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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Information Loss Via Visual Assessment of Radiologic Images Using Modified Version of the Low-Contrast Detailed Phantom at Direct DR System

Quality in radiology images can be assessed by determining the levels of information retained or lost in an image. Information loss in images has been recently assessed via a method based on information theory and the employment of a contrast-detail (CD) phantom. In this study, the traditional CD phantom (air-Perspex) and a modified CD phantom were used.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Low-resolution gamma-ray spectrometry for an information barrier based on a multi-criteria template-matching approach

Gamma-ray spectrometry has been successfully employed to identify unique items containing special nuclear materials. Template information barriers have been developed in the past to confirm items as warheads by comparing their gamma signature to the signature of true warheads. Their development has, however, not been fully transparent, and they may not be sensitive to some relevant evasion scenarios. Here, we develop a fully open template information barrier concept, based on low-resolution measurements, which, by design, reduces the extent of revealed sensitive information. The concept is based on three signatures of an item to be compared to a recorded template. The similarity of the spectrum is assessed by a modification of the Kolmogorov–Smirnov test to confirm the isotopic composition. The total gamma count rate must agree with the template as a measure of the projected surface of the object. In order to detect the diversion of fissile material from the interior of an item, a polyethylene mask is placed in front of the detector. Neutrons from spontaneous and induced fission events in the item produce 2.223 MeV gamma rays from neutron capture by hydrogen-1 in the mask. This peak is detected and its intensity scales with the item's fissile mass. This analysis is based on MCNP Monte Carlo simulations of various plutonium configurations suggests that this concept can distinguish a valid item from a variety of invalid ones. The concept intentionally avoids any assumptions about specific spectral features, such as looking for specific gamma peaks of specific isotopes, thereby facilitating a fully unclassified discussion. Finally, by making all aspects public and allowing interested participants to contribute to the development and benchmarking, we enable a more open and inclusive discourse on this matter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Linear models to perform treaty verification tasks for enhanced information security

Linear mathematical models were applied to binary-discrimination tasks relevant to arms control verification measurements in which a host party wishes to convince a monitoring party that an item is or is not treaty accountable. These models process data in list-mode format and can compensate for the presence of variability in the source, such as uncertain object orientation and location. The Hotelling observer applies an optimal set of weights to binned detector data, yielding a test statistic that is thresholded to make a decision. The channelized Hotelling observer applies a channelizing matrix to the vectorized data, resulting in a lower dimensional vector available to the monitor to make decisions. We demonstrate how incorporating additional terms in this channelizing-matrix optimization offers benefits for treaty verification. We present two methods to increase shared information and trust between the host and monitor. The first method penalizes individual channel performance in order to maximize the information available to the monitor while maintaining optimal performance. Second, we present a method that penalizes predefined sensitive information while maintaining the capability to discriminate between binary choices. Data used in this study was generated using Monte Carlo simulations for fission neutrons, accomplished with the GEANT4 toolkit. Custom models for plutonium inspection objects were measured in simulation by a radiation imaging system. Model performance was evaluated and presented using the area under the receiver operating characteristic curve.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improved departure from nucleate boiling prediction in rod bundles using a physics-informed machine learning-aided framework

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is a regulatory limit for the licensing of pressurized water reactors (PWRs) worldwide. Despite the abundance of predictive tools available to the reactor thermal-hydraulics community, the path for an accurate CHF model remains elusive. This work approaches the prediction of DNB through a physics-informed machine learning-aided framework (PIMLAF) with the objective of achieving superior predictive capabilities for a rod bundle. In view of the limitations in existing macro-scale physics-driven tools, an improved mechanistic model is first proposed, leveraging key concepts in the liquid sublayer dryout and bubble crowding mechanisms. Furthermore, the proposed mechanistic model is able to predict DNB in different heater geometries for a broad range of flow conditions without the need for recalibration. This model is then incorporated as the physics-informed component of the hybrid framework PIMLAF, which takes advantage of established understanding in the field (i.e., domain knowledge [DK]) and uses machine learning (ML) to capture undiscovered information from the mismatch between the actual and DK-predicted output. Two bundle-related case studies using the PWR subchannel and bundle tests (PSBT) database are carried out to illustrate the PIMLAF’s improved performance over traditional approaches for both interpolation and extrapolation purposes. In light of the PIMLAF’s promising potential to reduce prediction error, reactor vendors are encouraged to leverage their in-house experimental efforts and apply the hybrid framework to potentially achieve margin reductions in the minimum DNB ratio (MDNBR) for the designs of interest.

