Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data compression”

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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extreme compression of planetary gases: High-accuracy pressure-density measurements of hydrogen-helium mixtures above fourfold compression

Hydrogen (H 2 ) and helium (He), the most abundant elements in the universe, pose a unique challenge in measuring the equation of state of the mixture, owing to their differing physical properties. There remains a need for data with high enough precision to discriminate between existing equation of state (EOS) mix models in order to understand the internal structure of gas-giant planets. Here, we have measured the EOS of precompressed H 2 - He mixtures at conditions directly relevant to the planetary interiors using hypervelocity gas guns and Sandia’s Z machine with less than 10% uncertainty in density, enabling validation of mixture models. We precompressed 50:50 molar mixtures of H 2 -He to 0.1–0.2 GPa and directly measured particle velocity (in gas-gun experiments) and shock velocities (in Z-machine experiments). To complement the experimental efforts, we also computed the Hugoniots of precompressed H 2 -He mixtures using density-functional-theory-based molecular dynamics. Furthermore, we observe approximately 3- to 4.3-fold density compression at pressures up to 44 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Development of a multiphase equation of state for gallium with experiments and ab initio free-energy calculations

Here, we present a five-phase equation of state (EOS) for elemental gallium (Ga) that is developed using both experimental data and new theoretical predictions. Four experimentally observed solid phases (Ga-I, Ga-II, Ga-III, and Ga-IV) and one liquid phase are included. To improve our understanding of the thermal behavior of Ga and its phase boundaries under compression, we have performed ab initio density functional theory (DFT) free-energy calculations for the Ga-III and liquid phases, which enables us to determine the melt temperature to be 2214 ± 100 K at 110 GPa, extending significantly beyond the existing experimental melt data, which are limited to 25 GPa. In order to best describe the electron-thermal contribution, which dominates the liquid free energy at high temperatures, we have carried out averaged-atom-in-jellium DFT calculations to cover the entire temperature and density range of the EOS. The resulting multiphase Ga EOS is able to accurately reproduce a diverse variety of data, including known phase boundaries, the principal Hugoniot, low-pressure liquid isobars, and diamond-anvil-cell isotherm measurements at high pressures. It agrees more closely with key experimentally measured properties than other Ga EOS models targeted for high-pressure applications.

Wu, Christine J. [Lawrence Livermore National Labo↗
DOE OSTI2019

Partial molar properties from molecular simulation using multiple linear regression

Partial molar volumes, energies, and enthalpies can be computed from NpT-Gibbs ensemble simulations through a post-processing procedure that leverages fluctuations in composition, total volume, and total energy of a simulation box. By recording the instantaneous box volumes V and instantaneous number of molecules N i of each of n species for M frames, a large M ×n matrix N is constructed, as well as the M × 1 vector V. The 1 × n vector of partial molar volumes V¯ may then be solved using N • V¯=V. A similar construction permits calculation of partial molar energies using M instantaneous measurements of the total energy of the simulation box, and N • U¯=U. Partial molar enthalpies may be derived from U¯, V¯, and pressure p. These properties may be used to calculate enthalpy and entropy of transfer (absorption, extraction, and adsorption) for species in complex mixtures. The method is demonstrated on three systems in the NpT-Gibbs ensemble: a highly compressible natural gas condensate of methane, n-butane, and n-decane, the liquid-phase adsorption of 1,5-pentanediol and ethanol onto the MFI zeolite, and a relatively incompressible mixture of ethanol, n-dodecane, and water at liquid-liquid equilibrium. Property predictions are compared to those from numerical differentiation of simulation data sequentially changing the composition and from equations of state. Here, the method can also be extended to reaction equilibria in a closed system and is applied to a reactive first-principles Monte Carlo simulation of compressed nitrogen/oxygen.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Effects of carotenoids on lipid bilayers

