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NASA NTRS1994

X-ray absorption toward the red quasar 3C 212

A Roentgen Satellite (ROSAT) X-ray spectrum of the z = 1.049 'red quasar' 3C 212 has a strong low-energy cutoff. The spectrum can be fitted with a power law (of energy index 1.4(+0.8, -0.6) with low-energy photoelectric absorption in excess of the Galactic value that, if at the redhsift of the quasar, would have a column density of (0.9(+0.8, -0.6)) x 10(exp 22) atoms/sq cm. Possible sites for the absorption are a nuclear torus, an intervening damped Lyman-alpha system, or intracluster material (e.g., a cooling flow) around the quasar. The implied absorbing column density is sufficient to redden a normal quasar spectrum to the observed steep optical slope. The observed continuum, if dereddened by this amount, can produce the observed emission line fluxes and ratios. The absence of the graphite lambda-2175 feature in 3C 212 however, requires dust different from the local Milky Way composition, or an intervening absorber with z less than 0.4. Alternative acceptable fits to the X-ray spectrum are (1) a blackbody with a temperature of 0.7 keV (in the quasar frame) modified only by Galactic absorption, and (2) an optically thin thermal plasma with excess absorption. Although a blackbody spectrum would be unprecedented, the model is consistent with all the available X-ray and optical data and cannot be ruled out. We discuss possible observations that can discriminate among the above models.

Elvis, Martin↗
NASA NTRS2003

Autonomous Aircraft Operations using RTCA Guidelines for Airborne Conflict Management

A human-in-the-loop experiment was performed at the NASA Langley Research Center to study the feasibility of DAG-TM autonomous aircraft operations in highly constrained airspace. The airspace was constrained by a pair of special-use airspace (SUA) regions on either side of the pilot's planned route. Traffic flow management (TFM) constraints were imposed as a required time of arrival and crossing altitude at an en route fix. Key guidelines from the RTCA Airborne Conflict Management (ACM) concept were applied to autonomous aircraft operations for this experiment. These concepts included the RTCA ACM definitions of distinct conflict detection and collision avoidance zones, and the use of a graded system of conflict alerts for the flight crew. Three studies were conducted in the course of the experiment. The first study investigated the effect of hazard proximity upon pilot ability to meet constraints and solve conflict situations. The second study investigated pilot use of the airborne tools when faced with an unexpected loss of separation (LOS). The third study explored pilot interactions in an over-constrained conflict situation, with and without priority rules dictating who should move first. Detailed results from these studies were presented at the 5th USA/Europe Air Traffic Management R&D Seminar (ATM2003). This overview paper focuses on the integration of the RTCA ACM concept into autonomous aircraft operations in highly constrained situations, and provides an overview of the results presented at the ATM2003 seminar. These results, together with previously reported studies, continue to support the feasibility of autonomous aircraft operations.

Krishnamurthy, Karthik↗
NASA NTRSDate not supplied

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗
NASA NTRS2017

Revisiting Nuclear Thermal Propulsion for Human Mars Exploration

Nuclear Thermal Propulsion (NTP) has long been considered as a viable in-space transportation alternative for delivering crew and cargo to the Martian system. While technology development work in nuclear propulsion has continued over the year, general interest in NTP propulsion applications has historically been tied directly to the ebb and flow of interest in sending humans to explore Mars. As far back as the 1960’s, plans for NTP-based human Mars exploration have been proposed and periodically revisited having most recently been considered as part of NASA Design Reference Architecture (DRA) 5.0. NASA has been investigating human Mars exploration strategies tied to its current Journey to Mars for the past few years however, NTP has only recently been added into the set of alternatives under consideration for in-space propulsion under the Mars Study Capability (MSC) team, formerly the Evolvable Mars Campaign (EMC) team. The original charter of the EMC was to find viable human Mars exploration approaches that relied heavily on technology investment work already underway, specifically related to the development of large Solar Electric Propulsion (SEP) systems. The EMC team baselined several departures from traditional Mars exploration ground rules to enable these types of architectures. These ground rule changes included lower energy conjunction class trajectories with corresponding longer flight times, aggregation of mission elements in cis-Lunar space rather than Low Earth Orbit (LEO) and, in some cases, the pre-deployment of Earth return propulsion systems to Mars. As the MSC team continues to refine the in-space transportation trades, an NTP-based architecture that takes advantage of some of these ground rule departures is being introduced.

