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Locating Anomalies in Complex Data Sets Using Visualization and Simulation

The research goals are to create a simulation framework that can accept any combination of models written at the gate or behavioral level. The framework provides the ability to fault simulate and create scenarios of experiments using concurrent simulation. In order to meet these goals we have had to fulfill the following requirements. The ability to accept models written in VHDL, Verilog or the C languages. The ability to propagate faults through any model type. The ability to create experiment scenarios efficiently without generating every possible combination of variables. The ability to accept adversity of fault models beyond the single stuck-at model. Major development has been done to develop a parser that can accept models written in various languages. This work has generated considerable attention from other universities and industry for its flexibility and usefulness. The parser uses LEXX and YACC to parse Verilog and C. We have also utilized our industrial partnership with Alternative System's Inc. to import vhdl into our simulator. For multilevel simulation, we needed to modify the simulator architecture to accept models that contained multiple outputs. This enabled us to accept behavioral components. The next major accomplishment was the addition of "functional fault models". Functional fault models change the behavior of a gate or model. For example, a bridging fault can make an OR gate behave like an AND gate. This has applications beyond fault simulation. This modeling flexibility will make the simulator more useful for doing verification and model comparison. For instance, two or more versions of an ALU can be comparatively simulated in a single execution. The results will show where and how the models differed so that the performance and correctness of the models may be evaluated. A considerable amount of time has been dedicated to validating the simulator performance on larger models provided by industry and other universities.

Panetta, Karen↗

System monitoring and diagnosis with qualitative models

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Kuipers, Benjamin↗

A Model for Particle Microphysics, Turbulent Mixing, and Radiative Transfer in the Stratocumulus-Topped Marine Boundary Layer and Comparisons with Measurements

A detailed 1D model of the stratocumulus-topped marine boundary layer is described. The model has three coupled components: a microphysics module that resolves the size distributions of aerosols and cloud droplets, a turbulence module that treats vertical mixing between layers, and a multiple wavelength radiative transfer module that calculates radiative heating rates and cloud optical properties. The results of a 12-h model simulation reproduce reasonably well the bulk thermodynamics, microphysical properties, and radiative fluxes measured in an approx. 500-m thick, summertime marine stratocumulus cloud layer by Nicholls. However, in this case, the model predictions of turbulent fluxes between the cloud and subcloud layers exceed the measurements. Results of model simulations are also compared to measurements of a marine stratus layer made under gale conditions and with measurements of a high, thin marine stratocumulus layer. The variations in cloud properties are generally reproduced by the model, although it underpredicts the entrainment of overlying air at cloud top under gale conditions. Sensitivities of the model results are explored. The vertical profile of cloud droplet concentration is sensitive to the lower size cutoff of the droplet size distribution due to the presence of unactivated haze particles in the lower region of the modeled cloud. Increases in total droplet concentrations do not always produce less drizzle and more cloud water in the model. The radius of the mean droplet volume does not correlate consistently with drizzle, but the effective droplet radius does. The greatest impacts on cloud properties predicted by the model are produced by halving the width of the size distribution of input condensation nuclei and by omitting the effect of cloud-top radiative cooling on the condensational growth of cloud droplets. The omission of infrared scattering produces noticeable changes in cloud properties. The collection efficiencies for droplets less than 30-micrometers radius, and the value of the accommodation coefficient for condensational droplet growth, have noticeable effects on cloud properties. The divergence of the horizontal wind also has a significant effect on a 12-h model simulation of cloud structure. Conclusions drawn from the model are tentative because of the limitations of the 1D model framework. A principal simplification is that the model assumes horizontal homogeneity, and, therefore, does not resolve updrafts and downdrafts. Likely consequences of this simplification include overprediction of the growth of droplets by condensation in the upper region of the cloud, underprediction of droplet condensational growth in the lower region of the cloud, and underprediction of peak supersaturations.

