Results for “CAPACITY” — Page 43

NASA NTRS2011

A Validation Study of Merging and Spacing Techniques in a NAS-Wide Simulation

In November 2010, Intelligent Automation, Inc. (IAI) delivered an M&S software tool to that allows system level studies of the complex terminal airspace with the ACES simulation. The software was evaluated against current day arrivals in the Atlanta TRACON using Atlanta's Hartsfield-Jackson International Airport (KATL) arrival schedules. Results of this validation effort are presented describing data sets, traffic flow assumptions and techniques, and arrival rate comparisons between reported landings at Atlanta versus simulated arrivals using the same traffic sets in ACES equipped with M&S. Initial results showed the simulated system capacity to be significantly below arrival capacity seen at KATL. Data was gathered for Atlanta using commercial airport and flight tracking websites (like FlightAware.com), and analyzed to insure compatible techniques were used for result reporting and comparison. TFM operators for Atlanta were consulted for tuning final simulation parameters and for guidance in flow management techniques during high volume operations. Using these modified parameters and incorporating TFM guidance for efficiencies in flowing aircraft, arrival capacity for KATL was matched for the simulation. Following this validation effort, a sensitivity study was conducted to measure the impact of variations in system parameters on the Atlanta airport arrival capacity.

Glaab, Patricia C.↗

NASA NTRS2011

Combustor Computations for CO2-Neutral Aviation

Knowing the pure component C(sub p)(sup 0) or mixture C(sub p) (sup 0) as computed by a flexible code such as NIST-STRAPP or McBride-Gordon, one can, within reasonable accuracy, determine the thermophysical properties necessary to predict the combustion characteristics when there are no tabulated or computed data for those fluid mixtures 3or limited results for lower temperatures. (Note: C(sub p) (sup 0) is molar heat capacity at constant pressure.) The method can be used in the determination of synthetic and biological fuels and blends using the NIST code to compute the C(sub p) (sup 0) of the mixture. In this work, the values of the heat capacity were set at zero pressure, which provided the basis for integration to determine the required combustor properties from the injector to the combustor exit plane. The McBride-Gordon code was used to determine the heat capacity at zero pressure over a wide range of temperatures (room to 6,000 K). The selected fluids were Jet-A, 224TMP (octane), and C12. It was found that each heat capacity loci were form-similar. It was then determined that the results [near 400 to 3,000 K] could be represented to within acceptable engineering accuracy with the simplified equation C(sub p) (sup 0) = A/T + B, where A and B are fluid-dependent constants and T is temperature (K).

Hendricks, Robert C.↗

NASA NTRS2010

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O'Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Curreri, Peter A.↗

NASA NTRS2012

Fundamental Investigation of Si Anode in Li-Ion Cells

Silicon is a promising and attractive anode material to replace graphite for high capacity lithium ion cells since its theoretical capacity is approximately 10 times of graphite and it is an abundant element on earth. However, there are challenges associated with using silicon as Li-ion anode due to the significant first cycle irreversible capacity loss and subsequent rapid capacity fade during cycling. In this paper, cyclic voltammetry and electrochemical impedance spectroscopy are used to build a fundamental understanding of silicon anodes. The results show that it is difficult to form the SEI film on the surface of Si anode during the first cycle, the lithium ion insertion and de-insertion kinetics for Si are sluggish, and the cell internal resistance changes with the state of lithiation after electrochemical cycling. These results are compared with those for extensively studied graphite anodes. The understanding gained from this study will help to design better Si anodes.

Wu, James J.↗

NASA NTRS2012

Fundamental Investigation of Silicon Anode in Lithium-Ion Cells

Silicon is a promising and attractive anode material to replace graphite for high capacity lithium ion cells since its theoretical capacity is ~10 times of graphite and it is an abundant element on Earth. However, there are challenges associated with using silicon as Li-ion anode due to the significant first cycle irreversible capacity loss and subsequent rapid capacity fade during cycling. Understanding solid electrolyte interphase (SEI) formation along with the lithium ion insertion/de-insertion kinetics in silicon anodes will provide greater insight into overcoming these issues, thereby lead to better cycle performance. In this paper, cyclic voltammetry and electrochemical impedance spectroscopy are used to build a fundamental understanding of silicon anodes. The results show that it is difficult to form the SEI film on the surface of a Si anode during the first cycle; the lithium ion insertion and de-insertion kinetics for Si are sluggish, and the cell internal resistance changes with the state of lithiation after electrochemical cycling. These results are compared with those for extensively studied graphite anodes. The understanding gained from this study will help to design better Si anodes, and the combination of cyclic voltammetry with impedance spectroscopy provides a useful tool to evaluate the effectiveness of the design modifications on the Si anode performance.