Percy, Thomas K.↗
NASA NTRS2017

Airborne Trajectory Management (ABTM): A Blueprint for Greater Autonomy in Air Traffic Management

The aviation users of the National Airspace System (NAS) - the airlines, General Aviation (GA), the military and, most recently, operators of Unmanned Aircraft Systems (UAS) - are constrained in their operations by the design of the current paradigm for air traffic control (ATC). Some of these constraints include ATC preferred routes, departure fix restrictions and airspace ground delay programs. As a result, most flights cannot operate on their most efficient business trajectories and a great many flights are delayed even getting into the air, which imposes a significant challenge to maintaining efficient flight and network operations. Rather than accepting ever more sophisticated scheduling solutions to accommodate the existing constraints in the airspace, a series of increasingly capable airborne technologies, integrated with planned improvements in the ground system through the Federal Aviation Administration (FAA) Next Generation Air Traffic Management System (NextGen) programs, could produce much greater operational flexibility for flight path optimization by the aviation system users. These capabilities, described in research coming out of NASA's Aeronautics Research Mission Directorate, can maintain or improve operational safety while taking advantage of air and ground NextGen technologies in novel ways. The underlying premise is that the nation's physical airspace is still abundant and underused, and that the delays and inefficient flight operations resulting from artificial structure in airspace use and procedural constraints on those operations may not be necessary for safe and efficient flight. This article is not an indictment of today's NAS or the people who run it. Indeed, it is an exceptional achievement that Air Traffic Management (ATM) - the complex human/machine conglomeration of communications, navigation and surveillance equipment and the rules and procedures for controlling traffic in the airspace - has both the capacity and enables the degree of efficiency in air travel that it does. But it is also true that sixty years of the "radar religion" (i.e., reliance on radar-based command and control) has produced several generations of ATM system operators and researchers who believe that introducing automation within the existing functional structure of ATM is the only way to "modernize" the system. Even NextGen, which began as a proposal for "transformational" change in the way ATC is performed, has morphed over the last decade and a half to become just the inclusion of Global Positioning System (GPS) for navigation, Automatic Dependent Surveillance Broadcast (ADS-B) for surveillance, and Data Communications (Data Comm) for communications, while still operating in rigidly structured airspace with human controllers being responsible for separation and traffic flow management (TFM) within defined sectors of airspace, using the same horizontal separation standards that have been in use since raw primary radar was introduced in the 1950s. No system as massive as the current NAS ATM can be replaced with a better system while simultaneously meeting the transportation and other aviation needs of the nation. A new generation of more flexible operations must emerge and yet coexist in harmony with the current operation (i.e., share the same airspace without segregation), thereby enabling a long-term transformation to take place in the way increasing numbers of flights are handled. Market forces will be the ultimate driver of this transformation, and investment realities mandate that real benefits must accrue to the first operators to adopt these new capabilities. In fact, the kinds of missions envisioned in the emerging world of UAS operations, unachievable under conventional ATM, demand that this transformation take place. Airborne Trajectory Management (ABTM) is proposed as a series of transformational steps leading to vastly increased flexibility in flight operations and capacity in the airspace to accommodate many varied airspace uses while improving safety. As will be described, ABTM enables the gradual emergence of a new paradigm for user-based trajectory management in ATM that brings tangible benefits to equipped operators at every step while leveraging the air and ground investments of NextGen. There are five steps in this ABTM transformation.1 NASA has extensively studied the first and last of these steps, and a roadmap of increasing capabilities and benefits is proposed for bridging between these operational concepts.