Ackerman, Andrew S.↗

A Model for Particle Microphysics,Turbulent Mixing, and Radiative Transfer in the Stratocumulus-Topped Marine Boundary Layer and Comparisons with Measurements

A detailed 1D model of the stratocumulus-topped marine boundary layer is described. The model has three coupled components: a microphysics module that resolves the size distributions of aerosols and cloud droplets, a turbulence module that treats vertical mixing between layers, and a multiple wavelength radiative transfer module that calculates radiative heating rates and cloud optical properties. The results of a 12-h model simulation reproduce reasonably well the bulk thermodynamics, microphysical properties, and radiative fluxes measured in an approx. 500-m thick, summertime marine stratocumulus cloud layer by Nicholls. However, in this case, the model predictions of turbulent fluxes between the cloud and subcloud layers exceed the measurements. Results of model simulations are also compared to measurements of a marine stratus layer made under gate conditions and with measurements of a high, thin marine stratocumulus layer. The variations in cloud properties are generally reproduced by the model, although it underpredicts the entrainment of overlying air at cloud top under gale conditions. Sensitivities of the model results are explored. The vertical profile of cloud droplet concentration is sensitive to the lower size cutoff of the droplet size distribution due to the presence of unactivated haze particles in the lower region of the modeled cloud. Increases in total droplet concentrations do not always produce less drizzle and more cloud water in the model. The radius of the mean droplet volume does not correlate consistently with drizzle, but the effective droplet radius does. The greatest impacts on cloud properties predicted by the model are produced by halving the width of the size distribution of input condensation nuclei and by omitting the effect of cloud-top radiative cooling on the condensational growth of cloud droplets. The omission of infrared scattering produces noticeable changes in cloud properties. The collection efficiencies for droplets less than 30-micron radius, and the value of the accommodation coefficient for condensational droplet growth, have noticeable effects on cloud properties. The divergence of the horizontal wind also has a significant effect on a 12-h model simulation of cloud structure. Conclusions drawn from the model are tentative because of the limitations of the 1D model framework. A principal simplification is that the model assumes horizontal homogeneity, and, therefore, does not resolve updrafts and downdrafts. Likely consequences of this simplification include overprediction of the growth of droplets by condensation in the upper region of the cloud, underprediction of droplet condensational growth in the lower region of the cloud, and under-prediction of peak supersaturations.

Ackerman, Andrew S.↗

Navigating Team Dynamics: Automated Detection of Micro-Behaviors Between Team Members Through Longitudinal Interaction Data

The success in future long term space exploration missions will depend on the cooperation, coordination, and mutual understanding among the crew members. Micro-behaviors are momentary, subtle linguistic and paralinguistic indicators of thinking and feeling toward another member of the team (Cortina et al., 2001; Smith & Griffiths, 2022) that can significantly impact team dynamics and influence the overall team performance (Paromita & Chaspari, 2024). Due to their interactive nature, micro-behaviors have a sender (i.e., the team member expressing the micro-behavior) and a target (the team member impacted by the micro-behavior). Detection of these behaviors can assist in avoiding possible conflict among crew members and promoting the overall team success. Our prior research focused on an initial proof of concept of machine learning (ML) models and natural language processing (NLP) techniques that were used for automatically detect micro-behaviors among crew members of the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA) Campaigns 4 and 5 missions (Paromita et al., 2023). Results underscored the importance of incorporating contextual information in the ML models in the form of sentiment analysis, type of task, and dyadic interaction among team members. Here, we expand the scope of our prior work in two ways. First, we assess ML/NLP methods on new behavioral annotations coded using an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). Second, we expand the design of the ML model to preserve information about the role of each team member within the occurrence of the micro-behavior (in contrast to the previous model that only considered the sender and the target without determining the team member role). This allows to consider all team members' contributions in the conversation and model long-term dependencies in the dialogue. Our experiments for this study are conducted on data from 5 teams of the NASA HERA C4 (NASA grant NNX16AQ48G (PI: Bell)). Conversations were extracted from the 1.5 hour Team Interaction Battery (TIB) task that occurred 5 times in-mission per crew. This resulted in a total of 13,058 conversational turns (i.e., 17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls). Our findings with the revised behavioral coding and ML/NLP models indicate a 43.66% macro F1-score (i.e., 38.29% precision (P), 50.8% recall (R)) for a dialog state-tracking model that includes information from the sender only, and a 40.9% F1-score (i.e., 38.7% P, 43.36% R) for the same model that includes information from both the sender and the target of the micro-behavior. These are significantly higher compared to simple random forest models that classify behaviors strictly based on speech content and do not consider iterative team dynamics, achieving a 36.07% F1-score (i.e., 39.04% R, 33.53% P). Our findings demonstrate potential ways to leverage large conversational datasets to better capture complex team dynamics. We will discuss future directions including proposed models that can incorporate additional mission days and tasks beyond the TIB for objectively quantifying team behavior at high temporal resolution in space exploration missions.

