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

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Attitude determination and calibration using a recursive maximum likelihood-based adaptive Kalman filter

An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.

Kelly, D. A.↗
NASA NTRS1993

Maximum-Likelihood Detection Of Noncoherent CPM

Simplified detectors proposed for use in maximum-likelihood-sequence detection of symbols in alphabet of size M transmitted by uncoded, full-response continuous phase modulation over radio channel with additive white Gaussian noise. Structures of receivers derived from particular interpretation of maximum-likelihood metrics. Receivers include front ends, structures of which depends only on M, analogous to those in receivers of coherent CPM. Parts of receivers following front ends have structures, complexity of which would depend on N.

Divsalar, Dariush↗
NASA NTRS1991

On the use of maximum likelihood estimation for the assembly of Space Station Freedom

Distributed parameter models of the Solar Array Flight Experiment, the Mini-MAST truss, and Space Station Freedom assembly are discussed. The distributed parameter approach takes advantage of (1) the relatively small number of model parameters associated with partial differential equation models of structural dynamics, (2) maximum-likelihood estimation using both prelaunch and on-orbit test data, (3) the inclusion of control system dynamics in the same equations, and (4) the incremental growth of the structural configurations. Maximum-likelihood parameter estimates for distributed parameter models were based on static compliance test results and frequency response measurements. Because the Space Station Freedom does not yet exist, the NASA Mini-MAST truss was used to test the procedure of modeling and parameter estimation. The resulting distributed parameter model of the Mini-MAST truss successfully demonstrated the approach taken. The computer program PDEMOD enables any configuration that can be represented by a network of flexible beam elements and rigid bodies to be remodeled.

Taylor, Lawrence W., Jr.↗
NASA NTRS1993

Maximum-likelihood block detection of noncoherent continuous phase modulation

This paper examines maximum-likelihood block detection of uncoded full response CPM over an additive white Gaussian noise (AWGN) channel. Both the maximum-likelihood metrics and the bit error probability performances of the associated detection algorithms are considered. The special and popular case of minimum-shift-keying (MSK) corresponding to h = 0.5 and constant amplitude frequency pulse is treated separately. The many new receiver structures that result from this investigation can be compared to the traditional ones that have been used in the past both from the standpoint of simplicity of implementation and optimality of performance.

Simon, Marvin K.↗
NASA NTRS1994

Digital combining-weight estimation for broadband sources using maximum-likelihood estimates

An algorithm described for estimating the optimum combining weights for the Ka-band (33.7-GHz) array feed compensation system is compared with the maximum-likelihood estimate. This provides some improvement in performance, with an increase in computational complexity. However, the maximum-likelihood algorithm is simple enough to allow implementation on a PC-based combining system.

Rodemich, E. R.↗
NASA NTRS1994

Closed-loop carrier phase synchronization techniques motivated by likelihood functions

This article reexamines the notion of closed-loop carrier phase synchronization motivated by the theory of maximum a posteriori phase estimation with emphasis on the development of new structures based on both maximum-likelihood and average-likelihood functions. The criterion of performance used for comparison of all the closed-loop structures discussed is the mean-squared phase error for a fixed-loop bandwidth.

Tsou, H.↗
NASA NTRS1998

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes: A Recursive Maximum Likelihood Decoding - Part 3

The Viterbi algorithm is indeed a very simple and efficient method of implementing the maximum likelihood decoding. However, if we take advantage of the structural properties in a trellis section, other efficient trellis-based decoding algorithms can be devised. Recently, an efficient trellis-based recursive maximum likelihood decoding (RMLD) algorithm for linear block codes has been proposed. This algorithm is more efficient than the conventional Viterbi algorithm in both computation and hardware requirements. Most importantly, the implementation of this algorithm does not require the construction of the entire code trellis, only some special one-section trellises of relatively small state and branch complexities are needed for constructing path (or branch) metric tables recursively. At the end, there is only one table which contains only the most likely code-word and its metric for a given received sequence r = (r(sub 1), r(sub 2),...,r(sub n)). This algorithm basically uses the divide and conquer strategy. Furthermore, it allows parallel/pipeline processing of received sequences to speed up decoding.

Lin, Shu↗
NASA NTRS2000

The Extended-Image Tracking Technique Based on the Maximum Likelihood Estimation

This paper describes an extended-image tracking technique based on the maximum likelihood estimation. The target image is assume to have a known profile covering more than one element of a focal plane detector array. It is assumed that the relative position between the imager and the target is changing with time and the received target image has each of its pixels disturbed by an independent additive white Gaussian noise. When a rotation-invariant movement between imager and target is considered, the maximum likelihood based image tracking technique described in this paper is a closed-loop structure capable of providing iterative update of the movement estimate by calculating the loop feedback signals from a weighted correlation between the currently received target image and the previously estimated reference image in the transform domain. The movement estimate is then used to direct the imager to closely follow the moving target. This image tracking technique has many potential applications, including free-space optical communications and astronomy where accurate and stabilized optical pointing is essential.