42 ENGINEERING↗
DOE OSTI2024

Modeling information flow in a computer processor with a multi-stage queuing model

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into stages, and information can flow from one stage to another. The model is formulated as a spatially-extended, continuous-time Markov chain where space represents different stages. This model is equivalent to a spatially-extended version of the M/M/s queue. The main modeling feature is the throttling function which describes the processor slowdown when the amount of information falls below a certain threshold. We derive the stationary distribution for this stochastic model and develop a closure for a deterministic ODE system that approximates the evolution of the mean and variance of the stochastic model. In conclusion, we demonstrate the validity of the closure with numerical simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Simplifying the Quantum World: Demonstrations for Young Learners in an Informal Setting

A set of modules for the informal learning of quantum science was developed. They include (1) Waves and Bottling Light in Quantum Dots, (2) Quantization of Energy Levels, (3) Particle-Wave Duality, (4) Magnetism and Electron Spin, and (5) Quantum Entanglement. Their teaching objective is to clarify concepts in quantum science, and they have been presented together as part of an hour-long show to ∼250 adults and school-age children. The learning outcomes of the modules were assessed by pre- and postevent quizzes as well as interactive clicker questions. The results suggest effective learning of all of the assessed concepts. These modules are detailed in a way that makes them deployable, together or in part, in other formal or informal settings to support the dissemination of information about quantum science to the general public.

electron spin↗
DOE OSTI2025

Scrambling Signal Modularity in Bottom-up Assembled Synthetic Pseudomonas Consortia Reveals Robust Information Transfer

There is immense potential in crafting synthetic microbial communities for application in human health, agriculture, the environment, and even biomanufacturing where an appropriately constructed consortium can be assembled with tremendous biosynthetic or degradative capabilities. In many of these cases, bacterial signaling serves as a form of intercellular information transfer that guides the collective’s behavior. Such communication is complex, as many signals, signal disruptors, microbial species, physical barriers, and spatiotemporal constraints may be involved. Here, in this work, we demonstrate that a multisignal pathway for molecular information transfer within a consortium of several Pseudomonas spp. can be scrambled (genetically and organizationally) while the original message is still effectively conveyed. Assembled from the bottom up, we have employed two types of signaling molecules (i) a redox active secondary metabolite (rhizospheric signal, phloroglucinol), and (ii) a bacterial quorum sensing signal (3-oxo-C12 acylhomoserine lactone, AI-1). These signals can be intraconverted and acted upon by designated community members. We show how the order in which the signals are received, transduced, and subsequently transmitted can be rearranged with minimal impact on the intended outcome. In the consortial context, we found this messaging structure can be remarkably robust. Inspired by rhizospheric molecular signaling mechanisms, this work provides a conceptual framework for designing signaling and information transfer processes within assembled communities.

Biological and medical sciences↗
DOE OSTI2019

Using Information Theory to Evaluate Directional Precipitation Interactions Over the West Sahel Region in Observations and Models