Projna Paromita↗

Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC)

With the rapid growth in the capabilities of smaller satellites, satellite architectures that replace a single, extremely capable spacecraft with multiple, cheaper ones are gaining in popularity. Unfortunately, the orbit design process for constellations can be significantly more involved, especiallywhen the relative placement of the individual spacecraft within the constellation is not constrained by mission and/or science objectives. Optimizing a satellite constellation in the presence of multiple, competing objectives is a highly complex problem to which many traditional mathematical optimization methods cannot be applied and few tools exist to help mission designers search for promising candidate mission designs. The Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC) has been created to search for near-optimal constellation design options. GenETOC combines a modified version of the Non-dominated Sorting Genetic Algorithm II (NSGA II) with STK Components libraries (a 3rdparty .NET package created by Analytical Graphics Inc.) to create a framework that enables a mission designer to generate a simulation that models the design problem and obtain a family of potential, near-optimal solutions that can be investigated more in detail. GenETOC was developed in C# using the .NET framework with Windows Presentation Foundation (WPF) serving as the framework from which to create the graphical user interface (GUI). GenETOC user inputs can be categorized into three major data components: definition of the problem (areas of interest, satellite decision parameters, and sensor configurations), definition of performance objectives, and specification of the genetic algorithm (GA) parameters. In the problem definition component, the user is prompted to define the areas of interest against which the performance metrics will be computed, define the sensor parameters and attach them to specific spacecraft, select which satellite orbital parameters will be added to the decision space of the GA, and specify the range of desired values for each optimization parameter. For performance objectives, the user is presented with a list of available coverage and revisit performance based calculation options from which two metrics are chosen to serve as the objective functions that the GA will use to evaluate solutions during the optimization process. Finally, the definition of the GA parameters provides user control over the number of generations (number of optimization iterations), the population size (number of candidate constellations created in each generation), and the adaptive mutation and crossover threshold values (control parameters for how frequently each process occurs during the optimization). GenETOC has been extensively tested to verify the individual components of the optimization process. The GA has been tested against a suite of GA test problems to confirm convergence to the known two and three-dimensional Pareto fronts. The coverage and revisit performance metrics obtained in GenETOC are compared with STK desktop scenarios, confirming the constellations are being appropriately modeled within GenETOC simulations. A walkthrough of a simple, example problem is provided to illustrate the workings of GenETOC and to demonstrate the output available to the mission designer.

mission design↗

Development and Application of NASA SPoRT’s DustTracker-AI Model for Real-Time Identification and Tracking of Dust in Geostationary Satellite Imagery

The NASA Short-term Prediction Research and Transition (SPoRT) Center developed the DustTracker-AI model for identifying and tracking dust in NASA/NOAA Geostationary Operational Environmental Satellite (GOES) imagery in a real-time framework. A training dataset consisting of day and night dust cases was gathered over the southwestern consisting of 115 distinct images and over a million dust pixels and 256 million no dust pixels. The dataset was separated into training (60%), testing (20%), and validation (20%). A simple random forest machine learning model was developed originally to overcome the problem of night-time dust detection and has been expanded to a comprehensive day/night model for dust identification and tracking. This physically-based machine-learning approach uses NASA/NOAA GOES-16 Advanced Baseline Imager infrared imagery as inputs to the model. The model probability of dust output achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels for all dust images in the validation data set. In conjunction with developing the machine-learning model, the NASA Short-term Prediction Research and Transition Center (SPoRT) partnered with NOAA National Weather Service forecast offices to evaluate the model for utility in weather forecasting operations during the 2021 and 2023 late winter-spring seasons. Preliminary evaluation has indicated the majority of forecasters described the DustTracker-AI probabilities as having added confidence to interpreting the Dust RGB and other satellite products to objectively assess the dust extent and trends and increased the amount of time the dust plume could be tracked into the night as compared to use of the Dust RGB. More recently, SPoRT tested small scale events associated with thunderstorm outflow and burn scars to determine the model’s ability to capture local events. This presentation highlights design of the model, validation/evaluation of model performance, and example cases collected during end user product assessments.

