Turbulence Avoidance Research Articles

Effectiveness of Automatic Safety Systems in Reducing General Aviation Fatalities

General aviation accounts for 95% of fatal aviation accidents in the United States. Many of these fatalities may be preventable with the inclusion of advanced advisory or automatic aircraft safety systems; however, past research has rarely focused on the effect such systems could have if applied to general aviation. This paper addresses this gap by starting with proposed safety systems and scoring their effectiveness using detailed accident data rather than the more common approaches of analyzing accident categories or polling subject matter experts. Using a data-driven logical model, this paper evaluates four systems (terrain impact prevention, upset prevention, turbulence avoidance, and emergency landing) for potential to reduce fatalities. The scoring process appears in some detail, which starts with system requirements and National Transportation Safety Board data as inputs and results in expected fatal accident reductions. The analysis estimates that implementing all four systems may result in a 66.5% reduction in general aviation fatalities, with terrain impact prevention alone resulting in a possible 30.7% reduction. These results motivate immediate effort toward implementation and certification of aircraft safety systems into general aviation, not only to save the lives of hundreds of pilots and passengers a year, but also to prime small aircraft transportation for future developments.

The Importance of Convective Stage on Out-of-Cloud Convectively Induced Turbulence from High-Resolution Simulations

AbstractTurbulence (clear-air, mountain wave, convectively induced) is an aviation hazard that is a challenge to forecast due to the coarse resolution ultilized in operational weather models. Turbulence indices are commonly used to aid pilots in avoiding turbulence, but these indices have been designed and calibrated for midlatitude clear-air turbulence prediction (e.g., the Ellrod index). A significant limitation with current convectively induced turbulence (CIT) prediction is the lack of storm stage dependency. In this study, six high-resolution simulations of tropical oceanic and midlatitude continental convection are performed to characterize the turbulent environment near various convective types during the developing and mature stages. Second-order structure functions, a diagnostic commonly used to identify turbulence in turbulence prediction systems, are used to characterize the probability of turbulence for various convective types. Turbulence likelihood was found to be independent of region (i.e., tropical vs midlatitude) but dependent on convective stage. The probability of turbulence increased near developing convection for the majority of cases. Additional analysis of static stability and vertical wind shear, indicators of turbulence potential, showed that the convective environment near developing convection was more favorable for turbulence production than mature convection. Near developing convection, static stability decreased and vertical wind shear increased. Vertical wind shear near mature and developing convection was found to be weakly correlated to turbulence intensity in both the tropics and the midlatitudes. This study emphasizes the need for turbulence avoidance guidelines for the aviation community that are dependent on convective stage.

Dynamic Flight Routing Using Internet of Things Framework

With increased demand of quicker travel, both for passengers and cargo, there has been major advancements in commercial airlines and number of flights have increased significantly over the last few years. Novel challenges have been introduced due to the rising number of flights in the areas of safety, route planning and maintenance. In addition, for commercial flights, the surge in the number of passengers have also exposed avenues for improving the quality of flight travel, from entering the airport premises to leaving the same at the destination. Although there are many areas of flight and airport operations that can benefit from leveraging technological advancements, choosing safe flight path and making dynamic modifications to it is the critical aspect that needs to be addressed. Comprehending available information to adhere to the provided route and also avoiding known areas of air turbulence, adds to the financial benefit of the commercial airline as well as the safety of the airplane and the passengers are ensured. In this paper, the various aspects of improving the flight routing by providing dynamic intelligent path options to ensure adherence to the provided flight path possible is studied; options for improving the flight safety and turbulence avoidance, which benefits both the passengers and the aircraft are also explored. In addition, keeping aircraft away from conflict zones or war zones, and also from areas of natural disaster, like erupting volcanic ash or forest fires is relevant. Although these issues have been studied before, most of the techniques depend heavily on infrastructure that is on the ground. The basic model requires constant communication with an air traffic control tower, that would provide updates and changes to the flight path as necessary. This leads to some of these methods being unusable on flights operating on oceanic routes and away from the communication zone of the devices placed on land masses. Therefore, in this paper an Internet of Things based framework is proposed to address and handle the above mentioned issues. The framework is structured on the communication model of information exchange among aircraft within the range, as well as taking advantage of ground infrastructure if there is a possible network link to the same. A number of algorithms are proposed for dynamic intelligent routing of flights as well as detection and avoidance of air turbulence. The implementations of the proposed algorithms show improvements ranging from 10% to 30% in the methods as compared to using the infrastructure based conventional techniques.