Wu, James J.↗

NASA NTRS2012

Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

Sherry, Lance↗

NASA NTRS2012

Quantum Limits of Space-to-Ground Optical Communications

For a pure loss channel, the ultimate capacity can be achieved with classical coherent states (i.e., ideal laser light): (1) Capacity-achieving receiver (measurement) is yet to be determined. (2) Heterodyne detection approaches the ultimate capacity at high mean photon numbers. (3) Photon-counting approaches the ultimate capacity at low mean photon numbers. A number of current technology limits drive the achievable performance of free-space communication links. Approaching fundamental limits in the bandwidth-limited regime: (1) Heterodyne detection with high-order coherent-state modulation approaches ultimate limits. SOA improvements to laser phase noise, adaptive optics systems for atmospheric transmission would help. (2) High-order intensity modulation and photon-counting can approach heterodyne detection within approximately a factor of 2. This may have advantages over coherent detection in the presence of turbulence. Approaching fundamental limits in the photon-limited regime (1) Low-duty cycle binary coherent-state modulation (OOK, PPM) approaches ultimate limits. SOA improvements to laser extinction ratio, receiver dark noise, jitter, and blocking would help. (2) In some link geometries (near field links) number-state transmission could improve over coherent-state transmission

laser communications↗

NASA NTRS2013

Ion Exchange Technology Development in Support of the Urine Processor Assembly

The urine processor assembly (UPA) on the International Space Station (ISS) recovers water from urine via a vacuum distillation process. The distillation occurs in a rotating distillation assembly (DA) where the urine is heated and subjected to sub-ambient pressure. As water is removed, the original organics, salts, and minerals in the urine become more concentrated and result in urine brine. Eventually, water removal will concentrate the urine brine to super saturation of individual constituents, and precipitation occurs. Under typical UPA DA operating conditions, calcium sulfate or gypsum is the first chemical to precipitate in substantial quantity. During preflight testing with ground urine, the UPA achieved 85% water recovery without precipitation. However, on ISS, it is possible that crewmember urine can be significantly more concentrated relative to urine from ground donors. As a result, gypsum precipitated in the DA when operating at water recovery rates at or near 85%, causing the failure and subsequent re14 NASA Tech Briefs, September 2013 placement of the DA. Later investigations have demonstrated that an excess of calcium and sulfate will cause precipitation at water recovery rates greater than 70%. The source of the excess calcium is likely physiological in nature, via crewmembers' bone loss, while the excess sulfate is primarily due to the sulfuric acid component of the urine pretreatment. To prevent gypsum precipitation in the UPA, the Precipitation Prevention Project (PPP) team has focused on removing the calcium ion from pretreated urine, using ion exchange resins as calcium removal agents. The selectivity and effectiveness of ion exchange resins are determined by such factors as the mobility of the liquid phase through the polymer matrix, the density of functional groups, type of functional groups bound to the matrix, and the chemical characteristics of the liquid phase (pH, oxidation potential, and ionic strength). Previous experience with ion exchange resins has demonstrated that the most effective implementation for an ion exchange resin is a cartridge, or column, in which the resin is contained. Based on the results of equilibrium and sub-scale dynamic column testing, a possible solution for mitigating the calcium precipitation issue on the ISS has been identified. From an original pool of 13 ion exchange resins, two candidates have been identified that demonstrate substantial calcium removal on the sub-scale. The dramatic reduction in resin performance from published calcium uptake demonstrates the need for thorough evaluation of resins at the low pH and strong oxidizing environment present in the UPA. Chemical variations in the influent (calcium concentrations and pretreatment dosing) appear to have a noticeable impact on the calcium capacity of the resin. Low calcium concentrations and high pretreatment dosing will likely result in a decrease in calcium capacity. Conversely, low pre trea t - ment dosing will likely result in an increase in calcium capacity. In contrast, investigations at a variety of flow rates, length-to-diameter ratios, resin volumes, and flow regimes (continuous versus pulsed) show that changes in physical parameters do not have substantial impacts on resin performance in the very low specific velocity ranges of interest. This result is particularly useful because most commercial applications at higher specific velocities do show a relatively strong relationship between flow and capacity. The lack of a strong relationship will allow more flexibility in the implementation of an ion exchange bed for flight. Verification of subscale tests with flight-scale resin beds is recommended prior to implementation in the on-orbit UPA.

