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Soldering is a critical filler material joining process found in nearly all modern electronics. Ensuring solder joint reliability is crucial for the safety, performance, and cost-effectiveness of microelectronics.
The model is similar to the Binary Fission Model (BFM) in chapter three of the Stochastic Neutronics Primer Volume I, however, we add photons as a product of induced fission events (IFEs). We will find that tracking the population of an additional particle adds an additional layer of complexity because we are now looking for a joint probability distribution.
Slides showing work done to identify bolted joint dynamics during summer internship.
In this project, we successfully achieved all the goals we proposed: ① Code Development; ② Transition Joint Design; ③ Lab-scale GCTJ Testing Piece Development; ④ Heat Treatment; ⑤ Welding of DMW; ⑥ Mechanical Characterization; ⑦ Corrosion; ⑧ Fabrication of Prototype GCTJ; ⑨In-field Test in SWRI and ⑩Tech-economic Analysis.
We present the status of a joint search for muon neutrino disappearance in the Booster Neutrino Beam at Fermilab using the Short-Baseline Neutrino (SBN) Program's two-detector configuration, SBND and ICARUS. Charged-current interactions consistent with muon neutrinos and containing only a muon and at least one proton in the final state are reconstructed and selected using the SPINE deep learning-based particle reconstruction package. To exploit proton multiplicity information and enhance sensitivity to modeling effects, the selected sample is partitioned into exclusive channels with exactly one reconstructed proton and with more than one reconstructed proton. Comprehensive systematic uncertainties from the neutrino flux, interaction, and detector response are incorporated into the analysis, and the coverage of these systematic uncertainty models is validated using data from both detectors, including checks of near-far consistency in key kinematic and topology-sensitive observables. This analysis is intended for inclusion in SBN's first oscillation result.
The Daya Bay, MINOS and MINOS+ experiments have searched for sterile neutrino mixing using electron antineutrino and muon (anti)neutrino disappearance, respectively, within a minimally extended four-neutrino scenario. They have recently combined their results, together with those from the Bugey-3 reactor neutrino experiment, to set the most stringent limits to date on the $\theta_{\mu e}$ mixing angle over five orders of magnitude in the sterile mass-squared difference $|\Delta m^2_{41}|$. The new constraints are significantly more stringent than the previous ones and exclude the sterileneutrino parameter space allowed by the LSND and MiniBooNE observations at 99% C.L.(CL$_{s}$) for $|\Delta m^2_{41}| <$ 1.2 eV$^2$, weakening the interpretation of these observations by the presence of a sterile neutrino. The result of the joint Daya Bay, MINOS, MINOS+ and Bugey-3 search along with a brief overview of the searches done by each experiment is presented.
Weldments of 347H stainless steel are potentially susceptible to stress relaxation cracking at elevated service temperatures. Mitigation of stress relaxation cracking susceptibility within a multipass weld requires a good understanding of welding practices and manufacturing techniques to control high tensile residual stresses. Here in this work, the dependence of residual stress distribution in 347H stainless steel on base plate thickness, joint geometry design, and preheating condition was systematically investigated by using three-dimensional finite element models. The finite element models were validated through good agreement between neutron diffraction measurements and calculated elastic strains. The single-V-groove welds with and without a preheating step all produced similar peak von Mises residual stresses, above 450 MPa, within both the fusion zone and heat-affected zone (HAZ). In plates thicker than 0.5 in. (12.7 mm), high tensile residual stress could be observed in a relatively large area, from the middle of the plate thickness to underneath the top surface. A double-V groove shifted the high tensile stress area to the middle thickness of the weld. A single-J-groove weld was able to confine the residual stress to a very small region near the middle thickness within the fusion zone and suppressed the von Mises residual stress within the HAZ to below 400 MPa.