Connor H Welch↗

Scattering and Diffraction of Electromagnetic Radiation: An Effective Probe to Material Structure

Scattered electromagnetic waves from material bodies of different forms contain, in an intricate way, precise information on the intrinsic, geometrical and physical properties of the objects. Scattering theories, ever deepening, aim to provide dependable interpretation and prediction to the complicated interaction of electromagnetic radiation with matter. There are well-established multiple-scattering formulations based on classical electromagnetic theories. An example is the Generalized Multi-particle Mie-solution (GMM), which has recently been extended to a special version ̶ the GMM-PA approach, applicable to finite periodic arrays consisting of a huge number (e.g., >>106) of identical scattering centers [1]. The framework of the GMM-PA is nearly complete. When the size of the constituent unit scatterers becomes considerably small in comparison with incident wavelength, an appropriate array of such small element volumes may well be a satisfactory representation of a material entity having an arbitrary structure. X-ray diffraction is a powerful characterization tool used in a variety of scientific and technical fields, including material science. A diffraction pattern is nothing more than the spatial distribution of scattered intensity, determined by the distribution of scattering matter by way of its Fourier transform [1]. Since all linear dimensions entered into Maxwell's equations are normalized by wavelength, an analogy exists between optical and X-ray diffraction patterns. A large set of optical diffraction patterns experimentally obtained can be found in the literature [e.g., 2,3]. Theoretical results from the GMM-PA have been scrutinized using a large collection of publically accessible, experimentally obtained Fraunhofer diffraction patterns. As far as characteristic structures of the patterns are concerned, theoretical and experimental results are in uniform agreement; no exception has been found so far. Closely connected with the spatial distribution of scattered intensities are cross sections, such as for extinction, scattering, absorption, and radiation pressure, as a critical type of key quantity addressed in most theoretical and experimental studies of radiative scattering. Cross sections predicted from different scattering theories are supposed to be in general agreement. For objects of irregular shape, the GMM-PA solutions can be compared with the highly flexible Discrete Dipole Approximation (DDA) [4,5] when dividing a target to no more than ~106 unit cells. Also, there are different ways to calculate the cross sections in the GMM-PA, providing an additional means to examine the accuracy of the numerical solutions and to unveil potential issues concerning the theoretical formulations and numerical aspects. To solve multiple scattering by an assembly of material volumes through classical theories such as the GMM-PA, the radiative properties of the component scatterers, the complex refractive index in particular, must be provided as input parameters. When using a PA to characterize a material body, this involves the use of an adequate theoretical tool, an effective medium theory, to connect Maxwell's phenomenogical theory with the atomistic theory of matter. In the atomic theory, one regards matter as composed of interacting particles (atoms and molecules) embedded in the vacuum [6]. However, the radiative properties of atomic-scaled particles are known to be substantially different from bulk materials. Intensive research efforts in the fields of cluster science and nanoscience attempt to bridge the gap between bulk and atom and to understand the transition from classical to quantum physics. The GMM-PA calculations, which place virtually no restriction on the component-particle size, might help to gain certain insight into the transition.

Xu, Yu-Lin↗

CARETS: A prototype regional environmental information system. Volume 3: Toward a national land use information system

It is recommended that a national land use information system be established by an agency of the Federal Government. This recommendation comes at a time of increasing demand for scientific information in support of environmentally relevant land use planning and management at all levels of government. It is also a time when new airborne and spaceborne remote sensors, tested in cooperation with the National Aeronautics and Space Administration (NASA) and the Earth Resources Observation Systems (EROS) Program of the Department of the Interior, make possible the gathering of land use information rapidly and on an unprecedented scale. Furthermore, information handling technology is developing toward a capability to receive, store, and disseminate the huge quantities of data that would be involved. The recommendation for the national land use information system is based upon careful analysis of the results of remote sensing experiments funded by NASA, EROS, and the Geography Program of the Geological Survey, with specific examples drawn from the demonstration project known as the Central Atlantic Regional Ecological Test Site (CARETS). CARETS is cast in the framework of a regional land use information system, channeling the flow bf information generated in response to users' declaration of their needs, through stages dealing with remote sensing data gathering systems, data processing and land mensuration, calibration in-terms of environmental impact, and evaluation with feedback from users. The proposed system would develop and implement a unified approach to the description and interpretation of the changing uses of the nation's land resources, building upon the base of interagency and intergovernmental cooperation already achieved in the experimental work to date. The land use data base that is being derived from high-altitude aerial color infrared photography would be the initial component of the recommended system. High-altitude photographic coverage would immediately be extended to as much of the nation as possible as technological developments and economic considerations permit. The system would later expand to include multiple-sensor, multiple-platform data sources. Six system characteristics are recommended: (1) High capacity storage of data available for quick retrieval, inexpensive processing, and update, (2) provision of accuracy appropriate to the scale of survey or to the level of detail dictated by different types of management and decision requirements; (3) permanent, publicly accessible sensor records for historical interpretation; (4) compatibility of the recording, storage, and retrieval system with all types of inputs, from ground observer to satellite; (5) products of diverse formats and scales, responsive to user feedback; (6) and standardization of formats, scales, and storage inputs to permit nationwide comparability.