Carotenoids have been found to be important in improving the integrity of biomembranes in eukaryotes. However, the molecular details of how carotenoids modulate the physical properties of biomembranes are unknown. To this end, we have conducted a series of molecular dynamics simulations of different biologically-relevant membranes in the presence of carotenoids. The carotenoid effect on the membrane was found to be specific to the identity of the carotenoid and the composition of the membrane itself. Therefore, different classes of carotenoids produce a different effect on the membrane, and different membrane phases are affected differently by carotenoids. It is apparent from our data that carotenoids do trigger the bilayer to become thinner. The mechanism by which this occurs depends on two competing factors, the ability of the lipid tails of opposing monolayers to either (1) compress or (2) interdigitate as the bilayer condenses. Indeed, carotenoids directly influence the physical properties via these two mechanisms, thus compacting the bilayer. Furthermore, the degree to which these competing mechanisms are utilized depends on the bilayer phase and the carotenoid identity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Additive Manufactured Materials Studies

The production of additively manufactured (AM) materials, is a growing technology that potentially offers more cost effective ways to produce metallic components for various uses. Mechanical properties of some AM metals have been studied, but more work is needed to better understand their dynamic properties as a function of orientation. Due to the melting and reheating of molten metal during fabrication, these materials tend to have internal porosity and slightly different microstructures along the weldments and normal to the weldments that may cause the materials to behave differently than their forged counterparts. The AM process builds up a part layer by layer, which provides opportunities to tailor geometry and optimize structural performance in addition to minimizing the amount of material waste for oddly shaped parts, thereby reducing cost. These advanced materials hold great promise for revolutionizing design, fabrication, and assembly of engineered components and could be used for many NNSA-specific applications including armoring complex elements of nuclear weapons, and customized diagnostic components in subcritical experiments. We have conducted materials studies in collaboration with the University of Nevada, Las Vegas (UNLV) as well as Los Alamos National Laboratory (LANL) under our Site-Directed Research and Development program and the Nevada Science Initiative. We are currently placing emphasis on quantifying how dynamic properties are affected by directionality and porosity of the material. A study of dynamic failure events in forged, layered, and additive manufactured (AM) titanium alloy subject to hypervelocity impact was conducted in collaboration with UNLV. Experiments were conducted using a two stage light-gas gun, 0.22-caliber Lexan projectiles, and different types of titanium target plates. A four-channel Photonic Doppler Velocimetry (PDV) system was used to study the free surface velocities to provide an understanding of the different failure mechanisms in these materials. The experimental measurements were used to validate computational simulations, which describe the behavior of these materials under shock. It was determined that AM, forged titanium, and multi-layered stacks produce similar velocity profiles during the early stage of impact, with the AM targets exhibiting spall at lower velocities and the multi-layered stacks exhibiting vibrations between plates. Simulations of solid and layered forged materials provide a good match to experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

General search for supersymmetric particles in scenarios with compressed mass spectra using proton-proton collisions at $\sqrt{s}$ = 13 TeV

A general search is presented for supersymmetric particles (sparticles) in scenarios featuring compressed mass spectra using proton-proton collisions at a center-of-mass energy of 13 TeV, recorded with the CMS detector at the LHC. The analyzed data sample corresponds to an integrated luminosity of 138 fb −1 . A wide range of potential sparticle signatures are targeted, including pair production of electroweakinos, sleptons, and top squarks. The search focuses on events with a high transverse momentum system from initial-state-radiation jets recoiling against a potential sparticle system with significant missing transverse momentum. Events are categorized based on their lepton multiplicity, jet multiplicity, number of 𝑏-tagged jets, and kinematic variables sensitive to the sparticle masses and mass splittings. The sensitivity extends to higher parent sparticle masses than previously probed at the LHC for production of pairs of electroweakinos, sleptons, and top squarks with mass spectra featuring small mass splittings (compressed mass spectra). The observed results demonstrate agreement with the predictions of the background-only model. Lower mass limits are set at 95% confidence level on production of pairs of electroweakinos, sleptons, and top squarks that extend to 325, 275, and 780 GeV, respectively, for the most favorable compressed mass regime cases.

