Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “hydra”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydra Network Automatic Configuration (Hydra Autoconfig) v1

Hydra Autoconfig is an algorithm and software program to automatically configure a resilient network of independent ASICs that are capable of being connected as a Hydra network. The Hydra network itself is described in an invention disclosure titled: "Ad-Hoc Networks of Readout ASICs for Reliable Detector Instrumentation" (2020-091). The Hydra Autoconfig software works by first configuring a Hydra node. Then it recursively builds a Hydra network by attempting to link to each available upstream node in succession, keeping links that are verified. It then repeats on each newly generated node until no possible links remain. Once it is so configured, a reliable Hydra network of ASICs remains that can be reconfigured later to respond to damage or malfunction of one or more of the constituent ASICs.

Grace, Carl↗
DOE OSTI2012

Implosion and burn of fast ignition capsules-Calculations with HYDRA

We present a methodology for conducting the design calculations for fast ignition indirect-drive implosions with an embedded cone for introducing a second laser beam to ignite the compressed fuel. These calculations are tuned to achieve several design goals. We demonstrate a major feature of the implosion simulations, the lagging of the implosions along the cone. Possible avenues for enhancing the coupling of the fast electrons to the dense compressed DT fuel are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1983

The effect of fast and regeneration in light versus dark on regulation in the hydra-algal symbiosis

Green hydra are able to regenerate tentacles after fast durations which cause brown, i.e., asymbiotic, hydra to fail completely, but the presence of endosymbiotic algae does not always enhance regeneration in fasted hydra. Green hydra whose nutritional state falls below some threshold, exhibit a light induced inhibition of regeneration. That is, hydra, fasted in the light, then randomly assigned to light or dark after decapitation, regenerate better in the dark. This effect of light does not appear to be present either in brown hydra or in normally green hydra from which the algae were removed. In a large strain of Chlorohydra viridissima, after fasts of intermediate duration (10 and 15 days), this light induced inhibition of regeneration is associated with an increase in the number of algae per gastric cell in regenerating hydra relative to non-regenerating controls.

Bossert, P.↗
DOE OSTI2024

Hydra: Computer Vision for Online Data Quality Monitoring

Hydra is a system utilizing computer vision for near real-time data quality monitoring. Currently operational across all of Jefferson Lab’s experimental halls, it reduces the workload of shift takers by autonomously monitoring diagnostic plots during experiments. Hydra uses "off-the-shelf" supervised learning technologies and is supported by a comprehensive MySQL database. To simplify access, web apps have been developed to facilitate both labeling and monitoring of Hydra’s inferences. Hydra can connect with the alarm system and incorporates complete historical tracking, enabling it to identify issues that shift takers could miss. When issues are detected, a natural first question is: "Why does Hydra think there is a problem?" To answer, Hydra employs Gradient-weighted Class Activation Maps (GradCAM) to identify regions of the image that are important for the specific classification. This interpretive layer enhances transparency and trustworthiness, which is essential for integration with experiment workflows and operation. The Hydra system, results, and sociological considerations for deployment will be discussed.

Jeske, Torri↗
DOE OSTI2025

Hydra: An AI-Based Framework for Interpretable and Portable Data Quality Monitoring

Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7 during experiments. Generally, these sets of images are produced at a rate and quantity that is exceedingly difficult for shift crews to effectively monitor. Significant effort has been devoted to enhancing Hydra’s user interface, to ensure that it provides clear, actionable insights for shift workers and other users. Gradient Weighted Class Activation Maps (GradCAM) provide added interpretability, allowing users to visualize important regions of the image for classification. Hydra has been containerized to enable the creation of portable demos and seamless integration with container-based technologies such as Kubernetes and Docker. With the user interface enhancements and containerization, Hydra can be rapidly deployed for new use cases and experiments. This talk will describe the Hydra framework, its user interface and experience, and the challenges inherent in its design and deployment.

Britton, Thomas [Thomas Jefferson National Acceler↗
DOE OSTI2013

Astrometry and orbits of Nix, Kerberos, AND Hydra

We present new Hubble Space Telescope observations of three of Pluto's outer moons, Nix, Kerberos, and Hydra. This work revises previously published astrometry of Nix and Hydra from 2002 to 2003. New data from a four-month span during 2007 include observations designed to better measure the positions of Nix and Hydra. A third data set from 2010 also includes data on Nix and Hydra as well as some pre-discovery observations of Kerberos. The data were fitted using numerical point-spread function (PSF) fitting techniques to get accurate positions but also to remove the extended wings of the Pluto and Charon PSFs when working on these faint satellites. The resulting astrometric data were fitted with two-body Keplerian orbits that are useful for short-term predictions of the future positions of these satellites for stellar occultation and for guiding encounter planning for the upcoming New Horizons flyby of the Pluto system. The mutual inclinations of the satellites are all within 0.°2 of the plane of Charon's orbit. The periods for all continue to show that their orbits are near but distinct from integer period ratios relative to Charon. Based on our results, the period ratios are Hydra:Charon = 5.98094 ± 0.00001, Kerberos:Charon = 5.0392 ± 0.0003, and Nix:Charon = 3.89135 ± 0.00001. Based on period ratios alone, there is a trend of increased distance from an integer period ratio with decreasing distance from Charon. Our analysis shows that orbital uncertainties for Nix and Hydra are now low enough to permit useful stellar occultation predictions and for New Horizons encounter planning. In 2015 July, our orbits predict a position error of 60 km for Nix and 38 km for Hydra, well below other limiting errors that affect targeting. The orbit for Kerberos, however, still needs a lot of work as its uncertainty in 2015 is quite large at 22,000 km based on these data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Hydra: Computer Vision for Data Quality Monitoring

Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.

Roy, Ayan↗
DOE OSTI2016

Evidence that Hydra I is a tidally disrupting Milky Way dwarf galaxy

The Eastern Banded Structure (EBS) and Hydra I halo overdensities are very nearby (d ∼ 10 kpc) objects discovered in Sloan Digital Sky Survey (SDSS) data. Previous studies of the region have shown that EBS and Hydra I are spatially coincident, cold structures at the same distance, suggesting that Hydra I may be the EBS's progenitor. We combine new wide-field Dark Energy Camera (DECam) imaging and MMT/Hectochelle spectroscopic observations of Hydra I with SDSS archival spectroscopic observations to quantify Hydra I's present-day chemodynamical properties, and to infer whether it originated as a star cluster or dwarf galaxy. While previous work using shallow SDSS imaging assumed a standard old, metal-poor stellar population, our deeper DECam imaging reveals that Hydra I has a thin, well-defined main sequence turnoff of intermediate age (∼5–6 Gyr) and metallicity ([Fe/H] = −0.9 dex). We measure statistically significant spreads in both the iron and alpha-element abundances of σ{sub [Fe/H]}=0.13±0.02 dex and σ{sub [α/Fe]}=0.09±0.03 dex, respectively, and place upper limits on both the rotation and its proper motion. Hydra I's intermediate age and [Fe/H]—as well as its low [α/Fe], apparent [Fe/H] spread, and present-day low luminosity—suggest that its progenitor was a dwarf galaxy, which has subsequently lost more than 99.99% of its stellar mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

CIRCUMBINARY CHAOS: USING PLUTO'S NEWEST MOON TO CONSTRAIN THE MASSES OF NIX AND HYDRA

The Pluto system provides a unique local laboratory for the study of binaries with multiple low-mass companions. In this paper, we study the orbital stability of P4, the most recently discovered moon in the Pluto system. This newfound companion orbits near the plane of the Pluto-Charon (PC) binary, roughly halfway between the two minor moons Nix and Hydra. We use a suite of few body integrations to constrain the masses of Nix and Hydra, and the orbital parameters of P4. For the system to remain stable over the age of the solar system, the masses of Nix and Hydra likely do not exceed 5 Multiplication-Sign 10{sup 16} kg and 9 Multiplication-Sign 10{sup 16} kg, respectively. These upper limits assume a fixed mass ratio between Nix and Hydra at the value implied by their median optical brightness. Our study finds that stability is more sensitive to their total mass and that a downward revision of Charon's eccentricity (from our adopted value of 0.0035) is unlikely to significantly affect our conclusions. Our upper limits are an order of magnitude below existing astrometric limits on the masses of Nix and Hydra. For a density at least that of ice, the albedos of Nix and Hydra would exceed 0.3. This constraint implies they are icy, as predicted by giant impact models. Even with these low masses, P4 only remains stable if its eccentricity e {approx}< 0.02. The 5:1 commensurability with Charon is particularly unstable, combining stability constraints with the observed mean motion places the preferred orbit for P4 just exterior to the 5:1 resonance. These predictions will be tested when the New Horizons satellite visits Pluto. Based on the results for the PC system, we expect that circumbinary, multi-planet systems will be more widely spaced than their singleton counterparts. Further, circumbinary exoplanets close to the three-body stability boundary, such as those found by Kepler, are less likely to have other companions nearby.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Spectroscopic confirmation of the dwarf galaxies hydra II and Pisces II and the globular cluster Laevens 1

We present Keck/DEIMOS spectroscopy of stars in the recently discovered Milky Way satellites Hydra II, Pisces II, and Laevens 1. We measured a velocity dispersion of 5.4{sub −2.4}{sup +3.6} km s{sup −1} for Pisces II, but we did not resolve the velocity dispersions of Hydra II or Laevens 1. We marginally resolved the metallicity dispersions of Hydra II and Pisces II but not Laevens 1. Furthermore, Hydra II and Pisces II obey the luminosity–metallicity relation for Milky Way dwarf galaxies (〈[Fe/H]〉=−2.02±0.08 and −2.45±0.07, respectively), whereas Laevens 1 does not (〈[Fe/H]〉=−1.68±0.05). The kinematic and chemical properties suggest that Hydra II and Pisces II are dwarf galaxies, and Laevens 1 is a globular cluster. We determined that two of the previously observed blue stars near the center of Laevens 1 are not members of the cluster. A third blue star has ambiguous membership. Hydra II has a radial velocity 〈v{sub helio}〉=303.1±1.4 km s{sup −1}, similar to the leading arm of the Magellanic stream. The mass-to-light ratio for Pisces II is 370{sub −240}{sup +310} M{sub ⊙}/L{sub ⊙}. It is not among the most dark matter-dominated dwarf galaxies, but it is still worthy of inclusion in the search for gamma-rays from dark matter self-annihilation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Hydra-TH User's Manual, Dated: December 1, 2011 (V.LA-CC-11-120)

