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The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

The recent US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multi-model ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) then any single model ensemble. This multi-model approach is the basis for several international collaborative prediction research efforts, an operational European system and there are numerous examples of how this multi-model ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test Bed (CTB) NMME workshops (February 18, and April 8, 2011) a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data is readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (http://origin.cpc.ncep.noaa.gov/products/people/wd51yf/NMME/index.html). Moreover, the NMME forecast are already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, presents an overview of the multi-model forecast quality, and the complementary skill associated with individual models.

NOAA CPC

Computational Thermodynamic Study to Predict Complex Phase Equilibria in the Nickel-Base Superalloy Rene N6

A previous study by Ritzert et al. on the formation and prediction of topologically closed packed (TCP) phases in the nickel-base superalloy Rene' N6 is re-examined with computational thermodynamics. The experimental data on phase distribution in forty-four alloys with a composition within the patent limits of the nickel-base superalloy Rene' N6 provide a good basis for comparison to and validation of a commercial nickel superalloy database used with ThermoCalc. Volume fraction of the phases and partitioning of the elements are determined for the forty-four alloys in this dataset. The baseline heat treatment of 400 h at 1366 K was used. This composition set is particularly interesting since small composition differences lead to dramatic changes in phase composition. In general the calculated values follow the experimental trends. However, the calculations indicated no TCP phase formation when the experimental measurements gave a volume percent of TCP phase less than 2 percent. When TCP phases were predicted, the calculations under-predict the volume percent of TCP phases by a factor of 2 to 8. The calculated compositions of the gamma and gamma' phases show fair agreement with the measurements. However, the calculated compositions of the P Phase do not agree with those measured. This may be due to inaccuracies in the model parameters for P phase and/or issues with the microprobe analyses of these phases. In addition, phase fraction diagrams and sigma and P phase solvus temperatures are calculated for each of the alloys. These calculations indicate that P phase is the primary TCP phase formed for the alloys considered here at 1366 K. Finally, a series of isopleths are calculated for each of the seven alloying elements. These show the effect of each alloying element on creating TCP phases.

Copland, Evan H.

Cu-Zn binary phase diagram and diffusion couples

The objectives of this paper are to learn: (1) what information a binary phase diagram can yield; (2) how to construct and heat treat a simple diffusion couple; (3) how to prepare a metallographic sample; (4) how to operate a metallograph; (5) how to correlate phases found in the diffusion couple with phases predicted by the phase diagram; (6) how diffusion couples held at various temperatures could be used to construct a phase diagram; (7) the relation between the thickness of an intermetallic phase layer and the diffusion time; and (8) the effect of one species of atoms diffusing faster than another species in a diffusion couple.

Mccoy, Robert A.

Quantizing and sampling considerations in digital phased-locked loops

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

Hurst, G. T.

Theoretical prediction of phase relationships in planetary mantles

Thermodynamic and phase equilibrium data are used to generate an internally consistent set of enthalpies and entropies for important components of the CaO-MgO-Al2O3-SiO2 (CMAS) system in silica-undersaturated compositions. The addition of Na and Fe(2+) to the CMAS system produces shifts in the plagioclase, spinel and garnet stability fields. While the Morgan and Anders (1979) model Martian composition has stability fields of plagioclase and garnet lherzolite, and a small spinel lherzolite field at temperatures below 900 C, the Martian mantle composition of McGetchin and Smyth (1978) would not contain orthopyroxene, and a low pressure assemblage of plagioclase-spinel wehrlite would be replaced by garnet-spinel wehrlite at higher pressure. In both cases, the Fe-Mg ratio would be substantially greater than that found in primitive terrestrial basalts.

Wood, B. J.

Long term prediction of roll phase for an undisturbed spinning spacecraft

This paper describes the attitude control of the Pioneer 10 spacecraft since the loss of the sun-sensor signal in late 1983. It is necessary to control the attitude of the spin-stablized spacecraft so as to maintain communications with earth. Roll phase is calculated on earth using data from a science instrument on-board Pioneer 10, the imaging-photopolarimeter, which, along with its other functions, was designed to collect images of Jupiter during encounter in 1973. With calculation of instantaneous roll phase performed only once per week, the spacecraft roll angle can be predicted more than a week ahead for timing reorientation impulses. Attitude reorientation maneuvers based on roll phase predictions have been successfully executed for several years on Pioneer 10. Of 10 maneuvers analyzed in this paper, predictions were made for as many as 10 days in the future based on a roll-phase measurements spanning only 12 days of data. The average maneuver was planned by projecting the roll phase for 3 days (22,000 spacecraft revolutions) and resulted in a maneuver execution phase error of only 11 deg.

Smith, M. A.

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Daigle, Matthew

Preliminary modeling of high pressure partial melting - Implications for early lunar differentiation

A quantitative model is presented for equilibrium crystallization of lunar magmas at high pressure, which, viewed in reverse, is equivalent to equilibrium partial melting. Data are extrapolated from simple systems, mare basalt systems, and from experiments on terrestrial compositions. Liquidus phase equilibria in a portion of the CaO-MgO-Al2O3-SiO2 system serve as a guide for predicting phase equilibria in the natural system. High pressure partial melting sequences are calculated for several proposed whole moon compositions at nominal pressure of 10 and 20 kb. Results show that compositions with chondritic Ca/Al have quite different melting paths from those with subchondritic Ca/Al, and as a result the types of magmas produced are quite different. If the moon possesses a chondritic Ca/Al ratio, models which rely on small degrees of partial melting to produce the early lunar magnetism are suspect.

