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At least 1,243 records · Page 69

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DOE OSTI2026

Search for dijet resonances with data scouting in proton-proton collisions at $\sqrt{s}=13$ TeV

A search is presented for narrow resonances, with a mass between 0.6 and 1.8 TeV, decaying to pairs of jets, in proton-proton collisions at $\sqrt{s}=13$ TeV. The search is performed using dijets that are reconstructed, selected, and recorded in a compact form by the high-level trigger in a technique referred to as “data scouting”, from data collected in 2016–2018 corresponding to an integrated luminosity of 117 fb −1 . The dijet mass spectra are well described by a smooth parameterization, and no significant evidence for the production of new particles is observed. Model-independent upper limits are presented on the product of the cross section, branching fraction, and acceptance for the individual cases of narrow quark-quark, quark-gluon, and gluon-gluon resonances, and are compared to the predictions from a variety of models of narrow dijet resonance production. The upper limit on the coupling of a dark matter mediator to quarks is presented as a function of the mediator mass. The sensitivity of this search goes beyond what is expected from statistical scaling with the integrated luminosity alone, as a consequence of the use of fewer parameters in the background function within a more robust statistical procedure.

beyond Standard Model↗

DOE OSTI2023

Measurement of the total and differential Higgs boson production cross-sections at $ \sqrt{s} $ = 13 TeV with the ATLAS detector by combining the H → ZZ* → 4ℓ and H → γγ decay channels

The total and differential Higgs boson production cross-sections are measured through a combined statistical analysis of the H → ZZ* → 4ℓ and H → γγ decay channels. The results are based on a dataset of 139 fb –1 of proton–proton collisions at a centre-of-mass energy of 13 TeV, recorded by the ATLAS detector at the Large Hadron Collider. The measured total Higgs boson production cross-section is $55.5$$^{+4.0}_{–3.8}$ pb, consistent with the Standard Model prediction of 55.6 ± 2.5 pb. All results from the two decay channels are compatible with each other, and their combination agrees with the Standard Model predictions. A combined statistical interpretation of the measured fiducial cross-sections as a function of the Higgs boson transverse momentum is performed in order to probe the Yukawa couplings to the bottom and charm quarks. A similar interpretation is performed by including also the constraints from the measurements of Higgs boson production in association with a W or Z boson in the H → bb¯ and cc¯ decay channels.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Study of exclusive photoproduction of charmonium in ultra-peripheral lead-lead collisions

The cross-sections of exclusive (coherent) photoproduction J/ψ and ψ(2S) mesons in ultra-peripheral PbPb collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV are measured using a data sample corresponding to an integrated luminosity of 228 ± 10 µb -1 , collected by the LHCb experiment in 2018. The differential cross-sections are measured separately as a function of transverse momentum and rapidity in the nucleus-nucleus centre-of-mass frame for J/ψ and ψ(2S) mesons. The integrated cross-sections are measured to be $σ^{coh}_{J/ψ}$ = 5.965 ± 0.059 ± 0.232 ± 0.262 mb and $σ^{coh}_{ψ(2S)}$ = 0.923 ± 0.086 ± 0.028 ± 0.040 mb, where the first listed uncertainty is statistical, the second systematic and the third due to the luminosity determination. The cross-section ratio is measured to be $σ^{coh}_{ψ(2S)}$/$σ^{coh}_{J/ψ}$ = 0.155 ± 0.014 ± 0.003, where the first uncertainty is statistical and the second is systematic. These results are compatible with theoretical predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Measurement of e+e− → ωη′ cross sections at $$ \sqrt{s} $$ = 2.000 to 3.080 GeV

Abstract We measured the Born cross sections for the processe + e − →ωη′ at 22 center-of-mass energies from 2.000 to 3.080 GeV with the BESIII detector at the BEPCII collider. We observed a resonant structure with a statistical significance of 9.6σ. A Breit-Wigner fit determines its mass to beM R = (2153±30±31) MeV/c 2 and its width to be Γ R = (167±77±7) MeV, where the first uncertainties are statistical and the second are systematic.