Land use mapping↗

A Mossbauer investigation of iron-rich terrestrial hydrothermal vent systems: lessons for Mars exploration

Hydrothermal spring systems may well have been present on early Mars and could have served as a habitat for primitive life. The integrated instrument suite of the Athena Rover has, as a component on the robotic arm, a Mossbauer spectrometer. In the context of future Mars exploration we present results of Mossbauer analysis of a suite of samples from an iron-rich thermal spring in the Chocolate Pots area of Yellowstone National Park (YNP) and from Obsidian Pool (YNP) and Manitou Springs, Colorado. We have found that Mossbauer spectroscopy can discriminate among the iron-bearing minerals in our samples. Those near the vent and on the surface are identified as ferrihydrite, an amorphous ferric mineraloid. Subsurface samples, collected from cores, which are likely to have undergone inorganic and/or biologically mediated alteration (diagenesis), exhibit spectral signatures that include nontronite (a smectite clay), hematite (alpha-Fe2O3), small-particle/nanophase goethite (alpha-FeOOH), and siderite (FeCO3). We find for iron minerals that Mossbauer spectroscopy is at least as efficient in identification as X-ray diffraction. This observation is important from an exploration standpoint. As a planetary surface instrument, Mossbauer spectroscopy can yield high-quality spectral data without sample preparation (backscatter mode). We have also used field emission scanning electron microscopy (FESEM), in conjunction with energy-dispersive X ray (EDX) fluorescence spectroscopy, to characterize the microbiological component of surface sinters and the relation between the microbiological and the mineralogical framework. Evidence is presented that the minerals found in these deposits can have multi-billion-year residence times and thus may have survived their possible production in a putative early Martian hot spring up to the present day. Examples include the nanophase property and the Mossbauer signature for siderite, which has been identified in a 2.09-billion-year old hematite-rich chert stromatolite. Our research demonstrates that in situ Mossbauer spectroscopy can help determine whether hydrothermal mineral deposits exist on Mars, which is significant for exobiology because of the issue of whether that world ever had conditions conductive to the origin of life. As a useful tool for selection of samples suitable for transport to Earth, Mossbauer spectroscopy will not only serve geological interests but will also have potential for exopaleontology.

NASA Discipline Exobiology↗

Numerical Solution of the Radiative Transfer Equation: X-Ray Spectral Formation from Cylindrical Accretion onto a Magnetized Neutron Star

Predicting the emerging X-ray spectra in several astrophysical objects is of great importance, in particular when the observational data are compared with theoretical models. This requires developing numerical routines for the solution of the radiative transfer equation according to the expected physical conditions of the systems under study. Aims. We have developed an algorithm solving the radiative transfer equation in the Fokker-Planck approximation when both thermal and bulk Comptonization take place. The algorithm is essentially a relaxation method, where stable solutions are obtained when the system has reached its steady-state equilibrium. Methods. We obtained the solution of the radiative transfer equation in the two-dimensional domain defined by the photon energy E and optical depth of the system pi using finite-differences for the partial derivatives, and imposing specific boundary conditions for the solutions. We treated the case of cylindrical accretion onto a magnetized neutron star. Results. We considered a blackbody seed spectrum of photons with exponential distribution across the accretion column and for an accretion where the velocity reaches its maximum at the stellar surface and at the top of the accretion column, respectively. In both cases higher values of the electron temperature and of the optical depth pi produce flatter and harder spectra. Other parameters contributing to the spectral formation are the steepness of the vertical velocity profile, the albedo at the star surface, and the radius of the accretion column. The latter parameter modifies the emerging spectra in a specular way for the two assumed accretion profiles. Conclusions. The algorithm has been implemented in the XPEC package for X-ray fitting and is specifically dedicated to the physical framework of accretion at the polar cap of a neutron star with a high magnetic field (approx > 10(exp 12) G). This latter case is expected to be of typical accreting systems such as X-ray pulsars and supergiant fast X ray transients.

