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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1994

Wavelets, period-doubling, and time-frequency localization with application to organization of convection over the tropical western Pacific

In this paper, preliminary results in using orthogonal and continuous wavelet transform (WT) to identify period doubling and time-frequency localization in both synthetic and real data are presented. First, the Haar WT is applied to synthetic time series derived from a simple nonlinear dynamical system- a first-order quadratic difference equation. Second, the complex Morlet WT is used to study the time-frequency localization of tropical convection based on a high-resolution Japanese Geostationary Meteorological Satellite infrared (IR) radiance dataset. The Haar WT of the synthetic time series indicates the presence and distinct separation of multiple frequencies in a period-doubling sequence. The period-doubling process generates a multiplicity of intermediate frequencies, which are manifested in the nonuniformity in time with respect to the phase of oscillations in the lower frequencies. Wavelet transform also enables the detection of extremely weak signals in high-order subharmonics resulting from the period-doubling bifurcations. These signals are either undetected or considered statistically insignificant by traditional Fourier analysis. The Morlet WT of the IR radiance dataset indicates the presence of multiple timescales, which are localized in both frequency and time. There are two regimes in the variation of IR radiance, corresponding to the wet and dry periods. Multiple timescales, ranging from semidiurnal, diurnal, synoptic, to intraseasonal with embedding structures, are active in the wet regime. In particular, synoptic variability is more prominent during the wet phase of an intensive intraseasonal cycle. These are not only consistent with, but also show more details than, previous findings by using other techniques. The phase-locking relationships among the oscillations with different time-scales suggest that both synoptic and intraseasonal variations may be mixed oscillations due to the interaction of self-excited oscillations in the tropical atmosphere and external forcings such as annual and diurnal solar radiation variations. Both examples show that WT is a powerful tool for analysis of phenomena involving multiscale interactions that exhibit localization in both frequency and time. A discussion on the caveats in the use of WT in geophysical data analysis is also presented.

Weng, Hengyi↗
NASA NTRS1999

Effects of Buoyancy in Hydrogen Jet Diffusion Flames

This project was carried out to understand the effects of heat release and buoyancy on the flame structure of diffusion flames. Experiments were conducted at atmospheric pressure in both normal gravity and microgravity conditions in the NASA LeRC 2.2 s drop tower. Experiments were also conducted in a variable pressure combustion facility in normal gravity to scale buoyancy and thus, to supplement the drop tower experiments. Pure H2 or H2 mixed with He was used as the jet fluid to avoid the complexities associated with soot formation. Fuel jet burning in quiescent air was visualized and quantified by the Rainbow Schlieren Deflectometry (RSD) to obtain scalar profiles (temperature, oxygen concentration) within the flame. Burner tube diameter (d) was varied from 0.3 to 1.19 mm producing jet exit Reynolds numbers ranging from 40 to 1900, and generating flames encompassing laminar and transitional (laminar to turbulent) flow structure. Some experiments were also complemented with the CFD analysis. In a previous paper, we have presented details of the RSD technique, comparison of computed and measured scalar distributions, and effects of buoyancy on laminar and transitional H2 gas-jet diffusion flames. Results obtained from the RSD technique, variable pressure combustion chamber, and theoretical models have been published. Subsequently, we have developed a new drop rig with improved optical and image acquisition. In this set up, the schlieren images are acquired in real time and stored digitally in RAM of an onboard computer. This paper deals with laminar diffusion flames of pure H2 in normal and microgravity.

Agrawal, A. K.↗
NASA NTRSDate not supplied

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗
NASA NTRS2005

Gesture Based Control and EMG Decomposition

This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

Wheeler, Kevin R.↗
NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

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.

traffic complexity↗
NASA NTRS2012

Development of Waypoint Planning Tool in Response to NASA Field Campaign Challenges