Physics↗

DOE OSTI2022

Observation of the doubly Cabibbo-suppressed decays $D^+ → K^+π^0π^0$ and $D^+ → K^+π^0η$

By analyzing e + e - annihilation data corresponding to an integrated luminosity of 2.93 fb -1 collected at the center-of-mass energy of 3.773 GeV with the BESIII detector, we report the first observations of the doubly Cabibbo-suppressed decays D + → K + π 0 π 0 and D + → K + π 0 η. The branching fractions of D + → K + π 0 π 0 and D + → K + π 0 η are measured to be (2.1 ± 0.4 stat ± 0.1 syst ) x 10 -4 and (2.1 ± 0.5 stat ± 0.1 syst ) x 10 -4 with statistical significances of 8.8σ and 5.5σ, respectively. In addition, we search for the subprocesses D + → K * (892) + π 0 and D + → K * (892)+η with K * (892) + → K + π 0 . The branching fraction of D + → K * (892) + η is determined to be (4.4$^{+1.8}_{-1.5stat}$ ± 0.2 syst ) x 10 -4 , with a statistical significance of 3.2σ. No significant signal for D + → K * (892) + π 0 is found and we set an upper limit on the branching fraction of this decay at the 90% confidence level to be 5.4 x 10 -4 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Measurements of $$ {K}_S^0 $$-$$ {K}_L^0 $$ asymmetries in the decays $$ {\Lambda}_c^{+}\to p{K}_{L,S}^0 $$, $$ p{K}_{L,S}^0{\pi}^{+}{\pi}^{-} $$ and $$ p{K}_{L,S}^0{\pi}^0 $$

Abstract Usinge + e − annihilation data sets corresponding to an integrated luminosity of 4.5 fb −1 , collected with the BESIII detector at center-of-mass energies between 4.600 and 4.699 GeV, we report the first measurements of the absolute branching fractions$$ \mathcal{B}\left({\Lambda}_c^{+}\to p{K}_L^0\right) $$ B Λ c + → p K L 0 = (1.67±0.06±0.04)%,$$ \mathcal{B}\left({\Lambda}_c^{+}\to p{K}_L^0{\pi}^{+}{\pi}^{-}\right) $$ B Λ c + → p K L 0 π + π − = (1.69±0.10±0.05)%, and$$ \mathcal{B}\left({\Lambda}_c^{+}\to p{K}_L^0{\pi}^0\right) $$ B Λ c + → p K L 0 π 0 = (2.02±0.13±0.05)%, where the first uncertainties are statistical and the second systematic. Combining with the known branching fractions of$$ {\Lambda}_c^{+}\to p{K}_S^0 $$ Λ c + → p K S 0 ,$$ {\Lambda}_c^{+}\to p{K}_S^0{\pi}^{+}{\pi}^{-} $$ Λ c + → p K S 0 π + π − , and$$ {\Lambda}_c^{+}\to p{K}_S^0{\pi}^0 $$ Λ c + → p K S 0 π 0 , we present the first measurements of the$$ {K}_S^0 $$ K S 0 -$$ {K}_L^0 $$ K L 0 asymmetries$$ R\left({\Lambda}_c^{+},{K}_{S,L}^0X\right)=\frac{\mathcal{B}\left({\Lambda}_c^{+}\to {K}_S^0X\right)-\mathcal{B}\left({\Lambda}_c^{+}\to {K}_L^0X\right)}{\mathcal{B}\left({\Lambda}_c^{+}\to {K}_S^0X\right)+\mathcal{B}\left({\Lambda}_c^{+}\to {K}_L^0X\right)} $$ R Λ c + K S , L 0 X = B Λ c + → K S 0 X − B Λ c + → K L 0 X B Λ c + → K S 0 X + B Λ c + → K L 0 X in charmed baryon decays:$$ R\left({\Lambda}_c^{+},p{K}_{S,L}^0\right)=-0.025\pm 0.031 $$ R Λ c + p K S , L 0 = − 0.025 ± 0.031 ,$$ R\left({\Lambda}_c^{+},p{K}_{S,L}^0{\pi}^{+}{\pi}^{-}\right)=-0.027\pm 0.048 $$ R Λ c + p K S , L 0 π + π − = − 0.027 ± 0.048 and$$ R\left({\Lambda}_c^{+},p{K}_{S,L}^0{\pi}^0\right)=-0.015\pm 0.046 $$ R Λ c + p K S , L 0 π 0 = − 0.015 ± 0.046 . No significant asymmetries with statistical significance are observed.