Water availability has historically been one of the most significant threats to African regional social and economic well-being. Over the Sahel region, a megadrought during the 1960s and 1970s induced by an abrupt and substantial rainfall reduction caused widespread famine and death. The postdrought recovery, which is still ongoing, has been characterized by gradual increases in rainfall, but with dramatic fluctuations. The large negative human impacts, slow recovery, and variability raise important questions of why and how rainfall dynamics evolve and interact with other components of the regional climate system. Here we provide an observational assessment of rainfall interactions mechanisms (informed by directional transfer of information entropy) that regulate Sahel rainfall. We quantitatively demonstrate that (1) sea surface temperature over the Gulf of Guinea controls moisture advection and transport to the West Sahel region and (2) strong bidirectional interactions exist between local vegetation dynamics and rainfall patterns. Then we assess the directional interaction patterns from nine state-of-the-art Earth System Models (ESMs). We find that most ESMs are able to represent either the unidirectional control of sea surface temperature on precipitation or the bidirectional interaction between vegetation and precipitation. However, none of the ESMs represents both interactive patterns. The GFDL and IPSL-CM5A-LR models successfully reproduced observed patterns over ~50% of the West Sahel region but were not accurate in reproducing observed precipitation regional trends or interannual variation. We propose that the directional information transfer is a powerful mechanistic benchmark to assess model fidelity at the process level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗
DOE OSTI2019

Terminator-free template-independent enzymatic DNA synthesis for digital information storage

Abstract DNA is an emerging medium for digital data and its adoption can be accelerated by synthesis processes specialized for storage applications. Here, we describe a de novo enzymatic synthesis strategy designed for data storage which harnesses the template-independent polymerase terminal deoxynucleotidyl transferase (TdT) in kinetically controlled conditions. Information is stored in transitions between non-identical nucleotides of DNA strands. To produce strands representing user-defined content, nucleotide substrates are added iteratively, yielding short homopolymeric extensions whose lengths are controlled by apyrase-mediated substrate degradation. With this scheme, we synthesize DNA strands carrying 144 bits, including addressing, and demonstrate retrieval with streaming nanopore sequencing. We further devise a digital codec to reduce requirements for synthesis accuracy and sequencing coverage, and experimentally show robust data retrieval from imperfectly synthesized strands. This work provides distributive enzymatic synthesis and information-theoretic approaches to advance digital information storage in DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Splash, pop, sizzle: Information processing with phononic computing

Phonons, the quanta of mechanical vibration, are important to the transport of heat and sound in solid materials. Recent advances in the fundamental control of phonons (phononics) have brought into prominence the potential role of phonons in information processing. In this review, the many directions of realizing phononic computing and information processing are examined. Given the relative similarity of vibrational transport at different length scales, the related fields of acoustic, phononic, and thermal information processing are all included, as are quantum and classical computer implementations. Connections are made between the fundamental questions in phonon transport and phononic control and the device level approach to diodes, transistors, memory, and logic. .

36 MATERIALS SCIENCE↗
DOE OSTI2016

Optimal cross-sectional sampling for river modelling with bridges: An information theory-based method

The description of river topography has a crucial role in accurate one-dimensional (1D) hydraulic modelling. Specifically, cross-sectional data define the riverbed elevation, the flood-prone area, and thus, the hydraulic behavior of the river. Here, the problem of the optimal cross-sectional spacing is solved through an information theory-based concept. The optimal subset of locations is the one with the maximum information content and the minimum amount of redundancy. The original contribution is the introduction of a methodology to sample river cross sections in the presence of bridges. The approach is tested on the Grosseto River (IT) and is compared to existing guidelines. The results show that the information theory-based approach can support traditional methods to estimate rivers’ cross-sectional spacing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Two-frequency information recording in a three-level system using stimulated photon echo

The process of recording and reproducing information in a three-level system using stimulated photon echo is studied as a function of the amount of information embedded in the first and second two-frequency object laser pulses. It is shown that two-frequency information recording leads to an increase in the power of the stimulated photon echo response on one frequency transition and to its reduction on the other. (laser applications and other topics in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Sub-quantum Fisher information