Cotton, William B.↗
NASA NTRSDate not supplied

A Holistic DSMC Transport Database for Re-Entry and Ablation Modeling

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity solutions of environments containing combined continuum/rarified flow. The use of DSMC, a stochastic, particle-based method, is necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally very computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the used thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. While the transport models governing CFD and DSMC simulations are starkly different, they can effectively be linked via their use of reduced Chapman-Enskog collision integrals. In CFD, these integrals are typically stored as fitted polynomial expressions and used to directly compute gas transport properties via mixing rules or the full Chapman-Enskog formulation. In DSMC, they can be used to derive the collision parameters needed for the phenomenological collision cross-section models that govern particle interactions, via a Nelder-Mead optimization scheme. The goal of this work is to provide a unified DSMC transport database encompassing the vast majority of known gas species encountered during atmospheric entry, on Earth or any other Solar body. This goal is largely possible due to recently performed ab-initio quantum chemistry calculations. Combined with other high-fidelity literature sources, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 17000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute Variable Soft Sphere (VSS) collision model parameters for DSMC, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database will be able to be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below. Equilibrium mixture transport properties for a 19-species Titan atmospheric model [4] are computed using both fitted VSS parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches is less than 5% for the entire temperature range.

M R Gosma↗
NASA NTRS1992

Properties of Graphite Fiber Reinforced Copper Matrix Composites for Space Power Applications

The thermal and mechanical properties of pitch-based graphite fiber reinforced copper matrix (Gr/Cu) composites usable for space applications such as radiator fins were investigated. Thermal conductivity was measured as a function of fiber volume fraction and architecture. Results showed for unidirectional P-100 Gr/Cu composites, the longitudinal thermal conductivity was nearly independent of fiber volume fraction. Transverse thermal conductivities (perpendicular to the fibers) were strongly affected by the fiber volume fraction with higher volume fractions resulting in lower thermal conductivities. The effect of architecture on thermal conductivity followed the cosine squared law for simple architectures. Insufficient data are available currently to model more complex architectures, but adding fibers in the direction of the heat flow increases the thermal conductivity as low conductivity plies are supplemented by high conductivity plies. Thermal expansion tests were conducted on the Gr fibers and Gr/Cu composites. The results show a considerable thermal expansion mismatch between the fibers and the Cu matrix. The longitudinal thermal expansion showed a strong dependence on the architecture of the Gr/Cu composites. The composites also show a thermal expansion hysteresis. The hysteresis was eliminated by an engineered interface. Mechanical testing concentrated on the dynamic modulus and strength of the composites. The dynamic modulus of the Gr/Cu composites was 305 GPa up to 400 C, a value equivalent to Be. The strengths of the composites were less than expected, but this is attributed to the poor bond across the interface between the Gr fibers and Cu matrix. Testing of composites with an engineered interface is expected to yield strengths nearer the values predicted by the rule of mixtures.

Ellis, David L.↗
NASA NTRS2008

A Performance Assessment of an Airborne Separation Assistance System Using Realistic Complex Traffic Flows

This paper presents the results from a study that investigates the performance of a tactical Airborne Separation Assistance System (ASAS) in en route airspace, under varying demand levels, with realistic traffic flows. The ASAS concept studied here allows flight crews of equipped aircraft to perform separation from other air traffic autonomously. This study addresses the tactical aspects of an ASAS using aircraft state data (i.e. position and velocity) to detect and resolve projected conflicts. In addition, use of a conflict prevention system helps ASAS-equipped aircraft avoid maneuvers that may cause new conflicts. ASAS-capable aircraft are equipped with satellite-based navigation and Automatic Dependent Surveillance Broadcast (ADS-B) for transmission and receipt of aircraft state data. In addition to tactical conflict detection and resolution (CD&R), a complete, integrated ASAS is likely to incorporate a strategic CD&R component with a longer look-ahead time, using trajectory intent information. A system-wide traffic flow management (TFM) component, located at the FAA command center helps aircraft to avoid regions of excessive traffic density and complexity. A Traffic Alert and Collision Avoidance System (TCAS), as used today is the system of last resort. This integrated approach avoids sole reliance on the use of the tactical CD&R studied here, but the tactical component remains a critical element of the complete ASAS. The focus of this paper is to determine to what extent the proposed tactical component of ASAS alone can maintain aircraft separation at demand levels up to three times that of current traffic. The study also investigates the effect of mixing ASAS-equipped aircraft with unequipped aircraft (i.e. current day) that do not have the capability to self-separate. Position and velocity data for unequipped aircraft needs to be available to ASASequipped. Most likely, for this future concept, state data would be available from instrument flight rules (IFR) aircraft, equipped with at least ADS-B transmission capability. The objective is to reduce the number of losses of separation to a minimum and investigate the limits of tactical-only CD&R. Thus, the objective is not, expressly, to achieve zero losses of separation with tactical ASAS because this is one component of an integrated ASAS.