Physics↗

DOE OSTI2024

Observation of the semileptonic decays $$ {\textrm{D}}^0\to {\textrm{K}}_{\textrm{S}}^0{\pi}^{-}{\pi}^0{\textrm{e}}^{+}{\nu}_{\textrm{e}} $$ and $$ {\textrm{D}}^{+}\to {\textrm{K}}_{\textrm{S}}^0{\pi}^{+}{\pi}^{-}{\textrm{e}}^{+}{\nu}_{\textrm{e}} $$

Abstract By analyzinge + e − annihilation data corresponding to an integrated luminosity of 2.93 fb −1 collected at a center-of-mass energy of 3.773 GeV with the BESIII detector, the first observation of the semileptonic decays$$ {D}^0\to {K}_S^0{\pi}^{-}{\pi}^0{e}^{+}{\nu}_e $$ D 0 → K S 0 π − π 0 e + ν e and$$ {D}^{+}\to {K}_S^0{\pi}^{+}{\pi}^{-}{e}^{+}{\nu}_e $$ D + → K S 0 π + π − e + ν e is reported. In the hypothesis that all events correspond toK 1 (1270) decays, the branching fractions are measured to be$$ \mathcal{B}\left({D}^0\to {K}_1{(1270)}^{-}\left(\to {K}_S^0{\pi}^{-}{\pi}^0\right){e}^{+}{\nu}_e\right)=\left({1.69}_{-0.46}^{+0.53}\pm 0.15\right)\times {10}^{-4} $$ B D 0 → K 1 1270 − → K S 0 π − π 0 e + ν e = 1.69 − 0.46 + 0.53 ± 0.15 × 10 − 4 and$$ \mathcal{B}\left({D}^{+}\to {\overline{K}}_1{(1270)}^0\left(\to {K}_S^0{\pi}^{+}{\pi}^{-}\right){e}^{+}{\nu}^e\right)=\left({1.47}_{-0.40}^{+0.45}\pm 0.14\right)\times {10}^{-4} $$ B D + → K ¯ 1 1270 0 → K S 0 π + π − e + ν e = 1.47 − 0.40 + 0.45 ± 0.14 × 10 − 4 with statistical significance of 5.4σand 5.6σ, respectively. When combined with measurements of theK 1 (1270)→ K + π − πdecays, the absolute branching fractions are determined to be$$ \mathcal{B}\left({D}^0\to {K}_1{(1270)}^{-}{e}^{+}{\nu}_e\right)=\left({1.08}_{-0.13-0.10}^{+0.14+0.08}\pm 0.21\right)\times {10}^{-3} $$ B D 0 → K 1 1270 − e + ν e = 1.08 − 0.13 − 0.10 + 0.14 + 0.08 ± 0.21 × 10 − 3 and$$ \mathcal{B}\left({D}^{+}\to {\overline{K}}_1{(1270)}^0{e}^{+}{\nu}_e\right)=\left({1.70}_{-0.23}^{+0.26}\pm 0.13\pm 0.35\right)\times {10}^{-3} $$ B D + → K ¯ 1 1270 0 e + ν e = 1.70 − 0.23 + 0.26 ± 0.13 ± 0.35 × 10 − 3 . The first and second uncertainties are statistical and systematic, respectively, and the third uncertainties originate from the assumed branching fractions of theK 1 (1270)→ Kππdecays.

