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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
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 ↗
DOE OSTI2020

Characterization of elastic mechanical properties of Tuscaloosa Marine Shale from well logs using the vertical transversely isotropic model

To avoid steep declines in the Tuscaloosa Marine Shale (TMS) production, wells are fracture-stimulated to release the hydrocarbons trapped in the matrix of the formation. An accurate estimation of Young’s modulus and Poisson’s ratio is essential for hydraulic fracture propagation. In addition, ignoring the highly heterogeneous and anisotropic character of TMS can lead to erroneous stress values, which subsequently affect hydraulic fracture width estimates and the overall hydraulic fracturing process. We have developed an empirical 1D geomechanical model that takes into account VTI anisotropy, and it is used to characterize the elastic mechanical properties of TMS in two wells. In the analyzed formation, the vertical Poisson’s ratio is less than the horizontal Poisson’s ratio, which suggests the necessity of an alternative to the ANNIE equations. The stiffness coefficients [Formula: see text] and [Formula: see text] were estimated using the relationships developed from the ultrasonic core data available for the two TMS. Further, correlations between the static and dynamic properties from laboratory tests were used to improve the minimum horizontal stress calculation. We compare VTI Young’s moduli, Poisson’s ratios, and minimum horizontal stress with the isotropic solution. VTI modeling improves the estimation of the elastic mechanical properties. The isotropic solution underestimates the minimum horizontal stress in the formation. Moreover, it was shown that the 20 ft shale interval below the TMS base is characterized by a low Young’s modulus (the vertical Young’s modulus is equal to 20 GPa, whereas the horizontal Young’s modulus is equal to 40 GPa) and may be a frac barrier.

Geochemistry & Geophysics↗
DOE OSTI2022

Residual Dose and Environmental Monitoring for the Fermilab Main Injector Tunnel Using the Data Acquisition Logging Engine (Dale)

The Recycler and the Main Injector are part of the Fermilab Accelerator complex used to deliver proton beam to the different experiments. It is very important to control and minimize losses in both machines during operation, to reduce personnel dose from residual activation and to preserve component lifetime. To minimize losses, we need to identify the loss points and adjust the components accordingly. The Data Acquisition Loss Engine (DALE) platform has been developed within the Main Injector department and upgraded throughout the years. DALE is used to survey the entire enclosure for residual dose rates and environmental readings when unrestricted access to the enclosure is possible. Currently DALE has two radiation meters, which are aligned along each machine, so loss points can be identified for both at the same time. DALE attaches to the enclosure carts and is continuously in motion monitoring dose rates and other environmental readings. In this paper we will describe how DALE is used to provide radiation maps of the residual dose rates in the enclosure. We will also compare the loss points with the Beam Loss monitor data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Energy I-Corps Electron Beam (EB) Potential for International Trade of Logs

The purpose of this document is to capture the potential from Fermilab’s “Team EB Treement” at the DOE Energy I-Corps program. Energy I-Corps, a key initiative of the Office of Technology Transitions, pairs teams of researchers with industry mentors for an intensive two-month training where the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. The team was composed prior to the Energy I-Corp program; however, the program was a catalyst for education and information exchange between the team members and stakeholders, customers, and regulators. These exchanges were captured in the evolution of a Business Model Canvas (BMC) and a Value Proposition (VP). The BMC and VP underwent numerous transformations based on feedback from the conversations between members of the team and forest or agriculture industry stakeholders and the program instructors.

43 PARTICLE ACCELERATORS↗