Smith, Jeremy C.↗
NASA NTRS1994

An introduction to generalized functions with some applications in aerodynamics and aeroacoustics

In this paper, we start with the definition of generalized functions as continuous linear functionals on the space of infinitely differentiable functions with compact support. The concept of generalization differentiation is introduced next. This is the most important concept in generalized function theory and the applications we present utilize mainly this concept. First, some of the results of classical analysis, such as Leibniz rule of differentiation under the integral sign and the divergence theorem, are derived using the generalized function theory. It is shown that the divergence theorem remains valid for discontinuous vector fields provided that the derivatives are all viewed as generalized derivatives. This implies that all conservation laws of fluid mechanics are valid as they stand for discontinuous fields with all derivatives treated as generalized deriatives. Once these derivatives are written as ordinary derivatives and jumps in the field parameters across discontinuities, the jump conditions can be easily found. For example, the unsteady shock jump conditions can be derived from mass and momentum conservation laws. By using a generalized function theory, this derivative becomes trivial. Other applications of the generalized function theory in aerodynamics discussed in this paper are derivation of general transport theorems for deriving governing equations of fluid mechanics, the interpretation of finite part of divergent integrals, derivation of Oswatiitsch integral equation of transonic flow, and analysis of velocity field discontinuities as sources of vorticity. Applications in aeroacoustics presented here include the derivation of the Kirchoff formula for moving surfaces,the noise from moving surfaces, and shock noise source strength based on the Ffowcs Williams-Hawkings equation.

Farassat, F.↗
NASA NTRS2005

An XML Representation for Crew Procedures

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other activities start and stop), but do not capture the flow of data, materials, resources or priorities. Existing workflow representation languages are also limited to representing sequences of discrete activities, and cannot encode procedures involving continuous flow of information or materials between activities.

Simpson, Richard C.↗
NASA NTRS2000

Rate Constant and RRKM Product Study for the Reaction Between CH3 and C2H3 at T = 298K

The total rate constant k1 has been determined at P = 1 Torr nominal pressure (He) and at T = 298 K for the vinyl-methyl cross-radical reaction CH3 + C2H3 yields products. The measurements were performed in a discharge flow system coupled with collision-free sampling to a mass spectrometer operated at low electron energies. Vinyl and methyl radicals were generated by the reactions of F with C2H4 and CH4, respectively. The kinetic studies were performed by monitoring the decay of C2H3 with methyl in excess, 6 < |CH3|(sub 0)/|C2H3|(sub 0) < 21. The overall rate coefficient was determined to be k1(298 K) = (1.02 +/- 0.53)x10(exp -10) cubic cm/molecule/s with the quoted uncertainty representing total errors. Numerical modeling was required to correct for secondary vinyl consumption by reactions such as C2H3 + H and C2H3 + C2H3. The present result for k1 at T = 298 K is compared to two previous studies at high pressure (100-300 Torr He) and to a very recent study at low pressure (0.9-3.7 Torr He). Comparison is also made with the rate constant for the similar reaction CH3 + C2H5 and with a value for k1 estimated by the geometric mean rule employing values for k(CH3 + CH3) and k(C2H3 + C2H3). Qualitative product studies at T = 298 K and 200 K indicated formation of C3H6, C2H2, and C2H5 as products of the combination-stabilization, disproportionation, and combination-decomposition channels, respectively, of the CH3 + C2H3 reaction. We also observed the secondary C4H8 product of the subsequent reaction of C3H5 with excess CH3; this observation provides convincing evidence for the combination-decomposition channel yielding C3H5 + H. RRKM calculations with helium as the deactivator support the present and very recent experimental observations that allylic C-H bond rupture is an important path in the combination reaction. The pressure and temperature dependencies of the branching fractions are also predicted.