We report the quantum Fisher information (QFI) plays a crucial role in quantum information theory and in many practical applications such as quantum metrology. However, computing the QFI is generally a computationally demanding task. In this work we analyze a lower bound on the QFI which we call the sub-quantum Fisher information (sub-QFI). The bound can be efficiently estimated on a quantum computer for an n-qubit state using 2n qubits. The sub-QFI is based on the super-fidelity, an upper bound on Uhlmann's fidelity. We analyze the sub-QFI in the context of unitary families, where we derive several crucial properties including its geometrical interpretation. In particular, we prove that the QFI and the sub-QFI are maximized for the same optimal state, which implies that the sub-QFI is faithful to the QFI in the sense that both quantities share the same global extrema. Based on this faithfulness, the sub-QFI acts as an efficiently computable surrogate for the QFI for quantum sensing and quantum metrology applications. Finally, we provide additional meaning to the sub-QFI as a measure of coherence, asymmetry, and purity loss.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Energy cost of localization of relational quantum information

Entanglement of spatially separated quantum states is usually defined with respect to a reference frame provided by some external observer. Thus, if one wishes to localize the quantum information within a spatially separated entangled state, one must enact an entanglement extraction protocol also defined with respect to that external frame. Entanglement extraction for Gaussian ground states in such an external frame construction has been shown to require a minimum energy and is hence an interesting process for gravitational physics, where examinations of localization vs energy cost have a long history. General covariance, however, precludes dependence on external frames. In order to enact an extraction protocol in a generally covariant theory, dependence on the external reference frame must first be removed and the states made relational. Here, we examine the implementation of an extraction protocol for Gaussian states, whose center of mass and relational degrees of freedom are entangled, in a relational toy model where translation invariance stands in for full diffeomorphism invariance. Constructing fully relational states and the corresponding extraction/localization can, in principle, be done in two ways. External frame position information can be removed through 𝐺-twirling over translations or one can spontaneously break the translation symmetry via the gradient of an auxiliary field, or 𝑍-model. We determine the energetics of quantum information localization after the states have been made fully relational via both the 𝐺-twirl and 𝑍-model. We also show one can obtain the 𝐺-twirl construction from a 𝑍-model as a limit of positive operator valued measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Information Gain Based Dimensionality Selection for Classifying Text Documents

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Improved quality metrics for association and reproducibility in chromatin accessibility data using mutual information

Correlation metrics are widely utilized in genomics analysis and often implemented with little regard to assumptions of normality, homoscedasticity, and independence of values. This is especially true when comparing values between replicated sequencing experiments that probe chromatin accessibility, such as assays for transposase-accessible chromatin via sequencing (ATAC-seq). Such data can possess several regions across the human genome with little to no sequencing depth and are thus non-normal with a large portion of zero values. Despite distributed use in the epigenomics field, few studies have evaluated and benchmarked how correlation and association statistics behave across ATAC-seq experiments with known differences or the effects of removing specific outliers from the data. Here, we developed a computational simulation of ATAC-seq data to elucidate the behavior of correlation statistics and to compare their accuracy under set conditions of reproducibility. Using these simulations, we monitored the behavior of several correlation statistics, including the Pearson’s R and Spearman’s ρ coefficients as well as Kendall’s τ and Top–Down correlation. We also test the behavior of association measures, including the coefficient of determination R 2 , Kendall’s W, and normalized mutual information. Our experiments reveal an insensitivity of most statistics, including Spear man’s ρ, Kendall’s τ, and Kendall’s W, to increasing differences between simulated ATAC-seq replicates. The removal of co-zeros (regions lacking mapped sequenced reads) between simulated experiments greatly improves the estimates of correlation and association. After removing co-zeros, the R 2 coefficient and normalized mutual information display the best performance, having a closer one-to-one relationship with the known portion of shared, enhanced loci between simulated replicates. When comparing values between experimental ATAC-seq data using a random forest model, mutual information best predicts ATAC-seq replicate relationships. Collectively, this study demonstrates how measures of correlation and association can behave in epigenomics experiments. We provide improved strategies for quantifying relationships in these increasingly prevalent and important chromatin accessibility assays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Information security management system planning for CBRN facilities

The focus of this document is to provide guidance for the development of information security management system planning documents at chemical, biological, radiological, or nuclear (CBRN) facilities. It describes a risk-based approach for planning information security programs based on the sensitivity of the data developed, processed, communicated, and stored on facility information systems.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