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When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-in-trail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011.

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

The blade crossing event of a coaxial counter-rotating rotor is a potential source of noise and impulsive blade loads. Blade crossings occur many times during each rotor revolution. In previous research by the authors, this phenomenon was analyzed by simulating two airfoils passing each other at specified speeds and vertical separation distances, using the compressible Navier-Stokes solver OVERFLOW. The simulations explored mutual aerodynamic interactions associated with thickness, circulation, and compressibility effects. Results revealed the complex nature of the aerodynamic impulses generated by upper/lower airfoil interactions. In this paper, the coaxial rotor system is simulated using two trains of airfoils, vertically offset, and traveling in opposite directions. The simulation represents multiple blade crossings in a rotor revolution by specifying horizontal distances between each airfoil in the train based on the circumferential distance between blade tips.

Some selected segments of the ascent and the on-orbit data from the Space Shuttle flight, STS114, as well as some selected laboratory test article data have been analyzed using wavelets, power spectrum and autocorrelation function. Additionally, a simple approximate noise test was performed on these data segments to confirm the presence or absence of white noise behavior in the data. This study was initially directed at characterizing the on-orbit background against which a signature due to an impact during on-orbit operation could be identified. The laboratory data analyzed here mimic low velocity impact that the Orbiter may be subjected to during the very initial stages of ascent.

Linear regression is the primary data analysis method used in the development of air traffic delay models. When the data being studied does indeed have an underlying linear model, this approach would produce the best-fitting model as expected. However, it has been argued by ATM researchers [Wieland2005, Evans2004] that the underlying delay models are primarily non-linear. Furthermore, the delays being modeled often depend not only on the observable independent variables being studied but also on other variables not being considered. The traditional regression approach alone may not be best suited to study these type of problems. In this paper, we propose an alternate methodology based on partitioning the data using statistical and decision tree learning methods. We then show the utility of this model in a variety of different ATM modeling problems.

Renewable energy sources and their integration with other power sources to support remote communities is of interest for Mars applications as well as Earth communities. The NSF, NASA, and DOE have been jointly supporting development of a 100 kW cold weather wind turbine through grants and SBIR's independently managed by each agency but coordinated by NASA. The NSF grant is specific to address issues associated with the South Pole Application and a 3 kW direct drive unit is currently being tested there in support of the development of the 100 kW unit. An NREL contract is focused on development of the 100 kW direct drive generator. The NASA SBIR is focused on development of the 100 kW direct drive wind turbine.

PGBA, a plant growth facility developed for commercial space biotechnology research, successfully grew a total of 50 plants (6 species) during 10 days aboard the Space Shuttle Endeavor (STS-77), and has reflown aboard the Space Shuttle Columbia (STS-83 for 4 days and STS-94 for 16 days) with 55 plants and 10 species. The PGBA life support system provides atmospheric, thermal, and humidity control as well as lighting and nutrient supply in a 33 liter microgravity plant growth chamber. The atmosphere treatment system removes ethylene and other hydrocarbons, actively controls CO2 replenishment, and provides passive O2 control. Temperature and humidity are actively controlled.

This paper offers a concept for a regenerable, low-power system for purifying exhaust from a solid waste processor. The innovations in the concept include the use of a closed-loop regeneration cycle for the adsorber, which prevents contaminants from reaching the breathable air before they are destroyed, and the use of a humidity-swing desorption cycle, which uses less power than a thermal desorption cycle and requires no venting of air and water to space vacuum or planetary atmosphere. The process would also serve well as a trace contaminant control system for the air in the closed environment. A systems-level design is presented that shows how both the exhaust and air purification tasks could be performed by one processor. Data measured with a fixed-bed apparatus demonstrate the effects of the humidity swing on regeneration of the adsorbent.

The Plant Generic BioProcessing Apparatus (PGBA), a plant growth facility developed for commercial space biotechnology research, has flown successfully on 3 spaceflight missions for 4, 10 and 16 days. The environmental control systems of this plant growth chamber (28 liter/0.075 m2) provide atmospheric, thermal, and humidity control, as well as lighting and nutrient supply. Typical performance profiles of water transpiration and dehumidification, carbon dioxide absorption (photosynthesis) and respiration rates in the PGBA unit (on orbit and ground) are presented. Data were collected on single and mixed crops. Design options and considerations for the different sub-systems are compared with those of similar hardware.

The “low power-CO2 removal (LPCOR) system” is an advanced air revitalization system that is under development at NASA Ames Research Center. The LPCOR utilizes the fundamental design features of the ‘four bed molecular sieve’ (4BMS) CO2 removal technology of the International Space Station (ISS). LPCOR improves power efficiency by replacing the desiccant beds of the 4BMS with a membrane dryer and a state-of-the-art, structured adsorbent device that collectively require 25% of the thermal energy required by the 4BMS desiccant beds for regeneration. Compared to the 4BMS technology, it has the added functionality to deliver pure, compressed CO2 for oxygen recovery. The CO2 removal and recovery functions are performed in a two-stage adsorption compressor. CO2 is removed from the cabin air and partially compressed in the first stage. The second stage performs further compression and delivers the compressed CO2 to a reduction unit such as a Sabatier reactor for oxygen recovery.

A number of airlines have FOQA programs that analyze archived flight data. Although this analysis process is extremely useful for assessing airline concerns in the areas of aviation safety, operations, training, and maintenance, looking at flight data in isolation does not always provide the context necessary to support a comprehensive analysis. To improve the analysis process, the Aviation Data Integration Project (ADIP) has been developing techniques for integrating flight data with auxiliary sources of relevant aviation data. ADIP has developed an aviation data integration system (ADIS) comprised of a repository and associated integration middleware that provides rapid and secure access to various data sources, including weather data, airport operating condition (ATIS) reports, radar data, runway visual range data, and navigational charts.