Physics↗

DOE OSTI2024

Measurement of energy resolution with the NEXT-White silicon photomultipliers

The NEXT-White detector, a high-pressure gaseous xenon time projection chamber, demonstrated the excellence of this technology for future neutrinoless double beta decay searches using photomultiplier tubes (PMTs) to measure energy and silicon photomultipliers (SiPMs) to extract topology information. This analysis uses $^{83m}$Kr data from the NEXT-White detector to measure and understand the energy resolution that can be obtained with the SiPMs, rather than with PMTs. The energy resolution obtained of (10.9 ± 0.6)%, full-width half-maximum, is slightly larger than predicted based on the photon statistics resulting from very low light detection coverage of the SiPM plane in the NEXT-White detector. The difference in the predicted and measured resolution is attributed to poor corrections, which are expected to be improved with larger statistics. Furthermore, the noise of the SiPMs is shown to not be a dominant factor in the energy resolution and may be negligible when noise subtraction is applied appropriately, for high-energy events or larger SiPM coverage detectors. These results, which are extrapolated to estimate the response of large coverage SiPM planes, are promising for the development of future, SiPM-only, readout planes that can offer imaging and achieve similar energy resolution to that previously demonstrated with PMTs.[graphic not available: see fulltext]

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

A Goldstone boson equivalence for inflation

The effective field theory of single-field inflation characterizes the inflationary epoch in terms of a pattern of symmetry breaking. An operator acquires a time-dependent vacuum expectation value, defining a preferred spatial slicing. In the absence of dynamical gravity, the fluctuations around the time-dependent background are described by the Goldstone boson associated with this symmetry breaking process. With gravity, the Goldstone is eaten by the metric, becoming the scalar metric fluctuation. In this paper, we will show that in general single-field inflation, the statistics of scalar metric fluctuations are given by the statistics of this Goldstone boson decoupled from gravity up to corrections that are controlled as an expansion in slow-roll parameters. This even holds in the presence of additional parameters, like the speed of sound, that naively enhance the impact of the gravitational terms. In the process, we derive expressions for leading and sub-leading gravitational corrections to all-orders in the Goldstone boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Analytical estimation of the signal to noise ratio efficiency in axion dark matter searches using a Savitzky-Golay filter

The signal to noise ratio efficiency ϵ SNR in axion dark matter searches has been estimated using large-statistic simulation data reflecting the background information and the expected axion signal power obtained from a real experiment. This usually requires a lot of computing time even with the assistance of powerful computing resources. Employing a Savitzky-Golay filter for background subtraction, in this work, we estimated a fully analytical ϵ SNR without relying on large-statistic simulation data, but only with an arbitrary axion mass and the relevant signal shape information. Hence, our work can provide ϵ SNR using minimal computing time and resources prior to the acquisition of experimental data, without the detailed information that has to be obtained from real experiments. Axion haloscope searches have been observing the coincidence that the frequency independent scale factor ξ is approximately consistent with the ϵ SNR . This was confirmed analytically in this work, when the window length of the Savitzky-Golay filter is reasonably wide enough, i.e., at least 5 times the signal window.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Systematic quark/gluon identification with ratios of likelihoods