Hadron colliders↗
DOE OSTI2014

Structural, magnetic, and superconducting properties of pulsed-laser-deposition-grown La 1.85 Sr 0.15 CuO 4 / La 2 / 3 Ca 1 / 3 MnO 3 superlattices on (001)-oriented LaSrAlO 4 substrates

Epitaxial La 1.85 Sr 0.15 CuO 4 / La 2 / 3 Ca 1 / 3 MnO 3 (LSCO/LCMO) superlattices (SL) on (001)- oriented LaSrAlO 4 substrates have been grown with pulsed laser deposition (PLD) technique. Their structural, magnetic and superconducting properties have been determined with in-situ reflection high energy electron diffraction (RHEED), x-ray diffraction, specular neutron reflectometry, scanning transmission electron microscopy (STEM), electric transport, and magnetization measurements. We find that despite the large mismatch between the in-plane lattice parameters of LSCO (a = 0.3779 nm) and LCMO (a = 0.387 nm) these superlattices can be grown epitaxially and with a high crystalline quality. While the first LSCO layer remains clamped to the LSAO substrate, a sizeable strain relaxation occurs already in the first LCMO layer. The following LSCO and LCMO layers adopt a nearly balanced state in which the tensile and compressive strain effects yield alternating in-plane lattice parameters with an almost constant average value. No major defects are observed in the LSCO layers, while a significant number of vertical antiphase boundaries are found in the LCMO layers. The LSCO layers remain superconducting with a relatively high superconducting onset temperature of T c onset ≈ 36 K. The macroscopic superconducting response is also evident in the magnetization data due to a weak diamagnetic signal below 10 K for H ∥ ab and a sizeable paramagnetic shift for H ∥ c that can be explained in terms of a vortex-pinning-induced flux compression. The LCMO layers maintain a strongly ferromagnetic state with a Curie temperature of T Curie ≈ 190 K and a large low-temperature saturation moment of about 3.5 (1) μ B . These results suggest that the LSCO/LCMO superlattices can be used to study the interaction between the antagonistic ferromagnetic and superconducting orders and, in combination with previous studies on YBCO/LCMO superlattices, may allow one to identify the relevant mechanisms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗
DOE OSTI2021

Energy efficiency of blower heater non-purge compressed air dryers

This research focuses on twin tower regenerative closed loop desiccant dryers, specifically: blower heater non-purge (BHNP) with and without cooling water pumps, compressed-air heater purge (CHP), blower heater purge (BHP) and pressure swing heaterless (PSH). The research was conducted by collecting and analysing real time current draw data on air compressors and associated dryers at eight different facilities (13 air compressors) in terms of energy, power and cost. A decision tool was developed to depict the operational characteristics (power, energy and cost) of each type of dryer if used in conjunction with the selected compressor system. Finally, this research, on an equivalent normalised basis, compared and contrasted the different types of dryers in terms of performance and cost. Here, the research concluded that of the five types of desiccant dryer types observed the most energy efficient was the BHNP (with cooling water pump), subject to the operational conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Fast compressed sensing-based CBCT reconstruction using Barzilai-Borwein formulation for application to on-line IGRT