Changes in Vertical Distribution of Zooplankton under Wind-Induced Turbulence: A 36-Year Record

A multidecadal record of a local zooplankton community, stored in an open-access database, was analyzed with wind data to examine the impact of wind-induced turbulence on vertical distribution of zooplankton. Two major findings were made. First, the abundance of zooplankton assemblage (composed of copepods, cladocerans, etc.) in the upper layer (<10 m deep) decreased with increasing turbulence intensity, suggesting turbulence avoidance by zooplankton. Second, when focusing on each species, it was found that ambush (sit-and-wait) feeders showed statistically significant changes in response to turbulence, whereas suspension (filter) feeders did not. This is the first clear evidence that ambush feeders change vertical distribution in response to turbulence.

Refrigeration bound of heat-producing cylinders by superfluid helium

In this paper we go ahead in our studies on refrigeration of nanosystems by superfluid helium, as an appealing subject for future applications to computers or astronautical precision nanodevices. We first recall the effective thermal conductivity in laminar counterflow superfluid helium through arrays of mutually parallel cylinders and we discuss the conditions for the appearance of quantum turbulence around the heat-producing cylinders. We then consider the cooling of an array of heat-producing cylindrical nanosystems by means of superfluid-helium counterflow. We discuss the upper bound on heat removal set by avoidance of quantum turbulence and avoidance of phase transition to normal He I, for arrays of cylinders placed between two infinite insulating plates and with heat flowing in the two dimensions parallel to such plates.

Flight planning: node‐based trajectory prediction and turbulence avoidance

ABSTRACTTo tackle the ever‐growing demand for air travel, the aviation industry has expressed great interest in assessing the impact weather uncertainty has on flight planning. However, due to the opacity of commercial flight planning systems, there has been an absence of a suitable research platform which weather centres could use to test and convey advancements in numerical weather prediction (NWP) to benefit operational flight planning.In this paper, a simple yet versatile trajectory prediction system that aims to bridge the gap between NWP centres and the industry is proposed. The proposed system is based on A*, a node‐based pathfinding approach which is simple to implement and configured to suit any requirements. Unlike analytical solutions, research findings from the proposed system can be readily implemented in commercial flight planning systems. An example of how clear air turbulence could have been considered before take‐off and avoided is presented.

Prediction of Energy Dissipation Rates for Aviation Turbulence. Part II: Nowcasting Convective and Nonconvective Turbulence

AbstractIn addition to turbulence forecasts, which can be used for strategic planning for turbulence avoidance, short-term nowcasts can augment longer-term forecasts by providing much more timely and accurate turbulence locations for real-time tactical avoidance of turbulence hazards, especially those related to short-lived convection. This paper describes a turbulence-nowcasting algorithm that combines recent short-term turbulence forecasts with all currently available direct turbulence observations and inferences of turbulence from other sources. Building upon the need to provide forecasts that are aircraft independent, the nowcasts provide estimates of an atmospheric metric of turbulence, namely, the energy dissipation rate to the one-third power (EDR). Some observations directly provide EDR, such as in situ observations from select commercial aircraft and ground-based radar algorithm output, whereas others must be translated to EDR. A strategy is provided for mapping turbulence observations, such as pilot reports (PIREPs), and inferences from other relevant observational data sources, such as observed surface wind gusts, into EDR. These remapped observation values can then be combined with short-term turbulence forecasts and other convective diagnostics of turbulence to provide a turbulence nowcast of EDR in the national airspace. Case studies are provided to illustrate the algorithm procedure and benefits. The EDR nowcasts are compared with aircraft in situ EDR observations and PIREPs converted to EDR to obtain metrics of statistical performance. It is shown by one common performance metric, the area under the relative operating characteristic curve, that the turbulence nowcasts with assimilated observations considerably outperform the corresponding turbulence forecasts.

‘Sleeping beauties’: succession problems of adolescence

The author explores the succession problems of adolescence. She uses the Brothers Grimm’s fairy tale Sleeping Beauty to consider various characters and narratives possible in the analytic field during the succession process. Use of the characters in a fairy tale allows an analyst to play with the different roles the patient unconsciously assigns her. The author conceives of the avoidance of adolescent turbulence as a common reaction to adolescence, but one that can also become entrenched, and result in a restriction of emotional growth. The paper explores the psychic isolation of adolescence and the splitting required to manage the conflicting desires of the phase. The persistent absence of passion, including in the analytic process, constitutes a psychic retreat from developmental turbulence. The analyst of such an adolescent may need to allow them to be ‘somnolent’ for some time, but may eventually need to wake them (metaphorically) or even pierce the somnolent, avoidant state. The author uses clinical vignettes of late adolescents to demonstrate such transitions, exploring her countertransference experience as well as the reaction of adults to the succession process of adolescence.