Thorn, R. Peyton, Jr.↗
NASA NTRS2021

Constraining particle acceleration in Sgr A? with simultaneous GRAVITY, Spitzer, NuSTAR, and Chandra observations

We report the time-resolved spectral analysis of a bright near-infrared and moderate X-ray flare of Sgr A⋆. We obtained light curves in the M, K, and H bands in the mid- and near-infrared and in the 2 − 8 keV and 2 − 70 keV bands in the X-ray. The observed spectral slope in the near-infrared band is νLν ∝ ν0.5 ± 0.2; the spectral slope observed in the X-ray band is νLν ∝ ν−0.7 ± 0.5. Using a fast numerical implementation of a synchrotron sphere with a constant radius, magnetic field, and electron density (i.e., a one-zone model), we tested various synchrotron and synchrotron self-Compton scenarios. The observed near-infrared brightness and X-ray faintness, together with the observed spectral slopes, pose challenges for all models explored. We rule out a scenario in which the near-infrared emission is synchrotron emission and the X-ray emission is synchrotron self-Compton. Two realizations of the one-zone model can explain the observed flare and its temporal correlation: one-zone model in which the near-infrared and X-ray luminosity are produced by synchrotron self-Compton and a model in which the luminosity stems from a cooled synchrotron spectrum. Both models can describe the mean spectral energy distribution (SED) and temporal evolution similarly well. In order to describe the mean SED, both models require specific values of the maximum Lorentz factor γmax, which differ by roughly two orders of magnitude. The synchrotron self-Compton model suggests that electrons are accelerated to γmax ∼ 500, while cooled synchrotron model requires acceleration up to γmax ∼ 5 × 104. The synchrotron self-Compton scenario requires electron densities of 1010 cm−3 that are much larger than typical ambient densities in the accretion flow. Furthermore, it requires a variation of the particle density that is inconsistent with the average mass-flow rate inferred from polarization measurements and can therefore only be realized in an extraordinary accretion event. In contrast, assuming a source size of 1 RS, the cooled synchrotron scenario can be realized with densities and magnetic fields comparable with the ambient accretion flow. For both models, the temporal evolution is regulated through the maximum acceleration factor γmax, implying that sustained particle acceleration is required to explain at least a part of the temporal evolution of the flare.

R. Abuter↗
NASA NTRS2013

Analytic Theory of Titans Schumann Resonance: Constraints on Ionospheric Conductivity and Buried Water Ocean