Purpose: Compressed sensing theory has enabled an accurate, low-dose cone-beam computed tomography (CBCT) reconstruction using a minimal number of noisy projections. However, the reconstruction time remains a significant challenge for practical implementation in the clinic. In this work, we propose a novel gradient projection algorithm, based on the Gradient-Projection-Barzilai-Borwein formulation (GP-BB), that handles the total variation (TV)-norm regularization-based least squares problem for the CBCT reconstruction in a highly efficient manner, with speed acceptable for routine use in the clinic. Methods: CBCT is reconstructed by minimizing an energy function consisting of a data fidelity term and a TV-norm regularization term. Both terms are simultaneously minimized by calculating the gradient projection of the energy function with the step size determined using an approximate Hessian calculation at each iteration, based on the Barzilai-Borwein formulation. To speed up the process, a multiresolution optimization is used. In addition, the entire algorithm was designed to run with a single graphics processing unit (GPU) card. To evaluate the performance, the Shepp-Logan numerical phantom, the CatPhan 600 physical phantom, and a clinically-treated head-and-neck patient were acquired from the TrueBeam system (Varian Medical Systems, Palo Alto, CA). For each scan, in total, 364 projections were acquired in a 200 deg. rotation. The imager has 1024 x 768 pixels with 0.388 x 0.388-mm resolution. This was down-sampled to 512 x 384 pixels with 0.776 x 0.776-mm resolution for reconstruction. Evenly spaced angles were subsampled and used for varying the number of projections for the image reconstruction. To assess the performance of our GP-BB algorithm, we have implemented and compared with three compressed sensing-type algorithms, the two of which are popular and published (forward-backward splitting techniques), and the other one with a basic line-search technique. In addition, the conventional Feldkamp-Davis-Kress (FDK) reconstruction of the clinical patient data is compared as well. Results: In comparison with the other compressed sensing-type algorithms, our algorithm showed convergence in {<=}30 iterations whereas other published algorithms need at least 50 iterations in order to reconstruct the Shepp-Logan phantom image. With the CatPhan phantom, the GP-BB algorithm achieved a clinically-reasonable image with 40 projections in 12 iterations, in less than 12.6 s. This is at least an order of magnitude faster in reconstruction time compared with the most recent reports utilizing GPU technology given the same input projections. For the head-and-neck clinical scan, clinically-reasonable images were obtained from 120 projections in 34-78 s converging in 12-30 iterations. In this reconstruction range (i.e., 120 projections) the image quality is visually similar to or better than the conventional FDK reconstructed images using 364 projections. This represents a dose reduction of nearly 67% (120/364 projections) while maintaining a reasonable speed in clinical implementation. Conclusions: In this paper, we proposed a novel, fast, low-dose CBCT reconstruction algorithm using the Barzilai-Borwein step-size calculation. A clinically viable head-and-neck image can be obtained within {approx}34-78 s while simultaneously cutting the dose by approximately 67%. This makes our GP-BB algorithm potentially useful in an on-line image-guided radiation therapy (IGRT).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids

Here, we discuss the implementation of a finite element method, used to numerically solve the Euler equations of compressible flows, using an asynchronous runtime system (RTS). The algorithm is implemented for distributed-memory machines, using stationary unstructured 3D meshes, combining data-, and task-parallelism on top of the Charm++ RTS. Charm++’s execution model is asynchronous by default, allowing arbitrary overlap of computation and communication. Task-parallelism allows scheduling parts of an algorithm independently of, or dependent on, each other. Built-in automatic load balancing enables continuous redistribution of computational load by migration of work units based on real-time CPU load measurement. The RTS also features automatic checkpointing, fault tolerance, resilience against hardware failure, and supports power-, and energy-aware computation. We demonstrate scalability up to 25 x 10 9 cells at $\mathscr{O}$10 4 compute cores and the benefits of automatic load balancing for irregular workloads. The full source code with documentation is available at https://quinoacomputing.org.

