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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predicting Search Task Difficulty through a Discrete‐Time Action Log Representation on Spectrum Kernel

ABSTRACT Predicting perceived difficulty on a web search task is an open problem in the interactive information retrieval field. A common approach to tackle it, is through features obtained from full search sessions, which are then used to train classification models. In this poster we attempt to predict perceived task difficulty at different stages of the search process. To do so, we use the spectrum kernel for support vector machine (SVM) classification. Our preliminary results suggest that by using behavioral data from the first query segment, it is possible to provide timely classifications of whether a search task is perceived as hard or easy.

Gacitúa, Daniel↗
DOE OSTI2022

Universality (beyond leading log) of soft radiative corrections to $\hat q$ in $p_\perp$ broadening and energy loss

It has been known for many years that soft radiation can give potentially large double-logarithm corrections to $p_\perp$ broadening of a high-energy particle traveling through QCD matter, but that this soft radiation correction can be absorbed into an effective value $\hat q_{eff}$ for the medium $p_\perp$-broadening parameter $\hat q$. Here ``soft'' means high energy compared to medium scales but soft compared to the original high-energy particle traveling through the medium. A similar situation arises in the case of soft corrections to hard splitting of a high-energy particle, such as hard g → gg, where double logarithms can also be absorbed using the same effective $\hat q_{eff}$. In this paper, I study whether the same holds true for potentially large, subleading, {\it single}-logarthim corrections. The correspondence is more indirect for single logarithms, but I show (in the large-$N_c$ limit) that single logarithms from soft radiation in the case of $p_\perp$ broadening also determine the single logarithms from soft radiative corrections to hard g → gg splitting. Along the way, there is an interesting variation of the original BDMPS-Z calculation of splitting rates in the q(hat) approximation. I also discuss how, for soft-radiative corrections to hard splitting processes, there are two different types of ''$\hat q_{eff}$'' that come into play, which differ by ''$i\pi$'' terms that multiply single logarithms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Coherent gluon radiation: beyond leading-log accuracy

Abstract Results are presented for the medium-induced, soft coherent radiation spectrum for all 2 → 2 partonic channels in QCD, at leading-order inα s but beyond leading logarithmic accuracy. The general formula is valid in the full kinematic range of the underlying process, and reduces to previous results in special cases. The soft gluon radiation spectrum is expressed in terms of thecolor density matrixspecific to each channel, quantifying the entanglement between the color components of the 2 → 2 production amplitude. Beyond the leading logarithm, the spectrum depends explicitly on the off-diagonal elements of this matrix, owing to the soft gluon’s ability to probe the internal color structure of the parton pair.

Physics↗
DOE OSTI2024

Fracture Characterization Via AI‐Assisted Analysis of Temperature Logs

Abstract Fractures control fluid flow, mass transport, and heat transfer in a geothermal reservoir. This makes accurate characterization of fracture networks a prerequisite for optimal design and control of a reservoir's exploitation. We develop a deep‐learning procedure to identify fracture locations via interpretation of temporally and spatially continuous downhole temperature measurements. A long short‐term memory fully convolutional network (LSTM‐FCN) is used both to capture long‐term dependencies in sequential temperature data and to distill local features around fractures. A wellbore and fractured‐reservoir thermal model is established to generate temperature data for network training. The trained LSTM‐FCN exhibits a unique ability to detect multiple fractures intersecting a borehole. We use the LSTM‐FCN algorithm to evaluate the effectiveness of different‐stage wellbore temperature measurements on fracture detection in a complex fractured system. Our experiments reveal that the use of various‐stage temperature information as an input feature set improves the robustness of fracture detection to noise interference. This study indicates the practical feasibility of obtaining accurate fracture‐network reconstructions from temperature signals, at reasonable computational cost.

Yang, Xiaoyu↗
DOE OSTI2020

A log-barrier Newton-CG method for bound constrained optimization with complexity guarantees

Abstract We describe an algorithm based on a logarithmic barrier function, Newton’s method and linear conjugate gradients that seeks an approximate minimizer of a smooth function over the non-negative orthant. We develop a bound on the complexity of the approach, stated in terms of the required accuracy and the cost of a single gradient evaluation of the objective function and/or a matrix-vector multiplication involving the Hessian of the objective. The approach can be implemented without explicit calculation or storage of the Hessian.

O’Neill, Michael↗
DOE OSTI2024

Sudakov double logs in single-inclusive hadron production in DIS at small x from the color glass condensate formalism

We investigate the high Q 2 (photon virtuality) limit of single-inclusive hadron production in deep inelastic scattering at small x , using the color glass condensate formalism at next-to-leading order. We focus on the Λ QCD 2 ≪ p h 2 ≪ Q 2 kinematic regime, where p h is the produced hadron transverse momentum, and extract the Sudakov double logarithms. We further argue that compatibility between the color glass condensate calculation and transverse momentum dependent distribution factorization at one-loop order can only be achieved if the small-x evolution is kinematically constrained. Published by the American Physical Society 2024

Altinoluk, Tolga (ORCID:0000000182671331)↗
DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