När en helikopter befinner sig i brownout saknar besättningen referenser till omvärlden vilket kan försämra det spatiala medvetandet. Om besättningen inte har koll på helikopterns position i luftrummet kan det leda till skador på både materiel och besättning i samband med landning. Denna rapport undersökte, på ett övergripande plan, vilka möjligheter sensorer inom det elektromagnetiska spektret hade att bidra med information till det spatiala medvetandet. Rapporten fann att sensorerna behöver vara anpassningsbara till följd av stoftmolnets vida varierande karaktäristik. Sensorerna hade möjlighet att generera en bild av landningsplatsen före brownout inträffar. Radar lämpade sig bäst till att uppdatera bilden när brownout inträffat då de elektrooptiska sensorerna kraftigt begränsas av stoftmolnet. Däremot genererade de elektrooptiska sensorerna en bild av omgivningen som motsvarade ögats tolkning av samma omgivning, något som en radar har svårare att göra. / When a helicopter is in brownout the crew looses references to the world outside which could decrease the spatial awareness. If the crew does not know the accurate position of the helicopter it can lead to damage on both equipment and crew when landing. This report examined, on a general level, how sensors within the electromagnetic spectrum could contribute with information to the spatial awareness. The report found that the sensors need to be adaptable due to the widely varying characteristics of the dustcloud. The sensors were able to generate an image of the landingsite prior to brownout. Radar was best suited to updating the image when brownout had occurred, whereas the electro-optical sensors are highly attenuated by the dust cloud. However, the electro-optical sensors generated an image of the environment corresponding to the eye's interpretation of the same surrounding, something that a radar has greater difficulty with accomplishing.

The BOSS symbology for rotorcraft is specifically designed to provide the pilot with the necessary information and guidance to safely land in brownout environments. From the last BOSS study, issues were brought forth regarding the longitudinal velocity algorithm, which sets up a deceleration profile and commands the forward speed of the aircraft throughout the approach. Pilots commented that the algorithm lead the aircraft to be too slow for too long, effectively prolonging the brownout. Thus the purpose of this study was to investigate new algorithms to enable a faster approach with less time spent in brownout. The previous deceleration algorithm was also not robust in its ability to provide consistent guidance at variable starting distances and starting velocities. Therefore a new algorithm was developed capable of providing more consistent guidance from various starting positions and velocities. Additionally, through manipulation of its parameters, it was found possible to reduce the amount of time spent at low speeds in the approach. Four algorithms were subsequently developed with varying levels of aggressiveness. Eight highly skilled pilots participated in a simulation study using a generic fixed-base simulator with a high-fidelity rotorcraft H-60 model. Results found that as the aggressiveness of the algorithm increased, the time spent at low speeds and in brownout significantly decreased. Concurrently the pitch of the aircraft (and resulting deceleration) significantly increased, though the pitch values were within reasonable limits for IMC flight according to previous literature. One of the new algorithms was found to significantly reduce the amount of time spent at low speeds by 24% and also received the highest preference ranking and the highest comfort ratings.

The exploration of celestial bodies has recently advanced from rovers to rotorcraft. This includes the recent flights of Mars Ingenuity and the upcoming Dragonfly mission to explore the terrain of Saturn’s moon Titan as part of NASA’s New Frontiers Program. Flight-based landers can travel quickly to sites kilometers apart and land in complex terrain. Although cruise conditions for these rotorcrafts are well understood, studies are necessary to understand take-off and landing. In ground effect conditions, a rotor wake impinges and reflects off the ground, creating changes in aerodynamics such as increased lift. Additionally, operating over loose surfaces, the rotors can create clouds of dust obscuring the vehicle’s sensors, a hazard termed “brownout” from rotorcraft landing in sandy and snowy conditions on Earth. Take-off and landing events involve interactions between the rotor wake, fuselage, and ground, and lead to a multi-phase interface between the fluid atmosphere and the dispersed dust particles. The objective of this study is to computationally model and evaluate ground effect aerodynamic forces on the Dragonfly rotorcraft lander. A calculation of sediment distribution across the surface of the vehicle will provide insight to which components might be most affected by brownout.