Fairnelli, R.↗

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗

Transition Analysis for the CRM-NLF Wind Tunnel Configuration using Transport Equation Models and Linear Stability Correlations

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework rely upon transition correlations that were derived from a limited number of low-speed experiments. Furthermore, these models often account for only a subset of the relevant transition mechanisms and/or cannot accurately predict the sensitivity of those mechanisms to the changes in significant flow parameters. A preceding investigation had targeted the assessment of the transport-equation-based transition models in NASA's OVERFLOW 2.3b solver, namely, the amplification factor transport (AFT-2017b) equation model coupled with the Spalart-Allmaras RANS model and the Langtry-Menter transition models (LM2009 without crossflow effects and LM2015 including the modeling of crossflow transition) implemented with Menter’s shear-stress transport equation (SST2003) RANS model. Comparisons with recent measurements at transonic freestream conditions on the Common Research Model with Natural Laminar Flow (CRM-NLF) reinforced our earlier finding that all three of the above models significantly underpredict the reported extent of the laminar flow region over the entire span of the wing, regardless of the dominant instability mechanism(s) underlying the onset of the transition process. The underprediction of the laminar flow extent was attributed to the failure of the above models in accounting for the stabilizing effect of compressibility on the amplification of Tollmien-Schlichting instabilities. Based on previous linear stability studies related to compressibility effects, the present work proposes modifications to the two classes of transition models that reduce to the original form of each model at low subsonic speeds and do not require any nonlocal flow information or additional transport equation(s). The modifications are shown to significantly improve the predicted laminar extent of the flow and compare well against the data from the CRM-NLF experiment. Additionally, a previous assessment of transition prediction based on the dual, nonparallel N -factor method in conjunction with linear parabolized stability equations (PSE) is extended to additional angles of attack to provide the first comprehensive assessment of transition models based on nonparallel disturbance amplification over the CRM-NLF. In general, the transition criterion based on the dual, nonparallel N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at R eMAC = 15 million for all angles of attack investigated herein and provides additional validation of the improved predictions from the compressibility-corrected transition models.

CFD modeling↗

Transition Analysis for the CRM-NLF Wind Tunnel Configuration using Transport Equation Models and Linear Stability Correlations

Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework rely upon transition correlations that were derived from a limited number of low-speed experiments. Furthermore, these models often account for only a subset of the relevant transition mechanisms and/or cannot accurately predict the sensitivity of those mechanisms to the changes in significant flow parameters. A preceding investigation had targeted the assessment of the transport-equation-based transition models in NASA's OVERFLOW 2.3b solver, namely, the amplification factor transport (AFT-2017b) equation model coupled with the Spalart-Allmaras RANS model and the Langtry-Menter transition models (LM2009 without crossflow effects and LM2015 including the modeling of crossflow transition) implemented with Menter’s shear-stress transport equation (SST2003) RANS model. Comparisons with recent measurements at transonic freestream conditions on the Common Research Model with Natural Laminar Flow (CRM-NLF) reinforced our earlier finding that all three of the above models significantly underpredict the reported extent of the laminar flow region over the entire span of the wing, regardless of the dominant instability mechanism(s) underlying the onset of the transition process. The underprediction of the laminar flow extent was attributed to the failure of the above models in accounting for the stabilizing effect of compressibility on the amplification of Tollmien-Schlichting instabilities. Based on previous linear stability studies related to compressibility effects, the present work proposes modifications to the two classes of transition models that reduce to the original form of each model at low subsonic speeds and do not require any nonlocal flow information or additional transport equation(s). The modifications are shown to significantly improve the predicted laminar extent of the flow and compare well against the data from the CRM-NLF experiment. Additionally, a previous assessment of transition prediction based on the dual, nonparallel N -factor method in conjunction with linear parabolized stability equations (PSE) is extended to additional angles of attack to provide the first comprehensive assessment of transition models based on nonparallel disturbance amplification over the CRM-NLF. In general, the transition criterion based on the dual, nonparallel N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at R eMAC = 15 million for all angles of attack investigated herein and provides additional validation of the improved predictions from the compressibility-corrected transition models.