Mitchell, Julie↗

NASA NTRS2013

Data Mining for Understanding and Improving Decision-making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions.

Weather↗

NASA NTRS2013

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

data mining↗

NASA NTRS2015

Effects of Reduced Strength on Self-Selected Pacing for Long-Duration Activities

Strength and aerobic capacity are predictors of astronaut performance for extravehicular activities (EVA) during exploration missions. It is expected that astronauts will self‐select a pace below their ventilatory threshold (VT). PURPOSE: To determine the percentage of VT that subjects self‐select for prolonged occupational tasks. METHODS: Maximal aerobic capacity and a variety of lower‐body strength and power variables were assessed in 17 subjects who climbed 480 rungs on a ladder ergometer and then completed 10 km on a treadmill as quickly as possible using a self‐selected pace. The tasks were performed on 4 days, with a weighted suit providing 0% (suit fabric only), 40%, 60%, and 80% of additional bodyweight (BW), thereby altering the strength to BW ratio. Oxygen consumption and heart rate were continuously measured. Repeated measures ANOVA and post‐hoc comparisons were performed on the percent of VT values under each suited condition. RESULTS: Subjects consistently self‐paced at or below VT for both tasks and the pace was related to suit weight. At the midpoint for the ladder climb the 80% BW condition elicited the lowest metabolic cost (‐19+/-14% below VT), significantly different than the 0% BW (‐3+/-16%, P=0.002) and the 40% BW conditions (‐5+/-22%, P=0.023). The 60% BW condition (‐13+/-19%) was different than the 40% BW condition (P=0.034). Upon completion of the ladder task there were no differences among the conditions (0%BW: 3+/-18%; 40%BW: 3+/-21%; 60%BW: ‐ 8+/-25%; 80%BW: ‐10+/-18%). All subjects failed to complete 5km at 80%BW. At the midpoint of the treadmill test the three remaining conditions were all significantly different (0%BW: ‐20+/-15%; 40%BW: ‐ 33+/-15%; 60%BW: ‐41+/-19%). Upon completion of the treadmill test the 60% BW condition (‐38+/-12%) was significantly different than the 40% BW (‐28+/-15%, P=0.024). CONCLUSIONS: Decreasing relative strength results in progressive and disproportionate decreases (relative to VT) in self‐selected pacing during long‐duration activities. Thus, during prolonged, endurance‐type activities, large reductions in strength cause notable performance decrements despite no changes in aerobic capacity. These data highlight the importance of both aerobic capacity and muscle strength to the performance of prolonged EVA in exploration mission scenarios.

Buxton, Roxanne E.↗

NASA NTRS2008

Delay-Throughput Performance of the Deep-Space Ka-band Link

In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.

Shambayati, Shervin↗

NASA NTRS2008

Delay-Throughput Performance the Deep-Space Ka-Band Link

In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.

Shambayati, Shervin↗

NASA NTRS2016

Measuring Polanyi Potentials for Chemsorb 1000 and Chemsorb 3800

Polanyi adsorption potential plots are used to predict the adsorptive capacities of volatile organic compounds onto activated carbons. The design and construction of a test rig for measuring equilibrium adsorption capacities suitable for constructing Polanyi adsorption potential plots for candidate sorbents suitable for use in ECLS systems is presented. The adsorptive capacities of Chemsorb(TradeMark) 1000 and Chemsorb(TradeMark) 800 for ethanol and acetone were measured. The capacities and Polanyi adsorption potential plots for these commercially-available sorbents were compared to that of Barnebey Sutcliffe Type 3032, an acid-impregnated activated carbon utilized aboard the International Space Station.