Longhi, J.

Phase Distribution Phenomena for Simulated Microgravity Conditions: Experimental Work

This report summarizes the work accomplished at Rensselaer to study phase distribution phenomenon under simulated microgravity conditions. Our group at Rensselaer has been able to develop sophisticated analytical models to predict phase distribution in two-phase flows under variety of conditions. These models are based on physics and data obtained from carefully controlled experiments that are being conducted here. These experiments also serve to verify the models developed.

Singhal, Maneesh

Phase Distribution Phenomena for Simulated Microgravity Conditions: Experimental Work

This report summarizes the work accomplished at Rensselaer to study phase distribution phenomenon under simulated microgravity conditions. Our group at Rensselaer has been able to develop sophisticated analytical models to predict phase distribution in two-phase flows under a variety of conditions. These models are based on physics and data obtained from carefully controlled experiments that are being conducted here. These experiments also serve to verify the models developed.

Singhal, Maneesh

Investigation of direct integrated optics modulators

Direct modulation techniques applicable to integrated optics data preprocessors were investigated. Several methods of modulating a coherent optical beam by interaction with an incoherent beam were studied. It was decided to investigate photon induced conductivity changes in thin semiconductor cladding layers on optical waveguides. Preliminary calculations indicate significant changes can be produced in the phase shift in a propagating wave when the conductivity is changed by ten percent or more. Experimental devices to verify these predicted phase changes and experiments designed to prove the concept are described.

Batchman, T. E.

Space Environments and Effects Concept: Transitioning Research to Operations and Applications

The National Aeronautics and Space Administration (NASA) is embarking on a course to expand human presence beyond Low Earth Orbit (LEO) while expanding its mission to explore the solar system. Destinations such as Near Earth Asteroids (NEA), Mars and its moons, and the outer planets are but a few of the mission targets. NASA has established numerous offices specializing in specific space environments disciplines that will serve to enable these missions. To complement these existing discipline offices, a concept focusing on the development of space environment and effects application is presented. This includes space climate, space weather, and natural and induced space environments. This space environment and effects application is composed of 4 topic areas; characterization and modeling, engineering effects, prediction and operation, and mitigation and avoidance. These topic areas are briefly described below. Characterization and modeling of space environments will primarily focus on utilization during Program mission concept, planning, and design phases. Engineering effects includes materials testing and flight experiments producing data to be used in mission planning and design phases. Prediction and operation pulls data from existing sources into decision-making tools and empirical data sets to be used during the operational phase of a mission. Mitigation and avoidance will develop techniques and strategies used in the design and operations phases of the mission. The goal of this space environment and effects application is to develop decision-making tools and engineering products to support the mission phases of mission concept through operations by focusing on transitioning research to operations. Products generated by this space environments and effects application are suitable for use in anomaly investigations. This paper will outline the four topic areas, describe the need, and discuss an organizational structure for this space environments and effects application.

Edwards, David L.

An Initial Vibro-Acoustic Model for Predicting Electric Motor Noise

A system-level tool to predict electric motor noise, suitable for trade studies of eVTOL and UAM aircraft, does not exist. This work describes the ongoing effort to develop such a tool. It utilizes a 3 phase prediction routine that models the electro-magnetic interactions of the electric motor, the resulting structural vibrations of the motor rotor, and finally the acoustic propagation generated by those structural vibrations.

Electric Motor Noise

Late-time spectra and type Ia supernova models: New clues from the Hubble Space Telescope

Calculated late-time spectra of two classical hydrodynamical models for Type Ia supernovae (deflagration model W7 of Nomoto, Thielemann, & Yokoi, and delayed detonation model DD4 of Woosley & Weaver) are compared with observations of SN 1992A and other spectroscopically normal SNe Ia. An important new piece of information is provided by observations done with the Hubble Space Telescope (HST) which cover the ultraviolet range at the nebular phase of a SN Ia: SN 1992A in NGC 1380. For the first time a picture of SN Ia emission from the ultraviolet through the optical is obtained at these phases. Predictions of the classical model (W7 and DD4) are compared with the observed spectrum of SN 1992A and with the optical spectra of SN 1989M in NGC 4579 and SN 1990N in NGC 4639 at similar epochs. The absolute B and V magnitudes of the models are also estimated at these late phases. Taken at face value the nebular spectra of these 'classical' models are more consistent with the long extragalactic distance scale, pointing to distances to NGC 4579 around 21 +/- 3 Mpc and a slightly larger distance, 22 +/- 3 Mpc, to NGC 4639, on the back side of the Virgo Cluster. However, the calculated Fe(+3) luminosity as predicted from the models exceeds the observed limit from the HST data of SN 1992A. Other differences in the ratios of the line intensities between calculated and observed spectra, show some disagreement with the observed spectra at the nebular phases. They may not be the best choice for spectroscopically normal SNe Ia, and their use as an independent calibration of the extragalactic distance scale should be viewed with caution.

Ruiz-Lapuente, P.

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy