, title = {Leichtmetall-Stahl-Verbundguss im Nutzfahrzeugbau}, series = {Lightweight Design}, volume = {6}, journal = {Lightweight Design}, number = {2}, publisher = {Springer}, address = {Berlin}, issn = {2192-8738 (Online)}, pages = {38 -- 43}, year = {2013}, abstract = {In modernen Fahrzeugkarosserien der Großserie kommen zunehmend Materialmischbauweisen zur Anwendung. In Zusammenarbeit der Daimler AG, der Tower Automotive Holding GmbH, der Imperia GmbH sowie der Partnerunternehmen KSM Castings GmbH und Schaufler Tooling GmbH \& Co. KG wird das Leichtbaupotenzial von Stahlblech-AluminiumverbundgussHybriden am Beispiel des vorderen Dachquertr{\"a}gers des Mercedes-Benz Viano/Vito ausf{\"u}hrlich untersucht.}, language = {de} } @article{UlmerBraunChengetal.2023, author = {Ulmer, Jessica and Braun, Carsten and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation}, series = {International Journal of Production Research}, journal = {International Journal of Production Research}, publisher = {Taylor \& Francis}, issn = {0020-7543 (Print)}, doi = {10.1080/00207543.2023.2166140}, year = {2023}, abstract = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.}, language = {en} } @article{ThomaThomessenGardietal.2023, author = {Thoma, Andreas and Thomessen, Karolin and Gardi, Alessandro and Fisher, A. and Braun, Carsten}, title = {Prioritising paths: An improved cost function for local path planning for UAV in medical applications}, series = {The Aeronautical Journal}, journal = {The Aeronautical Journal}, number = {First View}, publisher = {Cambridge University Press}, address = {Cambridge}, issn = {0001-9240 (Print)}, doi = {10.1017/aer.2023.68}, pages = {1 -- 18}, year = {2023}, abstract = {Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50\% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26\%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30\%. These results show promise for further enhancements and to support broader applicability.}, language = {en} } @article{StiemerThomaBraun2023, author = {Stiemer, Luc Nicolas and Thoma, Andreas and Braun, Carsten}, title = {MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation}, series = {PLoS ONE}, volume = {18}, journal = {PLoS ONE}, number = {9}, publisher = {PLOS}, address = {San Fancisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0291415}, pages = {e0291415}, year = {2023}, abstract = {This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking algorithm for bumblebee tracking. It incorporates an offline trained appearance descriptor along with a Kalman Filter for appearance and motion matching. Different detector architectures for upstream detections (You Only Look Once (YOLOv5), Faster Region Proposal Convolutional Neural Network (Faster R-CNN), and RetinaNet) are investigated in a comparative study to optimize performance. The detection models were trained on a dataset containing 11359 labeled bumblebee images. YOLOv5 reaches an Average Precision of AP = 53, 8\%, Faster R-CNN achieves AP = 45, 3\% and RetinaNet AP = 38, 4\% on the bumblebee validation dataset, which consists of 1323 labeled bumblebee images. The tracker's appearance model is trained on 144 samples. The tracker (with Faster R-CNN detections) reaches a Multiple Object Tracking Accuracy MOTA = 93, 5\% and a Multiple Object Tracking Precision MOTP = 75, 6\% on a validation dataset containing 2000 images, competing with state-of-the-art computer vision methods. The framework allows reliable tracking of different bumblebees in the same video stream with rarely occurring identity switches (IDS). MBT3D has much lower IDS than other commonly used algorithms, with one of the lowest false positive rates, competing with state-of-the-art animal tracking algorithms. The developed framework reconstructs the 3-dimensional (3D) flight paths of the bumblebees by triangulation. It also handles and compares two alternative stereo camera pairs if desired.