The faint-end slope of the quasar luminosity function at z ~ 6 and its implication on the role of quasars in reionizing the intergalactic medium at early times has been an outstanding problem for some time. The identification of faint high-redshift quasars with luminosities of <10 44.5 erg s –1 is challenging. They are rare (few per square degree), and the separation of these unresolved quasars from late-type stars and compact star-forming galaxies is difficult from ground-based observations alone. In addition, source confusion becomes significant at >25 mag, with ~30% of sources having their flux contaminated by foreground objects when the seeing resolution is ~0''.7. We mitigate these issues by performing a pixel-level joint processing of ground and space-based data from Subaru/Hyper-SuprimeCam (HSC) and Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS). We create a deconfused catalog over the 1.64 deg 2 of the COSMOS field, after accounting for spatial varying point-spread functions and astrometric differences between the two data sets. We identify twelve low-luminosity (M UV ~ –21 mag) z > 6 quasar candidates through (i) their red color measured between ACS/F814W and HSC/i band and (ii) their compactness in the space-based data. Nondetections of our candidates in Hubble DASH data argues against contamination from late-type stars. Our constraints on the faint end of the quasar luminosity function at z ~ 6.4 suggest a negligibly small contribution to reionization compared to the star-forming galaxy population. The confirmation of our candidates and the evolution of number density with redshift could provide better insights into how supermassive galaxies grew in the first billion years of cosmic time.
We analyze stellar proper motions in the COSMOS field to assess the presence of bulk motions. At bright magnitudes (G-band 18.5–20.76 AB), we use the proper motions of 1010 stars in the Gaia DR2 catalog. At the faint end, we compute proper motions of 11,519 pointlike objects at i-band magnitudes 19–25 AB using Hubble ACS and Subaru HSC data, which span two epochs about 11 yr apart. In order to measure these proper motions with unprecedented accuracy at faint magnitudes, we developed a foundational set of astrometric tools that will be required for joint survey processing of data from the next generation of optical/infrared surveys. The astrometric grids of Hubble ACS and Subaru HSC mosaics were corrected at the catalog level using proper motion–propagated and parallax-corrected Gaia DR2 sources. These astrometric corrections were verified using compact extragalactic sources. Upon comparison of our measured proper motions with Gaia DR2, we estimate the uncertainties in our measurements to be ~2–3 mas yr –1 axis –1 , down to 25.5 AB mag. We correct proper motions for the mean motion of the Sun, and we find that late-type main-sequence stars predominantly in the thin disk in the COSMOS field have space velocities mainly toward the Galactic center. We detect candidate high-velocity (≥220 km s –1 ) stars, six of them at ~0.4–6 kpc, from the Gaia sample, and five of them at ~20 kpc, from the faint star HSC and ACS sample. The sources from the faint star sample may be candidate halo members of the Sangarius stream.
Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series.
We present a joint analysis of galaxy clustering and galaxy–galaxy lensing measurements from BOSS galaxies using a simulation-based emulation method combined with a halo occupation distribution model. Our emulators are constructed with the Aemulus ν simulations, a suite of wνCDM N-body simulations with massive neutrinos as independent particle species. We combine small-scale analysis of clustering from 0.1 to 60.2 h −1 Mpc and lensing from 1.7 to 60.2 h −1 Mpc to perform cosmological constraints. We split the BOSS galaxies into three redshift bins to measure their clustering and employ galaxies from Dark Energy Camera Legacy Survey and Hyper Suprime-Cam as source galaxies to measure lensing separately. We find that the addition of lensing significantly improves the constraining power on $S_8 = σ_8(Ω_m/0.3)^{0.5}$, with a weak improvement for fσ 8 . Our results of fσ 8 indicate tensions of around 1σ−4σ below the results of the cosmic microwave background observations of Planck. For S 8 , our results are also lower than Planck, and the tension can be mitigated when considering possible systematics in lensing measurement. As a by-product, our analysis prefers a nonzero neutrino mass but without strong significance, with the constraining power dominated by the clustering. Given the accuracy and precision of our model and the observational data, it is anticipated that larger and higher-quality spectroscopic data sets will improve the constraints on this fundamental property in the near future.
The Neutron Star Interior Composition Explorer collaboration recently published a joint estimate of the mass and the radius of PSR J0030+0451, derived via X-ray pulse-profile modeling. Raaijmakers et al. explored the implications of this measurement for the dense matter equation of state (EOS) using two parameterizations of the high-density EOS: a piecewise-polytropic model, and a model based on the speed of sound in neutron stars (NSs). In this work we obtain further constraints on the EOS following this approach, but we also include information about the tidal deformability of NSs from the gravitational wave signal of the compact binary merger GW170817. Further, we compare the constraints on the EOS to those set by the recent measurement of a 2.14 Me pulsar, included as a likelihood function approximated by a Gaussian, and find a small increase in information gain. To show the flexibility of our method, we also explore the possibility that GW170817 was a NS–black hole merger, which yields weaker constraints on the EOS.