Discriminating between quark- and gluon-initiated jets has long been a central focus of jet substructure, leading to the introduction of numerous observables and calculations to high perturbative accuracy. At the same time, there have been many attempts to fully exploit the jet radiation pattern using tools from statistics and machine learning. We propose a new approach that combines a deep analytic understanding of jet substructure with the optimality promised by machine learning and statistics. After specifying an approximation to the full emission phase space, we show how to construct the optimal observable for a given classification task. This procedure is demonstrated for the case of quark and gluons jets, where we show how to systematically capture sub-eikonal corrections in the splitting functions, and prove that linear combinations of weighted multiplicity is the optimal observable. In addition to providing a new and powerful framework for systematically improving jet substructure observables, we demonstrate the performance of several quark versus gluon jet tagging observables in parton-level Monte Carlo simulations, and find that they perform at or near the level of a deep neural network classifier. Combined with the rapid recent progress in the development of higher order parton showers, we believe that our approach provides a basis for systematically exploiting subleading effects in jet substructure analyses at the Large Hadron Collider (LHC) and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Increased inflammation as well as decreased endoplasmic reticulum stress and translation differentiate pancreatic islets from donors with pre-symptomatic stage 1 type 1 diabetes and non-diabetic donors

Aims/hypothesis Progression to type 1 diabetes is associated with genetic factors, the presence of autoantibodies and a decline in beta cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting beta cells prior to the onset of type 1 diabetes. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet-autoantibody-positive organ donors with pre-symptomatic stage 1 type 1 diabetes (HbA1c ≤42 mmol/mol [6.0%]). We aimed to identify pathways in islets that are indicative of beta cell dysfunction. Methods Multiple islet sections were collected through laser microdissection of frozen pancreatic tissues from organ donors positive for single or multiple islet autoantibodies (AAb + , n=5), and age (±2 years)- and sex-matched non-diabetic (ND) control donors (n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to MS-based proteomics and analysed with label-free quantification followed by pathway and functional annotations. Results Analyses resulted in ~4500 proteins identified with low false discovery rate (<1%), with 2165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on only the donors with stage 1 type 1 diabetes who were positive for multiple autoantibodies (mAAb + , n=3) and genetic risk compared with their matched ND controls (n=3) for the final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different (unadjusted p<0.025, q<0.15) for mAAb + vs ND donor islets. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including a proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single-cell RNA-seq datasets from AAb + individuals. Conclusions/interpretation In situ human islet proteome alterations in stage 1 type 1 diabetes centred around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation/HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on beta cell changes during type 1 diabetes progression and pathogenesis. Data availability The LC-MS raw datasets that support the findings of this study have been deposited in the online repository: MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with accession no. MSV000090212.

Autoantibody-positive↗

DOE OSTI2020

Projected changes in the terrestrial and oceanic regulators of climate variability across sub-Saharan Africa

Future changes in the sign and intensity of ocean–land–atmosphere interactions have been insufficiently studied, despite implications for regional climate change projections, extreme event statistics, and seasonal climate predictability. In response to this deficiency, the present study focuses on projected responses to the enhanced greenhouse effect in: (1) the mean state of the atmosphere and land surface; (2) oceanic and terrestrial drivers of sub-Saharan climate variability; and (3) total seasonal climate predictability of sub-Saharan Africa, a region known for its pronounced land–atmosphere coupling. Analysis focuses on output from 23 Earth System Models in the Coupled Model Intercomparison Project Phase Five for the late twentieth and twenty-first centuries. It is projected that the greatest warming across sub-Saharan Africa will occur over the Sahel, the monsoon season will become more persistent into late summer and autumn, short rains in the Horn of Africa (HOA) will intensify, and leaf area index will increase across the HOA. Stepwise Generalized Equilibrium Feedback Assessment, i.e. a multivariate statistical approach, is applied to the model output over sub-Saharan Africa in order to explore the oceanic and terrestrial drivers of regional climate. The models indicate that the study region’s climate variability is dominated by oceanic drivers, with secondary contributions from soil moisture and very modest impacts from vegetation. Overall, the general model consensus of future projections indicates a concerning diminished seasonal predictability of sub-Saharan African regional climate based on key oceanic and terrestrial predictors and an elevated role of the land surface (associated with soil moisture anomalies) compared to oceanic drivers in regulating regional climate variability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Future projections in tropical cyclone activity over multiple CORDEX domains from RegCM4 CORDEX-CORE simulations