abstract: Rotorcraft operation in austere environments can result in difficult operating conditions, particularly in the vicinity of sandy areas. The uplift of sediment by rotorcraft downwash, a phenomenon known as brownout, hinders pilot visual cues and may result in a potentially dangerous situation. Brownout is a complex multiphase flow problem that is not unique and depends on both the characteristics of the rotorcraft and the sediment. The lack of fundamental understanding constrains models and limits development of technologies that could mitigate the adverse effects of brownout. This provides the over-arching motivation of the current work focusing on models of particle-laden sediment beds. The particular focus of the current investigations is numerical modeling of near-surface fluid-particle interactions in turbulent boundary layers with and without coherent vortices superimposed on the background flow, that model rotorcraft downwash. The simulations are performed with two groups of particles having different densities both of which display strong vortex-particle interaction close to the source location. The simulations include cases with inter-particle collisions and gravitational settling. Particle effects on the fluid are ignored. The numerical simulations are performed using an Euler- Lagrange method in which a fractional-step approach is used for the fluid and with the particulate phase advanced using Discrete Particle Simulation. The objectives are to gain insight into the fluid-particle dynamics that influence transport near the bed by analyzing the competing effects of the vortices, inter-particle collisions, and gravity. Following the introduction of coherent vortices into the domain, the structures convect downstream, dissipate, and then recover to an equilibrium state with the boundary layer. The particle phase displays an analogous return to an equilibrium state as the vortices dissipate and the boundary layer recovers, though this recovery is slower than for the fluid and is sensitive to the particle response time. The effects of inter-particle collisions are relatively strong and apparent throughout the flow, being most effective in the boundary layer. Gravitational settling increases the particle concentration near the wall and consequently increase inter-particle collisions. / Dissertation/Thesis / M.S. Aerospace Engineering 2011

Brownout-fenomenet ligger till grund för ungefär 75 procent av alla flygolyckor inom NATO. Olyckorna sker under start och landningssekvenser i torra klimat då sand virvlar upp och försämrar pilotens sikt utifrån helikoptern. Under brownout förlorar piloten visuella referenser utanför helikoptern vilket gör att denne omedvetet kan tappa kontrollen över helikoptern och således kan hamna i plötsligt drift. Därför har NATO i samarbete med bland annat Totalförsvarets Forskningsinstitut (FOI) försökt finna en lösning på problemen som uppstår vid brownout. Syftet med föreliggande studie är främst att undersöka om deltagares användning av taktila driftdisplayer leder till mindre drift än vid användning av en visuell driftdisplay samt undersöka med vilken av de taktila displayerna som leder till minst drift. Samtliga displayer gav feedback för horisontell och vertikal drift och utvärderades med hjälp av FOIs egna helikoptersimulator. 12 personer med tidigare erfarenhet av helikoptersimulator deltog i studien. Deltagarna hade som uppgift att undvika drift genom att hovra på en höjd av 8000 fot under 120 sekunder per display, med totalt fyra olika displayer. Prestationsmåtten visade att det inte fanns några signifikanta skillnader mellan displayerna. Trots detta kan resultatet ses som positivt då det visar att taktil display som feedback för drift fungerar lika bra som en visuell display. Resultatet från de subjektiva skattningsmåtten visade däremot att den komplexa taktila displayen skattades signifikant sämre än den visuella displayen. Detta eftersom komplexiteten antagligen var så hög att displayen inte kunde användas på ett effektivt och intuitivt sätt. Slutligen skattades den visuella displayen och den rinnande taktila displayen generellt som de lättaste displayerna vid användning som feedback för drift.

Edge cloud is a distributed computing architecture that is growing in popularity. It aims to bring the cloud closer to the edge of a network, reducing latency and improving performance through the use of distributed servers (edge nodes) spread out geographically. However, in the case of sudden increases in user requests, a node may run short of resources and need to implement a strategy that allows the node's service to degrade its service quality to a level that requires fewer resources so that the service can still be delivered. One such strategy is brownout, a control theory-based algorithm that dynamically controls the node's service quality in order to meet e.g., a latency goal. This thesis explores the use of brownout, previously used in combination with load balancing in the cloud, in conjunction with load balancing in an edge-cloud environment. In this thesis, four load-balancing strategies are evaluated in a Kubernetes-based edge-cloud environment, along with an application that implements the brownout feature. Two of the strategies are originally designed to be used with brownout but made for the regular cloud, one is a recently introduced strategy that performs well in the edge cloud but is brownout unaware, and the last is a random load balancer used as a baseline (also brownout unaware). The goal of the evaluation is to determine the efficiency of these strategies in different edge-cloud scenarios, with regard to service quality-weighted throughput, average latency, adherence to a set latency goal, and outsourcing (requests load balanced to another edge node). The results show that the first two strategies perform worse than the random load balancer in many regards. Their performance is also less predictable and tends to get worse with increasing network delays. The edge cloud strategy, however, shows an improvement in performance when the brownout is introduced in the majority of the test scenarios.  Furthermore, the thesis introduced three possible modifications to make one of the cloud-based strategies perform better in the edge cloud. These modifications were tested in the same environment as the other load-balancing strategies and compared against each other. The first modification consisted of making the load-balancing logic treat its own node differently from other edge nodes.  The second version was devised to only outsource when a certain resource threshold is exceeded and the last version was designed to prioritize its own node when below a certain resource threshold. The last version improved on the others and performed better than the base version in all measured metrics. Compared to the edge cloud strategy with brownout, it performed better with regard to service quality-weighted throughput but was outperformed in all other metrics.