Chemsorb 3800↗

NASA NTRS2018

Impact of Different Trajectory Option Set Participation Levels within an Air Traffic Management Collaborative Trajectory Option Program

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport. Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations with higher TOS participation levels helped utilize the overall National Airspace System (NAS) resources as well as benefited the users who participated.

Yoo, Hyo-Sang↗

NASA NTRSDate not supplied

A Multiphysics Study to Improve Specific Energy of Primary Batteries for Low Temperature Operation for Deep Space Missions

Several lander missions on the outer planets such as Europa, Enceladus, and Titan require electrical power to operate scientific and communication equipment. The traditional power generation methods, such as a photovoltaic array, are not feasible as their efficiency drops significantly at these vast distances. The novel radioisotope power systems are not practical today based on current lander designs and the effectiveness of these systems. To perform in situ science on distant planets, a high specific energy battery (>700 Wh/kg) needs to operate for about 480 hours under cold temperatures (-40C or 0C) [1]. While a primary battery such as Li-CFx can provide high specific energy at room temperature, its specific capacity decreases significantly at low temperatures. One of the causes for this drop is low ion and electrical conductivity, and slower reaction kinetics. Slower transport and facile kinetics lead to an increase in the battery’s resistance and higher voltage drops during the cell operation, thus reducing specific capacity. Both the transport and kinetics show a strong dependence on temperature. Thus, a small temperature rise can lead to an increase in the reaction rate and ion conductivity; since the temperature, cell resistance, and specific capacity are interdependent. A conventional battery model accounts for ohmic, thermodynamic, and, electrochemical, and chemical decomposition heating. The ohmic heating can be controlled by designing a resistive microstructure and varying the ratios of the active materials [2]. The kinetics can be improved by increasing the surface area, reducing the particle size, or adding a catalyst. These parameters are often optimized to achieve high specific energy at room temperatures. A similar optimization study is not available at low temperatures and for a primary (high specific energy) battery. For this presentation, we will explore the effect of geometrical, microstructural, and material properties on optimal specific capacity at low temperatures through multiphysics simulations. The ion transport resistance depends on the porosity and the tortuosity of an electrode and the separator.

M. Mehta↗

NASA NTRS2020

Integrated Demand Management: The FCA Balancing Algorithm

The Collaborative Trajectory Options Program (CTOP) is a new NextGen function that resides within the FAA’s Traffic Flow Management System (TFMS) software. CTOP was designed to be used in the United States’ national airspace to control the distribution of air traffic demand, both temporally and geographically, through a set of Flow Constrained Areas (FCAs). Each FCA is assigned capacity values that represent an estimated upper limit of manageable demand, and CTOP controls to that capacity by using Expect Departure Clearance Time (EDCT) air traffic control clearances, and/or rerouting flights to an alternate FCA or out of the CTOP completely. CTOP’s decisions about which control options best meet system and user needs are based on the Trajectory Options Set (TOS) submitted by airline operators for each flight. The FCA Balancing Algorithm (FBA) described in this document is a proposed decision support capability that generates CTOP capacity entries for FCAs controlling traffic to a common downstream constraint. The FBA provides an equitable distribution of impact, and addresses the added complexity of assigning FCA capacity values for this specific type of use case, greatly simplifying the FAA air traffic manager’s task.

IDM↗

NASA NTRSDate not supplied

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

In this work, we propose a hybrid model for Li-ion battery discharge and aging prediction that leverages fleet-wide data to predict future capacity drops.The model is built upon an hybrid approach merging physics-based and empirical equations, as well as neural network models in a recurrent neural network cell. The hybrid physics-informed neural network can predict voltage discharge cycles given the loading profile, and estimate the used capacity of the battery under random-loading conditions by tracking aging parameters connected to the residual capacity of the battery. By merging information on the battery aging parameters with existing fleet-wide aging data, the model can predict the future residual capacity of the battery that is being monitored, and therefore enable predictions of voltage discharge curves far ahead in the battery life cycle. We validated the approach using the NASA Prognostics Data Repository Battery data-set, which contains experimental data on Li-ion batteries discharged at random loading conditions in a controlled environment. The approach also allows the identification of discrepancies between the battery aging trend and the trend observed at the fleet level, so that batteries behaving differently from the rest of the fleet can be subject to closer monitoring and further testing to refine predictions.

PINN↗