The characteristics of tropical cyclone (TC) activity over five TC basins lying within four Coordinated Regional Downscaling Experiment (CORDEX) domains are examined for present and future climate conditions using a new ensemble of simulations completed as part of the CORDEX-CORE initiative with the regional climate model RegCM4. The simulations are conducted at a 25 km horizontal grid spacing and are driven by three CMIP5 general circulation models (GCMs) under two Representative Concentration Pathways (RCP2.6 and RCP8.5). The RegCM4 captures most features of the observed TC climatology, except for the TC intensity, which is thus statistically adjusted using a bias correction procedure to account for the effect of the coarse model resolution. The RegCM4 exhibits an improved simulation of several TC statistics compared to the driving GCMs, over most basins analyzed. In future climate conditions we find significant increases in TC frequency over the North Indian Ocean, the Northwest Pacific and Eastern Pacific regions, which are consistent with an increase in mid-tropospheric relative humidity. The North Atlantic and Australasia regions show a decrease in TC frequency, mostly associated with an increase in wind shear. We also find a consistent increase in future storm rainfall rates associated with TCs and in the frequency of the most intense TCs over most domains. Finally, our study shows robust responses often, but not always, in line with previous studies, still implying the presence of significant uncertainties in the projection of TC characteristics, which need to be addressed using large ensembles of simulations with high-resolution models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Representative Phenomena of Cyclic Turbulent Combustion in High-Pressure Fuel Sprays

Abstract Cyclic variations in conventional diesel combustion engines can lead to large differences in engine out emissions even at steady operation. This study uses an optically accessible constant-pressure flow chamber to acquire fuel injections in quick succession to analyze mixing, auto-ignition, and combustion of diesel-surrogate n-heptane using multiple high-speed optical diagnostics. Prior studies have utilized fewer injections and/or they rely on analysis of ensemble average behavior. These approaches do not yield information on injection-to-injection variation or provide confidence in utilizing individual injection measurements for high-fidelity computational fluid dynamics(CFD) model validation. In this study, a large set of 500 injections is used to obtain global parameters including liquid length, vapor penetration length, ignition delay time, and lift-off length. Results for multiple injections are presented to illustrate large injection to injection variations. Potential sources for these variations are analyzed to conclude localized, small scale turbulence and rate of injection variations as the likely sources. Then, a statistical method based on z-scores is proposed and implemented to identify instantaneous injections that best represent the bulk data-set of jet boundaries measured independently by three different diagnostics. This synthesis of statistics-guided screening of data set and ensemble-average analysis offers higher confidence for CFD model validation relying upon both a representative single and average injection results.

42 ENGINEERING↗

DOE OSTI2020

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗

DOE OSTI2025

Topography-Induced TKE Budget Behavior Over an Amazon Forest

Data from three different heights (35, 50 and 81 m) of one of the ATTO Project towers in the Amazon forest were used to calculate the TKE (turbulence kinetic energy) budget and some other statistics within the RSL (roughness sublayer). The statistical analyses were carried out for unstable and stable cases. The vertical transport and the vertical advection terms do not explain the imbalances found in the TKE budget, highlighting the impor- tance of horizontal terms in complex terrain. Indeed, patterns independent of the time of day were found for vertical transport, horizontal and vertical velocity skewness, the mean vertical component velocity, and momentum and vertical TKE flux. Here, the highest values of mean vertical velocity were observed from the direction where there is a valley near the tower, which may indicate a topographical effect. Monin-Obukhov Similarity Theory (MOST) predictions for the mean velocity gradient, strictly applicable only in the inertial sublayer (ISL), gave reasonable predictions at 35 and 50 m, but dimensionless dissipation rates displayed large scatter. At 81 m, there were clear deviations from MOST for the two functions, disclosing the effect of topography. In addition, a neutral LES (large-eddy simu- lation) study showed good agreement with tower data for the same general wind direction.

ATTO project↗

DOE OSTI2022

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Gaikwad, Aniruddha (ORCID:0000000285642621)↗