Combined Winds and Turbulence Prediction System for Automated Air-Traffic Management Applications

AbstractA time-lagged ensemble of energy dissipation rate (EDR)-scale turbulence metrics is evaluated against in situ EDR observations from commercial aircraft over the contiguous United States and applied to air-traffic management (ATM) route planning. This method uses the Graphic Turbulence Guidance forecast methodology with three modifications. First, it uses the convection-permitting-scale (Δx = 3 km) Advanced Research version of the Weather Research and Forecasting Model (ARW) to capture cloud-resolving-scale weather phenomena. Second, turbulence metrics are computed for multiple ARW forecasts that are combined at the same forecast valid time, resulting in a time-lagged ensemble of multiple turbulence metrics. Third, probabilistic turbulence forecasts are provided on the basis of the ensemble results, which are applied to the ATM route planning. Results show that the ARW forecasts match well with observed weather patterns and the overall performance skill of the ensemble turbulence forecast when compared with the observed data is superior to any single turbulence metric. An example wind-optimal route (WOR) is computed using areas experiencing ≥10% probability of encountering severe-or-greater turbulence. Using these turbulence data, lateral turbulence avoidance routes starting from three different waypoints along the WOR from Los Angeles International Airport to John F. Kennedy International Airport are calculated. The examples illustrate the trade-off between flight time/fuel used and turbulence avoidance maneuvers.

Intensity of thunderstorm-generated turbulence revealed by large-eddy simulation

Thunderstorms are characterized by turbulent processes that constitute an important aviation hazard and cause vertical transport of atmospheric constituents. Turbulence occurs within cloud and in the surrounding clear air, but, despite its importance, the characteristics of thunderstorm-generated turbulence and its spatial distribution are poorly understood, especially outside of cloud. Here we use large-eddy simulation to characterize turbulence generated by a canonical thunderstorm. The simulation identifies regions of notable three-dimensional anisotropic turbulence more than 5 km above the storm, in a shallow layer above the storm's anvil, and a horizontally asymmetric pattern of weaker turbulence that extends more than 50 km horizontally away from the cloud. Our results provide the first continuous estimate of turbulence intensity in and around thunderstorms and represent a major step toward improved turbulence avoidance methods. The results have broader implications for understanding the fundamental aspects of how thunderstorms affect their environment through vertical exchange processes.

Path Generation Algorithm for Turbulence Avoidance Using Real-Time Optimization

This paper describes a novel algorithm for generating flight paths in real time that avoid turbulent regions detected by an onboard Doppler lidar. Adopting the distance traveled rather than the time as the independent variable in the state equations enables an exact expression to be obtained for the point-mass dynamics and reduces the number of constraints imposed by turbulence avoidance. Moreover, the algorithm estimates the global optimum by applying second-order cone programming relaxation to the original nonconvex problem. Based on this estimate, it then applies convex quadratic programming. This algorithm is well suited for real-time applications since it is guaranteed to converge in polynomial computation time and it is expected to generate practically useful paths. The high computational speed of the algorithm is demonstrated and the physical feasibilities of the calculated paths are analyzed by numerically simulating turbulence avoidance.

Recent Advances in the Understanding of Near-Cloud Turbulence

Anyone who has flown in a commercial aircraft is familiar with turbulence. Unexpected encounters with turbulence pose a safety risk to airline passengers and crew, can occasionally damage aircraft, and indirectly increase the cost of air travel. Deep convective clouds are one of the most important sources of turbulence. Cloud-induced turbulence can occur both within clouds and in the surrounding clear air. Turbulence associated with but outside of clouds is of particular concern because it is more difficult to discern using standard hazard identification technologies (e.g., satellite and radar) and thus is often the source of unexpected turbulence encounters. Although operational guidelines for avoiding near-cloud turbulence exist, they are in many ways inadequate because they were developed before the governing dynamical processes were understood. Recently, there have been significant advances in the understanding of the dynamics of near-cloud turbulence. Using examples, this article demonstrates how these advances have stemmed from improved turbulence observing and reporting systems, the establishment of archives of turbulence encounters, detailed case studies, and high-resolution numerical simulations. Some of the important phenomena that have recently been identified as contributing to near-cloud turbulence include atmospheric wave breaking, unstable upper-level thunderstorm outflows, shearing instabilities, and cirrus cloud bands. The consequences of these phenomena for developing new en route turbulence avoidance guidelines and forecasting methods are discussed, along with outstanding research questions.