Airborne real time observations are a major component of NASA's Earth Science research and satellite ground validation studies. For mission scientists, planning a research aircraft mission within the context of meeting the science objectives is a complex task because it requires real time situational awareness of the weather conditions that affect the aircraft track. Multiple aircrafts are often involved in NASA field campaigns. The coordination of the aircrafts with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions often determines the success of the campaign. A flight planning tool is needed to provide situational awareness information to the mission scientists, and help them plan and modify the flight tracks. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool that enables scientists to develop their own flight plans (also known as waypoints) with point -and-click mouse capabilities on a digital map filled with real time raster and vector data. The development of this Waypoint Planning Tool demonstrates the significance of mission support in responding to the challenges presented during NASA field campaigns. Analysis during and after each campaign helped identify both issues and new requirements, and initiated the next wave of development. Currently the Waypoint Planning Tool has gone through three rounds of development and analysis processes. The development of this waypoint tool is directly affected by the technology advances on GIS/Mapping technologies. From the standalone Google Earth application and simple KML functionalities, to Google Earth Plugin and Java Web Start/Applet on web platform, and to the rising open source GIS tools with new JavaScript frameworks, the Waypoint Planning Tool has entered its third phase of technology advancement. The newly innovated, cross ]platform, modular designed JavaScript ]controlled Way Point Tool is planned to be integrated with NASA Airborne Science Mission Tool Suite. Adapting new technologies for the Waypoint Planning Tool ensures its success in helping scientists reach their mission objectives. This presentation will discuss the development processes of the Waypoint Planning Tool in responding to field campaign challenges, identify new information technologies, and describe the capabilities and features of the Waypoint Planning Tool with the real time aspect, interactive nature, and the resultant benefits to the airborne science community.

He, Matt↗
NASA NTRS2019

Improvements to the Copernicus Trajectory Design and Optimization System for Complex Space Trajectories

The purpose of this assessment was to develop updates and new features for the NASA Copernicus Spacecraft Trajectory Design and Optimization analysis tool (version 5.0) for application to NASA programs and projects. These updates will significantly improve the ability to design and optimize complex trajectories over multiple trajectory phases; will allow the use of unique vehicle-specific guidance, control, and trajectory strategies and constraints; and the creation of an almost unlimited number of unique user-defined capabilities. The primary stakeholders for this assessment are the trajectory design and optimization analysts and engineers, and the chief engineers and project managers for existing programs, projects, and/or tasks that involve impulsive, finite burn, and/or continuous thrust trajectories (e.g., Sun, planet, comet, asteroid, halo orbit, Lagrange point, and distant retrograde orbit). The breadth of application spans the preliminary engineering and mission design concepts and optimization, to the development of candidate reference missions and integrated mission design for vehicle system design and operation, to the design and development of flight trajectories and associated propulsive maneuvers for real-time operations.

Murri, Daniel G.↗
NASA NTRS2008

Verification and Planning Based on Coinductive Logic Programming

Coinduction is a powerful technique for reasoning about unfounded sets, unbounded structures, infinite automata, and interactive computations [6]. Where induction corresponds to least fixed point's semantics, coinduction corresponds to greatest fixed point semantics. Recently coinduction has been incorporated into logic programming and an elegant operational semantics developed for it [11, 12]. This operational semantics is the greatest fix point counterpart of SLD resolution (SLD resolution imparts operational semantics to least fix point based computations) and is termed co- SLD resolution. In co-SLD resolution, a predicate goal p( t) succeeds if it unifies with one of its ancestor calls. In addition, rational infinite terms are allowed as arguments of predicates. Infinite terms are represented as solutions to unification equations and the occurs check is omitted during the unification process. Coinductive Logic Programming (Co-LP) and Co-SLD resolution can be used to elegantly perform model checking and planning. A combined SLD and Co-SLD resolution based LP system forms the common basis for planning, scheduling, verification, model checking, and constraint solving [9, 4]. This is achieved by amalgamating SLD resolution, co-SLD resolution, and constraint logic programming [13] in a single logic programming system. Given that parallelism in logic programs can be implicitly exploited [8], complex, compute-intensive applications (planning, scheduling, model checking, etc.) can be executed in parallel on multi-core machines. Parallel execution can result in speed-ups as well as in larger instances of the problems being solved. In the remainder we elaborate on (i) how planning can be elegantly and efficiently performed under real-time constraints, (ii) how real-time systems can be elegantly and efficiently model- checked, as well as (iii) how hybrid systems can be verified in a combined system with both co-SLD and SLD resolution. Implementations of co-SLD resolution as well as preliminary implementations of the planning and verification applications have been developed [4]. Co-LP and Model Checking: The vast majority of properties that are to be verified can be classified into safety properties and liveness properties. It is well known within model checking that safety properties can be verified by reachability analysis, i.e, if a counter-example to the property exists, it can be finitely determined by enumerating all the reachable states of the Kripke structure.

