DLR Design Challenge 2022 on Advanced Aerial Firefighting

Since 2017, the German Aerospace Center (DLR) has been organizing an annual student competition on conceptual aircraft design titled DLR Design Challenge. This education and training initiative is set to challenge the next generation of aircraft designers with topics tailored to current research questions in the field of aeronautics. This year’s challenge was about the development of an aerial firefighting system of systems including vehicle and fleet design with a strong emphasize on operationally-driven design aspects

Automated in-silico detection of cell populations in flow cytometry readouts and its application to leukemia disease monitoring

BACKGROUND: Identification of minor cell populations, e.g. leukemic blasts within blood samples, has become increasingly important in therapeutic disease monitoring. Modern flow cytometers enable researchers to reliably measure six and more variables, describing cellular size, granularity and expression of cell-surface and intracellular proteins, for thousands of cells per second. Currently, analysis of cytometry readouts relies on visual inspection and manual gating of one- or two-dimensional projections of the data. This procedure, however, is labor-intensive and misses potential characteristic patterns in higher dimensions. RESULTS: Leukemic samples from patients with acute lymphoblastic leukemia at initial diagnosis and during induction therapy have been investigated by 4-color flow cytometry. We have utilized multivariate classification techniques, Support Vector Machines (SVM), to automate leukemic cell detection in cytometry. Classifiers were built on conventionally diagnosed training data. We assessed the detection accuracy on independent test data and analyzed marker expression of incongruently classified cells. SVM classification can recover manually gated leukemic cells with 99.78% sensitivity and 98.87% specificity. CONCLUSION: Multivariate classification techniques allow for automating cell population detection in cytometry readouts for diagnostic purposes. They potentially reduce time, costs and arbitrariness associated with these procedures. Due to their multivariate classification rules, they also allow for the reliable detection of small cell populations

Aircraft Architecture and Fleet Assessment Framework for Urban Air Mobility using a System of Systems Approach

This research article explores Urban Air Mobility (UAM) from a System of Systems (SoS) perspective in order to understand the impact of different fully electric UAM aircraft architectures on the overall SoS capability. For this purpose, a framework, combining aircraft design methods with an agent-based simulation, is developed. Thereby, not only different UAM aircraft architectures, but also fleet combinations, technology scenarios, and operational strategies are studied and evaluated for different success criteria. The UAM fleets are simulated for 24-hour operations, considering non-uniform passenger demand, dispatch of passenger as well as deadhead flights, aircraft architectural performance, load factor, energy consumption, and turnaround procedures. A large design of experiments, consisting of approximately 5,000 design points, is executed. Eventually, this article demonstrates the proof of concept for the proposed SoS framework and provides several parameter sensitivities for a given UAM scenario. For such complex SoS, analytical methods would not suffice for understanding complex and often nonlinear interactions. Therefore, the proposed simulation driven framework proves to be successful by providing sensitivity study results, linking subsystem, system (aircraft) and system of system (fleet) level. Thus, the framework allows for comprehensive understanding of the SoS design space and is important for successful deployment or optimization of UAM aircraft & fleet for a given city and operational context

Exploration of Aerial Firefighting Fleet Effectiveness and Cost by System of Systems Simulations

Wildfires are becoming a more frequent and devastating phenomena across the globe. The suppression of these wildfires is a dangerous and complex activity considering the vast systems that need to operate together to monitor, mitigate, and suppress the fire. In addition, the required cooperation spans multiple institutes in different capacities. Thus, the recognition of the wildfire suppression scenario as a System of Systems (SoS) is valid. Due to the dangers associated with firefighting and the increased occurrence, there is scope for the design of unmanned aerial vehicles for wildfire suppression. In this work, a SoS driven aircraft design, cost, and fleet assessment methodology is utilized together with a wildfire simulation to investigate several sensitivities relating to design and operational parameters. Further, this paper investigates their impacts on the measures of effectiveness, i.e. burnt area and operating cost. These two parameters enable the identification of optimal fleet size for wildfire suppression for a given scenario and aircraft definition

System of Systems Simulation driven Urban Air Mobility Vehicle Design and Fleet Assessment

Urban Air Mobility (UAM) is increasingly becoming popular for Passenger or Cargo movement in dense smart cities. Several researches so far are focused on individual vehicle architectures such as multirotor or tiltrotor etc., but not much effort in a System of systems point of view where a homogenous fleet of vehicle with different passenger capacity, speed, and propulsive energy concepts are assessed in a framework for a successful UAM operations in a given city. An effort is made in this paper wherein, vehicle architecture is derived from the Concept of Operations (CONOPS) of scenarios such as urban and suburban operations and as well as propulsion subsystem for sustainable UAM. This paper approaches UAM aircraft design driven by System of Systems (SoS) approach and an agent-based simulation supports the vehicle architecture evaluation and fleet definition. The outcome of this study are: multiple aircraft design with subsystem architectures, ideal fleet size for the respective operational scenarios, autonomy and battery technology effectiveness on UAM throughput (to efficiently provide UAM on-demand service maximum passengers within 15 min wait time), and importantly, sustainability metrics such as total fleet energy required. Several System of Systems, system and subsystem level sensitivity research questions are addressed to understand the interlevel couplin

System of Systems Simulation Driven Wildfire Fighting Aircraft Design and Fleet Assessment

Large wildfires are increasingly occurring phenomenon in several since the past few years. The suppression of wildfires is complex considering heterogeneous independent constituent systems operating together to monitor, mitigate, and suppress the fire. In addition, the management of the disaster response involve multiple institutions in collaboration. Recognition of this wildfire fighting scenario, as a System of Systems (SoS) is valid. Aerial vehicles may play a big role in firefighting considering monitoring and suppression at early stages when the fire is still small. Thus, there is scope for designing a new Unmanned Aerial Vehicle (UAV) with a payload of 250 kg to 500 kg for aerial forest fire suppression, using a SoS wildfire simulation driven aircraft design approach, where the individual optimum performance of a system, especially of a new aircraft for firefighting, does not guarantee optimum overall firefighting mission effectiveness. Whereas an optimum combination of fleet, technology and operational tactics can effectively suppress fire. For this reason, this research focuses on four different aspects: 1) Applying the inverse design paradigm to a wildfire suppression air vehicle by coupling a fire propagation cellular automata model with a stochastic agent-based simulation of an evolved firefighting SoS. An efficient SoS framework to Evaluate fleet performance. 2) Four System of systems – system – subsystem interlinking research questions are addressed with corresponding sensitivity results. The impact of wildfire based on vehicle fleet size, vehicle architecture (Tiltrotor, Compound Heli, Multirotor or Lift cruise), payload carrying capability, response time and cruise speed. 3) The evolution of perfect combination of aerial vehicle fleet with different vehicle architectures, technologies and performances using simulations. 4) Obtaining a set of system level (aircraft level) Measures of Performance (MoP) for the large suppression UAVs that produce improved SoS-level Measures of Effectiveness (MoE) during an initial attack quantified by containment time and total fire burnt area. As addressed by research questions and results. The response time and Number of Aircraft has large impact on success of the firefighting mission. As the time advantage deteriorate, the wild fire expands exponentially

Exploration of Aerial Firefighting Fleet Effectiveness and Cost by System of Systems Simulations

Wildfires are becoming a more frequent and devastating phenomena across the globe. The suppression of these wildfires is a dangerous and complex activity considering the vast systems that need to operate together to monitor, mitigate, and suppress the fire. In addition, the required cooperation spans multiple institutes in different capacities. Thus, the recognition of the wildfire suppression scenario as a System of Systems (SoS) is valid. Due to the dangers associated with firefighting and the increased occurrence, there is scope for the design of unmanned aerial vehicles for wildfire suppression. In this work, a SoS driven aircraft design, cost, and fleet assessment methodology is utilized together with a wildfire simulation to investigate several sensitivities relating to design and operational parameters. Further, this paper investigates their impacts on the measures of effectiveness, i.e. burnt area and operating cost. These two parameters enable the identification of optimal fleet size for wildfire suppression for a given scenario and aircraft definition