実時間最適化による乱気流回避経路生成アルゴリズム

This paper describes a novel algorithm for solving flight trajectory optimization problems subject to avoidance constraints of turbulent regions detected by an airborne Doppler lidar. The algorithm adopts a second-order cone programming (SOCP) relaxation of an original non-convex problem so as to obtain the estimate of global optimum, and subsequently applies a convex quadratic programming (CQP) based on the estimate. Moreover, by adopting a travel distance as the independent variable of the dynamics, the linearization of nonlinear state equations and the reduction of the number of constraints are achieved. The algorithm is well-suited to real-time applications due to its guaranteed convergence in polynomial computational time, and is expected to provide practically useful trajectories. Through some numerical simulations of the turbulence avoidance, the fast computational speed of the algorithm as well as the reasonableness of the calculated trajectories is demonstrated.

Some Influences of Background Flow Conditions on the Generation of Turbulence due to Gravity Wave Breaking above Deep Convection

Abstract Deep moist convection generates turbulence in the clear air above and around developing clouds, penetrating convective updrafts and mature thunderstorms. This turbulence can be due to shearing instabilities caused by strong flow deformations near the cloud top, and also to breaking gravity waves generated by cloud–environment interactions. Turbulence above and around deep convection is an important safety issue for aviation, and improved understanding of the conditions that lead to out-of-cloud turbulence formation may result in better turbulence avoidance guidelines or forecasting capabilities. In this study, a series of high-resolution two- and three-dimensional model simulations of a severe thunderstorm are conducted to examine the sensitivity of above-cloud turbulence to a variety of background flow conditions—in particular, the above-cloud wind shear and static stability. Shortly after the initial convective overshoot, the above-cloud turbulence and mixing are caused by local instabilities in the vicinity of the cloud interfacial boundary. At later times, when the convection is more mature, gravity wave breaking farther aloft dominates the turbulence generation. This wave breaking is caused by critical-level interactions, where the height of the critical level is controlled by the above-cloud wind shear. The strength of the above-cloud wind shear has a strong influence on the occurrence and intensity of above-cloud turbulence, with intermediate shears generating more extensive regions of turbulence, and strong shear conditions producing the most intense turbulence. Also, more stable above-cloud environments are less prone to turbulence than less stable situations. Among other things, these results highlight deficiencies in current turbulence avoidance guidelines in use by the aviation industry.

Pointed Wings, Low Wingloading and Calm Air Reduce Migratory Flight Costs in Songbirds

Migratory bird, bat and insect species tend to have more pointed wings than non-migrants. Pointed wings and low wingloading, or body mass divided by wing area, are thought to reduce energy consumption during long-distance flight, but these hypotheses have never been directly tested. Furthermore, it is not clear how the atmospheric conditions migrants encounter while aloft affect their energy use; without such information, we cannot accurately predict migratory species' response(s) to climate change. Here, we measured the heart rates of 15 free-flying Swainson's Thrushes (Catharus ustulatus) during migratory flight. Heart rate, and therefore rate of energy expenditure, was positively associated with individual variation in wingtip roundedness and wingloading throughout the flights. During the cruise phase of the flights, heart rate was also positively associated with wind speed but not wind direction, and negatively but not significantly associated with large-scale atmospheric stability. High winds and low atmospheric stability are both indicative of the presence of turbulent eddies, suggesting that birds may be using more energy when atmospheric turbulence is high. We therefore suggest that pointed wingtips, low wingloading and avoidance of high winds and turbulence reduce flight costs for small birds during migration, and that climate change may have the strongest effects on migrants' in-flight energy use if it affects the frequency and/or severity of high winds and atmospheric instability.

Turbulence avoidance and the wind-driven transport of plankton in the surface Ekman layer

Observations of turbulence avoidance in zooplankton are compared to estimates of the wind-driven turbulence in the upper ocean. Plankton that avoid wind-driven turbulence by moving deeper are no longer transported by the wind-driven Ekman currents near the surface because they are no longer near the surface. Here, a threshold level of turbulence that triggers an avoidance response is estimated, and is used to infer the wind speed and water column stratification conditions that would lead to zooplankton leaving the Ekman layer. Turbulence avoidance is argued to lead to near-shore retention in wind-driven upwelling systems, and to a reduction of the delivery of zooplankton to Georges Bank from the deeper waters of the Gulf of Maine.