Bansal, Ajay↗
NASA NTRS1993

Code Validation Study for Base Flows

New and old rocket launch concepts recommend the clustering of motors for improved lift capability. The flowfield of the base region of the rocket is very complex and can contain high temperature plume gases. These hot gases can cause catastrophic problems if not adequately designed for. To assess the base region characteristics, advanced computational fluid dynamics (CFD) is being used. As a precursor to these calculations the CFD code requires validation on base flows. The primary objective of this code validation study was to establish a high level of confidence in predicting base flows with the USA CFD code. USA has been extensively validated for fundamental flows and other applications. However, base heating flows have a number of unique characteristics so it was necessary to extend the existing validation for this class of problems. In preparation for the planned NLS 1.5 Stage base heating analysis, six case sets were studied to extend the USA code validation data base. This presentation gives a cursive review of three of these cases. The cases presented include a 2D axi-symmetric study, a 3D real nozzle study, and a 3D multi-species study. The results of all the studies show good general agreement with data with no adjustments to the base numerical algorithms or physical models in the code. The study proved the capability of the USA code for modeling base flows within the accuracy of available data.

Ascoli, Edward P.↗
NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗
NASA NTRS2006

The X-ray Emitting Components towards l = 111 deg: The Local Hot Bubble and Beyond

We have obtained an XMM-Newton spectrum of the diffuse X-ray emission towards (l, b) = (111.14,1.11), a line of sight with a relatively simple distribution of absorbing clouds; > 9 x 10(exp 19)/sq cm at R>170 pc, a 6 x 10(exp 21)/sq cm molecular cloud at 2.5-3.3 kpc, and a total column of 1.2 x 10(exp 22)/sq cm. We find that the analysis of the XMM-Newton spectrum in conjunction with the RASS spectral energy distribution for the same direction requires three thermal components to be well fit: a "standard" Local Hot Bubble component with kT = 0.089, a component beyond the molecular cloud with kT = 0.59, and a component before the molecular cloud with kT = 0.21. The strength of the O VII 0.56 keV line from the Local Hot Bubble, 2.1+/-0.7 photons/sq cm/s/sr, is consistent with other recent measures. The 0.21 keV component has an emission measure of 0.0022+/-0.0006 pc and is not localized save as diffuse emission within the Galactic plane; it is the best candidate for a pervasive hot medium. The spatial separation of the approx. 0.2 keV component from the approx. 0.6 keV component suggests that the spectral decompositions of the emission from late-type spiral disks found in the literature do represent real temperature components rather than reflecting more complex temperature distributions.

Kuntz, K. D.↗
NASA NTRS2014

Innate Immune Responses of Drosophila Melanogaster are Altered by Spaceflight

Alterations and impairment of immune responses in humans present a health risk for space exploration missions. The molecular mechanisms under pinning innate immune defense can be confounded by the complexity of the acquired immune system of humans. Drosophila (fruit fly) innate immunity is simpler, and shares many similarities with human innate immunity at the level of molecular and genetic pathways. The goals of this study were to elucidate fundamental immune processes in Drosophila affected by spaceflight and to measure host-pathogen responses post-flight. Five containers, each containing ten female and five male fruit flies, were housed and bred on the space shuttle (average orbit altitude of330.35 km) for 12 days and 18.5 hours. A new generation of flies was reared in microgravity. In larvae, the immune system was examined by analyzing plasmatocyte number and activity in culture. In adults, the induced immune responses were analyzed by bacterial clearance and quantitative real-time polymerase chain reaction (qPCR) of selected genes following infection with E. coli. The RNA levels of relevant immune pathway genes were determined in both larvae and adults by microarray analysis. The ability of larval plasmatocytes to phagocytose E. coli in culture was attenuated following spaceflight, and in parallel, the expression of genes involved in cell maturation was down regulated. In addition, the level of constitutive expression of pattern recognition receptors and opsonins that specifically recognize bacteria, and of lysozymes, antimicrobial peptide (AMP) pathway and immune stress genes, hallmarks of humoral immunity, were also reduced in larvae. In adults, the efficiency of bacterial clearance measured in vivo following a systemic infection with E. coli post-flight, remained robust. We show that spaceflight altered both cellular and humoral immune responses in Drosophila and that the disruption occurs at multiple interacting pathways.

