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  • 1
    Electronic Resource
    Electronic Resource
    Effect of microcrystallite preparation conditions on the formation of colloid crystals of cellulose (1998)
    Springer
    Cellulose 5 (1998), S. 19-32 
    Details
    ISSN: 1572-882X
    Keywords: microcrystallite ; colloid-crystal ; ultrasound ; anisotropic phase ; hydrolysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Abstract Stable colloidal suspensions of cellulose microcrystallites may be prepared from filter paper by sulfuric acid hydrolysis. Above a critical concentration, the suspensions form a chiral nematic ordered phase, or ‘colloid crystal’. The preparation conditions govern the properties of the individual cellulose microcrystallites, and hence the liquid crystalline phase separation of the cellulose suspensions. The particle properties and the phase separation of the suspensions were strongly dependent on the hydrolysis temperature and time, and on the intensity of the ultrasonic irradiation used to disperse the particles. The particle size of the microcrystallites was characterized with transmission electron microscopy and photon correlation spectroscopy. The surface charge was determined by conductometric titration. It was possible to fractionate the microcrystallites by size using the partitioning between isotropic and liquid crystalline phases; the longer microcrystallites migrate to the liquid crystalline phase
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009260511939
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    Paper (German National Licenses)
    Fulltext
  • 2
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    Scenario Complexity for Unmanned Aircraft System Traffic (2019)
    In:  CASI
    Details
    Publication Date: 2019-07-31
    Description: This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN69705 , AIAA Aviation Forum 2019; Jun 17, 2019 - Jun 21, 2019; Dallas, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 3
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    Integrated Arrival and Departure Schedule Optimization Under Uncertainty (2014)
    In:  CASI
    Details
    Publication Date: 2019-07-12
    Description: In terminal airspace, integrating arrivals and departures with shared waypoints provides the potential of improving operational efficiency by allowing direct routes when possible. Incorporating stochastic evaluation as a post-analysis process of deterministic optimization, and imposing a safety buffer in deterministic optimization, are two ways to learn and alleviate the impact of uncertainty and to avoid unexpected outcomes. This work presents a third and direct way to take uncertainty into consideration during the optimization. The impact of uncertainty was incorporated into cost evaluations when searching for the optimal solutions. The controller intervention count was computed using a heuristic model and served as another stochastic cost besides total delay. Costs under uncertainty were evaluated using Monte Carlo simulations. The Pareto fronts that contain a set of solutions were identified and the trade-off between delays and controller intervention count was shown. Solutions that shared similar delays but had different intervention counts were investigated. The results showed that optimization under uncertainty could identify compromise solutions on Pareto fonts, which is better than deterministic optimization with extra safety buffers. It helps decision-makers reduce controller intervention while achieving low delays.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN14420 , AIAA Journal of Aircraft
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 4
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    Scenario Complexity for Unmanned Aircraft System Traffic (2019)
    In:  CASI
    Details
    Publication Date: 2019-07-24
    Description: This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time applications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN68546 , AIAA Aviation Forum 2019; Jun 17, 2019 - Jun 21, 2019; Dallas, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 5
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    A Stochastic Scheduler for Integrated Arrival, Departure and Surface Operations in Los Angeles (2015)
    In:  CASI
    Details
    Publication Date: 2019-07-24
    Description: In terminal airspace, integrating arrivals, departures, and surface operations with competing resources provides the potential of improving operational efficiency by removing barriers between different operations. This work develops a centralized stochastic scheduler for operations in a terminal area including airborne and surface operations using Non-dominated sorting genetic algorithm and Monte Carlo simulations. The scheduler handles completing resources between different flows, such as runway allocations, runway crossing, departure fixes, and other interaction way points between arrivals and departures. Meanwhile, the scheduler also takes time-varied uncertainties into account when optimizing schedules. The scheduler is run sequentially to identify the best and robust schedule for the next planning window. Resulting schedules decide the routes, speed or delays, and runway assignments with separation constraints at mergingdiverging waypoints in the air and crossing and separations on runways. The Los Angels terminal area was used as an example. The implementation of this stochastic scheduler for integrated arrival, departure and surface operations is completed. And several preliminary runs are finished for over 1,200 flights in LAX in a typical day. Sensitivity studies on various planning window sizes are presented, which shows that trade-off exits between planning window size and achievable minimum delay. Preliminary results on runway usage are also presented in this abstract. Because arrivals on the outer runways have to be followed by crossings on the inner runways, algorithmic runway allocation prefers inner runways for arrivals and outer runways for departures. More results will be presented in the final paper. And current terminal arrival and departure procedures based on first-come-first-serve procedure will also be set up and used as a baseline for comparison.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN19273 , 2015 AIAA Aviation Forum; Jun 22, 2015 - Jun 26, 2015; Dallas, TX; United States
    Format: application/pdf
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  • 6
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    Three Dimensional Sector Design with Optimal Number of Sectors (2009)
    In:  CASI
    Details
    Publication Date: 2019-08-13