42 ENGINEERING↗
DOE OSTI2022

Modeling the viscoplastic behavior of a semicrystalline polymer

In this study, a complex constitutive relation is identified using inverse modeling with the nominal mechanical response as sole experimental input. The methodology is illustrated for a semicrystalline thermoplastic in the presence of strain localization at finite deformations. The experimental database includes cylindrical tensile bars, compression pins and round notched bars loaded at strain rates spanning up to five decades and temperatures below and above T g . The data is organized into a calibration set and a validation set. The response of tensile specimens is determined using finite element analyses and a two-phase constitutive relation for semicrystalline polymers that accounts for temperature- and rate-sensitive plastic flow, pressure-sensitivity, small-strain softening and large-strain orientational hardening of the amorphous phase, along with the evolution of crystallinity. The large number of constitutive parameters is identified using an optimization tool coupled with the finite element solver and the calibration set from experiments. The methodology is shown to be successful in predicting the response of round notched bars and replicating the effects of temperature and strain rate on the severity of necking in tensile bars. The proposed model identification strategy is both simple and effective in comparison with other elaborate methods that attempt to access intrinsic behavior directly from high-fidelity experimental measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seismic Tremors From Sea‐Landfast Ice Interactions Near Utqiaġvik, Alaska

The mechanical state of Arctic landfast sea ice remains poorly constrained due to limited observations. This study investigates interactions between drifting sea ice and the coastal landfast ice near Utqiaġvik, Alaska by integrating data from broadband seismometer, Distributed Acoustic Sensing, and marine radar. We find that decreases in sea ice velocity, marking transitions from drift to compressive contact, coincide with increased seismic energy. Tremor characteristics vary seasonally with ice conditions. In January, dense ice packs produced sustained harmonic tremors with gliding and U-shaped spectral features, consistent with repetitive stick-slip motion at the ice–ice or ice–ground interface under velocity-weakening friction. In April, smaller fragmented floes generated short-lived, chaotic tremors linked to brittle failure and spatially dispersed impacts. These findings demonstrate that seismic tremors encode the mechanical properties of interacting ice, offering a new tool to distinguish ice regimes and monitor evolving Arctic coastal dynamics under climate change.

58 GEOSCIENCES↗
DOE OSTI2011

A VERY DEEP CHANDRA OBSERVATION OF A2052: BUBBLES, SHOCKS, AND SLOSHING

We present the first results from a very deep ({approx}650 ks) Chandra X-ray observation of A2052, as well as archival Very Large Array radio observations. The data reveal detailed structure in the inner parts of the cluster, including bubbles evacuated by radio lobes of the active galactic nucleus (AGN), compressed bubble rims, filaments, and loops. Two concentric shocks are seen, and a temperature rise is measured for the innermost one. On larger scales, we report the first detection of an excess surface brightness spiral feature. The spiral has cooler temperatures, lower entropies, and higher abundances than its surroundings, and is likely the result of sloshing gas initiated by a previous cluster-cluster or sub-cluster merger. Initial evidence for previously unseen bubbles at larger radii related to earlier outbursts from the AGN is presented.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Commissioning and operational results of helium refrigeration system at JLab for the 12GeV upgrade

The new 4.5 K refrigerator system at the Jefferson Lab (JLab) Central Helium Liquefier (CHL-2) for the 12 GeV upgrade was commissioned in late spring of 2013, following the commissioning of the new compressor system, and has been supporting 12 GeV LINAC commissioning since that time. Six design modes were tested during commissioning, consisting of a maximum capacity, nominal capacity, maximum liquefaction, maximum refrigeration, maximum fill and a stand-by/reduced load condition. The maximum capacity was designed to support a 238 g/s, 30 K and 1.16 bar cold compressor return flow, a 15 g/s, 4.5 K liquefaction load and a 12.6 kW, 35-55 K shield load. The other modes were selected to ensure proper component sizing and selection to allow the cold box to operate over a wide range of conditions and capacities. The cold box system is comprised of two physically independent cold boxes with interconnecting transfer-lines. The outside (upper) 300-60 K vertical cold box has no turbines and incorporates a liquid nitrogen pre-cooler and 80-K beds. The inside (lower) 60-4.5 K horizontal cold box houses seven turbines that are configured in four expansion stages including one Joule-Thompson expander and a 20-K bed. The helium compression system has five compressors to support three pressure levels in the cold box. This paper will summarize the analysis of the test data obtained over the wide range of operating conditions and capacities which were tested.

Knudsen, Peter N.↗