Marcu, Oana↗
NASA NTRSDate not supplied

Zero-Trust Architecture for Autonomous Edge Computing

We are at the apex of an aviation revolution where autonomy will play a central role in enabling complex, multi-agent systems to communicate, interact, and collaborate on a myriad of applications spanning autonomous swarms to wild-fire management. Autonomy is not an absolute but rather a spectrum ranging from a system requiring significant human intervention to one requiring little to none [1]. For example, the extreme, in the case of an autonomous aircraft, is one that operates independently in the airspace interacting with all other elements (air traffic controllers, other pilots) as if it were a human pilot. Critical to this vision is an architecture that enables autonomous agents to interact with minimal latency. Edge computing is an emerging architecture where compute and storage is pushed to the ‘edge’ of the network in order to minimize the round-trip time from agent to resource thereby mitigating the latency associated with cloud-only based approaches. Additionally, services can generate massive amounts of data (e.g., video feeds), which may require analysis in near real-time. Moving this data to the cloud for further processing may not be feasible due to latency, bandwidth, and cost. Privacy, security, and reliability can also be improved by edge computing architectures. However, this geo-distributed and dynamic* architecture complicates the establishment of unambiguous network security boundaries and can lead to vulnerabilities including man in the middle attacks, replay attacks, physical security breaches of edge nodes, signal interception, etc. This motivates the need for zero-trust architectures [2–4] which de-emphasize the notion of static network perimeters and, as the name implies, do not instill any innate trust in any particular agent. It is required that all agents must be authorized and approved in every transaction. In this paper, we present a zero-trust architecture suitable for edge-computing applications that demand significant low-latency, security, privacy, and reliability.

zero trust↗
NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗
NASA NTRS2001

Understanding the Puzzling X-Ray Spectrum of the SO Galaxy NGC 4382; NGC 43819: Spectral Analysis of the Prototypical Early Merger and ASCA Observations of a Dynamically Young Elliptical: NGC 4125

We have analyzed the ASCA observations of NGC 4382, NGC 4038/9, NGC 4125 and produced papers for publication. NGC 4382 is one of the E and SO galaxies detected with the lowest X-ray to optical luminosity ratio. These galaxies have a peculiar X-ray (0.1-3 keV) spectrum, with a significant excess of counts in the lowest spectral channels (less than 1 keV) relative to the spectral count distributions of X-ray brihter E and SO galaxies. Analyzing the ROSAT PSPC observation of NGC 4382 it was unclear whether this soft excess was due to a real very soft component in a multi-component spectrum, or reflected an extremely low metal abundance in an isothermal hot gas. Our ASCA observations show that the low-abundance single-temperature model does not fit well to the X-ray spectrum, in agreement with our previous suggestions. A better explanation is a composite spectrum with a very soft component (0.3 keV) in addition to a harder (5 keV) component from X-ray binaries. In this model, the abundance cannot be constrained. More complex spectral models are also possible. The ASCA observations of The Antennae - (NGC4038/9) show that at least two spectral components are required to describe the emission-thermal emission from a plasma at 0.8 keV, and a component at higher energies. The hot gas contributes about half of the flux in the 0.5 to 6 keV band. If the column density to the higher energy component is greater than 2 x 10 (exp 21) per square centimeter, then the fitted abundance in the hot gas component is less than 0.2 solar. This low abundance is not expected for the hot interstellar medium in NGC4038/9 in which supernovae and star formation (expected to enrich and heat the gas) are ongoing. We do not detect any spatial variations in the spectrum. We relate these findings to data obtained by other satellites (Einstein, ROSAT) for this interacting galaxy pair. NGC4125's ASCA data was analyzed jointly with its Beppo-SAX observation. A hard component (kT /sim 4-10 keV) is observed together with a thermal component with line emission.