    Description: The concept of dynamic sector design suggests a strategic approach to ease air traffic congestion, which is predicted to become a serious problem in the national airspace system by 2025. Considerable research has been conducted to address the sectorization problem. In previous work, an approach that combines the Voronoi diagrams, Genetic Algorithms (GA), and the iterative deepening algorithm was proposed. However, as originally formulated, the number of sectors used was predefined and only two-dimensional partitions were allowed, which constrained the method's ability to achieve good designs. The current work extends the earlier Voronoi-based method by treating the number of sectors as an additional decision variable, allowing 3D partitions, and developing more comprehensive costs.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN903 , NASA''s Technical Interchange Meeting and NextGen System Study NRA Workshop; Oct 13, 2009 - Oct 16, 2009; San Antonio, TX; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 7
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    Optimal Integration of Departures and Arrivals in Terminal Airspace (2013)
    In:  CASI
    Details
    Publication Date: 2019-07-12
    Description: Coordination of operations with spatially and temporally shared resources, such as route segments, fixes, and runways, improves the efficiency of terminal airspace management. Problems in this category are, in general, computationally difficult compared to conventional scheduling problems. This paper presents a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA). It was first applied to a test problem introduced in existing literature. An experiment with a test problem showed that new methods can solve the 20 aircraft problem in fast time with a 65% or 440 second delay reduction using shared departure fixes. In order to test its application in a more realistic and complicated problem, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial separation in current operations, which may introduce unnecessary delays. In this work, three types of separations - spatial, temporal, and hybrid separations - were formulated using the new algorithm. The hybrid separation combines both temporal and spatial separations. Results showed that although temporal separation achieved less delay than spatial separation with a small uncertainty buffer, spatial separation outperformed temporal separation when the uncertainty buffer was increased. Hybrid separation introduced much less delay than both spatial and temporal approaches. For a total of 15 interacting departures and arrivals, when compared to spatial separation, the delay reduction of hybrid separation varied between 11% or 3.1 minutes and 64% or 10.7 minutes corresponding to an uncertainty buffer from 0 to 60 seconds. Furthermore, as a comparison with the NSGA algorithm, a First-Come-First-Serve based heuristic method was implemented for the hybrid separation. Experiments showed that the results from the NSGA algorithm have 9% to 42% less delay than the heuristic method with varied uncertainty buffer sizes.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN5913
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 8
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    Optimal Integration of Departure and Arrivals in Terminal Airspace (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.
    Keywords: Air Transportation and Safety
    Type: AIAA Paper-2012-4977 , ARC-E-DAA-TN4677 , AIAA Guidance, Navigation, and Control Conference; Aug 13, 2012 - Aug 16, 2012; Minneapolis, MN; United States
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    NASA TECHNICAL REPORTS
  • 9
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    Route Optimization for Offloading Congested Meter Fixes (2016)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The Optimized Route Capability (ORC) concept proposed by the FAA facilitates traffic managers to identify and resolve arrival flight delays caused by bottlenecks formed at arrival meter fixes when there exists imbalance between arrival fixes and runways. ORC makes use of the prediction capability of existing automation tools, monitors the traffic delays based on these predictions, and searches the best reroutes upstream of the meter fixes based on the predictions and estimated arrival schedules when delays are over a predefined threshold. Initial implementation and evaluation of the ORC concept considered only reroutes available at the time arrival congestion was first predicted. This work extends previous work by introducing an additional dimension in reroute options such that ORC can find the best time to reroute and overcome the 'firstcome- first-reroute' phenomenon. To deal with the enlarged reroute solution space, a genetic algorithm was developed to solve this problem. Experiments were conducted using the same traffic scenario used in previous work, when an arrival rush was created for one of the four arrival meter fixes at George Bush Intercontinental Houston Airport. Results showed the new approach further improved delay savings. The suggested route changes from the new approach were on average 30 minutes later than those using other approaches, and fewer numbers of reroutes were required. Fewer numbers of reroutes reduce operational complexity and later reroutes help decision makers deal with uncertain situations.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN30240 , Digital Avionics Systems Conference (DASC); Sep 25, 2016 - Sep 29, 2016; Sacramento, CA; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 10
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    Initial Study of an Effective Fast-Time Simulation Platform for Unmanned Aircraft System Traffic Management (2017)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Small Unmanned Aerial Vehicles (sUAVs), typically 55 lbs and below, are envisioned to play a major role in surveilling critical assets, collecting important information, and delivering goods. Large scale small UAV operations are expected to happen in low altitude airspace in the near future. Many static and dynamic constraints exist in low altitude airspace because of manned aircraft or helicopter activities, various wind conditions, restricted airspace, terrain and man-made buildings, and conflict-avoidance among sUAVs. High sensitivity and high maneuverability are unique characteristics of sUAVs that bring challenges to effective system evaluations and mandate such a simulation platform different from existing simulations that were built for manned air traffic system and large unmanned fixed aircraft. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative focuses on enabling safe and efficient sUAV operations in the future. In order to help define requirements and policies for a safe and efficient UTM system to accommodate a large amount of sUAV operations, it is necessary to develop a fast-time simulation platform that can effectively evaluate requirements, policies, and concepts in a close-to-reality environment. This work analyzed the impacts of some key factors including aforementioned sUAV's characteristics and demonstrated the importance of these factors in a successful UTM fast-time simulation platform.
    Keywords: Air Transportation and Safety
    Type: ARC-E-DAA-TN42383 , AIAA Aviation 2017 Conference; Jun 05, 2017 - Jun 09, 2017; Denver, CO; United States
    Format: application/pdf
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    NASA TECHNICAL REPORTS
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