Turbulence avoidance: An alternate explanation of turbulence‐enhanced ingestion rates in the field

Field observations supporting the hypothesis that wind‐driven mixed‐layer turbulence enhances the prey ingestion by larval fish tend not to have the resolving power to distinguish an alternative hypothesis: that the fish larvae and their prey avoid the turbulence by swimming or sinking downward to the calmer waters, thereby enhancing their concentrations and increasing encounter rates of predator and prey. Here, evidence is supplied supporting the notion of the turbulence‐avoidance hypothesis, and some rough calculations are made to estimate the conditions under which it might apply, how large its effect might be, and the types of organisms that might benefit from it. It is suggested that the turbulence‐avoidance behavior could lead to significant increases in predator and prey concentrations below the mixed layer only hours after the onset of wind‐driven mixing. Larger larval and juvenile fish are expected to benefit the most from such a behavior because they are stronger swimmers and eat larger prey, which might also exhibit the turbulence‐avoidance behavior.

Harmful algal blooms: Their ecophysiology and general relevance to phytoplankton blooms in the sea

From 60 to 80 species of phytoplankton have been reported to be harmful; of these, 90% are flagellates, notably dinoflagellates. The effects of turbulence on harmful algal bloom (HAB) taxa, their photoadaptive strategies, growth rate, and nutrient uptake affinity (Ks) are considered. Flagellates, including HAB taxa, collectively have a lower nutrient uptake affinity than diatoms. Four major adaptations are suggested to have been evolved to offset the ecological disadvantages of their low nutrient affinity: nutrient retrieval migrations; mixotrophic tendencies; alle‐lelochemically enhanced interspecific competition; and allelopathic, antipredation defense mechanisms. Motility‐based behavioral features of flagellates contributing to their blooms include: phototaxis, vertical migration, pattern swimming, and aggregation, which facilitate nutrient retrieval, trace metal detoxification, antipredation, depth‐keeping, and turbulence avoidance. Neither a general physiological syndrome nor distinctive physiological profile distinguishes harmful flagellate species from nonharmful taxa. However, HAB flagellates exhibit significant ecophysiological differences when compared to diatoms, including greater biophysical vulnerability to turbulence, greater bloom dependence on water‐mass stratification, greater nutritional diversity involving mixotrophic tendencies, greater potential use of allelochemical mechanisms in interspecific competition and antipredation defenses, and unique behaviorial consequences of their motility. Flagellates use a “swim” strategy; diatoms a “sink” strategy.

Observations on the swimming and buoyancy ofCymbulia peroni(Gastropoda: Thecosomata) made from a submersible

The swimming and buoyancy of the gelatinous pteropod,Cymbulia peroni, was observed and recorded on videotape from a submersible in the western Mediterranean. When not swimmingCymbulia peronihangs neutrally buoyant, with its parapodia outstretched and motionless. Two modes of swimming were observed, slow swimming and rapid or ‘escape’ swimming. Slow swimming predominated, at speeds between 2 and 11 cm s−1. Most slow swimming was directed vertically up or down. Slow swimming is probably used for vertical migration and the avoidance of turbulence. Turbulence frequently occurs both at epipelagic and mesopelagic depths in the Mediterranean. Escape swimming was more rapid, and speeds up to 40 cm s−1were measured. Differences between slow and escape swimming appear to be quantitative rather than qualitative, in contrast to other cymbuliids.Cymbulia peroniis an active and vigorous swimmer, clearly capable of vertical migration, and probably attains speeds greater than the highest measured in this study. Its behaviour in the field differs dramatically from its behaviour in the laboratory.

Diving of the sea snake Pelamis platurus in the Gulf of Panam�

The horizontal movement patterns of eleven yellow-bellied sea snakes [Pelamis platurus (Linnaeus)] were determined incidentally to acoustic tracking studies of their diving behavior in the Gulf of Panama during 1983–1985. The average speed of the snakes was 1.9 km h-1 (range 0.3 to 7.1 km). Movement direction is influenced by phasic northsouth tidal currents and secondarily affected by combinations of factors that affect local current velocity. The velocity of diving snakes did not always agree with that observed for the surface current. Drift rate was not correlated with average or maximum dive depth, however, snakes that surfaced to breathe one or more times during a period had greater average drift rates than those that did not surface. The role of such factors as feeding, predator avoidance, thermoregulation, orientation, and the avoidance of surface turbulence are considered in a discussion of the adaptive significance of diving for P. platurus. Diving in this species may enable it to avoid surface disturbance, facilitate relative position changes within the surface drift, and contribute to various aspects of its feeding behavior.