Fabbiano, Giuseppina↗
NASA NTRS1990

Improving stability and strength characteristics of framed structures with nonlinear behavior

In this paper an optimal design procedure is introduced to improve the overall performance of nonlinear framed structures. The design methodology presented here is a multiple-objective optimization procedure whose objective functions involve the buckling eigenvalues and eigenvectors of the structure. A constant volume with bounds on the design variables is used in conjunction with an optimality criterion approach. The method provides a general tool for solving complex design problems and generally leads to structures with better limit strength and stability. Many algorithms have been developed to improve the limit strength of structures. In most applications geometrically linear analysis is employed with the consequence that overall strength of the design is overestimated. Directly optimizing the limit load of the structure would require a full nonlinear analysis at each iteration which would be prohibitively expensive. The objective of this paper is to develop an algorithm that can improve the limit-load of geometrically nonlinear framed structures while avoiding the nonlinear analysis. One of the novelties of the new design methodology is its ability to efficiently model and design structures under multiple loading conditions. These loading conditions can be different factored loads or any kind of loads that can be applied to the structure simultaneously or independently. Attention is focused on optimal design of space framed structures. Three-dimensional design problems are more complicated to carry out, but they yield insight into real behavior of the structure and can help avoiding some of the problems that might appear in planar design procedure such as the need for out-of-plane buckling constraint. Although researchers in the field of structural engineering generally agree that optimum design of three-dimension building frames especially in the seismic regions would be beneficial, methods have been slow to emerge. Most of the research in this area has dealt with the optimization of truss and plane frame structures.

Pezeshk, Shahram↗
NASA NTRSDate not supplied

Evaluation of Planetary Boundary Layer Structure from NASA Global Modeling and Assimilation Office’s Next Retrospective Analysis Product MERRA-21C

The Planetary Boundary Layer (PBL) is a complex interface between Earth’s surface and the atmosphere with high spatiotemporal variability in its characteristics, and accurate simulation and observation of the PBL has proven to be a challenge. In this study, we evaluate PBL structures from NASA Global Modeling and Assimilation Office (GMAO)’s next retrospective analysis product: the Goddard Earth Observing System Retrospective Analysis of the early 21st Century (GEOS-R21C), with 25-km horizontal resolution. The GEOS-R21C incorporates a wide range of observing systems and various improvements over previous GMAO reanalysis. We compare the PBL thermodynamic structure as well as PBL Height (PBLH) from GEOS-R21C with various PBL observations. For PBLH, definitions are different depending on each observing system. PBLHs derived from radiosonde observations and Global Navigation Satellite System Radio Occultation (GNSS RO) are based on bulk Richardson number and refractivity gradient, respectively. The results of the evaluation of PBL structure from GMAO’s next retrospective analysis product will be presented. In addition, comparison between near-real-time (NRT) commercial and NASA commercial GNSS RO PBLH will also be discussed.

Eun-Gyeong Yang↗
NASA NTRS2010

Serious Games that Improve Performance

Serious games can help people function more effectively in complex settings, facilitate their role as team members, and provide insight into their team's mission. In such games, coordination and cooperation among team members are foundational to the mission's success and provide a preview of what individuals and the team as a whole could choose to do in a real scenario. Serious games often model events requiring life-or-death choices, such as civilian rescue during chemical warfare. How the players communicate and what actions they take can determine the number of lives lost or saved. However, merely playing a game is not enough to realize its most practical value, which is in learning what actions and communication methods are closest to what the mission requires. Teams often play serious games in isolation, so when the game is complete, an analytical stage is needed to extract the strategies used and examine each strategy's success relative to the others chosen. Recognizing the importance of this next stage, Noblis has been developing Game Analysis, software that parses individual game play into meaningful units and generates a strategic analysis. Trainers create a custom game-specific grammar that reflects the objects and range of actions allowable in a particular game, which Game Analysis then uses to parse the data and generate a practical analysis. Trainers have then enough information to represent strategies in tools, such as Gantt and heat map charts. First-responder trainees in North Carolina have already partnered Hot-Zone and Game Analysis with great success.

McGowan, Clement, III↗