@article{PfaffEnningSutter2022,
  author    = {Pfaff, Raphael and Enning, Manfred and Sutter, Stefan},
  title     = {A risk‑based approach to automatic brake tests for rail freight service: incident analysis and realisation concept},
  series = {SN Applied Sciences},
  volume    = {4},
  journal   = {SN Applied Sciences},
  number    = {4},
  publisher = {Springer},
  address   = {Cham},
  issn      = {2523-3971},
  doi       = {10.1007/s42452-022-05007-x},
  pages     = {1 -- 14},
  year      = {2022},
  abstract  = {This study reviews the practice of brake tests in freight railways, which is time consuming and not suitable to detect certain failure types. Public incident reports are analysed to derive a reasonable brake test hardware and communication architecture, which aims to provide automatic brake tests at lower cost than current solutions. The proposed solutions relies exclusively on brake pipe and brake cylinder pressure sensors, a brake release position switch as well as radio communication via standard protocols. The approach is embedded in the Wagon 4.0 concept, which is a holistic approach to a smart freight wagon. The reduction of manual processes yields a strong incentive due to high savings in manual labour and increased productivity.},
  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{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{MoehrenBergmannJanseretal.2024,
  author    = {M{\"o}hren, Felix and Bergmann, Ole and Janser, Frank and Braun, Carsten},
  title     = {Assessment of structural mechanical effects related to torsional deformations of propellers},
  series = {CEAS Aeronautical Journal},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer},
  address   = {Wien},
  issn      = {1869-5590 (eISSN)},
  doi       = {10.1007/s13272-024-00737-7},
  pages     = {22 Seiten},
  year      = {2024},
  abstract  = {Lifting propellers are of increasing interest for Advanced Air Mobility. All propellers and rotors are initially twisted beams, showing significant extension-twist coupling and centrifugal twisting. Torsional deformations severely impact aerodynamic performance. This paper presents a novel approach to assess different reasons for torsional deformations. A reduced-order model runs large parameter sweeps with algebraic formulations and numerical solution procedures. Generic beams represent three different propeller types for General Aviation, Commercial Aviation, and Advanced Air Mobility. Simulations include solid and hollow cross-sections made of aluminum, steel, and carbon fiber-reinforced polymer. The investigation shows that centrifugal twisting moments depend on both the elastic and initial twist. The determination of the centrifugal twisting moment solely based on the initial twist suffers from errors exceeding 5\% in some cases. The nonlinear parts of the torsional rigidity do not significantly impact the overall torsional rigidity for the investigated propeller types. The extension-twist coupling related to the initial and elastic twist in combination with tension forces significantly impacts the net cross-sectional torsional loads. While the increase in torsional stiffness due to initial twist contributes to the overall stiffness for General and Commercial Aviation propellers, its contribution to the lift propeller's stiffness is limited. The paper closes with the presentation of approximations for each effect identified as significant. Numerical evaluations are necessary to determine each effect for inhomogeneous cross-sections made of anisotropic material.},
  language  = {en}
}
@article{LaarmannThomaMischetal.2023,
  author    = {Laarmann, Lukas and Thoma, Andreas and Misch, Philipp and R{\"o}th, Thilo and Braun, Carsten and Watkins, Simon and Fard, Mohammad},
  title     = {Automotive safety approach for future eVTOL vehicles},
  series = {CEAS Aeronautical Journal},
  journal   = {CEAS Aeronautical Journal},
  publisher = {Springer Nature},
  issn      = {1869-5590 (Online)},
  doi       = {10.1007/s13272-023-00655-0},
  pages     = {11 Seiten},
  year      = {2023},
  abstract  = {The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL's crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.},
  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}
}