Tsou, Haiping↗
NASA NTRS2016

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Climate-change impacts↗
NASA NTRS2020

The Multi-Mission Maximum Likelihood Framework threeML: Multi-wavelength Astronomy in Practice

The Multi-Mission Maximum Likelihood framework (threeML)is a flexi-ble python-based framework for multiwavelength data analysis in astronomy. ThreeMLallows joint likelihood fits of data recorded by many different instruments, from radio to gamma rays. This is achieved by encapsulating data access into instrument-specific plugins, leaving the rest of the analysis agnostic of the data format. In this paper, I out-line threeML’s design and major components, with a focus on the modeling language(astromodels) and the data-access plugins

Henrike Fleischhack↗
NASA NTRS2022

Landslide Likelihood Prediction using Machine Learning Algorithms

The supply of electricity via power plants is criticalto the operation of many critical infrastructure systems in mod-ern society. Natural hazards can disrupt the power supply, causepower outages that can halt economic growth, and impede emer-gency response until power is restored. The proposed work aimsto predict the landslides likelihood in these critical infrastructurelocations in the Northeastern USA using integrated databases ofexplanatory variables and machine learning algorithms. First,data related to landslides are obtained and merged, includingtopographic, soil moisture, and precipitation-related data. Fiveregression algorithms, namely: Random Forest, Extreme Gradi-ent Boosting (XGBoost), K-Nearest Neighbor regression (KNN),Linear Support Vector Regressor (SVR), and Linear regression,are utilized to predict the landslide probability and evaluatedon the dataset. The accuracy of the models is assessed by usingstatistical metrics such as mean absolute error (MAE), meansquared error (MSE), and root mean squared error (RMSE).The study results show that Random Forest outperformed othermodels with the mutual information feature selection method.It achieved an MSE of 0.0011 with mutual information-basedfeature selection and an MSE of 0.00157 without feature selection.KNN regressor outperformed the other models with an MSEof 0.00139 with correlation-based information selection. Theproposed landslide identification model with Random Forestalgorithm shows outstanding robustness and great potential intackling the landslide likelihood prediction by employing MLalgorithms.

Vasundhara Acharya↗
NASA NTRSDate not supplied

Frequency Domain Quasi Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - Estimate noise parameters - Extra outputs mean extra parameters to estimate - Usually assume noise model to simplify - Output Error and Equation Error - Results in biased estimates of the parameters - Sensing flexible aircraft have many outputs - Quasi maximum likelihood exploits redundancy of outputs

Jeffrey Ouellette↗
DOE OSTI2017

Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses

We present the methodology for and detail the implementation of the Dark Energy Survey (DES) 3x2pt DES Year 1 (Y1) analysis, which combines configuration-space two-point statistics from three different cosmological probes: cosmic shear, galaxy-galaxy lensing, and galaxy clustering, using data from the first year of DES observations. We have developed two independent modeling pipelines and describe the code validation process. We derive expressions for analytical real-space multi-probe covariances, and describe their validation with numerical simulations. We stress-test the inference pipelines in simulated likelihood analyses that vary 6-7 cosmology parameters plus 20 nuisance parameters and precisely resemble the analysis to be presented in the DES 3x2pt analysis paper, using a variety of simulated input data vectors with varying assumptions. We find that any disagreement between pipelines leads to changes in assigned likelihood $\Delta \chi^2 \le 0.045$ with respect to the statistical error of the DES Y1 data vector. We also find that angular binning and survey mask do not impact our analytic covariance at a significant level. We determine lower bounds on scales used for analysis of galaxy clustering (8 Mpc$~h^{-1}$) and galaxy-galaxy lensing (12 Mpc$~h^{-1}$) such that the impact of modeling uncertainties in the non-linear regime is well below statistical errors, and show that our analysis choices are robust against a variety of systematics. These tests demonstrate that we have a robust analysis pipeline that yields unbiased cosmological parameter inferences for the flagship 3x2pt DES Y1 analysis. We emphasize that the level of independent code development and subsequent code comparison as demonstrated in this paper is necessary to produce credible constraints from increasingly complex multi-probe analyses of current data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Decision trees for incorporating the likelihood of excessive hydrologic alteration into hydropower-ecosystem tradeoffs