Hydra-TH is a hybrid finite-element/finite-volume code built using the Hydra toolkit specifically to attack a broad class of incompressible, viscous fluid dynamics problems prevalent in the thermal-hydraulics community. The purpose for this manual is provide sufficient information for an experience analyst to use Hydra-TH in an effective way. The Hydra-TH User's Manual present a brief overview of capabilities and visualization interfaces. The execution and restart models are described before turning to the detailed description of keyword input. Finally, a series of example problems are presented with sufficient data to permit the user to verify the local installation of Hydra-TH, and to permit a convenient starting point for more detailed and complex analyses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Nonlinear elasticity and short-range mechanical coupling govern the rate and symmetry of mouth opening in Hydra

Hydra has a tubular bilayered epithelial body column with a dome-shaped head on one end and a foot on the other. Hydra lacks a permanent mouth: its head epithelium is sealed. Upon neuronal activation, a mouth opens at the apex of the head which can exceed the body column diameter in seconds, allowing Hydra to ingest prey larger than itself. While the kinematics of mouth opening are well characterized, the underlying mechanism is unknown. We show that Hydra mouth opening is generated by independent local contractions that require tissue-level coordination. We model the head epithelium as an active viscoelastic nonlinear spring network. The model reproduces the size, timescale and symmetry of mouth opening. It shows that radial contractions, travelling inwards from the outer boundary of the head, pull the mouth open. Nonlinear elasticity makes mouth opening larger and faster, contrary to expectations. Here, the model correctly predicts changes in mouth shape in response to external forces. By generating innervated : nerve-free chimera in experiments and simulations, we show that nearest-neighbor mechanical signaling suffices to coordinate mouth opening. Hydra mouth opening shows that in the absence of long-range chemical or neuronal signals, short-range mechanical coupling is sufficient to produce long-range order in tissue deformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Integration of Hydra-TH in VERA (L2 Milestone THM.CFD.P5.01)

This report describes the work carried out for completion of the Thermal Hydraulics Methods (THM) Level 2 Milestone THM.CFD.P5.01 for the Consortium for Advanced Simulation of Light Water Reactors (CASL). This milestone focused primarily on the initial integration of Hydra-TH in VERA. The primary objective for this milestone was the integration of Hydra-TH as a standalone executable in VERA. A series of code extensions/modifications have been made to Hydra-TH to facilitate integration of Hydra-TH in VERA and to permit future tighter integration and physics coupling. A total of 61 serial and 64 parallel regression tests have been supplied with Hydra-TH. These tests are are being executed in the TriBITS environment. Once the VERA team enables the full suite of tests, the results can be posted to the VERA CDash site. Future work will consider the use of the LIME 2.0 interface for tighter integration in VERA with additional efforts focused on multiphysics coupling with radiation transport, fuel performance, and solid/structural mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Performance Characteristics of HYDRA - a Multi-Physics simulation code from Lawrence Livermore National Laboratory

HYDRA is used to simulate a variety of experiments carried out at the National Ignition Facility (NIF) [4] and other high energy density physics facilities. HYDRA has packages to simulate radiation transfer, atomic physics, hydrodynamics, laser propagation, and a number of other physics effects. HYDRA has over one million lines of code and includes both MPI and thread-level (OpenMP and pthreads) parallelism. This paper measures the performance characteristics of HYDRA using hardware counters on an IBM BlueGene/Q system. We report key ratios such as bytes/instruction and memory bandwidth for several different physics packages. The total number of bytes read and written per time step is also reported. We show that none of the packages which use significant time are memory bandwidth limited on a Blue Gene/Q. HYDRA currently issues very few SIMD instructions. The pressure on memory bandwidth will increase if high levels of SIMD instructions can be achieved.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

HYDRA: High Speed Simulation Architecture for Precision Spacecraft Formation Flying

This viewgraph presentation describes HYDRA, which is architecture to facilitate high-fidelity and real-time simulation of formation flying missions. The contents include: 1) Motivation; 2) Objective; 3) HYDRA-Description and Overview; 4) HYDRA-Hierarchy; 5) Communication in HYDRA; 6) Simulation Specific Concerns in HYDRA; 7) Example application (Formation Acquisition); and 8) Sample Problem Results.

simpulations↗