CFD modeling↗

Comparison of the X-Ray and Radio Light Curves of Quasar PKS 1510--089

We present results for the X-ray-bright superluminal AGN PKS 1510-089 (z=0.36) monitored weekly with the Rossi X-Ray Timing Explorer for the past four years in order to study the origin of X-ray emission from this extremely variable blazer. These RXTE data are compared with weekly cm-band flux and polarization observations from the Michigan Diameter telescope, to identify correlated activity and associated frequency-dependent time delays for constraining X-ray emission models; and bimonthly 7mm VLBA total and linearly polarized intensity imaging to identify temporal associations between X-ray events and the ejection of superluminal components and disturbances in the magnetic field, to test if the X-ray energy release is related to changes in the inner jet flow. Both the X-ray (2-20 keV) and radio flux are highly variable on timescales of weeks. The VLBA mas structure is dominated by a bright core with a weak jet; both the ejection of very fast superluminal knots and changes in the fractional polarization and EVPA of the core on timescales of one to four months are identified. Two outbursts in 1997 are well-resolved in both the centimeter and X-ray bands. Both the strong temporal association and the similar outburst shape support a causal relation, and a discrete cross-correlation analysis identifies that the X-ray lags the radio by 16 days during the bursts. Starting in 1998 the behavior changes: the correlation is weaker with the X-ray possibly leading the radio by six days. During the full time window there is a correlation between bands as expected if the radio photons are upscattered to X-ray energies. The time correlations and difference between the flat X-ray spectral index (0.0 <= alpha <= 0.5 where F(sub v) is proportional to v(exp -alpha)), and the mm-wave synchrotron spectrum (alpha = 0.8) are discussed within the framework of viable SSC models.

Aller, M. F.↗

Hierarchical Strategy for Rapid Analysis Environment

A new philosophy is developed wherein the hierarchical definition of data is made use of in creating a better environment to conduct analyses of practical problems. This system can be adapted to conduct virtually any type of analysis, since this philosophy is not bound to any specific kind of analysis. It provides a framework to manage different models and its results and more importantly, the interaction between the different models. Thus, it is ideal for many types of finite element analyses like globalAoca1 analysis and those that involve multiple scales and fields. The system developed during the course of this work is just a demonstrator of the basic concepts. A complete implementation of this strategy could potentially make a major impact on the way analyses are conducted. It could considerably reduce the time frame required to conduct the analysis of real-life problems by efficient management of the data involved and reducing the human effort involved. It also helps in better decision making because of more ways to interpret the results. The strategy has been currently implemented for structural analysis, but with more work it could be extended to other fields of science when the finite element method is used to solve the differential equations numerically. This report details the work that has been done during the course of this project and its achievements and results. The following section discusses the meaning of the word hierarchical and the different references to the term in the literature. It talks about the development of the finite element method, its different versions and how hierarchy has been used to improve the methodology. The next section describes the hierarchical philosophy in detail and explains the different concepts and terms associated with it. It goes on to describe the implementation and the features of the demonstrator. A couple of problems are analyzed using the demonstrator program to show the working of the system. The two problems considered are two dimensional plane stress analysis problems. The results are compared with those obtained using conventional analysis. The different challenges faced during the development of this system are discussed. Finally, we conclude with suggestions for future work to add more features and extend it to a wider range of problems.

Whitcomb, John↗

Evaluation of a Shuttle Derived Vehicle (SDV) for Cargo Transportation

In this new era of space exploration, a host of launch vehicles are being examined for possible use in transporting cargo and crew to low Earth orbit and beyond. Launch vehicles derived from the Space Shuttle Program (SSP), known as Shuttle Derived Vehicles (SDVs), are prime candidates for heavy-lift duty because of their potential to minimize non-recurring costs and because the Shuttle can leverage off proven high-performance flight systems with established ground and flight support. To determine the merits of SDVs, a detailed evaluation was performed. This evaluation included a trade study and risk assessment of options based on performance, safety reliability, cost, operations, and evolution. The purpose of this paper is to explain the approach, processes, and tools used to evaluate launch vehicles for heavy lift cargo transportation. The process included defining the trade space, characterizing the concepts, analyzing the systems, and scoring the options. The process also included a review by subject experts from NASA and industry to compare past and recent study data and assess the risks. A set of technical performance measures (TPMs) was generated based on the study requirements and constraints. Tools such as INTROS and POST were used to calculate performance, FIRST was used for prediction of reliability, and other software packages, both commercial and NASA-owned, were applied to study the trade space. By following a clear process and using the right tools a thorough assessment was performed. An SDV can be classified as either a side-mount vehicle (SMV) or an in-line vehicle OLV). An SMV is a Space Shuttle where the Orbiter is replaced by a cargo carrier. An ILV is comprised of a modified Shuttle External Tank (ET) with engines mounted to the bottom and cargo mounted atop. For both families of vehicles, Solid Rocket Boosters (SRBs) are attached to the ET. The first derivate of Shuttle is defined as the vehicle with minimum changes necessary to transform the Space Shuttle into an SDV. Deltas from the first derivate were also formulated to study more SDV options. Examples of deltas include replacing the SRBs with larger and/or more SRBs, adding an upper stage, increasing the size of the ET, changing the engines, and modifying the elements. Challenges for SDV range from tailoring infrastructure to meeting the exploration schedule. Although SDV is based on the Space Shuttle, it still includes development risk for designing and building a Cargo Carrier. There are also performance challenges in that Shuttle is not optimized for cargo-only missions, but it is a robust system built on reusability. Balancing the strengths and weaknesses of the Shuttle to meet Lunar and Mars mission objectives provides the framework for an informative trade study. SDV was carefully analyzed and the results of the study provide invaluable data for use in the new exploration initiative.

Roman, Jose M.↗

Coupled Data Assimilation for Integrated Earth System Analysis and Prediction: Goals, Challenges, and Recommendations

The purpose of this report is to identify fundamental issues for coupled data assimilation (CDA), such as gaps in science and limitations in forecasting systems, in order to provide guidance to the World Meteorological Organization (WMO) on how to facilitate more rapid progress internationally. Coupled Earth system modeling provides the opportunity to extend skillful atmospheric forecasts beyond the traditional two-week barrier by extracting skill from low-frequency state components such as the land, ocean, and sea ice. More generally, coupled models are needed to support seamless prediction systems that span timescales from weather, subseasonal to seasonal (S2S), multiyear, and decadal. Therefore, initialization methods are needed for coupled Earth system models, either applied to each individual component (called Weakly Coupled Data Assimilation - WCDA) or applied the coupled Earth system model as a whole (called Strongly Coupled Data Assimilation - SCDA). Using CDA, in which model forecasts and potentially the state estimation are performed jointly, each model domain benefits from observations in other domains either directly using error covariance information known at the time of the analysis (SCDA), or indirectly through flux interactions at the model boundaries (WCDA). Because the non-atmospheric domains are generally under-observed compared to the atmosphere, CDA provides a significant advantage over single-domain analyses. Next, we provide a synopsis of goals, challenges, and recommendations to advance CDA: Goals: (a) Extend predictive skill beyond the current capability of NWP (e.g. as demonstrated by improving forecast skill scores), (b) produce physically consistent initial conditions for coupled numerical prediction systems and reanalyses (including consistent fluxes at the domain interfaces), (c) make best use of existing observations by allowing observations from each domain to influence and improve the full earth system analysis, (d) develop a robust observation-based identification and understanding of mechanisms that determine the variability of weather and climate, (e) identify critical weaknesses in coupled models and the earth observing system, (f) generate full-field estimates of unobserved or sparsely observed variables, (g) improve the estimation of the external forcings causing changes to climate, (h) transition successes from idealized CDA experiments to real-world applications. Challenges: (a) Modeling at the interfaces between interacting components of coupled Earth system models may be inadequate for estimating uncertainty or error covariances between domains, (b) current data assimilation methods may be insufficient to simultaneously analyze domains containing multiple spatiotemporal scales of interest, (c) there is no standardization of observation data or their delivery systems across domains, (d) the size and complexity of many large-scale coupled Earth system models makes it is difficult to accurately represent uncertainty due to model parameters and coupling parameters, (e) model errors lead to local biases that can transfer between the different Earth system components and lead to coupled model biases and long-term model drift, (e) information propagation across model components with different spatiotemporal scales is extremely complicated, and must be improved in current coupled modeling frameworks, (h) there is insufficient knowledge on how to represent evolving errors in non-atmospheric model components (e.g. as sea ice, land and ocean) on the timescales of NWP.

CDA↗