This study presents an approximate model for the atypical Schumann resonance in Titan's atmosphere that accounts for the observations of electromagnetic waves and the measurements of atmospheric conductivity performed with the Huygens Atmospheric Structure and Permittivity, Wave and Altimetry (HASI-PWA) instrumentation during the descent of the Huygens Probe through Titan's atmosphere in January 2005. After many years of thorough analyses of the collected data, several arguments enable us to claim that the Extremely Low Frequency (ELF) wave observed at around 36 Hz displays all the characteristics of the second harmonic of a Schumann resonance. On Earth, this phenomenon is well known to be triggered by lightning activity. Given the lack of evidence of any thunderstorm activity on Titan, we proposed in early works a model based on an alternative powering mechanism involving the electric current sheets induced in Titan's ionosphere by the Saturn's magnetospheric plasma flow. The present study is a further step in improving the initial model and corroborating our preliminary assessments. We first develop an analytic theory of the guided modes that appear to be the most suitable for sustaining Schumann resonances in Titan's atmosphere. We then introduce the characteristics of the Huygens electric field measurements in the equations, in order to constrain the physical parameters of the resonating cavity. The latter is assumed to be made of different structures distributed between an upper boundary, presumably made of a succession of thin ionized layers of stratospheric aerosols spread up to 150 km and a lower quasi-perfect conductive surface hidden beneath the non-conductive ground. The inner reflecting boundary is proposed to be a buried water-ammonia ocean lying at a likely depth of 55-80 km below a dielectric icy crust. Such estimate is found to comply with models suggesting that the internal heat could be transferred upwards by thermal conduction of the crust, while convective processes cannot be ruled out.

TITAN↗
NASA NTRS2017

Reconfigurable Model Execution in the OpenMDAO Framework

NASA's OpenMDAO framework facilitates constructing complex models and computing their derivatives for multidisciplinary design optimization. Decomposing a model into components that follow a prescribed interface enables OpenMDAO to assemble multidisciplinary derivatives from the component derivatives using what amounts to the adjoint method, direct method, chain rule, global sensitivity equations, or any combination thereof, using the MAUD architecture. OpenMDAO also handles the distribution of processors among the disciplines by hierarchically grouping the components, and it automates the data transfer between components that are on different processors. These features have made OpenMDAO useful for applications in aircraft design, satellite design, wind turbine design, and aircraft engine design, among others. This paper presents new algorithms for OpenMDAO that enable reconfigurable model execution. This concept refers to dynamically changing, during execution, one or more of: the variable sizes, solution algorithm, parallel load balancing, or set of variables-i.e., adding and removing components, perhaps to switch to a higher-fidelity sub-model. Any component can reconfigure at any point, even when running in parallel with other components, and the reconfiguration algorithm presented here performs the synchronized updates to all other components that are affected. A reconfigurable software framework for multidisciplinary design optimization enables new adaptive solvers, adaptive parallelization, and new applications such as gradient-based optimization with overset flow solvers and adaptive mesh refinement. Benchmarking results demonstrate the time savings for reconfiguration compared to setting up the model again from scratch, which can be significant in large-scale problems. Additionally, the new reconfigurability feature is applied to a mission profile optimization problem for commercial aircraft where both the parametrization of the mission profile and the time discretization are adaptively refined, resulting in computational savings of roughly 10% and the elimination of oscillations in the optimized altitude profile.

Hwang, John T.↗
NASA NTRS2000

Prediction of Coronal Mass Ejections from Vector Magnetograms: Results from More Active Regions

In a previous pilot study of four predominantly bipolar active regions observed by the MSFC vector magnetograph in 1991-92, we found that two quantitative measures of the global nonpotentiality of an active region were promising predictors of whether the active region produced coronal mass ejections (CMES) during its rotation across the Sun. The two quantitative measures are 1) the length (L(sub ss)) of the segments along the active region's main neutral line on which the vector magnetic field is both strong and strongly sheared, and 2) the global net current (I(sub N) flowing up one side of the bipole and down the other. Two of the active regions had large measured global nonpotentiality (L(sub ss) approximately >10(exp 5) km and I(sub N) approximately >4x 10(exp 12) Amp) and produced three CMEs each. The other two active regions had much smaller measured global nonpotentiality and produced no CMES. We have now expanded our sample of active regions by a factor of 3 with active regions from 1991 to the present. We have calibrated the line-of-sight magnetic field by comparing it to the line-of-sight field measured by Kitt Peak and/or SOHO/MDI. We have resolved the 180 deg. ambiguity in the transverse field by using three different methods, and compared the resulting global net currents. We will compare the two measures of global nonpotentiality to each other and to the CME productivity of each active i-eolon in our expanded set. We will examine the extent to which these results from the expanded set confirm or modify the tentative rule for CME prediction that we found in our pilot study.

Falconer, D. A.↗
NASA NTRS1993

Soft x ray properties of the Geminga pulsar

The ROSAT soft x ray spectrum and pulse profile of the Geminga pulsar are analyzed and interpreted in terms of thermal emission from the surface of the neutron star. The x ray spectrum appears to consist of two blackbody components with T(sub 1) = (5.2 +/- 1.0) x 10 (exp 5) K and T(sub 2) approximately 3 x 10(exp 6) K, respectively. The inferred ratio of surface areas, A(sub 2)/A(sub 1), is approximately 3 x 10(exp -5). Both components are highly modulated at the pulsar rotation period, but the harder x ray pulse is narrower, and leads the main (soft) x ray pulse by about 105 deg of phase. The soft x ray component is interpreted as photospheric cooling of much of the neutron star's surface area, while the small, hot region could be part of the much smaller polar cap heated by energetic particles flowing inward from the magnetospheric accelerator which is responsible for the production of Geminga's gamma rays. Geminga's gamma ray emission is consistent with outer-magnetosphere accelerator models for highly inclined dipoles. These predict the beaming of energetic gamma rays close enough to the star to give copious e(+/-) production in the stellar magnetic field and a large circumstellar pair density from pair inflow toward the surface. These pairs may quench radio emission, and also reflect most of the hard polar cap x rays back to the stellar surface by cyclotron resonance scattering. They are then reemitted from that much larger area at the lower temperature T(sub 1). The single-peaked nature of the x ray pulse and its energy-dependent phase suggest an off-center dipole geometry for the surface magnetic field. Under the assumption that the soft x ray emission comes from the full surface of a neutron star of radius R = 10 km, a distance estimate of (150-400) pc is derived. This range is consistent with the fit interstellar column density of (1.5 +/- 0.5) x 10(exp 20) cm(exp -2). Distances less than 150 pc are probably ruled out both by the lower limit on the column density, and also by the requirement that the Rayleigh-Jeans extrapolation of the soft x ray spectrum not exceed the observed blue flux of the faint optical counterpart. This distance estimate implies that Geminga's efficiency for converting spindown power into gamma-rays is near unity, and that there may be significant beaming of the gamma rays as well. These results tend to bolster the prospect that most of the unidentified high-energy gamma ray sources in the Galactic plane are pulsars, some of which may be radio quiet.

Halpern, J. P.↗
NASA NTRS2002

Maximally Expressive Task Modeling

Planning and scheduling systems organize "tasks" into a timeline or schedule. The tasks are defined within the scheduling system in logical containers called models. The dictionary might define a model of this type as "a system of things and relations satisfying a set of rules that, when applied to the things and relations, produce certainty about the tasks that are being modeled." One challenging domain for a planning and scheduling system is the operation of on-board experiment activities for the Space Station. The equipment used in these experiments is some of the most complex hardware ever developed by mankind, the information sought by these experiments is at the cutting edge of scientific endeavor, and the procedures for executing the experiments are intricate and exacting. Scheduling is made more difficult by a scarcity of space station resources. The models to be fed into the scheduler must describe both the complexity of the experiments and procedures (to ensure a valid schedule) and the flexibilities of the procedures and the equipment (to effectively utilize available resources). Clearly, scheduling space station experiment operations calls for a "maximally expressive" modeling schema. Modeling even the simplest of activities cannot be automated; no sensor can be attached to a piece of equipment that can discern how to use that piece of equipment; no camera can quantify how to operate a piece of equipment. Modeling is a human enterprise-both an art and a science. The modeling schema should allow the models to flow from the keyboard of the user as easily as works of literature flowed from the pen of Shakespeare. The Ground Systems Department at the Marshall Space Flight Center has embarked on an effort to develop a new scheduling engine that is highlighted by a maximally expressive modeling schema. This schema, presented in this paper, is a synergy of technological advances and domain-specific innovations.

Japp, John↗
NASA NTRS1993

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Ortiz, C. J.↗