Determining the fundamental role of gravity in vital biological systems in space is one of six science and research areas that provides the philosophical underpinning for why NASA exists. The study of cells, tissues, and microorganisms in a spaceflight environment holds the promise of answering multiple intriguing questions about how gravity affects living systems. To enable these studies, specimens must be maintained in an environment similar to that used in a laboratory. Cell culture studies under normal laboratory conditions involve maintaining a highly specialized environment with the necessary temperature, humidity control, nutrient, and gas exchange conditions. These same cell life support conditions must be provided by the International Space Station (ISS) Cell Culture Unit (CCU) in the unique environment of space. The CCU is a perfusion-based system that must function in microgravity, at unit gravity (1g) on earth, and from 0.1g up to 2g aboard the ISS centrifuge rotor.

Remote Tower Sensor Systems are proof-of-concept prototypes being developed by NASA/Ames Research Center (NASA/ARC) with collaboration with the FAA and NOAA. RTSS began with the deployment of an Airport Approach Zone Camera System that includes real-time weather observations at San Francisco International Airport. The goal of this research is to develop, deploy, and demonstrate remotely operated cameras and sensors at several major airport hubs and un-towered airports. RTSS can provide real-time weather observations of airport approach zone. RTSS will integrate and test airport sensor packages that will allow remote access to real-time airport conditions and aircraft status.

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of super-computers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance.

New variable environment Modified Energy Cascade (MEC) crop models were developed for all the Advanced Life Support (ALS) candidate crops and implemented in SIMULINK. The MEC models are based on the Volk, Bugbee, and Wheeler Energy Cascade (EC) model and are derived from more recent Top-Level Energy Cascade (TLEC) models. The MEC models were developed to simulate crop plant responses to day-to-day changes in photosynthetic photon flux, photoperiod, carbon dioxide level, temperature, and relative humidity. The original EC model allowed only changes in light energy and used a less accurate linear approximation. For constant nominal environmental conditions, the simulation outputs of the new MEC models are very similar to those of earlier EC models that use parameters produced by the TLEC models. There are a few differences. The new MEC models allow setting the time for seed emergence, have more realistic exponential canopy growth, and have corrected harvest dates for potato and tomato.

We examine the requirements for on-board aircraft sensor systems that would allow pilots to “see through” poor weather, especially fog, and land and rollout aircraft under conditions that currently cause flight cancellations and airport closures. Three visual aspects of landing and rollout are distinguished: guidance, hazard detection and hazard recognition. The visual features which support the tasks are discussed. Three broad categories of sensor technology are examined: passive millimeter wave (PMMW), imaging radar, and passive infrared (IR). PMMW and imaging radar exhibit good weather penetration, but poor spatial and temporal resolution. Imaging radar exhibits good weather penetration, but typically relies on a flat-earth assumption which can lead to interpretive errors. PMMW systems have a narrow field of view. IR has poorer weather penetration but good spatial resolution.

A three country effort (U.S., Russia, and Bulgaria) has upgraded the plant growth facilities on the Mir Space Station and used the new facility to grow wheat for 90 days. The Svet plant-growth facility was reactivated and used in an initial experiment as part of the Shuttle/Mir program, August to November, 1995. The Svet system, used first to grow cabbage and radish during a 1990 experiment, was augmented by the addition of a U.S. developed Gas Exchange Measurement System (GEMS) that measures a range of environmental parameters plus transpiration, photosynthesis, and possibly respiration. Environmental parameters include cabin, chamber, root-zones, and leaf temperatures. Light levels, relative humidity, oxygen, and atmospheric pressure are also measured. High-accuracy water-vapor and carbon-dioxide concentrations and differences are measured using specially developed IRGA systems.

NASA is exploring a research activity to identify the technologies that will enable an Extreme Short Take-Off and Landing (ESTOL) aircraft. ESTOL aircraft have the potential to offer a viable solution to airport congestion, delay, capacity, and community noise concerns. This can be achieved by efficiently operating in the underutilized or unused airport ground and airspace infrastructure, while operating simultaneously, but not interfering with, conventional air traffic takeoffs and landings. Concurrently, the Air Force is exploring ESTOL vehicle solutions in the same general performance class as the NASA ESTOL vehicle to meet a number of Advanced Air Mobility missions. The capability goals of both the military and civil vehicles suggests synergistic technology development benefits. This paper presents a summary of the activities being supported by the NASA ESTOL Vehicle Sector.

Propulsion system sizing for mechanical flap and externally blown flap aircraft is demonstrated. Included in this study is the effect of various levels of noise suppression on the aircraft final design characteristics. Both aircraft are sized to operate from a 3000 ft runway and perform the same mission. For each aircraft concept, propulsion system sizing is demonstrated for two different engine cycles-one having a fan pressure ratio of 1.5 and a bypass ratio of 9 and the other having a fan pressure ratio of 1.25 and a bypass ratio of 17.8. The results presented include the required thrust to weight ratio, wing loading, resulting gross weight and direct operating costs as functions of the engine noise level for each combination of engine cycle and aircraft concept.

We have developed top-level crop models for analysis of Advanced Life Support (ALS) systems that use plants to grow food. The crops modeled are candidates for ALS use: bean (dry), lettuce, peanut, potato (white), rice, soybean, sweet potato, tomato, and wheat. The crop models are modified versions of the energy cascade crop growth model originally developed for wheat by Volk, Bugbee, and Wheeler. The models now simulate the effects of temperature, carbon dioxide level, planting density, and relative humidity on canopy gas exchange, in addition to the effects of light level and photoperiod included in the original model. The energy cascade model has also been extended to predict the times of canopy closure, grain setting (senescence), and maturity (harvest) as functions of the environmental conditions.