With the proliferation of mobile devices and smart cameras, detecting anomalies and predicting their mobility are critical for enhancing safety in ubiquitous computing systems. Due to data privacy regulations and limited communication bandwidth, it is infeasible to collect, transmit, and store all data from mobile devices at a central location. To overcome this challenge, we propose FedADMP, a federated learning based joint Anomaly Detection and Mobility Prediction framework. FedADMP adaptively splits the training process between the server and clients to reduce computation loads on clients. To protect the privacy of user data, clients in FedADMP upload only intermediate model parameters to the cloud server. We also develop a differential privacy method to prevent the cloud server and external attackers from inferring private information during the model upload procedure. Extensive experiments using real-world datasets show that FedADMP consistently outperforms existing methods.
We present joint South Pole Telescope and XMM-Newton observations of eight massive galaxy clusters (0.8–2 × 10$^{15}$ M$_{⊙}$) spanning a redshift range of 0.16–0.35. Employing a novel Sunyaev–Zel’dovich + X-ray fitting technique, we effectively constrain the thermodynamic properties of these clusters out to the virial radius. The resulting best-fit electron density, deprojected temperature, and deprojected pressure profiles are in good agreement with previous observations of massive clusters. For the majority of the cluster sample (five out of eight clusters), the entropy profiles exhibit a self-similar behavior near the virial radius. We further derive hydrostatic mass, gas mass, and gas fraction profiles for all clusters up to the virial radius. Comparing the enclosed gas fraction profiles with the universal gas fraction profile, we obtain nonthermal pressure fraction profiles for our cluster sample at >0.5R$_{500}$, demonstrating a steeper increase between R$_{500}$ and R$_{200}$ that is consistent with the hydrodynamical simulations. Our analysis yields nonthermal pressure fraction ranges of 8%–28% (median: 15% ± 11%) at R$_{500}$ and 21%–35% (median: 27% ± 12%) at R$_{200}$. Notably, weak-lensing mass measurements are available for only four clusters in our sample, and our recovered total cluster masses, after accounting for nonthermal pressure, are consistent with these measurements.
In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.
SOUTHEAST REGIONAL CARBON STORAGE PARTNERSHIP: OFFSHORE GULF OF MEXICO: Presentations from 2020 Joint Partnership Meeting with GoMCarb Project
In March of 2020 we were well on our way to organizing and hosting one of the premier scanning probe microscopy (SPM) conferences in Breckenridge, Colorado, USA. For the first time, the meeting would synergistically combine International Scanning Probe Microscopy (ISPM) and Scanning Probe Microscopy on Soft and Polymeric Materials (SPMonSPM), to increase the breadth of audience expertise and experience. We coined the joint conference iSPM 3 – a moniker we hope will persist in future events. The plan for 2020 iSPM 3 screeched to a halt in mid-March, amidst the COVID-19 pandemic. Luckily, we were able to regroup and reimagine the conference for 2021 as a virtual experience. The conference took place June 28th to July 2nd with a mix of live and pre-recorded content. Spread throughout the week were 4 live panel discussions, 3 plenary talks, 23 invited talks, 75 contributed talks, 15 posters and 3 social events. The technical program represented much of the latest and most impactful research in the field. The panel discussions sought to step back from specific research findings and assess the state of SPM as it pertains to some of the most pressing opportunities and influential successes. The lively discussions painted a vibrant future for SPM in both breadth and detail, and we hope that similar discussion can be a mainstay of future SPM conferences. In this work, we attempt to distill some of that discussion to motivate researchers across the field of SPM in the coming years.
A composite torque pipe to metal fitting joint including concentric inner and outer shells formed with respective smooth conical surfaces projecting distally and respectively tapered radially inwardly and radially outwardly to form an annulus expanding in thickness for receipt of a tapered connector ring complementally shaped at one end of a composite pipe and bonded along the interface. The present invention includes selecting the sleeves with the corresponding shells and, forming the torque pipe with the tapered ring and bonding the tapered ring in the annulus.