Engineering topics
Publications and source records attributed to Chen, H.
Due to an error in production, the error margins of many values were incorrectly published. Table 1 details the locations of the errors and their corrections.
The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60–80 t capable of probing the remaining weakly interacting massive particle-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in 136 Xe using a natural-abundance xenon target. XLZD can reach a 3σ discovery potential half-life of 5.7 × 10 27 years (and a 90% CL exclusion of 1.3 × 10 28 years) with 10 years of data taking, corresponding to a Majorana mass range of 7.3–31.3 meV (4.8–20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community.
The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of 124Xe through the process of two-neutrino double electron capture, utilizing a 1.39 kg × yr isotopic exposure from the first LZ science run. A half-life of $T$$^{2v2EC}_{1/2}$ = (1.09 ± 0.14 stat ± 0.05 sys ) x 10 22 yr is observed with a statistical significance of 8.3σ, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the 1.4σ level.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
The National Diagnostic Working Group (NDWG) has led the effort to fully exploit the major inertial confinement fusion/high-energy density facilities in the US with the best available diagnostics. These diagnostics provide key data used to falsify early theories for ignition and suggest new theories, recently leading to an experiment that exceeds the Lawson condition required for ignition. The factors contributing to the success of the NDWG, collaboration and scope evolution, and the methods of accomplishment of the NDWG are discussed in this Review. Examples of collaborations in neutron and gamma spectroscopy, x-ray and neutron imaging, x-ray spectroscopy, and deep-ultraviolet Thomson scattering are given. Here, an abbreviated history of the multi-decade collaborations and the present semiformal management framework is given together with the latest National Diagnostic Plan.
Numerical data used to draw the figures in the manuscript
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
New short-pulse kilojoule, Petawatt-class lasers, which have recently come online and are coupled to large-scale, many-beam long-pulse facilities, undoubtedly serve as very exciting tools to capture transformational science opportunities in high energy density physics. These short-pulse lasers also happen to reside in a unique laser regime: very high-energy (kilojoule), relatively long (multi-picosecond) pulse-lengths, and large (10s of micron) focal spots, where their use in driving energetic particle beams is largely unexplored. Proton acceleration via Target Normal Sheath Acceleration (TNSA) using the Advanced Radiographic Capability (ARC) short-pulse laser at the National Ignition Facility in the Lawrence Livermore National Laboratory is demonstrated for the first time, and protons of up to 18 MeV are measured using laser irradiation of >1 ps pulse-lengths and quasi-relativistic (10 18 W/cm 2 ) intensities. This is indicative of a super-ponderomotive electron acceleration mechanism that sustains acceleration over long (multi-picosecond) time-scales and allows for proton energies to be achieved far beyond what the well-established scalings of proton acceleration via TNSA would predict at these modest intensities. Furthermore, the characteristics of the ARC laser (large ~100 μ m diameter focal spot, flat spatial profile, multi-picosecond, relatively low prepulse) provide acceleration conditions that allow for the investigation of 1D-like particle acceleration. A high flux ~50 J of laser-accelerated protons is experimentally demonstrated. In conclusion, a new capability in multi-picosecond particle-in-cell simulation is applied to model the data, corroborating the high proton energies and elucidating the physics of multi-picosecond particle acceleration.
For the past two decades a slowly growing consensus has been that rising temperature is being caused by increases in carbon dioxide (CO 2 ) in the Earth’s atmosphere. What is less consensual is what to do about it. Solutions range from reducing emissions to various ways to capture CO 2 (from effluents of power plants, as plants, etc.) and store it away from the atmosphere. The problem is of such magnitude that it is likely that we will need many methods. Also some methods would cause draconian harm to global economies. This work is about the storage part of the reducing of CO 2 in the atmosphere. There have been many methods proposed for storing CO 2 : in vegetation, at the bottom of oceans, in land farms, and in subsurface formations. The latter is particularly prominent given the large estimated volume in porous formation in the Earth, and the 50-year old experience in injecting CO 2 for enhanced oil recovery. This report is about the science behind subsurface storage, called here geological carbon storage or GCS. Effective GCS requires that billions of metric tons of CO 2 be injected into storage reservoirs annually. GCS feasibility requires balancing the opposing impacts of large emplacement (injection) rates without compromising caprock seal integrity during injection. Once injected, the challenge is to assure the injected CO 2 remains permanently stored. Under most conditions, CO 2 is in a supercritical state, or scCO 2 . scCO 2 is immiscible with the subsurface brine and has a factor of ten smaller viscosity, leading to the development of two-phase fluid flow and scCO 2 bypassing. After the injection of large volumes of scCO 2 , the pore pressure, state of stress, chemical, thermal, and biological steady-state or equilibrium conditions in the subsurface are disrupted, which may lead to unpredictable behavior because the responses to these changes are often non-linear. Current challenges for efficient and reliable scCO 2 storage are: (1) sustaining large injection rates; (2) using available pore space efficiently, and (3) controlling undesired or unexpected behavior, such as scCO 2 leakage. Various aspects of these challenges are addressed by collaborative projects within Center for Frontiers in Subsurface Energy Security (CFSES). Challenge 1 – Sustaining large storage rates. To offset the annual CO 2 emissions of in the United States, ~7 billion metric tons of CO 2 must be injected into the storage reservoirs annually. Injected CO 2 forms a plume that starts spreading, displacing originally resident brine, though inefficiently so. Because of its low viscosity, and buoyant forces, a CO 2 plume rises to the reservoir rock-caprock interface. Injecting large volumes of scCO 2 at sufficiently high rates into subsurface storage formations leads to increases in pore pressures, potential expansion of the reservoir rock, and may result in fracturing of the reservoir rock and/or caprock. CFSES research uses existing and new experimental and modeling approaches to identify chemical-physical controls on the permeability and pore pressure dynamics, anticipating geomechanical (fracturing) events, predicting multi-phase flow patterns and trapping of CO 2 . Challenge 2 – Using pore space with unprecedented efficiency. Since large volumes of scCO 2 are to be stored, the volume available in storage reservoirs must be used efficiently. Storage efficiency is defined as a fraction of pore space occupied by carbon dioxide. Current estimates are that less than 5 percent of available pore volume is available for storage because scCO 2 , having a smaller density and viscosity than reservoir brine, tends to form viscous fingers, and bypass available pore space. This flow regime results in a CO 2 plume spreading over large areas in subsurface. The research goal in Challenge 2 is to advance the fundamental understanding of two-phase flow through porous media, including molecular-to meter- scale experimental and modeling approaches. This work leads to novel strategies to ensure that injected CO 2 occupies more than 5% of the pore space, ideally up to 50%. Challenge 3 – Controlling undesired or unexpected behavior. Following the injection of scCO 2 , the subsurface reservoir re-equilibrates to different physical and chemical states. This re-equilibration in space and time could lead to unexpected and/or undesired behavior: fracturing of reservoir rock and/or caprock, development of preferential flow paths, CO 2 leakage (to the surface or overlaying fresh water reservoirs), induced seismicity, and activation of faults. One of the main research goals of CFSES was to advance the fundamental understanding of how individual chemical and physical processes are coupled. We particularly focused on the chemical-mechanical coupling, and flow-mechanical coupling. We collected experimental and modeling data to determine the temporal and spatial scales of the coupled processes, which may lead to pore collapse caused by creep, activation of fractures and faults, chemically-induced fracture propagation, and self-focusing of scCO 2 flow.
Abstract not provided
We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identifi-cation or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.
Abstract not provided
Abstract not provided