Detrimental ecological impacts have often been observed or anticipated when changes in streamflow indicators exceed percent deviation thresholds believed to be ecologically critical. Yet, short pre- and post-impact flow records often make it difficult to determine whether changes exceeding tolerable thresholds are due to dam operations or natural variability. Through a hypothetical reservoir operations example, we incorporate the uncertainty of dam-induced streamflow changes into a Bayesian decision tree framework that evaluates tradeoffs between expected regrets associated with hydropower and ecology. The likelihood of over-protection (type I) and under-protection (type II) errors associated with hypothesis tests are used to compute expected hydropower and ecosystem regrets associated with dam operation decisions. We examine changes to high (annual Q5) and low flows (annual Q95) in typical years using a modified and extended nonparametric ranked-sum test that accounts for percent deviation thresholds. A multiple comparison test is then used to determine the likelihood of at least one threshold violation. An example shows that our decision-theoretic approach can lead to different dam operation recommendations than do other common methods, and highlights limitations that arise when the type I error rate is selected a priori. While we illustrate a hydropower-ecosystem tradeoff, our approach can also be applied to other multi-stakeholder reservoir and river management conflicts.

Bayesian decision-making, environmental flows, flo↗
DOE OSTI2023

System and method for identifying objects of interest in images based on likelihood map decluttering

An automatic threat recognition system and method is disclosed for scanning the x-ray CT image of an article to identify the objects of interest (OOIs) contained within the article, which are otherwise not always quickly apparent or discernable to an individual. The system uses a computer to receive information from two-dimensional (2D) image slices from a reconstructed computed tomography (CT) scan image and to produce a plurality of voxels for each slice of the 2D image. The computer analyzes the voxels to create a likelihood map (LM) representing likelihoods that voxels making up the CT image are associated with a material of interest (MOI). The computer further analyzes the LM to construct neighborhoods of voxels within the LM, and classifies each voxel neighborhood based on its features, thereby decluttering the LM to facilitate the process of connecting voxels of a like MOI together to form segments. The computer classifies each candidate segment based on its features, thereby identifying those segments that correspond to objects of interest.

Paglieroni, David W.↗
DOE OSTI2015

Analysis of the likelihood of post-closure criticality in a geological disposal facility - 14349

Radioactive Waste Management (RWM) is responsible for implementing geological disposal of the UK's higher activity radioactive wastes. These wastes include significant quantities of fissile nuclides and, therefore, demonstration of the criticality safety of the wastes under disposal conditions forms an important component of RWM's disposal system safety case. At the time of disposal, controls will ensure that all waste packages are sub-critical, and the containment provided by the engineered barrier system of a geological disposal facility (GDF) will ensure that criticality is prevented for some time after disposal. However, as waste packages begin to degrade, fissile and other materials may be mobilised, which could affect the potential for criticality. Therefore, the possibility for the evolution of conditions in a GDF to result in criticality requires assessment. RWM established the 'Likelihood of Criticality' research project to develop qualitative and quantitative arguments to demonstrate that criticality after closure of a GDF is unlikely. The project included consideration of the criticality safety of disposal concepts for intermediate and high level waste, spent fuel, separated plutonium and highly-enriched uranium in different generic geological settings. The results are underpinned by the construction of post-closure criticality scenarios that have been evaluated using high-level judgments about scenario credibility as well as modelling of evolving conditions in a GDF. In the latter case, a probabilistic modelling approach has been undertaken to address uncertainty in the calculation of concentrations and masses of fissile material that could occur at potential accumulation sites. The potential for criticality has been judged based on comparisons of the calculated fissile masses with minimum values required for criticality at different locations in the barrier system. This paper explains the novel approach taken to evaluating the likelihood of criticality in a GDF based on the probabilistic modelling of waste package evolution and plutonium and uranium migration. The role of this research in RWM's work to demonstrate the criticality safety of a GDF in the UK is presented in a companion paper, which also draws on the results of a parallel research project that demonstrates that, even if a criticality were to occur, then its consequences would be insignificant to GDF performance. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Gamma-Ray Point-Source Localization and Sparse Image Reconstruction using Poisson Likelihood

Gamma-ray imaging trys to reconstruct the spatial and intensity distribution of gamma-emitting radionuclides from a set of measurements. Wholly, this problem is solved by discretizing the spatial dimensions and employing the maximum likelihood expectation maximization (ML-EM) algorithm, with or without some form of regularization. While the generality of this formulation enables use in a wide variety of scenarios, it is susceptible to overfitting, limited by the discretization of spatial coordinates, and can be computationally expensive. We present a novel approach to 3D gamma-ray image reconstruction for scenarios where sparsity may be assumed, for example radiological source search. In this work we first formulate a point-source localization (PSL) approach as an optimization problem where both position and source intensity are continuous variables. We then extend and generalize this formulation to an iterative algorithm called additive point-source localization (APSL) for sparse parametric image reconstruction. A set of simulated source search scenarios using a single non-directional detector are considered, finding improved image accuracy and computational efficiency with APSL over traditional grid-based methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