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NASA NTRSDate not supplied

Data & Reasoning Fabric Minimum Viable Product

A Data & Reasoning Fabric (DRF) is envisioned to enable the full potential of air mobility by providing all data and reasoning where they are needed. The DRF provides a marketplace based on an open foundational ecosystem of data and reasoning exchange between the many systems that must seamlessly interplay to manage the complex and dense airspace operations required to achieve advanced air mobility goals. The DRF marketplace is decentralized and will not be owned by any single party. To deliver reference designs and development environments that catalyze broad private and public sector buy-in and self-sustaining development of DRF and associated standards, DRF activities will collaboratively test these technologies, open standards and architectures, and an integrated framework with end-users. The DRF activity is developing a Minimum Viable Product (MVP) called the DRF Accelerator which will enable the rapid deployment of candidate data and reasoning services to test and evaluate the DRF core system functionality. The DRF Project is engaging with government and industry end-users and stakeholders, to: (1) assess the technical feasibility of the DRF Accelerator; (2) assess the likelihood of adoption, through shared test and evaluation; and (3) identify what data and services can be shared across DRF.

DRF↗
NASA NTRS2003

A Dynamic Risk Model for Evaluation of Space Shuttle Abort Scenarios

The Space Shuttle is an advanced manned launch system with a respectable history of service and a demonstrated level of safety. Recent studies have shown that the Space Shuttle has a relatively low probability of having a failure that is instantaneously catastrophic during nominal flight as compared with many US and international launch systems. However, since the Space Shuttle is a manned. system, a number of mission abort contingencies exist to primarily ensure the safety of the crew during off-nominal situations and to attempt to maintain the integrity of the Orbiter. As the Space Shuttle ascends to orbit it transverses various intact abort regions evaluated and planned before the flight to ensure that the Space Shuttle Orbiter, along with its crew, may be returned intact either to the original launch site, a transoceanic landing site, or returned from a substandard orbit. An intact abort may be initiated due to a number of system failures but the highest likelihood and most challenging abort scenarios are initiated by a premature shutdown of a Space Shuttle Main Engine (SSME). The potential consequences of such a shutdown vary as a function of a number of mission parameters but all of them may be related to mission time for a specific mission profile. This paper focuses on the Dynamic Abort Risk Evaluation (DARE) model process, applications, and its capability to evaluate the risk of Loss Of Vehicle (LOV) due to the complex systems interactions that occur during Space Shuttle intact abort scenarios. In addition, the paper will examine which of the Space Shuttle subsystems are critical to ensuring a successful return of the Space Shuttle Orbiter and crew from such a situation.

Henderson, Edward M.↗
NASA NTRS2019

A Bayesian Analysis of SDSS J0914+0853, a Low-mass Dual AGN Candidate

We present the first results from Bayesian AnalYsis of Multiple AGN in X-rays (BAYMAX), a tool that uses a Bayesian framework to quantitatively evaluate whether a given Chandra observation is more likely a single or dual point source. Although the most robust method of determining the presence of dual active galactic nuclei (AGNs) is to use X-ray observations, only sources that are widely separated relative to the instrumentʼs point-spread function are easy to identify. It becomes increasingly difficult to distinguish dual AGNs from single AGNs when the separation is on the order of Chandraʼs angular resolution (<1″). Using likelihood models for single and dual point sources, BAYMAX quantitatively evaluates the likelihood of an AGN for a given source. Specifically, we present results from BAYMAX analyzing the lowest-mass dual AGN candidate to date, SDSS J0914+0853, where archival Chandra data shows a possible secondary AGN ∼ 0"3 from the primary. Analyzing a new 50 ks Chandra observation, results from BAYMAX shows that SDSS J0914+0853 is most likely a single AGN with a Bayes factor of 13.5 in favor of a single point source model. Further, posterior distributions from the dual point source model are consistent with emission from a single AGN. We find a very low probability of SDSS J0914+0853 being a dual AGN system with a flux ratio f>0.3 and separation r>0"3. Overall, BAYMAX will be an important tool for correctly classifying candidate dual AGNs in the literature, as well as studying the dual AGN population where past spatial resolution limits have prevented systematic analyses.

Active galaxies↗
DOE OSTI2020

Interpreting High-resolution Spectroscopy of Exoplanets using Cross-correlations and Supervised Machine Learning

We present a new method for performing atmospheric retrieval on ground-based, high-resolution data of exoplanets. Our method combines cross-correlation functions with a random forest, a supervised machine-learning technique, to overcome challenges associated with high-resolution data. A series of cross-correlation functions are concatenated to give a “CCF-sequence” for each model atmosphere, which reduces the dimensionality by a factor of ∼100. The random forest, trained on our grid of ∼65,000 models, provides a likelihood-free method of retrieval. The precomputed grid spans 31 values of both temperature and metallicity, and incorporates a realistic noise model. We apply our method to HARPS-N observations of the ultra-hot Jupiter KELT-9b and obtain a metallicity consistent with solar (logM = − 0.2 ± 0.2). Our retrieved transit chord temperature (T=6000{sub −200}{sup +0}K) is unreliable as strong ion lines lie outside of the extent of the training set, which we interpret as being indicative of missing physics in our atmospheric model. We compare our method to traditional nested sampling, as well as other machine-learning techniques, such as Bayesian neural networks. We demonstrate that the likelihood-free aspect of the random forest makes it more robust than nested sampling to different error distributions, and that the Bayesian neural network we tested is unable to reproduce complex posteriors. We also address the claim in Cobb et al. 2019 that our random forest retrieval technique can be overconfident but incorrect. We show that this is an artifact of the training set, rather than of the machine-learning method, and that the posteriors agree with those obtained using nested sampling.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

Development of an LSI maximum-likelihood convolutional decoder for advanced forward error correction capability on the NASA 30/20 GHz program

The particular coding option identified as providing the best level of coding gain performance in an LSI-efficient implementation was the optimal constraint length five, rate one-half convolutional code. To determine the specific set of design parameters which optimally matches this decoder to the LSI constraints, a breadboard MCD (maximum-likelihood convolutional decoder) was fabricated and used to generate detailed performance trade-off data. The extensive performance testing data gathered during this design tradeoff study are summarized, and the functional and physical MCD chip characteristics are presented.

Clark, R. T.↗
DOE OSTI2025

Modified gravity constraints from the full shape modeling of clustering measurements from DESI 2024

We present cosmological constraints on deviations from general relativity (GR) from the first-year of clustering observations from the Dark Energy Spectroscopic Instrument (DESI) in combination with other available datasets including the CMB data from Planck with CMB-lensing from Planck and ACT, BBN constraints on the physical baryon density, the galaxy weak lensing and clustering from DESY3 and supernova data from DESY5. We first consider the μ(a,k)–Σ(a,k) modified gravity (MG) parameterization (as well as η(a,k)) in a ΛCDM and a w 0 w a CDM cosmological backgrounds. Using a functional form for time-only evolution gives μ 0 = 0.11 +0.44 -0.54 from DESI(FS+BAO)+BBN and a wide prior on n s . Using DESI(FS+BAO)+CMB+DESY3+DESY5-SN, we obtain μ 0 = 0.05 ± 0.22 and Σ 0 = 0.008 ± 0.045 and similarly μ 0 = 0.02 +0.19 -0.24 and η 0 = 0.09 +0.36 -0.60 , in an ΛCDM background. In w 0 w a CDM we obtain μ 0 = -0.24 +0.32 -0.28 and Σ 0 = 0.006 ± 0.043, consistent with GR, and we still find a preference of the data for a dynamical dark energy with w 0 > -1 and w a < 0. Using functional dependencies in both time and scale gives μ 0 and Σ 0 with a same level of precision as above but other scale MG parameters remain hard to constrain. We then move to binned parameterizations in a ΛCDM background starting with two bins in redshift and obtain, μ 1 = 1.02 ± 0.13, μ 2 = 1.04 ± 0.11, Σ 1 = 1.021 ± 0.029 and Σ 2 = 1.022 +0.027 -0.023 , all consistent with the unity value of GR in the binning formalism. We then extend the analysis to combine two bins in redshift and two in scale giving 8 MG parameters that we find all consistent with GR. We note that we find here that the tension reported in previous studies about Σ 0 being inconsistent with GR when using Planck PR3 data goes away when we use the recent LoLLiPoP+HiLLiPoP likelihoods. As noted in previous studies, this seems to indicate that the tension is indeed related to the CMB lensing anomaly in PR3 which is also resolved when using the recent likelihoods. We then constrain the class of Horndeski theory in the effective field theory of dark energy approach. We consider both EFT-basis and α-basis in the analysis. Assuming a power law parameterization for the EFT function Ω, which controls non-minimal coupling, we obtain Ω 0 = 0.012 +0.001 -0.012 and s 0 = 0.996 +0.54 -0.20 from the combination of DESI(FS+BAO)+DESY5SN+CMB in a ΛCDM background, which are consistent with GR. Similar results are obtained when using the α-basis and assuming no-braiding (α B = 0) giving c M < 1.14 at 95% CL in a ΛCDM background, also in agreement with GR. However, we see a mild yet consistent indication for c B > 0 when α B is allowed to vary which will require further study to determine whether this is due to systematics or new physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Pulse-shape discrimination against low-energy Ar-39 beta decays in liquid argon with 4.5 tonne-years of DEAP-3600 data

The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39 Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator: the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time: (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Recursive estimation of prior probabilities using the mixture approach

The problem of estimating the prior probabilities q sub k of a mixture of known density functions f sub k(X), based on a sequence of N statistically independent observations is considered. It is shown that for very mild restrictions on f sub k(X), the maximum likelihood estimate of Q is asymptotically efficient. A recursive algorithm for estimating Q is proposed, analyzed, and optimized. For the M = 2 case, it is possible for the recursive algorithm to achieve the same performance with the maximum likelihood one. For M 2, slightly inferior performance is the price for having a recursive algorithm. However, the loss is computable and tolerable.

Kazakos, D.↗
NASA NTRS1991

A Dynamic Testing Complexity Metric

This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

Voas, Jeffrey↗
DOE OSTI2021

The XFaster Power Spectrum and Likelihood Estimator for the Analysis of Cosmic Microwave Background Maps

We present the XFaster analysis package, XFaster is a fast, iterative angular power spectrum estimator based on a diagonal approximation to the quadratic Fisher matrix estimator. XFaster uses Monte Carlo simulations to compute noise biases and filter transfer functions and is thus a hybrid of both Monte Carlo and quadratic estimator methods. In contrast to conventional pseudo-C ℓ based methods, the algorithm described here requires a minimal number of simulations, and does not require them to be precisely representative of the data to estimate accurate covariance matrices for the bandpowers. The formalism works with polarization-sensitive observations and also data sets with identical, partially overlapping, or independent survey regions. The method was first implemented for the analysis of BOOMERanG data (Netterfield et al. 2002; Jones et al. 2006), and also used as part of the Planck analysis (Rocha et al. 2011). Here, we describe the full, publicly available analysis package, written in Python, as developed for the analysis of data from the 2015 flight of the SPIDER instrument (SPIDER Collaboration 2021). The package includes extensions for self-consistently estimating null spectra and for estimating fits for Galactic foreground contributions. We show results from the extensive validation of XFaster using simulations, and its application to the SPIDER data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Measurement of the $c$-jet mistagging efficiency in $t\bar{t}$ events using $pp$ collision data at $\sqrt{s}=13$ $\text {TeV}$ collected with the ATLAS detector

A technique is presented to measure the efficiency with which c-jets are mistagged as b-jets (mistagging efficiency) using tt¯ events, where one of the W bosons decays into an electron or muon and a neutrino and the other decays into a quark–antiquark pair. The measurement utilises the relatively large and known W → cs branching ratio, which allows a measurement to be made in an inclusive c-jet sample. The data sample used was collected by the ATLAS detector at √s = 13 TeV and corresponds to an integrated luminosity of 139 fb –1 . Events are reconstructed using a kinematic likelihood technique which selects the mapping between jets and tt¯ decay products that yields the highest likelihood value. The distribution of the b-tagging discriminant for jets from the hadronic W decays in data is compared with that in simulation to extract the mistagging efficiency as a function of jet transverse momentum. The total uncertainties are in the range 3–17%. The measurements generally agree with those in simulation but there are some differences in the region corresponding to the most stringent b-jet tagging requirement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1981

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

Mark, W. D.↗
NASA NTRS1985

More than you want to know about maximum likelihood estimation

The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic estimation concepts. Some of these basic concepts are presented. The maximum likelihood estimator is briefly discussed and the aircraft equations of motion that the estimator uses. The basic concepts of minimization and estimation are examined for a simple computed aircraft example. The cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation from flight data is discussed. Some of the major conclusions for the computed example are also developed for the analysis of flight data.

Iliff, K. W.↗
NASA NTRS1983

Optimal design and use of retry in fault tolerant real-time computer systems

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Lee, Y. H.↗
NASA NTRS1985

Maximum Likelihood Estimation with Emphasis on Aircraft Flight Data

Accurate modeling of flexible space structures is an important field that is currently under investigation. Parameter estimation, using methods such as maximum likelihood, is one of the ways that the model can be improved. The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic estimation concepts. Some of these basic concepts are presented. The maximum likelihood estimator and the aircraft equations of motion that the estimator uses are briefly discussed. The basic concepts of minimization and estimation are examined for a simple computed aircraft example. The cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation from flight data is discussed. Specific examples of estimation of structural dynamics are included. Some of the major conclusions for the computed example are also developed for the analysis of flight data.

Iliff, K. W.↗
NASA NTRS1981

Selected stability and control derivatives from the first Space Shuttle entry

Primary stability and control derivative estimates garnered from the first Shuttle entry are reported. The craft was the first vehicle to maneuver over a wide range of hypersonic velocities, yielding data on flight characteristics from previously unexplored regimes. The flight envelope was confined to entry and safe landing, with no additional maneuvers to gain control data. Data for a Mach number range of 25-1.5 and altitudes of 515,000-50,000 ft are provided, and functional ranges of the Shuttle control surfaces and attitude jets are outlined. On-board systems gathered data on aerodynamic coefficient identification, flight condition and Euler angles, and jet chamber pressures. A maximum likelihood estimation program, which contained unknown stability and control derivatives, was used for control; a control input determined the value of the unknown derivatives, and the input and spacecraft response were measured. Longitudinal and lateral directional maneuvers and their derivative estimates are described, noting wind contamination of the sideslip measurements below Mach 3. Further maneuvering and stability tests are projected for subsequent flights.

Iliff, K. W.↗
NASA NTRS2010

Product Lifecycle Management and the Quest for Sustainable Space Explorations

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decision-making. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful concept to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting.

Caruso, Pamela W.↗
NASA NTRS2010

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decisionmaking. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful tool to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting. Sustainable space exploration solutions demand that all lifecycle phases be optimized. Adopting PLM, which has been used by the automotive industry for many years, for aerospace applications provides a foundation for strong, disciplined systems engineering and accountable return on investment by making lifecycle considerations variables in an iterative decision-making process. This paper combines the perspectives of the founding father of PLM, along with the experience of Engineering leaders who are implementing these processes and practices real-time. As the nation moves from an industrial-based society to one where information is a valued commodity, future NASA programs and projects will benefit from the experience being gained today for the exploration missions of tomorrow.

Caruso, Pamela W.↗