}, language = {en} } @article{SerrorHackHenzeetal.2021, author = {Serror, Martin and Hack, Sacha and Henze, Martin and Schuba, Marko and Wehrle, Klaus}, title = {Challenges and Opportunities in Securing the Industrial Internet of Things}, series = {IEEE Transactions on Industrial Informatics}, volume = {17}, journal = {IEEE Transactions on Industrial Informatics}, number = {5}, publisher = {IEEE}, address = {New York}, issn = {1941-0050}, doi = {10.1109/TII.2020.3023507}, pages = {2985 -- 2996}, year = {2021}, language = {en} } @article{Schueckhaus2020, author = {Sch{\"u}ckhaus, Ulrich}, title = {Die SkyCab-Erfinder im WFMG-Interview}, series = {Business in MG}, journal = {Business in MG}, number = {1}, pages = {6 -- 7}, year = {2020}, language = {de} } @article{SchwagerFleschSchwarzboezletal.2022, author = {Schwager, Christian and Flesch, Robert and Schwarzb{\"o}zl, Peter and Herrmann, Ulf and Teixeira Boura, Cristiano Jos{\´e}}, title = {Advanced two phase flow model for transient molten salt receiver system simulation}, series = {Solar Energy}, volume = {232}, journal = {Solar Energy}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0038-092X (print)}, doi = {10.1016/j.solener.2021.12.065}, pages = {362 -- 375}, year = {2022}, abstract = {In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.}, language = {en} } @article{SchulzeFeyerlPischinger2023, author = {Schulze, Sven and Feyerl, G{\"u}nter and Pischinger, Stefan}, title = {Advanced ECMS for hybrid electric heavy-duty trucks with predictive battery discharge and adaptive operating strategy under real driving conditions}, series = {Energies}, volume = {16}, journal = {Energies}, number = {13}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {10.3390/en16135171}, pages = {29 Seiten, Art. Nr.: 5171}, year = {2023}, abstract = {To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15\% more efficiently by 2025 and 30\% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2\% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.}, language = {en} } @article{RoethPielenWolffetal.2018, author = {R{\"o}th, Thilo and Pielen, Michael and Wolff, Klaus and L{\"u}diger, Thomas}, title = {Urbane Fahrzeugkonzepte f{\"u}r die Shared Mobility}, series = {Automobiltechnische Zeitschrift - ATZ}, volume = {120}, journal = {Automobiltechnische Zeitschrift - ATZ}, number = {1}, publisher = {Springer Vieweg}, address = {Wiesbaden}, issn = {0001-2785}, doi = {10.1007/s35148-017-0176-8}, pages = {18 -- 23}, year = {2018}, abstract = {Urbane Mobilit{\"a}tskonzepte der Zukunft erfordern neue Unternehmensformen, idealerweise aus Old Economy und New Economy, sowie eine enge Anbindung an die gesellschaftsrelevante Zukunftsforschung. F{\"u}r neue Fahrzeugkonzepte des Carsharing bedeutet dies, dass alle kostenverursachenden Faktoren erfasst und analysiert werden m{\"u}ssen. Die FH Aachen, share2drive und FEV geben einen Ausblick auf die zuk{\"u}nftige Fahrzeugklasse der Personal Public Vehicles als „Rolling Device".}, language = {de} } @article{RuppSchulzeKuperjans2018, author = {Rupp, Matthias and Schulze, Sven and Kuperjans, Isabel}, title = {Comparative life cycle analysis of conventional and hybrid heavy-duty trucks}, series = {World electric vehicle journal}, volume = {9}, journal = {World electric vehicle journal}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2032-6653}, doi = {10.3390/wevj9020033}, pages = {Article No. 33}, year = {2018}, abstract = {Heavy-duty trucks are one of the main contributors to greenhouse gas emissions in German traffic. Drivetrain electrification is an option to reduce tailpipe emissions by increasing energy conversion efficiency. To evaluate the vehicle's environmental impacts, it is necessary to consider the entire life cycle. In addition to the daily use, it is also necessary to include the impact of production and disposal. This study presents the comparative life cycle analysis of a parallel hybrid and a conventional heavy-duty truck in long-haul operation. Assuming a uniform vehicle glider, only the differing parts of both drivetrains are taken into account to calculate the environmental burdens of the production. The use phase is modeled by a backward simulation in MATLAB/Simulink considering a characteristic driving cycle. A break-even analysis is conducted to show at what mileage the larger CO2eq emissions due to the production of the electric drivetrain are compensated. The effect of parameter variation on the break-even mileage is investigated by a sensitivity analysis. The results of this analysis show the difference in CO2eq/t km is negative, indicating that the hybrid vehicle releases 4.34 g CO2eq/t km over a lifetime fewer emissions compared to the diesel truck. The break-even analysis also emphasizes the advantages of the electrified drivetrain, compensating the larger emissions generated during production after already a distance of 15,800 km (approx. 1.5 months of operation time). The intersection coordinates, distance, and CO2eq, strongly depend on fuel, emissions for battery production and the driving profile, which lead to nearly all parameter variations showing an increase in break-even distance.}, language = {en} } @article{Pfaff2023, author = {Pfaff, Raphael}, title = {Braking distance prediction for vehicle consist in low-speed on-sight operation: a Monte Carlo approach}, series = {Railway Engineering Science}, volume = {31}, journal = {Railway Engineering Science}, number = {2}, publisher = {SpringerOpen}, issn = {2662-4753 (eISSN)}, doi = {10.1007/s40534-023-00303-7}, pages = {135 -- 144}, year = {2023}, abstract = {The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.}, language = {en} } @article{PetersonRoethUibel2017, author = {Peterson, Leif Arne and R{\"o}th, Thilo and Uibel, Thomas}, title = {Einsatz von Holzwerkstoffen in Fahrzeugstrukturen}, series = {Bauen mit Holz}, journal = {Bauen mit Holz}, number = {3}, publisher = {Bruderverlag}, address = {K{\"o}ln}, issn = {0005-6545}, pages = {32 -- 38}, year = {2017}, language = {de} } @article{NeuJanserKhatibietal.2017, author = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.}, title = {Fully Automated Operational Modal Analysis using multi-stage clustering}, series = {Mechanical Systems and Signal Processing}, volume = {Vol. 84, Part A}, journal = {Mechanical Systems and Signal Processing}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0888-3270}, doi = {10.1016/j.ymssp.2016.07.031}, pages = {308 -- 323}, year = {2017}, language = {en} } @article{NeuJanserKhatibietal.2016, author = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.}, title = {Automated modal parameter-based anomaly detection under varying wind excitation}, series = {Structural Health Monitoring}, volume = {15}, journal = {Structural Health Monitoring}, number = {6}, publisher = {Sage}, address = {London}, issn = {1475-9217}, doi = {10.1177/1475921716665803}, pages = {1 -- 20}, year = {2016}, abstract = {Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.}, language = {en} } @article{KreyerMuellerEsch2020, author = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas}, title = {A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles}, series = {SAE International Journal of Commercial Vehicles}, volume = {13}, journal = {SAE International Journal of Commercial Vehicles}, number = {2}, publisher = {SAE International}, address = {Warrendale, Pa.}, issn = {1946-3928}, doi = {10.4271/02-13-02-0009}, pages = {129 -- 143}, year = {2020}, abstract = {The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0}, series = {IEEE Access}, volume = {8}, journal = {IEEE Access}, number = {Art. 9108222}, publisher = {IEEE}, address = {New York, NY}, issn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {111381 -- 111393}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @article{KhayyamJamaliBabHadiasharetal.2020, author = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo}, title = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0}, series = {IEEE Access}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York, NY}, isbn = {2169-3536}, doi = {10.1109/ACCESS.2020.2999898}, pages = {1 -- 12}, year = {2020}, abstract = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.}, language = {en} } @article{HoevelerBauknechtWolfetal.2020, author = {Hoeveler, B. and Bauknecht, Andr{\´e} and Wolf, C. Christian and Janser, Frank}, title = {Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight}, series = {Journal of Aircraft}, volume = {57}, journal = {Journal of Aircraft}, number = {4}, publisher = {AIAA}, address = {Reston, Va.}, issn = {1533-3868}, doi = {10.2514/1.C035422}, year = {2020}, abstract = {It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility G{\"o}ttingen of DLR, German Aerospace Center in G{\"o}ttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25\% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1\%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan.}, language = {en} }